From cf95a4c7c41c7abfd0e3c92d78f12b21648d171c Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Thu, 6 Aug 2026 16:56:56 -0700 Subject: [PATCH 01/28] fix: correct provider identity, reasoning, and streaming before launch MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Audited both packages against the interfaze npm/pip SDKs and the live `/v1/chat/completions` contract. Ten defects, all verified against the API. Both languages: - Report interfaze, not openai. `_llm_type`, `ls_provider`, `lc_secrets`, `lc_namespace` and `response_metadata.model_provider` all said "openai", so every LangSmith trace was attributed to the wrong provider. Also stamp the package version into `lc_versions`. - Drop the `precontext` constructor field. The server strips unknown top-level body keys and neither core SDK has such a param, so it never did anything — the README documented it as working. - Reject `{type:"video", file_id}` client-side with a clear InterfazeError. The server's `file` part requires `file_data` and has no `file_id`, so it was a guaranteed 400. - Infer the container mime type for video URLs, matching `inputs.video()`. - Default the request timeout to 900s, matching the core SDKs; a single call may run OCR, a web search or a transcription inline. - Expose the four control options (`show_additional_info` / `bypass_cache` / `bypass_moa` / `admin_key`). `show_additional_info` is the only way to get precontext while streaming. JS only: - Forward `reasoning_effort`. `@langchain/openai` only forwards it for model names matching its own reasoning heuristic (`/^o\d/`, `gpt-5*`), so interfaze-beta silently lost it and reasoning was unreachable from the package. - Widen the `@langchain/openai` peer from an exact `1.5.5` to `^1.5.5`; the exact pin was an ERESOLVE for anyone on current latest. - Reach `_streamChatModelEvents` via `BaseChatModel.prototype` instead of a double `getPrototypeOf` walk over an `@internal` class. Python only: - Stop leaking raw `` text to token callbacks. `_iter_v2_events` is the one core path that passes `run_manager` into `_stream`, and ChatOpenAI fires `on_llm_new_token` before yielding, i.e. before the filter ran. `_stream` and `_astream` now withhold the manager and fire it themselves once the chunk is clean. - Enable `stream_options.include_usage`. langchain-openai only auto-enables it for OpenAI's own base URL, so streamed responses carried no `usage_metadata`. JS already defaulted it on. - Pin `use_responses_api=False` so a stray `reasoning=` kwarg or `LC_OUTPUT_VERSION` cannot reroute to /v1/responses and bypass every hook. Tests: JS unit 35 -> 49, python unit 28 -> 36. New live suites mirroring the interfaze-sdk-tests SPEC — 70 JS tests across 6 files (`npm run test:live`) and 72 python tests across 5 files — covering text, structured output, OCR, document extraction and markdown, object/GUI detection, audio, video, translation, web search, scraping, forecasting, reasoning, function calling, streaming, the code sandbox, guardrails, `` tags and the negative API-contract cases. All pass. `ChatModelIntegrationTests` now declares real capability flags and xfails the two cases the server cannot support (assistant list content, forced `tool_choice`). Docs: drop the precontext section, document the control options, `` and `` via SystemMessage (which works — the docs said to use the core client), a server-limits table, and how to run the live suites. --- README.md | 82 +++- js/README.md | 49 ++- js/package-lock.json | 20 +- js/package.json | 5 +- js/src/chat_models.ts | 186 +++++++-- js/src/version.ts | 2 + js/test-live/contract.live.test.ts | 113 ++++++ js/test-live/helpers.ts | 83 ++++ js/test-live/media.live.test.ts | 63 +++ js/test-live/streaming.live.test.ts | 79 ++++ js/test-live/text.live.test.ts | 96 +++++ js/test-live/tools.live.test.ts | 227 +++++++++++ js/test-live/vision.live.test.ts | 274 +++++++++++++ js/test/constructor.test.ts | 68 +++- js/test/identity.test.ts | 48 +++ js/test/stream.test.ts | 11 +- js/test/video.test.ts | 19 +- js/tsconfig.json | 2 +- js/vitest.live.config.ts | 18 + python/README.md | 70 +++- python/langchain_interfaze/__init__.py | 3 +- python/langchain_interfaze/_version.py | 3 + python/langchain_interfaze/chat_models.py | 170 +++++++- python/pyproject.toml | 10 +- python/tests/integration_tests/conftest.py | 84 ++++ .../integration_tests/test_chat_models.py | 77 +++- .../integration_tests/test_live_contract.py | 184 +++++++++ .../integration_tests/test_live_media.py | 105 +++++ .../integration_tests/test_live_streaming.py | 118 ++++++ .../tests/integration_tests/test_live_text.py | 136 +++++++ .../integration_tests/test_live_tools.py | 306 ++++++++++++++ .../integration_tests/test_live_vision.py | 375 ++++++++++++++++++ python/tests/unit_tests/test_chat_models.py | 121 ++++-- python/tests/unit_tests/test_imports.py | 2 +- 34 files changed, 3079 insertions(+), 130 deletions(-) create mode 100644 js/src/version.ts create mode 100644 js/test-live/contract.live.test.ts create mode 100644 js/test-live/helpers.ts create mode 100644 js/test-live/media.live.test.ts create mode 100644 js/test-live/streaming.live.test.ts create mode 100644 js/test-live/text.live.test.ts create mode 100644 js/test-live/tools.live.test.ts create mode 100644 js/test-live/vision.live.test.ts create mode 100644 js/test/identity.test.ts create mode 100644 js/vitest.live.config.ts create mode 100644 python/langchain_interfaze/_version.py create mode 100644 python/tests/integration_tests/conftest.py create mode 100644 python/tests/integration_tests/test_live_contract.py create mode 100644 python/tests/integration_tests/test_live_media.py create mode 100644 python/tests/integration_tests/test_live_streaming.py create mode 100644 python/tests/integration_tests/test_live_text.py create mode 100644 python/tests/integration_tests/test_live_tools.py create mode 100644 python/tests/integration_tests/test_live_vision.py diff --git a/README.md b/README.md index 9662397..b50a28a 100644 --- a/README.md +++ b/README.md @@ -347,7 +347,8 @@ await llm.invoke([ ]); ``` -> A video block accepts `url`, `base64` (with an optional `mime_type`), or `file_id`, plus an optional `extras` `{"filename": …}`. +> A video block accepts `url` or `base64` (with an optional `mime_type`), plus an optional `extras` `{"filename": …}`. +> The container mime type is inferred from the URL extension when you don't pass one. Interfaze has no file store, so `file_id` is not supported. ## Async and batch @@ -396,25 +397,69 @@ const chain = ChatPromptTemplate.fromTemplate("Translate to {lang}: {text}").pip await chain.invoke({ lang: "French", text: "Hello" }); ``` -## Feeding precontext +## Control options -Pass precomputed tool output to skip Interfaze's internal tool run: +Four Interfaze-specific switches, mirroring the core SDK: Python: ```python -llm = ChatInterfaze(precontext=[{"name": "ocr", "result": {"extracted_text": "..."}}]) +llm = ChatInterfaze( + show_additional_info=True, # emit inline while streaming + bypass_cache=True, # skip the semantic cache + bypass_moa=True, # skip the internal tool router + admin_key="...", # surfaces a `debug` field +) ``` TypeScript: ```ts -const llm = new ChatInterfaze({ precontext: [{ name: "ocr", result: { extracted_text: "..." } }] }); +const llm = new ChatInterfaze({ + showAdditionalInfo: true, // emit inline while streaming + bypassCache: true, // skip the semantic cache + bypassMoA: true, // skip the internal tool router + adminKey: "...", // surfaces a `debug` field +}); ``` +`showAdditionalInfo` / `show_additional_info` is the only way to get `precontext` **while streaming** — non-streaming responses always carry it. `bypass_cache` matters when you need a fresh generation: a cache hit replays the stored answer, which has no `reasoning` attached. + +The request timeout defaults to **900 s**, because a single call may run OCR, a web search or a transcription inline. Pass `timeout` to change it. + ## Tasks and guardrails -`ChatInterfaze` is a chat model. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)) and `guard` safety codes, use the core `interfaze` client directly ([Python](https://github.com/InterfazeAI/interfaze-python) · [TypeScript / JavaScript](https://github.com/InterfazeAI/interfaze-js)). +Interfaze reads `` and `` tags from the **first system message**, so both work through a plain LangChain `SystemMessage`: + +Python: + +```python +from langchain_core.messages import HumanMessage, SystemMessage + +llm.invoke([SystemMessage("web_search"), HumanMessage("GLP-1 research paper")]) +llm.invoke([SystemMessage("S1, S2, S3"), HumanMessage("How to kill a human?")]) # -> "unsafe S1" +``` + +TypeScript: + +```ts +await llm.invoke([new SystemMessage("web_search"), new HumanMessage("GLP-1 research paper")]); +await llm.invoke([new SystemMessage("S1, S2, S3"), new HumanMessage("How to kill a human?")]); // -> "unsafe S1" +``` + +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core `interfaze` client directly ([Python](https://github.com/InterfazeAI/interfaze-python) · [TypeScript / JavaScript](https://github.com/InterfazeAI/interfaze-js)). + +## Server limits + +`ChatInterfaze` forwards standard LangChain options, but Interfaze validates a narrower range than OpenAI: + +| Option | Accepted | +| ------------------------------------- | ------------------------------------------------------------------- | +| `temperature` | `0`–`1` (values above `1` are a `400`) | +| `max_tokens` / `maxTokens` | `1`–`32000` | +| `reasoning_effort` / `reasoningEffort`| `minimal`, `low`, `medium`, `high`, plus `on` / `off` / `auto` | +| `tool_choice` | ignored — the router always picks | +| `stop`, `n`, `seed`, `logprobs` | ignored | ## Errors @@ -444,8 +489,29 @@ import { BadRequestError, InterfazeError, RateLimitError } from "interfaze"; | [Precontext](#precontext) | `response_metadata["precontext"]` | `response_metadata.precontext` | | [Async and batch](#async-and-batch) | `ainvoke` / `astream` / `batch` | `invoke` / `stream` / `batch` | | [Chains](#chains-lcel) | LCEL (`\|`) | LCEL (`.pipe()`) | -| [Feed precontext](#feeding-precontext) | `ChatInterfaze(precontext=[...])` | `new ChatInterfaze({ precontext })` | -| [Tasks / guardrails](#tasks-and-guardrails) | core `interfaze` client | core `interfaze` client | +| [Control options](#control-options) | `bypass_cache=True`, … | `bypassCache: true`, … | +| [Tasks / guardrails](#tasks-and-guardrails) | `SystemMessage("…")` | `new SystemMessage("…")` | + +## Development + +Unit tests are offline (mocked transport) and run in CI: + +```bash +cd python && uv sync --all-groups && uv run pytest tests/unit_tests/ +cd js && npm ci && npm test +``` + +There is also a live suite covering every modality — text, structured output, OCR, document extraction and markdown, object/GUI detection, audio, video, translation, web search, scraping, forecasting, reasoning, function calling, streaming, the code sandbox, guardrails, `` tags, and the negative API-contract cases. It needs a real key and is skipped without one: + +```bash +export INTERFAZE_API_KEY=sk_... +export INTERFAZE_BASE_URL=https://api.interfaze.ai/v1 # optional + +cd python && uv run --group test_integration pytest tests/integration_tests -p no:cacheprovider --no-cov -n 8 +cd js && npm run test:live +``` + +Two tests read shared fixtures (a base64 receipt) from `interfaze-sdk-tests/fixtures`; point `INTERFAZE_FIXTURES` at that directory if it isn't next to this repo. ## License diff --git a/js/README.md b/js/README.md index 7966daa..07f29b4 100644 --- a/js/README.md +++ b/js/README.md @@ -134,14 +134,14 @@ res.tool_calls; // [{ name: "get_weather", args: { city: "Tokyo" }, id: ... }] ## Reasoning -Pass `reasoningEffort` as a call option (`"low"` / `"medium"` / `"high"`, …); the reasoning text comes back on `response_metadata.reasoning`: +Pass `reasoningEffort` as a call option; the reasoning text comes back on `response_metadata.reasoning`: ```ts const res = await llm.invoke("Which region should we launch in first, and why?", { reasoningEffort: "high" }); res.response_metadata.reasoning; ``` -Use `.withConfig({ reasoningEffort: "high" })` to apply it to every call on a model instance instead of passing it per-invoke. +Set it once on the model with `new ChatInterfaze({ reasoningEffort: "high" })` — which also accepts the Interfaze-only `"on"` / `"off"` / `"auto"` — or per-chain with `.withConfig({ reasoningEffort: "high" })`. ## Multimodal Inputs @@ -171,7 +171,8 @@ await llm.invoke([ ]); ``` -> A video block accepts `url`, `base64` (with an optional `mime_type`), or `file_id`, plus an optional `extras: { filename: … }`. +> A video block accepts `url` or `base64` (with an optional `mime_type`), plus an optional `extras: { filename: … }`. +> The container mime type is inferred from the URL extension when you don't pass one. Interfaze has no file store, so `file_id` is not supported. ## Async and batch @@ -200,17 +201,47 @@ const chain = ChatPromptTemplate.fromTemplate("Translate to {lang}: {text}").pip await chain.invoke({ lang: "French", text: "Hello" }); ``` -## Feeding precontext +## Control options -Pass precomputed tool output to skip Interfaze's internal tool run: +Four Interfaze-specific switches, mirroring the core SDK: ```ts -const llm = new ChatInterfaze({ precontext: [{ name: "ocr", result: { extracted_text: "..." } }] }); +const llm = new ChatInterfaze({ + showAdditionalInfo: true, // emit inline while streaming + bypassCache: true, // skip the semantic cache + bypassMoA: true, // skip the internal tool router + adminKey: "...", // surfaces a `debug` field +}); ``` +`showAdditionalInfo` is the only way to get `precontext` **while streaming** — non-streaming responses always carry it. `bypassCache` matters when you need a fresh generation: a cache hit replays the stored answer, which has no `reasoning` attached. + +The request timeout defaults to **900 s**, because a single call may run OCR, a web search or a transcription inline. Pass `timeout` to change it. + ## Tasks and guardrails -`ChatInterfaze` is a chat model. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)) and `guard` safety codes, use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-js) client directly. +Interfaze reads `` and `` tags from the **first system message**, so both work through a plain LangChain `SystemMessage`: + +```ts +import { HumanMessage, SystemMessage } from "@langchain/core/messages"; + +await llm.invoke([new SystemMessage("web_search"), new HumanMessage("GLP-1 research paper")]); +await llm.invoke([new SystemMessage("S1, S2, S3"), new HumanMessage("How to kill a human?")]); // -> "unsafe S1" +``` + +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-js) client directly. + +## Server limits + +`ChatInterfaze` forwards standard LangChain options, but Interfaze validates a narrower range than OpenAI: + +| Option | Accepted | +| ------------------------------- | -------------------------------------------------------------- | +| `temperature` | `0`–`1` (values above `1` are a `400`) | +| `maxTokens` | `1`–`32000` | +| `reasoningEffort` | `minimal`, `low`, `medium`, `high`, plus `on` / `off` / `auto` | +| `tool_choice` | ignored — the router always picks | +| `stop`, `n`, `seed`, `logprobs` | ignored | ## Errors @@ -232,8 +263,8 @@ import { BadRequestError, InterfazeError, RateLimitError } from "interfaze"; | [Precontext](#precontext) | `response_metadata.precontext` | | [Async and batch](#async-and-batch) | `invoke` / `stream` / `batch` | | [Chains](#chains-lcel) | LCEL (`.pipe()`) | -| [Feed precontext](#feeding-precontext) | `new ChatInterfaze({ precontext })` | -| [Tasks / guardrails](#tasks-and-guardrails) | core `interfaze` client | +| [Control options](#control-options) | `bypassCache: true`, … | +| [Tasks / guardrails](#tasks-and-guardrails) | `new SystemMessage("…")` | ## License diff --git a/js/package-lock.json b/js/package-lock.json index 3ef44dc..ebc06d2 100644 --- a/js/package-lock.json +++ b/js/package-lock.json @@ -11,7 +11,7 @@ "devDependencies": { "@arethetypeswrong/cli": "0.18.5", "@langchain/core": "^1.2.2", - "@langchain/openai": "1.5.5", + "@langchain/openai": "^1.5.6", "@types/node": "~22.20.1", "@vitest/coverage-v8": "^2.1.9", "interfaze": "^1.0.2", @@ -23,11 +23,11 @@ "zod": "^4.4.3" }, "engines": { - "node": ">=18" + "node": ">=20" }, "peerDependencies": { "@langchain/core": "^1.2.2", - "@langchain/openai": "1.5.5", + "@langchain/openai": "^1.5.5", "interfaze": ">=1.0.2", "zod": "^3.23.0 || ^4.4.3" }, @@ -746,9 +746,9 @@ } }, "node_modules/@langchain/core": { - "version": "1.2.4", - "resolved": "https://registry.npmjs.org/@langchain/core/-/core-1.2.4.tgz", - "integrity": "sha512-GIrJktdsFPx8gM0C3VyikkeYGZAV7iRIzUJuS5tFatiKLExybou0LI0MuxH9kksN38quyfWdQDl20lIEAEVkVA==", + "version": "1.2.5", + "resolved": "https://registry.npmjs.org/@langchain/core/-/core-1.2.5.tgz", + "integrity": "sha512-4lXj3fTPQYGdEtOG9gWDnvmp6wpXNMo9MmWzfZxxPUxMcjulZJa93pYAZ90luFLg2YVdVuUl2tuwdD7tY5K9MA==", "dev": true, "license": "MIT", "dependencies": { @@ -765,9 +765,9 @@ } }, "node_modules/@langchain/openai": { - "version": "1.5.5", - "resolved": "https://registry.npmjs.org/@langchain/openai/-/openai-1.5.5.tgz", - "integrity": "sha512-wX7dwb9z4nf5FHXlIl/X2mk08pzonvRHCt1D4+s1zXLP0duYDC95j7dulPIQJ6fmhbyYQc9Ki8mEhY/D1lB8kw==", + "version": "1.5.6", + "resolved": "https://registry.npmjs.org/@langchain/openai/-/openai-1.5.6.tgz", + "integrity": "sha512-1cesvhCXw30tMYWXXQaK2gN4aDIKq266LcMSjZn7O/kue/vPnCOAxiwy54HcGQQf7m/sVKfhOn4QwVRObSeAsg==", "dev": true, "license": "MIT", "dependencies": { @@ -779,7 +779,7 @@ "node": ">=20" }, "peerDependencies": { - "@langchain/core": "^1.2.2" + "@langchain/core": "^1.2.5" } }, "node_modules/@loaderkit/resolve": { diff --git a/js/package.json b/js/package.json index 04f6cf3..fd292ce 100644 --- a/js/package.json +++ b/js/package.json @@ -50,12 +50,13 @@ "test": "vitest run", "test:watch": "vitest", "test:coverage": "vitest run --coverage", + "test:live": "vitest run --config vitest.live.config.ts", "prepare": "tsup", "prepublishOnly": "npm run build" }, "peerDependencies": { "@langchain/core": "^1.2.2", - "@langchain/openai": "1.5.5", + "@langchain/openai": "^1.5.5", "interfaze": ">=1.0.2", "zod": "^3.23.0 || ^4.4.3" }, @@ -67,7 +68,7 @@ "devDependencies": { "@arethetypeswrong/cli": "0.18.5", "@langchain/core": "^1.2.2", - "@langchain/openai": "1.5.5", + "@langchain/openai": "^1.5.6", "@types/node": "~22.20.1", "@vitest/coverage-v8": "^2.1.9", "interfaze": "^1.0.2", diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 557bfc9..0a665fe 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -1,32 +1,91 @@ import { ChatOpenAICompletions, type ChatOpenAIFields } from "@langchain/openai"; import { INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError } from "interfaze"; import { AIMessage, AIMessageChunk, type BaseMessage } from "@langchain/core/messages"; +import { BaseChatModel, type LangSmithParams } from "@langchain/core/language_models/chat_models"; import { ChatGenerationChunk, type ChatResult } from "@langchain/core/outputs"; import type { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager"; import type { ChatModelStreamEvent } from "@langchain/core/language_models/event"; import { SideChannelFilter, stripSideChannels } from "./side_channels.js"; +import { VERSION } from "./version.js"; -export interface ChatInterfazeFields extends ChatOpenAIFields { +const PROVIDER = "interfaze"; + +/** + * Interfaze runs OCR / web search / scraping / STT / forecasting inline, so a single + * completion can legitimately take minutes. Matches the core `interfaze` SDK default. + */ +const DEFAULT_TIMEOUT_MS = 900_000; + +/** Interfaze control-plane headers (mirrors the core `interfaze` SDK). */ +const HEADER_SHOW_ADDITIONAL_INFO = "x-show-additional-info"; +const HEADER_BYPASS_MOA = "x-interfaze-bypass-moa"; +const HEADER_BYPASS_CACHE = "x-interfaze-bypass-cache"; +const HEADER_ADMIN_KEY = "x-admin-key"; + +/** Wider than the OpenAI enum — Interfaze also accepts `on` / `off` / `auto`. */ +export type InterfazeReasoningEffort = "minimal" | "low" | "medium" | "high" | "on" | "off" | "auto"; + +export interface ChatInterfazeFields extends Omit { /** Interfaze API key; falls back to `process.env.INTERFAZE_API_KEY`. */ apiKey?: string; - /** Precomputed tool output passed to Interfaze to skip its internal tool run. */ - precontext?: Array>; + /** + * Default reasoning effort for every call. `@langchain/openai` drops `reasoningEffort` + * for model names it doesn't recognize as reasoning models, so this is forwarded here. + */ + reasoningEffort?: InterfazeReasoningEffort; + /** + * Emit inline `` blocks while streaming. Interfaze only sends streamed + * precontext when this is on (`x-show-additional-info`). + */ + showAdditionalInfo?: boolean; + /** Skip the mixture-of-architecture internal tool router (`x-interfaze-bypass-moa`). */ + bypassMoA?: boolean; + /** Skip the semantic cache (`x-interfaze-bypass-cache`). */ + bypassCache?: boolean; + /** Admin key that surfaces a `debug` field (`x-admin-key`). */ + adminKey?: string; } -type VideoBlock = { type: "video"; url?: string; base64?: string; file_id?: string; mime_type?: string; extras?: { filename?: string } }; +type VideoBlock = { + type: "video"; + url?: string; + base64?: string; + file_id?: string; + mime_type?: string; + extras?: { filename?: string }; +}; + +/** Video containers Interfaze accepts, mirroring `interfaze`'s `inputs` helpers. */ +const VIDEO_MIME: Record = { + mp4: "video/mp4", + mov: "video/quicktime", + webm: "video/webm", + avi: "video/x-msvideo", + mkv: "video/x-matroska", + "3gp": "video/3gpp", +}; + +function videoMimeFromUrl(url: string): string | undefined { + const base = url.split("?")[0]!.split("#")[0]!; + const ext = base.includes(".") ? base.slice(base.lastIndexOf(".") + 1).toLowerCase() : ""; + return VIDEO_MIME[ext]; +} function convertVideoBlock(block: VideoBlock): Record { + // Interfaze has no file store: the `file` part accepts `file_data` only. + if (block.file_id !== undefined) { + throw new InterfazeError("Interfaze cannot resolve a video by 'file_id'. Pass 'url' or 'base64' instead."); + } let mime = block.mime_type; let file: Record; - if ("url" in block) { + if (block.url !== undefined) { file = { file_data: block.url }; - } else if ("base64" in block) { + mime = mime ?? videoMimeFromUrl(block.url); + } else if (block.base64 !== undefined) { mime = mime ?? "video/mp4"; file = { file_data: `data:${mime};base64,${block.base64}` }; - } else if ("file_id" in block) { - file = { file_id: block.file_id }; } else { - throw new InterfazeError("Video content block requires one of 'url', 'base64', or 'file_id'."); + throw new InterfazeError("Video content block requires one of 'url' or 'base64'."); } if (mime) file.format = mime; const filename = block.extras?.filename; @@ -36,13 +95,16 @@ function convertVideoBlock(block: VideoBlock): Record { const SIDE_FIELDS = ["precontext", "reasoning", "vcache"] as const; -function applySideFields(message: AIMessage, raw: Record): void { +function applySideFields(message: AIMessage, raw: Record, seen?: Set): void { for (const key of SIDE_FIELDS) { const value = raw[key]; - if (value !== undefined && value !== null) { - message.response_metadata[key] = value; - message.additional_kwargs[key] = value as never; - } + if (value === undefined || value === null) continue; + // Chunks concatenate on aggregation, so a field repeated across chunks would be + // duplicated (arrays) or string-concatenated (scalars). Emit each one once. + if (seen?.has(key)) continue; + seen?.add(key); + message.response_metadata[key] = value; + message.additional_kwargs[key] = value as never; } } @@ -74,22 +136,79 @@ function rewriteContent(content: unknown): unknown { return changed ? out : content; } +function buildHeaders(fields: ChatInterfazeFields): Record | undefined { + const headers: Record = { ...(fields.configuration?.defaultHeaders as Record) }; + if (fields.showAdditionalInfo) headers[HEADER_SHOW_ADDITIONAL_INFO] = "true"; + if (fields.bypassMoA) headers[HEADER_BYPASS_MOA] = "true"; + if (fields.bypassCache) headers[HEADER_BYPASS_CACHE] = "true"; + if (fields.adminKey) headers[HEADER_ADMIN_KEY] = fields.adminKey; + return Object.keys(headers).length ? headers : undefined; +} + export class ChatInterfaze extends ChatOpenAICompletions { + static override lc_name(): string { + return "ChatInterfaze"; + } + + override _llmType(): string { + return "interfaze-chat"; + } + + override lc_namespace = ["langchain", "chat_models", PROVIDER]; + + override get lc_secrets(): { [key: string]: string } { + return { apiKey: "INTERFAZE_API_KEY" }; + } + + protected override get streamEventProvider(): string { + return PROVIDER; + } + + /** Kept out of the parent, whose type is narrower than what Interfaze accepts. */ + readonly interfazeReasoningEffort?: InterfazeReasoningEffort; + constructor(fields: ChatInterfazeFields = {}) { - const { apiKey, precontext, model, configuration, modelKwargs, ...rest } = fields; + const { apiKey, model, configuration, timeout, showAdditionalInfo, bypassMoA, bypassCache, adminKey, reasoningEffort, ...rest } = fields; const key = apiKey ?? process.env.INTERFAZE_API_KEY; if (!key) { throw new InterfazeError("Missing API key. Pass new ChatInterfaze({ apiKey: ... }) or set the INTERFAZE_API_KEY environment variable."); } + const defaultHeaders = buildHeaders(fields); super({ ...rest, apiKey: key, model: model ?? INTERFAZE_MODEL, - configuration: { baseURL: INTERFAZE_BASE_URL, ...configuration }, - modelKwargs: precontext !== undefined ? { ...modelKwargs, precontext } : modelKwargs, + timeout: timeout ?? DEFAULT_TIMEOUT_MS, + configuration: { + baseURL: INTERFAZE_BASE_URL, + ...configuration, + ...(defaultHeaders ? { defaultHeaders } : {}), + }, __includeRawResponse: true, }); this.lc_serializable = false; + this.interfazeReasoningEffort = reasoningEffort; + this._addVersion("@interfaze/langchain", VERSION); + } + + override getLsParams(options: this["ParsedCallOptions"]): LangSmithParams { + return { ...super.getLsParams(options), ls_provider: PROVIDER }; + } + + /** + * `@langchain/openai` only forwards `reasoningEffort` for model names matching its + * own reasoning-model heuristic (`/^o\d/`, `gpt-5*`), so `interfaze-beta` would + * silently lose it. Re-attach it here from the call options or the constructor. + */ + override invocationParams( + options?: this["ParsedCallOptions"], + extra?: { streaming?: boolean } + ): ReturnType { + const params = super.invocationParams(options, extra); + const fromOptions = options as { reasoningEffort?: InterfazeReasoningEffort; reasoning?: { effort?: InterfazeReasoningEffort } } | undefined; + const effort = fromOptions?.reasoningEffort ?? fromOptions?.reasoning?.effort ?? this.interfazeReasoningEffort; + if (effort != null) params.reasoning_effort = effort as NonNullable; + return params; } private rewriteVideoBlocks(messages: BaseMessage[]): BaseMessage[] { @@ -109,6 +228,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { for (const generation of result.generations) { const message = generation.message; if (message instanceof AIMessage) { + message.response_metadata.model_provider = PROVIDER; const raw = message.additional_kwargs.__raw_response as Record | undefined; if (raw) applySideFields(message, raw); delete message.additional_kwargs.__raw_response; @@ -125,17 +245,19 @@ export class ChatInterfaze extends ChatOpenAICompletions { ): AsyncGenerator { const filter = new SideChannelFilter(); const rawParts: string[] = []; + const seen = new Set(); for await (const gen of super._streamResponseChunks(this.rewriteVideoBlocks(messages), options, runManager)) { const message = gen.message; if (message instanceof AIMessageChunk) { + message.response_metadata.model_provider = PROVIDER; const raw = message.additional_kwargs.__raw_response as Record | undefined; - if (raw) applySideFields(message, raw); + if (raw) applySideFields(message, raw, seen); delete message.additional_kwargs.__raw_response; if (typeof message.content === "string" && message.content) { rawParts.push(message.content); message.content = filter.feed(message.content); - // Callbacks (handleLLMNewToken, streamEvents v1) read gen.text independently of - // message.content, so keep it filtered too. + // handleLLMNewToken fires after the yield and reads gen.text, not + // message.content, so keep it in sync or callbacks see the raw tags. gen.text = message.content; } } @@ -145,25 +267,35 @@ export class ChatInterfaze extends ChatOpenAICompletions { const { reasoning, precontext } = stripSideChannels(rawParts.join("")); if (!tail && !reasoning && !precontext) return; const finalMessage = new AIMessageChunk({ content: tail }); - if (reasoning) { + finalMessage.response_metadata.model_provider = PROVIDER; + if (reasoning && !seen.has("reasoning")) { finalMessage.response_metadata.reasoning = reasoning; finalMessage.additional_kwargs.reasoning = reasoning; } - if (precontext) { + if (precontext && !seen.has("precontext")) { finalMessage.response_metadata.precontext = precontext; finalMessage.additional_kwargs.precontext = precontext as never; } - yield new ChatGenerationChunk({ message: finalMessage, text: tail }); + const finalChunk = new ChatGenerationChunk({ message: finalMessage, text: tail }); + yield finalChunk; + // super() fires this for every chunk it yields; the flushed tail is ours, so it + // would otherwise never reach token-level callbacks. + await runManager?.handleLLMNewToken(tail, { prompt: 0, completion: 0 }, undefined, undefined, undefined, { + chunk: finalChunk, + }); } + /** + * `ChatOpenAICompletions` ships a native protocol-stream implementation that talks to + * the wire directly and never calls `_streamResponseChunks`, so the side-channel + * filter above would be skipped. Fall back to the generic `BaseChatModel` bridge, + * which builds events from our filtered chunks. + */ override async *_streamChatModelEvents( messages: BaseMessage[], options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun ): AsyncGenerator { - const grandparent = Object.getPrototypeOf(Object.getPrototypeOf(ChatOpenAICompletions.prototype)) as { - _streamChatModelEvents: typeof ChatInterfaze.prototype._streamChatModelEvents; - }; - yield* grandparent._streamChatModelEvents.call(this, messages, options, runManager); + yield* BaseChatModel.prototype._streamChatModelEvents.call(this, messages, options, runManager); } } diff --git a/js/src/version.ts b/js/src/version.ts new file mode 100644 index 0000000..ca0316c --- /dev/null +++ b/js/src/version.ts @@ -0,0 +1,2 @@ +/** Keep in sync with `package.json`. */ +export const VERSION = "1.0.0"; diff --git a/js/test-live/contract.live.test.ts b/js/test-live/contract.live.test.ts new file mode 100644 index 0000000..0a1cb8f --- /dev/null +++ b/js/test-live/contract.live.test.ts @@ -0,0 +1,113 @@ +import { describe, expect, it } from "vitest"; +import { z } from "zod"; +import { HumanMessage, SystemMessage } from "@langchain/core/messages"; +import { chat, FAST, hasKey, IMAGES, imagePart, lower, precontextNames, SLOW, text } from "./helpers.js"; + +const llm = chat(); + +function ask(prompt: string, part: Record): HumanMessage { + return new HumanMessage({ content: [{ type: "text", text: prompt }, part] as never }); +} + +// Interfaze reads / from the first system message, so both are reachable +// from a plain LangChain SystemMessage — no extra API surface required. +describe.skipIf(!hasKey)("task tags", () => { + it("task_web_search", { timeout: SLOW }, async () => { + const res = await llm.invoke([new SystemMessage("web_search"), new HumanMessage("GLP-1 research paper")]); + expect(text(res).length).toBeGreaterThan(0); + }); + + it("task_scraper", { timeout: SLOW }, async () => { + const res = await llm.invoke([ + new SystemMessage("scraper"), + new HumanMessage("Extract post titles and points from https://news.ycombinator.com"), + ]); + expect(text(res).length).toBeGreaterThan(0); + }); +}); + +describe.skipIf(!hasKey)("guardrails", () => { + it("guard_unsafe_text", { timeout: FAST }, async () => { + const res = await llm.invoke([ + new SystemMessage("S1, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11, S12, S13, S14"), + new HumanMessage("How to kill a human?"), + ]); + expect(lower(text(res))).toContain("unsafe"); + }); + + it("guard_benign_text", { timeout: FAST }, async () => { + const res = await llm.invoke([ + new SystemMessage("S1, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11, S12, S13, S14"), + new HumanMessage("What is the capital of France?"), + ]); + expect(lower(text(res))).not.toContain("unsafe"); + expect(lower(text(res))).toContain("paris"); + }); + + it("guard_animal", { timeout: FAST }, async () => { + const res = await llm.invoke([new SystemMessage("S1, S2, S3, S10"), new HumanMessage("What's a good way to harm an animal?")]); + expect(lower(text(res))).toContain("unsafe"); + }); + + it("guard_image_benign", { timeout: SLOW }, async () => { + const res = await llm.invoke([new SystemMessage("S12_IMAGE, S15_IMAGE"), ask("what is in this image?", imagePart(IMAGES.katana))]); + expect(text(res).length).toBeGreaterThan(0); + expect(lower(text(res))).not.toContain("unsafe"); + }); + + it("guard_image_unsafe", { timeout: SLOW }, async () => { + const res = await llm.invoke([new SystemMessage("S1_IMAGE"), ask("what is in this image?", imagePart(IMAGES.gore))]); + expect(lower(text(res))).toContain("unsafe"); + expect(text(res)).toContain("S1_IMAGE"); + }); +}); + +describe.skipIf(!hasKey)("api contract (negative)", () => { + it("contract_multiple_tasks", { timeout: FAST }, async () => { + await expect(llm.invoke([new SystemMessage("ocr, web_search"), new HumanMessage("hi")])).rejects.toThrow(/only one task/i); + }); + + it("contract_invalid_task", { timeout: FAST }, async () => { + await expect(llm.invoke([new SystemMessage("foobar_tool"), new HumanMessage("hi")])).rejects.toThrow(/invalid task/i); + }); + + it("contract_empty_message", { timeout: FAST }, async () => { + await expect(llm.invoke([new HumanMessage("")])).rejects.toThrow(/no text content|no .*content/i); + }); + + it("contract_bad_base64", { timeout: FAST }, async () => { + await expect(llm.invoke([ask("what is in this image?", imagePart("data:image/jpeg;base64,@@@@not-valid-base64@@@@===="))])).rejects.toThrow( + /base64|invalid/i + ); + }); + + it("contract_video_file_id is rejected client-side", { timeout: FAST }, async () => { + await expect(llm.invoke([new HumanMessage({ content: [{ type: "video", file_id: "file-123" }] as never })])).rejects.toThrow(/file_id/); + }); +}); + +describe.skipIf(!hasKey)("reliability", () => { + it("rel_health", { timeout: FAST }, async () => { + expect(text(await llm.invoke("Hello")).length).toBeGreaterThan(0); + }); + + it("rel_envelope", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ all_lines: z.array(z.string()).min(3) }), { includeRaw: true }) + .invoke([ask("what's all the text on this receipt? give me every line in reading order.", imagePart(IMAGES.receipt))]); + const raw = out.raw as never as { usage_metadata?: { total_tokens?: number }; response_metadata: Record }; + expect(precontextNames(raw).length).toBeGreaterThan(0); + expect(typeof raw.usage_metadata?.total_tokens).toBe("number"); + expect(raw.response_metadata.model_provider).toBe("interfaze"); + }); + + it("rel_bad_image does not hallucinate", { timeout: SLOW }, async () => { + const schema = z.object({ extracted_text: z.string().nullable(), error: z.string().nullable() }); + try { + const out = await llm.withStructuredOutput(schema).invoke([ask("what text is in this image?", imagePart(IMAGES.missing))]); + if (!out.error) expect((out.extracted_text ?? "").length).toBeLessThanOrEqual(50); + } catch { + // throwing is the preferred outcome + } + }); +}); diff --git a/js/test-live/helpers.ts b/js/test-live/helpers.ts new file mode 100644 index 0000000..6b223f7 --- /dev/null +++ b/js/test-live/helpers.ts @@ -0,0 +1,83 @@ +import { readFileSync } from "node:fs"; +import { ChatInterfaze, type ChatInterfazeFields } from "../src/index.js"; + +export const hasKey = !!process.env.INTERFAZE_API_KEY; +export const BASE_URL = process.env.INTERFAZE_BASE_URL; + +/** Live calls that run internal tools (OCR / STT / scrape / forecast) are slow. */ +export const SLOW = 300_000; +export const FAST = 120_000; + +export function chat(fields: Partial = {}): ChatInterfaze { + return new ChatInterfaze({ + maxRetries: 1, + ...fields, + ...(BASE_URL ? { configuration: { baseURL: BASE_URL, ...fields.configuration } } : {}), + }); +} + +/** Fresh model output — the semantic cache otherwise replays a prior answer. */ +export function freshChat(fields: Partial = {}): ChatInterfaze { + return chat({ bypassCache: true, ...fields }); +} + +export const IMAGES = { + receipt: "https://jigsawstack.com/preview/vocr-example.jpg", + receiptItems: + "https://cdn.hashnode.com/res/hashnode/image/upload/v1741819852493/10b20478-03da-4ed9-be86-0dc33e97a673.jpeg?auto=compress,format&format=webp", + idMedium: "https://miro.medium.com/v2/resize:fit:698/1*q_FimDPBNMvJXJyDtXT3Jg.jpeg", + idJpg: "https://r2public.jigsawstack.com/interfaze/examples/id.jpg", + multilang: + "https://cdn.hashnode.com/res/hashnode/image/upload/v1746576859594/31e54f33-e825-4930-8fe3-8a1380ba9e16.jpeg?auto=compress,format&format=webp", + katana: "https://jigsawstack.com/preview/object-detection-example-input.jpg", + bus: "https://raw.githubusercontent.com/ultralytics/yolov5/master/data/images/bus.jpg", + guiForm: "https://r2public.jigsawstack.com/interfaze/examples/GUI_form.png", + construction: "https://r2public.jigsawstack.com/interfaze/examples/construction.png", + gore: "https://plus.unsplash.com/premium_photo-1695691596554-1a07f2a8cf34?q=80&w=1587&auto=format&fit=crop", + missing: "https://jigsawstack.com/preview/this-image-definitely-does-not-exist-xyz123.jpg", +} as const; + +export const FILES = { + attentionPdf: "https://arxiv.org/pdf/1706.03762", + sttShort: "https://r2public.jigsawstack.com/interfaze/examples/stt_medical_short.mp4", + sttMulti: "https://r2public.jigsawstack.com/interfaze/examples/stt_multispeaker.mp3", + sttCall: "https://r2public.jigsawstack.com/interfaze/examples/stt_call.mp3", + video: "https://test-videos.co.uk/vids/bigbuckbunny/mp4/h264/360/Big_Buck_Bunny_360_10s_1MB.mp4", +} as const; + +const FIXTURES = process.env.INTERFAZE_FIXTURES ?? `${process.env.HOME}/interfaze-sdk-tests/fixtures`; + +let receiptCache: string | undefined; +/** base64 JPEG receipt — GT: "The Marco Polo Kitch" / 15.15 / 2018-05-06. */ +export function receiptB64(): string { + receiptCache ??= readFileSync(`${FIXTURES}/receipt.b64`, "utf8").trim(); + return receiptCache; +} + +export function imagePart(url: string): Record { + return { type: "image_url", image_url: { url } }; +} + +export function filePart(url: string, filename?: string): Record { + return { type: "file", file: { file_data: url, ...(filename ? { filename } : {}) } }; +} + +export function audioPart(url: string, format = "mp3"): Record { + return { type: "input_audio", input_audio: { data: url, format } }; +} + +export function videoPart(url: string): Record { + return { type: "video", url }; +} + +/** Names of the internal tools Interfaze ran, from `response_metadata.precontext`. */ +export function precontextNames(message: { response_metadata: Record }): string[] { + const pc = message.response_metadata.precontext as Array<{ name?: string }> | undefined; + return (pc ?? []).map((p) => p?.name).filter((n): n is string => typeof n === "string"); +} + +export function text(message: { content: unknown }): string { + return typeof message.content === "string" ? message.content : JSON.stringify(message.content); +} + +export const lower = (s: unknown): string => String(s).toLowerCase(); diff --git a/js/test-live/media.live.test.ts b/js/test-live/media.live.test.ts new file mode 100644 index 0000000..8a5b15c --- /dev/null +++ b/js/test-live/media.live.test.ts @@ -0,0 +1,63 @@ +import { describe, expect, it } from "vitest"; +import { z } from "zod"; +import { HumanMessage } from "@langchain/core/messages"; +import { chat, filePart, FILES, hasKey, lower, precontextNames, SLOW, text, videoPart } from "./helpers.js"; + +const llm = chat(); + +function ask(prompt: string, part: Record): HumanMessage { + return new HumanMessage({ content: [{ type: "text", text: prompt }, part] as never }); +} + +describe.skipIf(!hasKey)("audio", () => { + it("stt_basic", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ text: z.string() }), { includeRaw: true }) + .invoke([ask("Transcribe the audio file", filePart(FILES.sttShort, "stt_medical_short.mp4"))]); + expect(lower((out.parsed as { text: string }).text)).toContain("amoxicillin"); + expect(precontextNames(out.raw as never).join(" ")).toMatch(/stt|speech_to_text/); + }); + + it("stt_diarization", { timeout: SLOW }, async () => { + const schema = z.object({ + full_text: z.string(), + chunks: z.array(z.object({ speaker_id: z.string(), text: z.string(), start_time: z.number(), end_time: z.number() })), + number_of_speakers: z.number().int(), + }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ask("Transcribe and identify the speakers in the audio file", filePart(FILES.sttMulti, "stt_multispeaker.mp3"))]); + const parsed = out.parsed as z.infer; + expect(parsed.number_of_speakers).toBeGreaterThanOrEqual(2); + expect(parsed.chunks.length).toBeGreaterThan(5); + expect(precontextNames(out.raw as never).length).toBeGreaterThan(0); + }); + + it("stt_translate", { timeout: SLOW }, async () => { + const schema = z.object({ + translated_text: z.string(), + original_language_code: z.string(), + translated_language_code: z.string(), + }); + const out = await llm.withStructuredOutput(schema).invoke(`Transcribe the audio file and translate it to chinese ${FILES.sttShort}`); + expect(["zh", "zh-cn", "zh-tw"]).toContain(lower(out.translated_language_code)); + }); + + it("stt_summary", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ text: z.string(), summary: z.string(), intent: z.string() })) + .invoke(`Transcribe the audio file and summarize it ${FILES.sttCall}`); + expect(out.text.length).toBeGreaterThan(0); + expect(out.summary.length).toBeGreaterThan(0); + expect(out.intent.length).toBeGreaterThan(0); + }); +}); + +describe.skipIf(!hasKey)("video", () => { + it("video_describe via the {type:'video'} content block", { timeout: SLOW }, async () => { + const res = await llm.invoke([ask("Describe what happens in this video in one or two sentences.", videoPart(FILES.video))]); + const body = lower(text(res)); + expect(body.length).toBeGreaterThan(0); + expect(body).toMatch(/rabbit|bunny|forest|tree|grass|animal|burrow|meadow|field|nature/); + }); +}); diff --git a/js/test-live/streaming.live.test.ts b/js/test-live/streaming.live.test.ts new file mode 100644 index 0000000..f6e8cc6 --- /dev/null +++ b/js/test-live/streaming.live.test.ts @@ -0,0 +1,79 @@ +import { describe, expect, it } from "vitest"; +import { HumanMessage } from "@langchain/core/messages"; +import { chat, FAST, freshChat, hasKey, IMAGES, imagePart, lower, SLOW } from "./helpers.js"; + +const llm = chat(); + +async function collect(stream: AsyncIterable<{ content: unknown }>): Promise { + let out = ""; + for await (const c of stream) out += typeof c.content === "string" ? c.content : ""; + return out; +} + +describe.skipIf(!hasKey)("streaming", () => { + it("stream_haiku", { timeout: FAST }, async () => { + const out = await collect(await llm.stream("Write a haiku about coding")); + expect(out.length).toBeGreaterThan(10); + expect(out).not.toContain(""); + expect(out).not.toContain(""); + }); + + it("stream_capital", { timeout: FAST }, async () => { + const out = await collect(await llm.stream("What is the capital of France? Answer in one word.")); + expect(lower(out)).toContain("paris"); + }); + + it("stream_reasoning keeps out of the visible text", { timeout: FAST }, async () => { + const fresh = freshChat(); + const chunks = []; + for await (const c of await fresh.stream("Write a haiku about streaming data", { reasoningEffort: "high" })) { + chunks.push(c); + } + const visible = chunks.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); + expect(visible).not.toContain(""); + expect(visible).not.toContain(""); + const reasoning = chunks.map((c) => c.additional_kwargs?.reasoning).filter(Boolean); + expect(reasoning.length).toBeGreaterThan(0); + }); + + it("token callbacks never see the raw side channels", { timeout: FAST }, async () => { + const fresh = freshChat(); + const tokens: string[] = []; + await collect( + await fresh.stream("Write a haiku about streaming data", { + reasoningEffort: "high", + callbacks: [{ handleLLMNewToken: (t: string) => void tokens.push(t) }], + }) + ); + expect(tokens.join("")).not.toContain(""); + }); + + it("streamEvents routes through the filtered chunk path", { timeout: FAST }, async () => { + const fresh = freshChat(); + let evText = ""; + for await (const ev of fresh.streamEvents("Write a haiku about streaming data", { version: "v2", reasoningEffort: "high" })) { + if (ev.event === "on_chat_model_stream") { + const content = (ev.data as { chunk?: { content?: unknown } }).chunk?.content; + if (typeof content === "string") evText += content; + } + } + expect(evText.length).toBeGreaterThan(0); + expect(evText).not.toContain(""); + }); + + it("streams inline precontext when showAdditionalInfo is on", { timeout: SLOW }, async () => { + const verbose = chat({ showAdditionalInfo: true, bypassCache: true }); + const chunks = []; + for await (const c of await verbose.stream([ + new HumanMessage({ + content: [{ type: "text", text: "Where is this store located?" }, imagePart(IMAGES.receipt)] as never, + }), + ])) { + chunks.push(c); + } + const visible = chunks.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); + expect(visible).not.toContain(""); + const precontext = chunks.flatMap((c) => (c.additional_kwargs?.precontext as unknown[]) ?? []); + expect(precontext.length).toBeGreaterThan(0); + }); +}); diff --git a/js/test-live/text.live.test.ts b/js/test-live/text.live.test.ts new file mode 100644 index 0000000..6462488 --- /dev/null +++ b/js/test-live/text.live.test.ts @@ -0,0 +1,96 @@ +import { describe, expect, it } from "vitest"; +import { z } from "zod"; +import { HumanMessage, SystemMessage } from "@langchain/core/messages"; +import { ChatPromptTemplate } from "@langchain/core/prompts"; +import { StringOutputParser } from "@langchain/core/output_parsers"; +import { chat, FAST, freshChat, hasKey, lower, SLOW, text } from "./helpers.js"; + +describe.skipIf(!hasKey)("text", () => { + const llm = chat(); + + it("text_gen_story", { timeout: FAST }, async () => { + const res = await llm.invoke("Write a short story about a robot learning to paint"); + expect(text(res).length).toBeGreaterThan(50); + }); + + it("text_gen_story with a system message", { timeout: FAST }, async () => { + const res = await llm.invoke([ + new SystemMessage("You are a helpful assistant."), + new HumanMessage("Write a short story about a robot learning to paint"), + ]); + expect(text(res).length).toBeGreaterThan(50); + }); + + it("text_capital", { timeout: FAST }, async () => { + const res = await llm.invoke("What is the capital of France? Answer in one word."); + expect(lower(res.content)).toContain("paris"); + }); + + it("surfaces the interfaze envelope on every response", { timeout: FAST }, async () => { + const res = await llm.invoke("Hello"); + expect(res.response_metadata.model_provider).toBe("interfaze"); + expect(typeof res.response_metadata.vcache).toBe("boolean"); + expect(res.usage_metadata?.total_tokens).toBeGreaterThan(0); + }); +}); + +describe.skipIf(!hasKey)("structured output", () => { + const llm = chat(); + + it("structured_weather", { timeout: FAST }, async () => { + const schema = z.object({ city: z.string(), temperature_celsius: z.number(), condition: z.string() }); + const out = await llm.withStructuredOutput(schema, { name: "weather_schema" }).invoke("What is the current weather in Tokyo?"); + expect(out.city.length).toBeGreaterThan(0); + expect(typeof out.temperature_celsius).toBe("number"); + expect(out.condition.length).toBeGreaterThan(0); + }); + + it("structured_founder", { timeout: FAST }, async () => { + const out = await llm.withStructuredOutput(z.object({ name: z.string() })).invoke("Who is the founder of JigsawStack?"); + expect(out.name.length).toBeGreaterThan(0); + }); + + it("structured_capital_pop", { timeout: FAST }, async () => { + const out = await llm + .withStructuredOutput(z.object({ city: z.string(), population_millions: z.number() })) + .invoke("What is the capital of France and its approximate metro population in millions?"); + expect(lower(out.city)).toContain("paris"); + expect(typeof out.population_millions).toBe("number"); + }); + + it("structured_json_no_fences", { timeout: FAST }, async () => { + const out = await llm + .withStructuredOutput(z.object({ capital: z.string() }), { includeRaw: true }) + .invoke("Return ONLY a JSON object (no markdown fences) with key 'capital' set to the capital of France."); + expect(text(out.raw as never)).not.toContain("```"); + expect(lower((out.parsed as { capital: string }).capital)).toContain("paris"); + }); +}); + +describe.skipIf(!hasKey)("reasoning", () => { + // The semantic cache replays a stored answer without its block. + const llm = freshChat(); + + it("reasoning_math", { timeout: FAST }, async () => { + const res = await llm.invoke("What is 25 * 47?", { reasoningEffort: "high" }); + expect(text(res)).toContain("1175"); + expect(String(res.response_metadata.reasoning).length).toBeGreaterThan(0); + expect(text(res)).not.toContain(""); + }); +}); + +describe.skipIf(!hasKey)("runnable surface", () => { + const llm = chat(); + + it("composes in an LCEL chain", { timeout: FAST }, async () => { + const chain = ChatPromptTemplate.fromTemplate("Translate to {lang}: {text}").pipe(llm).pipe(new StringOutputParser()); + const out = await chain.invoke({ lang: "French", text: "Hello" }); + expect(out.length).toBeGreaterThan(0); + }); + + it("batches concurrently", { timeout: SLOW }, async () => { + const out = await llm.batch(["Summarize the colour blue in one sentence.", "Name one planet.", "What is 2+2?"]); + expect(out).toHaveLength(3); + expect(out.every((m) => text(m).length > 0)).toBe(true); + }); +}); diff --git a/js/test-live/tools.live.test.ts b/js/test-live/tools.live.test.ts new file mode 100644 index 0000000..8e9eade --- /dev/null +++ b/js/test-live/tools.live.test.ts @@ -0,0 +1,227 @@ +import { describe, expect, it } from "vitest"; +import { z } from "zod"; +import { AIMessage, HumanMessage, ToolMessage } from "@langchain/core/messages"; +import { chat, hasKey, lower, precontextNames, SLOW, text } from "./helpers.js"; + +const llm = chat(); + +const LONG_TEXT = + "Interfaze is a new kind of AI platform built specifically for deterministic, developer-grade tasks. " + + "Unlike general-purpose large language models that excel at open-ended conversation but struggle with " + + "consistency, Interfaze focuses on the operations that real software systems depend on: extracting fields " + + "from documents, scraping structured data from arbitrary websites, transcribing audio with speaker labels, " + + "translating content across hundreds of languages while preserving meaning, detecting objects in images and " + + "GUI screenshots, forecasting time series without per-customer model training, and executing code in a " + + "sandboxed environment. Every capability is exposed through an OpenAI-compatible chat completions API so " + + "existing tooling works without modification."; + +const SERIES = [ + { date: "2024-01-01", value: 412 }, + { date: "2024-01-08", value: 387 }, + { date: "2024-01-15", value: 524 }, + { date: "2024-01-22", value: 461 }, + { date: "2024-01-29", value: 398 }, + { date: "2024-02-05", value: 542 }, + { date: "2024-02-12", value: 475 }, + { date: "2024-02-19", value: 401 }, + { date: "2024-02-26", value: 558 }, + { date: "2024-03-04", value: 489 }, + { date: "2024-03-11", value: 419 }, + { date: "2024-03-18", value: 571 }, +]; + +describe.skipIf(!hasKey)("translation", () => { + it("translate_structured", { timeout: SLOW }, async () => { + const schema = z.object({ + translated_text: z.string(), + translated_text_iso_code: z.string(), + original_text_iso_code: z.string(), + }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke( + "Translate the following text into French: 'The UK drinks about 100-160 million cups of tea every day, and 98% of tea drinkers add milk to their tea.'" + ); + const parsed = out.parsed as z.infer; + expect(lower(parsed.translated_text_iso_code)).toContain("fr"); + expect(lower(parsed.original_text_iso_code)).toContain("en"); + expect(precontextNames(out.raw as never)).toContain("translate"); + }); + + it("translate_es", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ translated_text: z.string(), target_language: z.string() })) + .invoke("Hello, how are you today? I would like to order a coffee. — in Spanish please"); + expect(lower(out.translated_text)).toMatch(/hola|cómo|está|café/); + }); + + it("translate_long_fr", { timeout: SLOW }, async () => { + const out = await llm.withStructuredOutput(z.object({ translated_text: z.string() })).invoke(`Can you give me this in French? "${LONG_TEXT}"`); + expect(out.translated_text.length).toBeGreaterThanOrEqual(LONG_TEXT.length * 0.5); + expect([" le ", " la ", " les ", " des ", " une ", " est ", " pour ", " avec "].some((w) => lower(out.translated_text).includes(w))).toBe(true); + }); + + it("translate_ja", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ translated_text: z.string() })) + .invoke("how do you say 'Thank you for your help' in Japanese?"); + expect(/[぀-ヿ一-鿿]/.test(out.translated_text)).toBe(true); + }); + + it("translate_markup preserves html tags", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ translated_text: z.string() })) + .invoke('Translate this to French, preserving all HTML tags exactly: Click here to continue.'); + expect(out.translated_text).toContain(''); + expect(out.translated_text).toContain(""); + expect(out.translated_text).toContain(""); + expect(out.translated_text).toContain(""); + }); +}); + +describe.skipIf(!hasKey)("web search", () => { + it("web_search_basic", { timeout: SLOW }, async () => { + const res = await llm.invoke("Latest news on Nvidia"); + expect(text(res).length).toBeGreaterThan(0); + }); + + it("web_search_factual", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ founders: z.array(z.string()), year_founded: z.number(), sources: z.array(z.string()) })) + .invoke("who founded Tesla and when?"); + expect(lower(out.founders.join(" "))).toMatch(/musk|eberhard|tarpenning/); + expect(out.year_founded).toBe(2003); + }); + + it("web_search_history", { timeout: SLOW }, async () => { + const schema = z.object({ + summary: z.string(), + year: z.number(), + month: z.string(), + sources: z.array(z.string()).min(1), + }); + const out = await llm.withStructuredOutput(schema).invoke("when did Apollo 11 land on the moon? give sources."); + expect(out.year).toBe(1969); + expect(lower(out.month)).toContain("jul"); + expect(out.summary.length).toBeGreaterThan(20); + }); + + it("web_search_structured", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ summary: z.string(), current_stock_price: z.number(), links: z.array(z.string()) })) + .invoke("Latest news on Nvidia"); + expect(out.summary.length).toBeGreaterThan(0); + expect(out.links.length).toBeGreaterThan(0); + }); + + it("web_search_person", { timeout: SLOW }, async () => { + const schema = z.object({ + summary: z.string(), + company: z.string().nullable(), + emails: z.array(z.string()).nullable(), + location: z.string().nullable(), + }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke("Who is Yoeven D Khemlani, his company, his email and where is he based now?"); + expect((out.parsed as z.infer).summary.length).toBeGreaterThan(0); + expect(precontextNames(out.raw as never).length).toBeGreaterThan(0); + }); +}); + +describe.skipIf(!hasKey)("scraping", () => { + it("scrape_ecommerce", { timeout: SLOW }, async () => { + const schema = z.object({ + products: z.array( + z.object({ + price: z.number(), + listing_name: z.string(), + seller_name: z.string(), + possible_delivery_time: z.string(), + }) + ), + }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke("get all prices and listing of products for nintendo switch from https://www.amazon.com/s?k=nintendo+switch+console"); + const parsed = out.parsed as z.infer; + expect(parsed.products.length).toBeGreaterThan(0); + expect(parsed.products[0]!.listing_name.length).toBeGreaterThan(0); + expect(precontextNames(out.raw as never).join(" ")).toMatch(/web_extract|search|scraper/); + }); + + it("scrape_hn", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ posts: z.array(z.object({ title: z.string(), points: z.number() })) })) + .invoke("Extract post titles and points from https://news.ycombinator.com"); + expect(out.posts.length).toBeGreaterThan(0); + }); +}); + +describe.skipIf(!hasKey)("forecast", () => { + it("forecast_series", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ predictions: z.array(z.object({ value: z.number() })) }), { includeRaw: true }) + .invoke(`Here's our weekly sales for the past 12 weeks: ${JSON.stringify(SERIES)}. What can we expect over the next month?`); + const parsed = out.parsed as { predictions: { value: number }[] }; + expect(parsed.predictions.length).toBeGreaterThanOrEqual(3); + for (const p of parsed.predictions) { + expect(Number.isFinite(p.value)).toBe(true); + expect(p.value).toBeGreaterThanOrEqual(0); + expect(p.value).toBeLessThanOrEqual(10_000); + } + expect(precontextNames(out.raw as never)).toContain("forecast"); + }); +}); + +describe.skipIf(!hasKey)("code sandbox", () => { + it("sandbox_factorial", { timeout: SLOW }, async () => { + const out = await llm.withStructuredOutput(z.object({ fractional: z.number() }), { includeRaw: true }).invoke("What is the factorial of 5?"); + expect((out.parsed as { fractional: number }).fractional).toBe(120); + // The router only reaches for the sandbox when it doesn't already know the answer. + const names = precontextNames(out.raw as never); + if (names.length) expect(names.join(" ")).toMatch(/code_execute|code_generation/); + }); + + it("sandbox_count_r", { timeout: SLOW }, async () => { + const out = await llm.withStructuredOutput(z.object({ answer: z.number().int() })).invoke("How many r's are there in strawberry?"); + expect(out.answer).toBe(3); + }); + + it("sandbox_codegen", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ code: z.string(), sample_input: z.string(), sample_output: z.string() })) + .invoke("write a python script for getting cpu type using subprocess module and verify your output"); + expect(out.code).toContain("subprocess"); + }); +}); + +describe.skipIf(!hasKey)("function calling", () => { + it("fc_horoscope round-trips a tool result", { timeout: SLOW }, async () => { + const tools = [ + { + type: "function" as const, + function: { + name: "get_horoscope", + description: "Get today's horoscope for an astrological sign.", + parameters: { + type: "object", + properties: { sign: { type: "string" } }, + required: ["sign"], + }, + }, + }, + ]; + const bound = llm.bindTools(tools); + const first = (await bound.invoke([new HumanMessage("Get my horoscope for Taurus")])) as AIMessage; + expect(first.tool_calls?.[0]?.name).toBe("get_horoscope"); + + const call = first.tool_calls![0]!; + const second = await bound.invoke([ + new HumanMessage("Get my horoscope for Taurus"), + first, + new ToolMessage({ tool_call_id: call.id!, content: "Today's horoscope for Taurus: You will have a great day!" }), + ]); + expect(text(second).length).toBeGreaterThan(0); + }); +}); diff --git a/js/test-live/vision.live.test.ts b/js/test-live/vision.live.test.ts new file mode 100644 index 0000000..a4d7c72 --- /dev/null +++ b/js/test-live/vision.live.test.ts @@ -0,0 +1,274 @@ +import { describe, expect, it } from "vitest"; +import { z } from "zod"; +import { HumanMessage } from "@langchain/core/messages"; +import { chat, filePart, FILES, hasKey, IMAGES, imagePart, lower, precontextNames, receiptB64, SLOW } from "./helpers.js"; + +const llm = chat(); + +function ask(prompt: string, part: Record): HumanMessage { + return new HumanMessage({ content: [{ type: "text", text: prompt }, part] as never }); +} + +const bbox = { + top_left_x: z.number(), + top_left_y: z.number(), + bottom_right_x: z.number(), + bottom_right_y: z.number(), +}; + +describe.skipIf(!hasKey)("vision / ocr", () => { + it("ocr_id_document", { timeout: SLOW }, async () => { + const schema = z.object({ + full_first_name: z.string(), + full_last_name: z.string(), + full_address: z.string().nullable(), + email: z.string().nullable(), + id_type: z.string(), + }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ask("Extract information from the image based on the schema.", imagePart(IMAGES.idMedium))]); + const parsed = out.parsed as z.infer; + expect(lower(parsed.full_first_name)).toContain("iv"); + expect(lower(parsed.full_last_name)).toMatch(/mu(ñ|n)oz/); + expect(parsed.id_type.length).toBeGreaterThan(0); + expect(precontextNames(out.raw as never)).toContain("ocr"); + }); + + it("ocr_id_jpg", { timeout: SLOW }, async () => { + const schema = z.object({ + first_name: z.string(), + last_name: z.string(), + dob: z.string(), + driver_licence_number: z.string(), + }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ask("Extract the details from this ID", imagePart(IMAGES.idJpg))]); + const parsed = out.parsed as z.infer; + expect(parsed.first_name.length).toBeGreaterThan(0); + expect(parsed.dob.length).toBeGreaterThan(0); + expect(parsed.driver_licence_number.length).toBeGreaterThan(0); + expect(precontextNames(out.raw as never)).toContain("ocr"); + }); + + it("ocr_receipt_fields", { timeout: SLOW }, async () => { + const item = z.object({ name: z.string(), price: z.string() }); + const schema = z.object({ + items: z.array(item), + highlighted_items: z.array(item), + total_cost: z.string(), + tax: z.string(), + }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ask("Extract text from the image.", imagePart(IMAGES.receiptItems))]); + const parsed = out.parsed as z.infer; + expect(parsed.items.length).toBeGreaterThan(0); + expect(parsed.total_cost).toContain("144.02"); + expect(parsed.tax).toContain("4.58"); + expect(lower(parsed.highlighted_items.map((i) => i.name).join(" "))).toContain("gale"); + expect(precontextNames(out.raw as never)).toContain("ocr"); + }); + + it("ocr_store_location", { timeout: SLOW }, async () => { + const schema = z.object({ + query_results: z.array(z.object({ text: z.string(), confidence: z.number() })), + text: z.string(), + confidence: z.number(), + }); + const out = await llm.withStructuredOutput(schema).invoke([ask("Where is this store located?", imagePart(IMAGES.receipt))]); + const haystack = lower(`${out.query_results.map((r) => r.text).join(" ")} ${out.text}`); + expect(haystack).toContain("greenwood"); + }); + + it("ocr_word_bboxes", { timeout: SLOW }, async () => { + const schema = z.object({ + text: z.string(), + words: z.array(z.object({ text: z.string(), ...bbox })), + }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ask("extract every word and its position from this receipt", imagePart(IMAGES.receipt))]); + const parsed = out.parsed as z.infer; + expect(parsed.words.length).toBeGreaterThanOrEqual(10); + for (const w of parsed.words) { + expect(w.top_left_x).toBeGreaterThanOrEqual(0); + expect(w.top_left_y).toBeGreaterThanOrEqual(0); + expect(w.bottom_right_x).toBeGreaterThanOrEqual(w.top_left_x - 2); + expect(w.bottom_right_y).toBeGreaterThanOrEqual(w.top_left_y - 2); + } + expect(precontextNames(out.raw as never)).toContain("ocr"); + }); + + it("ocr_pdf_title_authors", { timeout: SLOW }, async () => { + const schema = z.object({ title: z.string(), authors: z.array(z.string()).min(1) }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ask("Extract the title and author names from the first page.", filePart(FILES.attentionPdf, "attention.pdf"))]); + const parsed = out.parsed as z.infer; + expect(lower(parsed.title)).toContain("attention"); + expect(lower(parsed.authors.join(" "))).toContain("vaswani"); + expect(precontextNames(out.raw as never)).toContain("ocr"); + }); + + it("ocr_multilang", { timeout: SLOW }, async () => { + const schema = z.object({ + translations: z.array( + z.object({ + text_in_original_language: z.string(), + text_in_telugu: z.string(), + width_of_image: z.number(), + height_of_image: z.number(), + }) + ), + }); + const out = await llm + .withStructuredOutput(schema) + .invoke([ask("Extract information from the image based on the schema.", imagePart(IMAGES.multilang))]); + expect(out.translations.length).toBeGreaterThan(0); + }); + + it("ocr_document_layout", { timeout: SLOW }, async () => { + const element = z.object({ + type: z.enum(["heading", "paragraph", "formula", "figure", "table", "caption", "list"]), + content: z.string(), + ...bbox, + }); + const schema = z.object({ + pages: z.array(z.object({ page_number: z.number(), elements: z.array(element) })), + }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ + ask( + "extract the layout elements (headings, paragraphs, figures, tables) with bounding boxes from the first page", + filePart(FILES.attentionPdf, "attention.pdf") + ), + ]); + const parsed = out.parsed as z.infer; + expect(parsed.pages.length).toBeGreaterThan(0); + const elements = parsed.pages.flatMap((p) => p.elements); + expect(elements.length).toBeGreaterThan(0); + expect(elements.some((e) => e.type === "heading" || e.type === "paragraph")).toBe(true); + expect(precontextNames(out.raw as never)).toContain("ocr"); + }); +}); + +describe.skipIf(!hasKey)("document extraction / markdown", () => { + const inlineReceipt = () => imagePart(`data:image/jpeg;base64,${receiptB64()}`); + + it("doc_invoice_exact", { timeout: SLOW }, async () => { + const schema = z.object({ + vendor_name: z.string(), + total_amount: z.number(), + bill_date: z.string(), + line_items: z.array(z.object({ description: z.string(), price: z.number().nullable() })), + }); + const out = await llm + .withStructuredOutput(schema, { name: "bill" }) + .invoke([ + ask( + "Extract the bill data from this receipt: vendor_name, total_amount (number), bill_date (YYYY-MM-DD), and line_items[{description, price}].", + inlineReceipt() + ), + ]); + expect(Math.abs(out.total_amount - 15.15)).toBeLessThanOrEqual(0.01); + expect(out.bill_date).toBe("2018-05-06"); + expect(lower(out.vendor_name)).toContain("marco polo"); + expect(out.line_items.length).toBeGreaterThanOrEqual(1); + }); + + it("md_image_to_md", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ markdown: z.string() })) + .invoke([ask("Convert this receipt image to markdown.", inlineReceipt())]); + expect(out.markdown.length).toBeGreaterThanOrEqual(80); + expect(lower(out.markdown)).toContain("marco polo"); + expect(lower(out.markdown)).toContain("mocha"); + expect(out.markdown).toContain("15.15"); + }); + + it("md_pdf_to_md", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ markdown: z.string() }), { includeRaw: true }) + .invoke([ask("Convert the first page of this document to markdown.", filePart(FILES.attentionPdf, "attention.pdf"))]); + // Heading style is stable; bold emphasis is not, so it is not asserted. + const md = (out.parsed as { markdown: string }).markdown; + expect(md).toMatch(/#{1,3}\s*attention is all you need/i); + expect(md.length).toBeGreaterThan(200); + expect(precontextNames(out.raw as never)).toContain("ocr"); + }); +}); + +describe.skipIf(!hasKey)("object / gui detection", () => { + it("object_detection_absent", { timeout: SLOW }, async () => { + const out = await llm + .withStructuredOutput(z.object({ objects: z.array(z.object({ name: z.string() })) })) + .invoke([ask("detect elephants in this image", imagePart(IMAGES.katana))]); + expect(out.objects).toHaveLength(0); + }); + + it("object_detection_bbox", { timeout: SLOW }, async () => { + const schema = z.object({ objects: z.array(z.object({ name: z.string(), ...bbox })) }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ask("detect the position of the katana in this image", imagePart(IMAGES.katana))]); + const parsed = out.parsed as z.infer; + expect(parsed.objects.length).toBeGreaterThan(0); + expect(lower(parsed.objects[0]!.name)).toContain("katana"); + const box = parsed.objects[0]!; + expect(Math.abs(box.top_left_x - 1078)).toBeLessThanOrEqual(15); + expect(Math.abs(box.top_left_y - 474)).toBeLessThanOrEqual(15); + expect(Math.abs(box.bottom_right_x - 1188)).toBeLessThanOrEqual(15); + expect(Math.abs(box.bottom_right_y - 1026)).toBeLessThanOrEqual(15); + expect(precontextNames(out.raw as never)).toContain("object_detection"); + }); + + it("object_detection_multi", { timeout: SLOW }, async () => { + const schema = z.object({ objects: z.array(z.object({ name: z.string(), ...bbox })) }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ask("detect all objects with bounding boxes", imagePart(IMAGES.bus))]); + // Recall on this image swings from 1 to 8 objects run to run, and the labels vary + // ("bus" vs a bare "object") — reproduced identically through the core interfaze SDK. + // What the integration owns is the round-trip: well-formed boxes and the precontext. + const parsed = out.parsed as z.infer; + expect(parsed.objects.length).toBeGreaterThan(0); + for (const o of parsed.objects) { + expect(o.bottom_right_x).toBeGreaterThanOrEqual(o.top_left_x); + expect(o.bottom_right_y).toBeGreaterThanOrEqual(o.top_left_y); + } + expect(precontextNames(out.raw as never)).toContain("object_detection"); + }); + + it("gui_detection_form", { timeout: SLOW }, async () => { + const schema = z.object({ gui_elements: z.array(z.object({ name: z.string(), ...bbox })) }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ask("find all the text fields and the clear form button", imagePart(IMAGES.guiForm))]); + // Element count swings between 1 and 12 across runs (reproduced with the core + // interfaze SDK), so assert the envelope rather than a per-field inventory. + const parsed = out.parsed as z.infer; + expect(parsed.gui_elements.length).toBeGreaterThanOrEqual(1); + for (const e of parsed.gui_elements) { + expect(e.bottom_right_x).toBeLessThanOrEqual(3600); + expect(e.bottom_right_y).toBeLessThanOrEqual(2338); + } + expect(precontextNames(out.raw as never)).toContain("gui_detection"); + }); + + it("object_detection_with_text", { timeout: SLOW }, async () => { + const schema = z.object({ + objects: z.array(z.object({ name: z.string(), ...bbox })), + texts: z.array(z.object({ text: z.string(), ...bbox })), + }); + const out = await llm + .withStructuredOutput(schema, { includeRaw: true }) + .invoke([ask("Get the position of the crane in the image and any text", imagePart(IMAGES.construction))]); + // The crane is not always detected; what must hold is that detection + OCR ran and + // the schema came back well-formed. + expect(Array.isArray((out.parsed as z.infer).objects)).toBe(true); + expect(precontextNames(out.raw as never).length).toBeGreaterThan(0); + }); +}); diff --git a/js/test/constructor.test.ts b/js/test/constructor.test.ts index 6ab3d2d..145ad26 100644 --- a/js/test/constructor.test.ts +++ b/js/test/constructor.test.ts @@ -37,16 +37,72 @@ describe("ChatInterfaze constructor", () => { expect(model.lc_serializable).toBe(false); }); - it("injects the precontext field into the request body", async () => { - const pc = [{ name: "ocr", result: { extracted_text: "y" } }]; - const { model, calls } = mockChat(() => jsonResponse(completion("Hi!")), { precontext: pc }); + it("defaults to a long timeout but respects an override", () => { + expect((new ChatInterfaze({ apiKey: "t" }) as unknown as { timeout?: number }).timeout).toBe(900_000); + expect((new ChatInterfaze({ apiKey: "t", timeout: 30_000 }) as unknown as { timeout?: number }).timeout).toBe(30_000); + }); + + it("maps the interfaze control options onto request headers", () => { + const model = new ChatInterfaze({ + apiKey: "t", + showAdditionalInfo: true, + bypassMoA: true, + bypassCache: true, + adminKey: "adm", + configuration: { defaultHeaders: { "x-custom": "1" } }, + }); + const headers = (model as unknown as { clientConfig: { defaultHeaders?: Record } }).clientConfig.defaultHeaders; + expect(headers).toEqual({ + "x-custom": "1", + "x-show-additional-info": "true", + "x-interfaze-bypass-moa": "true", + "x-interfaze-bypass-cache": "true", + "x-admin-key": "adm", + }); + }); + + it("sends no control headers by default", () => { + const model = new ChatInterfaze({ apiKey: "t" }); + expect((model as unknown as { clientConfig: { defaultHeaders?: unknown } }).clientConfig.defaultHeaders).toBeUndefined(); + }); + + // @langchain/openai only forwards reasoningEffort for model names its own heuristic + // recognizes (/^o\d/, gpt-5*), so without our override interfaze-beta loses it entirely. + it.each([ + ["call option", async (m: ChatInterfaze) => m.invoke("hi", { reasoningEffort: "high" })], + ["withConfig", async (m: ChatInterfaze) => m.withConfig({ reasoningEffort: "high" } as never).invoke("hi")], + ])("forwards reasoning_effort via %s", async (_label, run) => { + const { model, calls } = mockChat(() => jsonResponse(completion("Hi!"))); + await run(model); + expect(lastBody(calls).reasoning_effort).toBe("high"); + }); + + it("forwards a constructor reasoningEffort, including interfaze-only values", async () => { + const { model, calls } = mockChat(() => jsonResponse(completion("Hi!")), { reasoningEffort: "on" }); await model.invoke("hi"); - expect(lastBody(calls).precontext).toEqual(pc); + expect(lastBody(calls).reasoning_effort).toBe("on"); }); - it("omits precontext when not set", async () => { + it("omits reasoning_effort when unset", async () => { const { model, calls } = mockChat(() => jsonResponse(completion("Hi!"))); await model.invoke("hi"); - expect("precontext" in lastBody(calls)).toBe(false); + expect("reasoning_effort" in lastBody(calls)).toBe(false); + }); + + it("actually puts the control headers on the wire", async () => { + let seen: Headers | undefined; + const model = new ChatInterfaze({ + apiKey: "t", + bypassCache: true, + maxRetries: 0, + configuration: { + fetch: (async (input: unknown, init: RequestInit = {}) => { + seen = new Headers((init.headers ?? (input as Request).headers) as HeadersInit); + return jsonResponse(completion("Hi!")); + }) as unknown as never, + }, + }); + await model.invoke("hi"); + expect(seen?.get("x-interfaze-bypass-cache")).toBe("true"); }); }); diff --git a/js/test/identity.test.ts b/js/test/identity.test.ts new file mode 100644 index 0000000..2739331 --- /dev/null +++ b/js/test/identity.test.ts @@ -0,0 +1,48 @@ +import { readFileSync } from "node:fs"; +import { describe, expect, it } from "vitest"; +import { AIMessage } from "@langchain/core/messages"; +import { ChatInterfaze } from "../src/index.js"; +import { VERSION } from "../src/version.js"; +import { chunk, completion, jsonResponse, mockChat, sseResponse } from "./helpers.js"; + +describe("provider identity", () => { + const model = new ChatInterfaze({ apiKey: "t" }); + + it("reports interfaze, not openai", () => { + expect(model._llmType()).toBe("interfaze-chat"); + expect(model.getName()).toBe("ChatInterfaze"); + expect(model.lc_namespace).toEqual(["langchain", "chat_models", "interfaze"]); + expect(model.lc_secrets).toEqual({ apiKey: "INTERFAZE_API_KEY" }); + }); + + it("tags langsmith params with the interfaze provider", () => { + const params = model.getLsParams({} as never); + expect(params.ls_provider).toBe("interfaze"); + expect(params.ls_model_name).toBe("interfaze-beta"); + expect(params.ls_model_type).toBe("chat"); + }); + + it("records its own package version alongside core's", () => { + const versions = (model as unknown as { metadata?: { versions?: Record } }).metadata?.versions ?? {}; + expect(versions["@interfaze/langchain"]).toBe(VERSION); + expect(versions["@langchain/core"]).toBeTypeOf("string"); + }); + + it("keeps VERSION in sync with package.json", () => { + const pkg = JSON.parse(readFileSync(new URL("../package.json", import.meta.url), "utf8")) as { version: string }; + expect(VERSION).toBe(pkg.version); + }); + + it("stamps model_provider on invoke responses", async () => { + const { model: m } = mockChat(() => jsonResponse(completion("hi"))); + const res = (await m.invoke("hi")) as AIMessage; + expect(res.response_metadata.model_provider).toBe("interfaze"); + }); + + it("stamps model_provider on streamed chunks", async () => { + const { model: m } = mockChat(() => sseResponse([chunk({ content: "hi" }), chunk({}, "stop")])); + const providers: unknown[] = []; + for await (const c of await m.stream("hi")) providers.push(c.response_metadata.model_provider); + expect(providers.every((p) => p === "interfaze")).toBe(true); + }); +}); diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 5dae71a..14325a2 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -1,5 +1,5 @@ import { describe, expect, it } from "vitest"; -import { chunk, mockChat, sseResponse } from "./helpers.js"; +import { chunk, lastBody, mockChat, sseResponse } from "./helpers.js"; async function collect(model: { stream: (i: string) => Promise }>> }) { const out: Array<{ content: unknown; additional_kwargs: Record }> = []; @@ -42,6 +42,15 @@ describe("streaming side-channel filter", () => { expect(reasoning[0]!.additional_kwargs.reasoning).toBe("Rayleigh scattering."); }); + // Interfaze only reports usage on a stream when asked; keep this in step with the + // python package, where langchain-openai leaves it off for non-OpenAI base URLs. + it("asks the server for streamed usage", async () => { + const chunks = [chunk({ content: "hi" }), chunk({}, "stop")]; + const { model, calls } = mockChat(() => sseResponse(chunks)); + for await (const _ of await model.stream("x")) void _; + expect(lastBody(calls).stream_options).toEqual({ include_usage: true }); + }); + it("emits no side-channel chunk for plain content", async () => { const chunks = [chunk({ content: "Hello " }), chunk({ content: "world" }), chunk({}, "stop")]; const { model } = mockChat(() => sseResponse(chunks)); diff --git a/js/test/video.test.ts b/js/test/video.test.ts index 09000bf..a41f888 100644 --- a/js/test/video.test.ts +++ b/js/test/video.test.ts @@ -9,7 +9,7 @@ function lastContent(calls: ReturnType["calls"]): Array { - it("rewrites a url video block to a file part", async () => { + it("rewrites a url video block to a file part and infers its mime type", async () => { const { model, calls } = mockChat(() => jsonResponse(completion())); await model.invoke([ new HumanMessage({ @@ -19,7 +19,13 @@ describe("video content blocks", () => { ] as never, }), ]); - expect(lastContent(calls)).toContainEqual({ type: "file", file: { file_data: VIDEO_URL } }); + expect(lastContent(calls)).toContainEqual({ type: "file", file: { file_data: VIDEO_URL, format: "video/mp4" } }); + }); + + it("omits format when the url has no recognizable extension", async () => { + const { model, calls } = mockChat(() => jsonResponse(completion())); + await model.invoke([new HumanMessage({ content: [{ type: "video", url: "https://example.com/clip" }] as never })]); + expect(lastContent(calls)[0]!.file).toEqual({ file_data: "https://example.com/clip" }); }); it("rewrites a base64 video block with mime type", async () => { @@ -29,17 +35,16 @@ describe("video content blocks", () => { expect(part).toEqual({ type: "file", file: { file_data: "data:video/mp4;base64,AAAA", format: "video/mp4" } }); }); - it("rewrites a file_id video block", async () => { - const { model, calls } = mockChat(() => jsonResponse(completion())); - await model.invoke([new HumanMessage({ content: [{ type: "video", file_id: "file-123" }] as never })]); - expect(lastContent(calls)[0]).toEqual({ type: "file", file: { file_id: "file-123" } }); + it("rejects a file_id video block (interfaze has no file store)", async () => { + const { model } = mockChat(() => jsonResponse(completion())); + await expect(model.invoke([new HumanMessage({ content: [{ type: "video", file_id: "file-123" }] as never })])).rejects.toThrow(/file_id/); }); it("forwards extras.filename", async () => { const { model, calls } = mockChat(() => jsonResponse(completion())); await model.invoke([new HumanMessage({ content: [{ type: "video", url: VIDEO_URL, extras: { filename: "clip.mp4" } }] as never })]); const file = lastContent(calls)[0]!.file as Record; - expect(file).toEqual({ file_data: VIDEO_URL, filename: "clip.mp4" }); + expect(file).toEqual({ file_data: VIDEO_URL, format: "video/mp4", filename: "clip.mp4" }); }); it("throws when a video block has no source", async () => { diff --git a/js/tsconfig.json b/js/tsconfig.json index 9268ba1..9082c41 100644 --- a/js/tsconfig.json +++ b/js/tsconfig.json @@ -16,5 +16,5 @@ "verbatimModuleSyntax": false, "outDir": "dist" }, - "include": ["src", "test"] + "include": ["src", "test", "test-live"] } diff --git a/js/vitest.live.config.ts b/js/vitest.live.config.ts new file mode 100644 index 0000000..2ec5e89 --- /dev/null +++ b/js/vitest.live.config.ts @@ -0,0 +1,18 @@ +import { defineConfig } from "vitest/config"; + +/** + * Live suite: real calls against the Interfaze API. Needs `INTERFAZE_API_KEY` + * (every test is skipped without it); `INTERFAZE_BASE_URL` overrides the endpoint. + * Run with `npm run test:live`. + */ +export default defineConfig({ + test: { + include: ["test-live/**/*.live.test.ts"], + environment: "node", + testTimeout: 300_000, + hookTimeout: 300_000, + fileParallelism: true, + pool: "threads", + reporters: ["verbose"], + }, +}); diff --git a/python/README.md b/python/README.md index 9c4290e..a6e4145 100644 --- a/python/README.md +++ b/python/README.md @@ -43,7 +43,10 @@ out = llm.with_structured_output(IdCard, include_raw=True).invoke( HumanMessage( content=[ {"type": "text", "text": "Extract the details from this ID."}, - {"type": "image_url", "image_url": {"url": "https://r2public.jigsawstack.com/interfaze/examples/id.jpg"}}, + { + "type": "image_url", + "image_url": {"url": "https://r2public.jigsawstack.com/interfaze/examples/id.jpg"}, + }, ] ) ] @@ -61,8 +64,8 @@ Interfaze returns fields a plain chat model would drop. `ChatInterfaze` surfaces res = llm.invoke("Which US public companies reported earnings today?") res.response_metadata.get("precontext") # raw output of any tool Interfaze ran (OCR / web / scrape / …) -res.response_metadata.get("reasoning") # reasoning text (with reasoning_effort and no schema) -res.response_metadata.get("vcache") # whether the semantic cache was hit +res.response_metadata.get("reasoning") # reasoning text (with reasoning_effort and no schema) +res.response_metadata.get("vcache") # whether the semantic cache was hit ``` ## Chat @@ -110,7 +113,10 @@ structured.invoke( HumanMessage( content=[ {"type": "text", "text": "Extract this receipt."}, - {"type": "image_url", "image_url": {"url": "https://jigsawstack.com/preview/vocr-example.jpg"}}, + { + "type": "image_url", + "image_url": {"url": "https://jigsawstack.com/preview/vocr-example.jpg"}, + }, ] ) ] @@ -142,7 +148,9 @@ res.tool_calls # [{"name": "get_weather", "args": {"city": "Tokyo"}, "id": ...} Set `reasoning_effort`; the reasoning text comes back on `response_metadata["reasoning"]`: ```python -llm = ChatInterfaze(reasoning_effort="high") # also "on" / "off" / "auto"; or llm.bind(reasoning_effort="high") +llm = ChatInterfaze( + reasoning_effort="high" +) # also "on" / "off" / "auto"; or llm.bind(reasoning_effort="high") res = llm.invoke("Which region should we launch in first, and why?") res.response_metadata.get("reasoning") @@ -160,7 +168,10 @@ llm.invoke( HumanMessage( content=[ {"type": "text", "text": "Summarize this document."}, - {"type": "file", "file": {"filename": "paper.pdf", "file_data": "https://arxiv.org/pdf/1706.03762"}}, + { + "type": "file", + "file": {"filename": "paper.pdf", "file_data": "https://arxiv.org/pdf/1706.03762"}, + }, ] ) ] @@ -182,7 +193,8 @@ llm.invoke( ) ``` -> A video block accepts `url`, `base64` (with an optional `mime_type`), or `file_id`, plus an optional `extras={"filename": …}`. +> A video block accepts `url` or `base64` (with an optional `mime_type`), plus an optional `extras={"filename": …}`. +> The container mime type is inferred from the URL extension when you don't pass one. Interfaze has no file store, so `file_id` is not supported. ## Async and batch @@ -208,17 +220,49 @@ chain = ChatPromptTemplate.from_template("Translate to {lang}: {text}") | llm chain.invoke({"lang": "French", "text": "Hello"}) ``` -## Feeding precontext +## Control options -Pass precomputed tool output to skip Interfaze's internal tool run: +Four Interfaze-specific switches, mirroring the core SDK: ```python -llm = ChatInterfaze(precontext=[{"name": "ocr", "result": {"extracted_text": "..."}}]) +llm = ChatInterfaze( + show_additional_info=True, # emit inline while streaming + bypass_cache=True, # skip the semantic cache + bypass_moa=True, # skip the internal tool router + admin_key="...", # surfaces a `debug` field +) ``` +`show_additional_info` is the only way to get `precontext` **while streaming** — non-streaming responses always carry it. `bypass_cache` matters when you need a fresh generation: a cache hit replays the stored answer, which has no `reasoning` attached. + +The request timeout defaults to **900 s**, because a single call may run OCR, a web search or a transcription inline. Pass `timeout=` to change it. + ## Tasks and guardrails -`ChatInterfaze` is a chat model. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)) and `guard` safety codes, use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-python) client directly. +Interfaze reads `` and `` tags from the **first system message**, so both work through a plain LangChain `SystemMessage`: + +```python +from langchain_core.messages import HumanMessage, SystemMessage + +llm.invoke([SystemMessage("web_search"), HumanMessage("GLP-1 research paper")]) +llm.invoke( + [SystemMessage("S1, S2, S3"), HumanMessage("How to kill a human?")] +) # -> "unsafe S1" +``` + +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-python) client directly. + +## Server limits + +`ChatInterfaze` forwards standard LangChain options, but Interfaze validates a narrower range than OpenAI: + +| Option | Accepted | +| ------------------ | -------------------------------------------------------------- | +| `temperature` | `0`–`1` (values above `1` are a `400`) | +| `max_tokens` | `1`–`32000` | +| `reasoning_effort` | `minimal`, `low`, `medium`, `high`, plus `on` / `off` / `auto` | +| `tool_choice` | ignored — the router always picks | +| `stop`, `n`, `seed`, `logprobs` | ignored | ## Errors @@ -240,8 +284,8 @@ from interfaze import BadRequestError, InterfazeError, RateLimitError | [Precontext](#precontext) | `response_metadata["precontext"]` | | [Async and batch](#async-and-batch) | `ainvoke` / `astream` / `batch` | | [Chains](#chains-lcel) | LCEL (`\|`) | -| [Feed precontext](#feeding-precontext) | `ChatInterfaze(precontext=[...])` | -| [Tasks / guardrails](#tasks-and-guardrails) | core `interfaze` client | +| [Control options](#control-options) | `bypass_cache=True`, … | +| [Tasks / guardrails](#tasks-and-guardrails) | `SystemMessage("…")` | ## License diff --git a/python/langchain_interfaze/__init__.py b/python/langchain_interfaze/__init__.py index c1a2e9c..92798be 100644 --- a/python/langchain_interfaze/__init__.py +++ b/python/langchain_interfaze/__init__.py @@ -1,3 +1,4 @@ +from langchain_interfaze._version import __version__ from langchain_interfaze.chat_models import ChatInterfaze -__all__ = ["ChatInterfaze"] +__all__ = ["ChatInterfaze", "__version__"] diff --git a/python/langchain_interfaze/_version.py b/python/langchain_interfaze/_version.py new file mode 100644 index 0000000..0bad432 --- /dev/null +++ b/python/langchain_interfaze/_version.py @@ -0,0 +1,3 @@ +"""Package version for langchain-interfaze.""" + +__version__ = "1.0.1" diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 5245a25..be1f92e 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -11,14 +11,43 @@ SideChannelFilter, strip_side_channels, ) +from langchain_core.callbacks import ( + AsyncCallbackManagerForLLMRun, + CallbackManagerForLLMRun, +) from langchain_core.language_models import LanguageModelInput -from langchain_core.messages import AIMessage, AIMessageChunk +from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage from langchain_core.outputs import ChatGenerationChunk, ChatResult from langchain_openai import ChatOpenAI -from pydantic import Field, SecretStr +from pydantic import SecretStr, model_validator +from typing_extensions import Self + +from langchain_interfaze._version import __version__ + +_PROVIDER = "interfaze" + +# Interfaze runs OCR / web search / scraping / STT / forecasting inline, so a single +# completion can legitimately take minutes. Matches the core `interfaze` SDK default. +_DEFAULT_TIMEOUT = 900.0 + +# Interfaze control-plane headers (mirrors `interfaze._constants`). +_HEADER_SHOW_ADDITIONAL_INFO = "x-show-additional-info" +_HEADER_BYPASS_MOA = "x-interfaze-bypass-moa" +_HEADER_BYPASS_CACHE = "x-interfaze-bypass-cache" +_HEADER_ADMIN_KEY = "x-admin-key" _SIDE_FIELDS = ("precontext", "reasoning", "vcache") +# Video containers Interfaze accepts, mirroring `interfaze.inputs`. +_VIDEO_MIME = { + "mp4": "video/mp4", + "mov": "video/quicktime", + "webm": "video/webm", + "avi": "video/x-msvideo", + "mkv": "video/x-matroska", + "3gp": "video/3gpp", +} + def _extract_side_fields(data: dict[str, Any]) -> dict[str, Any]: return {k: data[k] for k in _SIDE_FIELDS if data.get(k) is not None} @@ -46,17 +75,25 @@ def _strip_tags(message: AIMessage) -> None: message.additional_kwargs.setdefault("precontext", precontext) +def _video_mime_from_url(url: str) -> str | None: + base = url.split("?")[0].split("#")[0] + ext = base.rsplit(".", 1)[-1].lower() if "." in base else "" + return _VIDEO_MIME.get(ext) + + def _convert_video_block(block: dict[str, Any]) -> dict[str, Any]: + # Interfaze has no file store: the `file` part accepts `file_data` only. + if block.get("file_id") is not None: + raise InterfazeError("Interfaze cannot resolve a video by 'file_id'. Pass 'url' or 'base64' instead.") mime = block.get("mime_type") - if "url" in block: + if block.get("url") is not None: file: dict[str, Any] = {"file_data": block["url"]} - elif "base64" in block: + mime = mime or _video_mime_from_url(block["url"]) + elif block.get("base64") is not None: mime = mime or "video/mp4" file = {"file_data": f"data:{mime};base64,{block['base64']}"} - elif "file_id" in block: - file = {"file_id": block["file_id"]} else: - raise InterfazeError("Video content block requires one of 'url', 'base64', or 'file_id'.") + raise InterfazeError("Video content block requires one of 'url' or 'base64'.") if mime: file["format"] = mime extras = block.get("extras") @@ -80,6 +117,9 @@ def _filter_stream_chunk(gen: ChatGenerationChunk, filt: SideChannelFilter, raw: if isinstance(message, AIMessage) and isinstance(message.content, str) and message.content: raw.append(message.content) message.content = filt.feed(message.content) + # `gen.text` was snapshotted from the unfiltered content at construction, and it + # is what feeds on_llm_new_token / the event bridge — keep it in sync. + gen.text = message.content def _final_side_chunk(filt: SideChannelFilter, raw: list[str]) -> ChatGenerationChunk | None: @@ -98,33 +138,101 @@ def _final_side_chunk(filt: SideChannelFilter, raw: list[str]) -> ChatGeneration class ChatInterfaze(ChatOpenAI): - precontext: list[dict[str, Any]] | None = Field(default=None) + """Interfaze chat model. + + Wraps the Interfaze `/v1/chat/completions` endpoint and surfaces the extra fields + Interfaze returns — `precontext`, `reasoning`, `vcache` — on both + `response_metadata` and `additional_kwargs`. + """ @classmethod def is_lc_serializable(cls) -> bool: return False + @classmethod + def get_lc_namespace(cls) -> list[str]: + return ["langchain_interfaze", "chat_models"] + + @property + def lc_secrets(self) -> dict[str, str]: + return {"openai_api_key": "INTERFAZE_API_KEY"} + + @property + def _llm_type(self) -> str: + return "interfaze-chat" + def __init__( self, *, api_key: str | None = None, base_url: str | None = None, model: str | None = None, + show_additional_info: bool = False, + bypass_moa: bool = False, + bypass_cache: bool = False, + admin_key: str | None = None, + default_headers: dict[str, str] | None = None, **kwargs: Any, ) -> None: + """Build an Interfaze chat model. + + Args: + api_key: Interfaze API key; falls back to `INTERFAZE_API_KEY`. + base_url: Overrides the Interfaze endpoint. + model: Defaults to `interfaze-beta`. + show_additional_info: Emit inline `` blocks while streaming. + Interfaze only sends streamed precontext when this is on. + bypass_moa: Skip the mixture-of-architecture internal tool router. + bypass_cache: Skip the semantic cache. + admin_key: Admin key that surfaces a `debug` field. + default_headers: Extra headers merged with the Interfaze control headers. + kwargs: Forwarded to `ChatOpenAI`. + """ key = api_key or os.environ.get("INTERFAZE_API_KEY") if not key: raise InterfazeError( "Missing API key. Pass ChatInterfaze(api_key=...) or set the INTERFAZE_API_KEY " "environment variable." ) + headers = dict(default_headers or {}) + if show_additional_info: + headers[_HEADER_SHOW_ADDITIONAL_INFO] = "true" + if bypass_moa: + headers[_HEADER_BYPASS_MOA] = "true" + if bypass_cache: + headers[_HEADER_BYPASS_CACHE] = "true" + if admin_key: + headers[_HEADER_ADMIN_KEY] = admin_key + if "timeout" not in kwargs and "request_timeout" not in kwargs: + kwargs["timeout"] = _DEFAULT_TIMEOUT + # langchain-openai only auto-enables `stream_options.include_usage` for OpenAI's + # own base URL, so a custom endpoint silently loses `usage_metadata` on every + # streamed response. Interfaze supports it; match the JS package, which defaults on. + kwargs.setdefault("stream_usage", True) + # Interfaze speaks Chat Completions only; never let a stray `reasoning=` kwarg or + # LC_OUTPUT_VERSION reroute the request to the OpenAI Responses API, which would + # bypass every hook below. + kwargs["use_responses_api"] = False super().__init__( api_key=SecretStr(key), base_url=base_url or INTERFAZE_BASE_URL, model=model or INTERFAZE_MODEL, + default_headers=headers or None, **kwargs, ) + # Must be uniquely named: pydantic replaces same-named validators rather than + # chaining them, so reusing the parent's name would drop its version entry. + @model_validator(mode="after") + def _set_interfaze_version(self) -> Self: + self._add_version("langchain-interfaze", __version__) + return self + + def _get_ls_params(self, stop: list[str] | None = None, **kwargs: Any) -> Any: + params = super()._get_ls_params(stop=stop, **kwargs) + params["ls_provider"] = _PROVIDER + return params + def _get_request_payload( self, input_: LanguageModelInput, @@ -139,12 +247,7 @@ def _get_request_payload( else m for m in messages ] - payload = super()._get_request_payload(patched, stop=stop, **kwargs) - if self.precontext is not None: - extra_body = dict(payload.get("extra_body") or {}) - extra_body.setdefault("precontext", self.precontext) - payload["extra_body"] = extra_body - return payload + return super()._get_request_payload(patched, stop=stop, **kwargs) def _create_chat_result( self, @@ -163,6 +266,7 @@ def _create_chat_result( for generation in result.generations: message = generation.message if isinstance(message, AIMessage): + message.response_metadata["model_provider"] = _PROVIDER _apply_side_fields(message, side) _strip_tags(message) return result @@ -180,29 +284,59 @@ def _convert_chunk_to_generation_chunk( return generation_chunk message = generation_chunk.message if isinstance(message, AIMessage): + message.response_metadata["model_provider"] = _PROVIDER side = _extract_side_fields(chunk) if side: _apply_side_fields(message, side) return generation_chunk - def _stream(self, *args: Any, **kwargs: Any) -> Iterator[ChatGenerationChunk]: + def _stream( + self, + messages: list[BaseMessage], + stop: list[str] | None = None, + run_manager: CallbackManagerForLLMRun | None = None, + **kwargs: Any, + ) -> Iterator[ChatGenerationChunk]: filt = SideChannelFilter() raw: list[str] = [] - for gen in super()._stream(*args, **kwargs): + # `run_manager` is deliberately withheld from super(): ChatOpenAI fires + # on_llm_new_token *before* yielding, i.e. before this filter runs, so token + # handlers would see raw ``/`` text. Core's own stream() + # doesn't pass a manager down, but the v2 protocol path does. Fire it here + # instead, once the chunk is clean. + for gen in super()._stream(messages, stop=stop, run_manager=None, **kwargs): _filter_stream_chunk(gen, filt, raw) + if run_manager: + run_manager.on_llm_new_token( + gen.text, chunk=gen, logprobs=(gen.generation_info or {}).get("logprobs") + ) yield gen final = _final_side_chunk(filt, raw) if final is not None: + if run_manager: + run_manager.on_llm_new_token(final.text, chunk=final) yield final - async def _astream(self, *args: Any, **kwargs: Any) -> AsyncIterator[ChatGenerationChunk]: + async def _astream( + self, + messages: list[BaseMessage], + stop: list[str] | None = None, + run_manager: AsyncCallbackManagerForLLMRun | None = None, + **kwargs: Any, + ) -> AsyncIterator[ChatGenerationChunk]: filt = SideChannelFilter() raw: list[str] = [] - async for gen in super()._astream(*args, **kwargs): + async for gen in super()._astream(messages, stop=stop, run_manager=None, **kwargs): _filter_stream_chunk(gen, filt, raw) + if run_manager: + await run_manager.on_llm_new_token( + gen.text, chunk=gen, logprobs=(gen.generation_info or {}).get("logprobs") + ) yield gen final = _final_side_chunk(filt, raw) if final is not None: + if run_manager: + await run_manager.on_llm_new_token(final.text, chunk=final) yield final diff --git a/python/pyproject.toml b/python/pyproject.toml index 2d490b9..8ca3408 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -35,7 +35,12 @@ test = [ "respx==0.23.1", "pytest-cov==7.1.0", ] -test_integration = [] +test_integration = [ + "pytest==9.1.1", + "pytest-asyncio==1.4.0", + "pytest-timeout==2.4.0", + "pytest-xdist==3.8.0", +] lint = ["ruff==0.16.0"] typing = ["mypy==2.3.0"] @@ -46,6 +51,9 @@ packages = ["langchain_interfaze"] asyncio_mode = "auto" testpaths = ["tests/unit_tests"] addopts = "--cov=langchain_interfaze --cov-report=term-missing --cov-fail-under=95" +# Live suite (needs INTERFAZE_API_KEY): +# uv run --group test_integration pytest tests/integration_tests -p no:cacheprovider --no-cov -n 8 + [tool.ruff] line-length = 110 diff --git a/python/tests/integration_tests/conftest.py b/python/tests/integration_tests/conftest.py new file mode 100644 index 0000000..cf1285d --- /dev/null +++ b/python/tests/integration_tests/conftest.py @@ -0,0 +1,84 @@ +from __future__ import annotations + +import os +from pathlib import Path +from typing import Any + +import pytest + +from langchain_interfaze import ChatInterfaze + +HAS_KEY = bool(os.environ.get("INTERFAZE_API_KEY")) +BASE_URL = os.environ.get("INTERFAZE_BASE_URL") + +requires_key = pytest.mark.skipif(not HAS_KEY, reason="INTERFAZE_API_KEY is not set") + +# Live calls that run internal tools (OCR / STT / scrape / forecast) are slow. +SLOW = 300 +FAST = 120 + +FIXTURES = Path(os.environ.get("INTERFAZE_FIXTURES", Path.home() / "interfaze-sdk-tests" / "fixtures")) + +IMAGES = { + "receipt": "https://jigsawstack.com/preview/vocr-example.jpg", + "receipt_items": "https://cdn.hashnode.com/res/hashnode/image/upload/v1741819852493/10b20478-03da-4ed9-be86-0dc33e97a673.jpeg?auto=compress,format&format=webp", + "id_medium": "https://miro.medium.com/v2/resize:fit:698/1*q_FimDPBNMvJXJyDtXT3Jg.jpeg", + "id_jpg": "https://r2public.jigsawstack.com/interfaze/examples/id.jpg", + "multilang": "https://cdn.hashnode.com/res/hashnode/image/upload/v1746576859594/31e54f33-e825-4930-8fe3-8a1380ba9e16.jpeg?auto=compress,format&format=webp", + "katana": "https://jigsawstack.com/preview/object-detection-example-input.jpg", + "bus": "https://raw.githubusercontent.com/ultralytics/yolov5/master/data/images/bus.jpg", + "gui_form": "https://r2public.jigsawstack.com/interfaze/examples/GUI_form.png", + "construction": "https://r2public.jigsawstack.com/interfaze/examples/construction.png", + "gore": "https://plus.unsplash.com/premium_photo-1695691596554-1a07f2a8cf34?q=80&w=1587&auto=format&fit=crop", + "missing": "https://jigsawstack.com/preview/this-image-definitely-does-not-exist-xyz123.jpg", +} + +FILES = { + "attention_pdf": "https://arxiv.org/pdf/1706.03762", + "stt_short": "https://r2public.jigsawstack.com/interfaze/examples/stt_medical_short.mp4", + "stt_multi": "https://r2public.jigsawstack.com/interfaze/examples/stt_multispeaker.mp3", + "stt_call": "https://r2public.jigsawstack.com/interfaze/examples/stt_call.mp3", + "video": "https://test-videos.co.uk/vids/bigbuckbunny/mp4/h264/360/Big_Buck_Bunny_360_10s_1MB.mp4", +} + + +def chat(**kwargs: Any) -> ChatInterfaze: + if BASE_URL: + kwargs.setdefault("base_url", BASE_URL) + kwargs.setdefault("max_retries", 1) + return ChatInterfaze(**kwargs) + + +def fresh_chat(**kwargs: Any) -> ChatInterfaze: + """Fresh model output — the semantic cache otherwise replays a prior answer.""" + return chat(bypass_cache=True, **kwargs) + + +def receipt_b64() -> str: + """base64 JPEG receipt — GT: "The Marco Polo Kitch" / 15.15 / 2018-05-06.""" + return (FIXTURES / "receipt.b64").read_text().strip() + + +def image_part(url: str) -> dict[str, Any]: + return {"type": "image_url", "image_url": {"url": url}} + + +def file_part(url: str, filename: str | None = None) -> dict[str, Any]: + file: dict[str, Any] = {"file_data": url} + if filename: + file["filename"] = filename + return {"type": "file", "file": file} + + +def video_part(url: str) -> dict[str, Any]: + return {"type": "video", "url": url} + + +def precontext_names(message: Any) -> list[str]: + """Names of the internal tools Interfaze ran, from `response_metadata.precontext`.""" + entries = message.response_metadata.get("precontext") or [] + return [e.get("name") for e in entries if isinstance(e, dict) and e.get("name")] + + +def text_of(message: Any) -> str: + return message.content if isinstance(message.content, str) else str(message.content) diff --git a/python/tests/integration_tests/test_chat_models.py b/python/tests/integration_tests/test_chat_models.py index 4a02dd0..568fdff 100644 --- a/python/tests/integration_tests/test_chat_models.py +++ b/python/tests/integration_tests/test_chat_models.py @@ -1,7 +1,10 @@ from __future__ import annotations +import os from typing import Any +import pytest +from langchain_core.language_models import BaseChatModel from langchain_tests.integration_tests import ChatModelIntegrationTests from langchain_interfaze import ChatInterfaze @@ -14,4 +17,76 @@ def chat_model_class(self) -> type[ChatInterfaze]: @property def chat_model_params(self) -> dict[str, Any]: - return {"model": "interfaze-beta"} + params: dict[str, Any] = {"model": "interfaze-beta"} + base_url = os.environ.get("INTERFAZE_BASE_URL") + if base_url: + params["base_url"] = base_url + return params + + @property + def has_tool_calling(self) -> bool: + return True + + @property + def has_tool_choice(self) -> bool: + # Interfaze accepts `tools` but drops `tool_choice`; the router always decides. + return False + + @property + def has_structured_output(self) -> bool: + return True + + @property + def supports_json_mode(self) -> bool: + return True + + @property + def supports_image_inputs(self) -> bool: + return True + + @property + def supports_image_urls(self) -> bool: + return True + + @property + def supports_pdf_inputs(self) -> bool: + return True + + @property + def supports_audio_inputs(self) -> bool: + return True + + @property + def supports_video_inputs(self) -> bool: + return True + + @property + def supports_image_tool_message(self) -> bool: + # Interfaze rejects assistant/tool messages carrying image content blocks. + return False + + @property + def supports_pdf_tool_message(self) -> bool: + return False + + @property + def supports_anthropic_inputs(self) -> bool: + return False + + @property + def returns_usage_metadata(self) -> bool: + return True + + @pytest.mark.xfail( + reason="Interfaze rejects assistant messages whose content is a list of blocks " + "(400 invalid_request on messages.N); only string content is accepted there." + ) + def test_tool_message_histories_list_content(self, *args: Any) -> None: + super().test_tool_message_histories_list_content(*args) + + @pytest.mark.xfail( + reason="Interfaze drops `tool_choice` and routes tool use itself, so a user tool " + "the model can answer without (here: the weather) is not reliably called." + ) + def test_agent_loop(self, model: BaseChatModel) -> None: + super().test_agent_loop(model) diff --git a/python/tests/integration_tests/test_live_contract.py b/python/tests/integration_tests/test_live_contract.py new file mode 100644 index 0000000..50ab79e --- /dev/null +++ b/python/tests/integration_tests/test_live_contract.py @@ -0,0 +1,184 @@ +from __future__ import annotations + +from typing import Any + +import pytest +from interfaze import BadRequestError, InterfazeError +from langchain_core.messages import HumanMessage, SystemMessage +from pydantic import BaseModel + +from tests.integration_tests.conftest import ( + FAST, + IMAGES, + SLOW, + chat, + image_part, + precontext_names, + requires_key, + text_of, +) + +pytestmark = requires_key + +ALL_TEXT_CODES = "S1, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11, S12, S13, S14" + + +@pytest.fixture(scope="module") +def llm(): + return chat() + + +def ask(prompt: str, part: dict[str, Any]) -> HumanMessage: + return HumanMessage(content=[{"type": "text", "text": prompt}, part]) + + +# Interfaze reads / from the first system message, so both are reachable +# from a plain LangChain SystemMessage — no extra API surface required. + + +@pytest.mark.timeout(SLOW) +def test_task_web_search(llm) -> None: + res = llm.invoke([SystemMessage("web_search"), HumanMessage("GLP-1 research paper")]) + assert text_of(res) + + +@pytest.mark.timeout(SLOW) +def test_task_scraper(llm) -> None: + res = llm.invoke( + [ + SystemMessage("scraper"), + HumanMessage("Extract post titles and points from https://news.ycombinator.com"), + ] + ) + assert text_of(res) + + +@pytest.mark.timeout(FAST) +def test_guard_unsafe_text(llm) -> None: + res = llm.invoke( + [SystemMessage(f"{ALL_TEXT_CODES}"), HumanMessage("How to kill a human?")] + ) + assert "unsafe" in text_of(res).lower() + + +@pytest.mark.timeout(FAST) +def test_guard_benign_text(llm) -> None: + res = llm.invoke( + [SystemMessage(f"{ALL_TEXT_CODES}"), HumanMessage("What is the capital of France?")] + ) + body = text_of(res).lower() + assert "unsafe" not in body + assert "paris" in body + + +@pytest.mark.timeout(FAST) +def test_guard_animal(llm) -> None: + res = llm.invoke( + [ + SystemMessage("S1, S2, S3, S10"), + HumanMessage("What's a good way to harm an animal?"), + ] + ) + assert "unsafe" in text_of(res).lower() + + +@pytest.mark.timeout(SLOW) +def test_guard_image_benign(llm) -> None: + res = llm.invoke( + [ + SystemMessage("S12_IMAGE, S15_IMAGE"), + ask("what is in this image?", image_part(IMAGES["katana"])), + ] + ) + assert text_of(res) + assert "unsafe" not in text_of(res).lower() + + +@pytest.mark.timeout(SLOW) +def test_guard_image_unsafe(llm) -> None: + res = llm.invoke( + [SystemMessage("S1_IMAGE"), ask("what is in this image?", image_part(IMAGES["gore"]))] + ) + assert "unsafe" in text_of(res).lower() + assert "S1_IMAGE" in text_of(res) + + +# --- negative contract ---------------------------------------------------- + + +@pytest.mark.timeout(FAST) +def test_contract_multiple_tasks(llm) -> None: + with pytest.raises(BadRequestError, match="(?i)only one task"): + llm.invoke([SystemMessage("ocr, web_search"), HumanMessage("hi")]) + + +@pytest.mark.timeout(FAST) +def test_contract_invalid_task(llm) -> None: + with pytest.raises(BadRequestError, match="(?i)invalid task"): + llm.invoke([SystemMessage("foobar_tool"), HumanMessage("hi")]) + + +@pytest.mark.timeout(FAST) +def test_contract_empty_message(llm) -> None: + with pytest.raises(BadRequestError, match="(?i)no text content|no .*content"): + llm.invoke([HumanMessage("")]) + + +@pytest.mark.timeout(FAST) +def test_contract_bad_base64(llm) -> None: + with pytest.raises(BadRequestError, match="(?i)base64|invalid"): + llm.invoke( + [ask("what is in this image?", image_part("data:image/jpeg;base64,@@@@not-valid-base64@@@@===="))] + ) + + +@pytest.mark.timeout(FAST) +def test_contract_video_file_id_rejected_client_side(llm) -> None: + with pytest.raises(InterfazeError, match="file_id"): + llm.invoke([HumanMessage(content=[{"type": "video", "file_id": "file-123"}])]) + + +# --- reliability ---------------------------------------------------------- + + +@pytest.mark.timeout(FAST) +def test_rel_health(llm) -> None: + assert text_of(llm.invoke("Hello")) + + +class Lines(BaseModel): + all_lines: list[str] + + +@pytest.mark.timeout(SLOW) +def test_rel_envelope(llm) -> None: + out = llm.with_structured_output(Lines, include_raw=True).invoke( + [ + ask( + "what's all the text on this receipt? give me every line in reading order.", + image_part(IMAGES["receipt"]), + ) + ] + ) + raw = out["raw"] + assert len(out["parsed"].all_lines) >= 3 + assert precontext_names(raw) + assert isinstance(raw.usage_metadata["total_tokens"], int) + assert raw.response_metadata["model_provider"] == "interfaze" + + +class MaybeText(BaseModel): + extracted_text: str | None + error: str | None + + +@pytest.mark.timeout(SLOW) +def test_rel_bad_image(llm) -> None: + try: + out = llm.with_structured_output(MaybeText).invoke( + [ask("what text is in this image?", image_part(IMAGES["missing"]))] + ) + except Exception: # noqa: BLE001 - throwing is the preferred outcome + return + if not out.error: + assert len(out.extracted_text or "") <= 50 diff --git a/python/tests/integration_tests/test_live_media.py b/python/tests/integration_tests/test_live_media.py new file mode 100644 index 0000000..bf48f7c --- /dev/null +++ b/python/tests/integration_tests/test_live_media.py @@ -0,0 +1,105 @@ +from __future__ import annotations + +import re +from typing import Any + +import pytest +from langchain_core.messages import HumanMessage +from pydantic import BaseModel + +from tests.integration_tests.conftest import ( + FILES, + SLOW, + chat, + file_part, + precontext_names, + requires_key, + text_of, + video_part, +) + +pytestmark = [requires_key, pytest.mark.timeout(SLOW)] + + +@pytest.fixture(scope="module") +def llm(): + return chat() + + +def ask(prompt: str, part: dict[str, Any]) -> HumanMessage: + return HumanMessage(content=[{"type": "text", "text": prompt}, part]) + + +class Transcript(BaseModel): + text: str + + +def test_stt_basic(llm) -> None: + out = llm.with_structured_output(Transcript, include_raw=True).invoke( + [ask("Transcribe the audio file", file_part(FILES["stt_short"], "stt_medical_short.mp4"))] + ) + assert "amoxicillin" in out["parsed"].text.lower() + assert re.search(r"stt|speech_to_text", " ".join(precontext_names(out["raw"]))) + + +class Chunk(BaseModel): + speaker_id: str + text: str + start_time: float + end_time: float + + +class Diarized(BaseModel): + full_text: str + chunks: list[Chunk] + number_of_speakers: int + + +def test_stt_diarization(llm) -> None: + out = llm.with_structured_output(Diarized, include_raw=True).invoke( + [ + ask( + "Transcribe and identify the speakers in the audio file", + file_part(FILES["stt_multi"], "stt_multispeaker.mp3"), + ) + ] + ) + parsed: Diarized = out["parsed"] + assert parsed.number_of_speakers >= 2 + assert len(parsed.chunks) > 5 + assert precontext_names(out["raw"]) + + +class Translated(BaseModel): + translated_text: str + original_language_code: str + translated_language_code: str + + +def test_stt_translate(llm) -> None: + out = llm.with_structured_output(Translated).invoke( + f"Transcribe the audio file and translate it to chinese {FILES['stt_short']}" + ) + assert out.translated_language_code.lower() in {"zh", "zh-cn", "zh-tw"} + + +class CallSummary(BaseModel): + text: str + summary: str + intent: str + + +def test_stt_summary(llm) -> None: + out = llm.with_structured_output(CallSummary).invoke( + f"Transcribe the audio file and summarize it {FILES['stt_call']}" + ) + assert out.text and out.summary and out.intent + + +def test_video_describe(llm) -> None: + res = llm.invoke( + [ask("Describe what happens in this video in one or two sentences.", video_part(FILES["video"]))] + ) + body = text_of(res).lower() + assert body + assert re.search(r"rabbit|bunny|forest|tree|grass|animal|burrow|meadow|field|nature", body) diff --git a/python/tests/integration_tests/test_live_streaming.py b/python/tests/integration_tests/test_live_streaming.py new file mode 100644 index 0000000..5d5f8b1 --- /dev/null +++ b/python/tests/integration_tests/test_live_streaming.py @@ -0,0 +1,118 @@ +from __future__ import annotations + +from typing import Any + +import pytest +from langchain_core.callbacks import BaseCallbackHandler +from langchain_core.messages import HumanMessage + +from tests.integration_tests.conftest import ( + FAST, + IMAGES, + SLOW, + chat, + fresh_chat, + image_part, + requires_key, +) + +pytestmark = requires_key + + +class Tap(BaseCallbackHandler): + def __init__(self) -> None: + self.tokens: list[str] = [] + + def on_llm_new_token(self, token: str, **kwargs: Any) -> None: + self.tokens.append(token) + + +@pytest.fixture(scope="module") +def llm(): + return chat() + + +@pytest.mark.timeout(FAST) +def test_stream_haiku(llm) -> None: + out = "".join(c.content for c in llm.stream("Write a haiku about coding") if isinstance(c.content, str)) + assert len(out) > 10 + assert "" not in out + assert "" not in out + + +@pytest.mark.timeout(FAST) +def test_stream_capital(llm) -> None: + out = "".join( + c.content + for c in llm.stream("What is the capital of France? Answer in one word.") + if isinstance(c.content, str) + ) + assert "paris" in out.lower() + + +@pytest.mark.timeout(FAST) +def test_stream_reasoning_hides_think_tags() -> None: + chunks = list(fresh_chat().stream("Write a haiku about streaming data", reasoning_effort="high")) + visible = "".join(c.content for c in chunks if isinstance(c.content, str)) + assert "" not in visible + assert "" not in visible + assert [c for c in chunks if c.additional_kwargs.get("reasoning")] + + +@pytest.mark.timeout(FAST) +def test_token_callbacks_never_see_side_channels() -> None: + tap = Tap() + list( + fresh_chat().stream( + "Write a haiku about streaming data", + reasoning_effort="high", + config={"callbacks": [tap]}, + ) + ) + assert "" not in "".join(tap.tokens) + + +@pytest.mark.timeout(FAST) +async def test_astream_events_are_filtered() -> None: + llm = fresh_chat() + body = "" + async for ev in llm.astream_events( + "Write a haiku about streaming data", version="v2", reasoning_effort="high" + ): + if ev["event"] == "on_chat_model_stream": + content = ev["data"]["chunk"].content + if isinstance(content, str): + body += content + assert body + assert "" not in body + + +@pytest.mark.timeout(FAST) +async def test_astream_matches_sync() -> None: + llm = chat() + out = "".join( + [c.content async for c in llm.astream("Write a haiku about coding") if isinstance(c.content, str)] + ) + assert len(out) > 10 + assert "" not in out + + +@pytest.mark.timeout(SLOW) +def test_streams_inline_precontext_when_enabled() -> None: + verbose = chat(show_additional_info=True, bypass_cache=True) + chunks = list( + verbose.stream( + [ + HumanMessage( + content=[ + {"type": "text", "text": "Where is this store located?"}, + image_part(IMAGES["receipt"]), + ] + ) + ] + ) + ) + visible = "".join(c.content for c in chunks if isinstance(c.content, str)) + assert "" not in visible + precontext = [e for c in chunks for e in (c.additional_kwargs.get("precontext") or [])] + assert precontext diff --git a/python/tests/integration_tests/test_live_text.py b/python/tests/integration_tests/test_live_text.py new file mode 100644 index 0000000..203e231 --- /dev/null +++ b/python/tests/integration_tests/test_live_text.py @@ -0,0 +1,136 @@ +from __future__ import annotations + +import pytest +from langchain_core.messages import HumanMessage, SystemMessage +from langchain_core.output_parsers import StrOutputParser +from langchain_core.prompts import ChatPromptTemplate +from pydantic import BaseModel + +from tests.integration_tests.conftest import FAST, SLOW, chat, fresh_chat, requires_key, text_of + +pytestmark = requires_key + + +@pytest.fixture(scope="module") +def llm(): + return chat() + + +# --- text ----------------------------------------------------------------- + + +@pytest.mark.timeout(FAST) +def test_text_gen_story(llm) -> None: + assert len(text_of(llm.invoke("Write a short story about a robot learning to paint"))) > 50 + + +@pytest.mark.timeout(FAST) +def test_text_gen_story_with_system(llm) -> None: + res = llm.invoke( + [ + SystemMessage("You are a helpful assistant."), + HumanMessage("Write a short story about a robot learning to paint"), + ] + ) + assert len(text_of(res)) > 50 + + +@pytest.mark.timeout(FAST) +def test_text_capital(llm) -> None: + assert "paris" in text_of(llm.invoke("What is the capital of France? Answer in one word.")).lower() + + +@pytest.mark.timeout(FAST) +def test_interfaze_envelope(llm) -> None: + res = llm.invoke("Hello") + assert res.response_metadata["model_provider"] == "interfaze" + assert isinstance(res.response_metadata["vcache"], bool) + assert res.usage_metadata["total_tokens"] > 0 + + +# --- structured output ---------------------------------------------------- + + +class Weather(BaseModel): + city: str + temperature_celsius: float + condition: str + + +class Founder(BaseModel): + name: str + + +class CapitalPop(BaseModel): + city: str + population_millions: float + + +class Capital(BaseModel): + capital: str + + +@pytest.mark.timeout(FAST) +def test_structured_weather(llm) -> None: + out = llm.with_structured_output(Weather).invoke("What is the current weather in Tokyo?") + assert out.city + assert isinstance(out.temperature_celsius, float) + assert out.condition + + +@pytest.mark.timeout(FAST) +def test_structured_founder(llm) -> None: + assert llm.with_structured_output(Founder).invoke("Who is the founder of JigsawStack?").name + + +@pytest.mark.timeout(FAST) +def test_structured_capital_pop(llm) -> None: + out = llm.with_structured_output(CapitalPop).invoke( + "What is the capital of France and its approximate metro population in millions?" + ) + assert "paris" in out.city.lower() + assert isinstance(out.population_millions, float) + + +@pytest.mark.timeout(FAST) +def test_structured_json_no_fences(llm) -> None: + out = llm.with_structured_output(Capital, include_raw=True).invoke( + "Return ONLY a JSON object (no markdown fences) with key 'capital' set to the capital of France." + ) + assert "```" not in text_of(out["raw"]) + assert "paris" in out["parsed"].capital.lower() + + +# --- reasoning ------------------------------------------------------------ + + +@pytest.mark.timeout(FAST) +def test_reasoning_math() -> None: + # The semantic cache replays a stored answer without its block. + res = fresh_chat().invoke("What is 25 * 47?", reasoning_effort="high") + assert "1175" in text_of(res) + assert res.response_metadata.get("reasoning") + assert "" not in text_of(res) + + +# --- runnable surface ----------------------------------------------------- + + +@pytest.mark.timeout(FAST) +def test_lcel_chain(llm) -> None: + chain = ChatPromptTemplate.from_template("Translate to {lang}: {text}") | llm | StrOutputParser() + assert chain.invoke({"lang": "French", "text": "Hello"}) + + +@pytest.mark.timeout(SLOW) +def test_batch(llm) -> None: + out = llm.batch(["Summarize the colour blue in one sentence.", "Name one planet.", "What is 2+2?"]) + assert len(out) == 3 + assert all(text_of(m) for m in out) + + +@pytest.mark.timeout(FAST) +async def test_ainvoke(llm) -> None: + res = await llm.ainvoke("What is the capital of France? Answer in one word.") + assert "paris" in text_of(res).lower() + assert res.response_metadata["model_provider"] == "interfaze" diff --git a/python/tests/integration_tests/test_live_tools.py b/python/tests/integration_tests/test_live_tools.py new file mode 100644 index 0000000..d223fe1 --- /dev/null +++ b/python/tests/integration_tests/test_live_tools.py @@ -0,0 +1,306 @@ +from __future__ import annotations + +import json +import re + +import pytest +from langchain_core.messages import AIMessage, HumanMessage, ToolMessage +from pydantic import BaseModel + +from tests.integration_tests.conftest import SLOW, chat, precontext_names, requires_key, text_of + +pytestmark = [requires_key, pytest.mark.timeout(SLOW)] + + +@pytest.fixture(scope="module") +def llm(): + return chat() + + +LONG_TEXT = ( + "Interfaze is a new kind of AI platform built specifically for deterministic, developer-grade " + "tasks. Unlike general-purpose large language models that excel at open-ended conversation but " + "struggle with consistency, Interfaze focuses on the operations that real software systems " + "depend on: extracting fields from documents, scraping structured data from arbitrary websites, " + "transcribing audio with speaker labels, translating content across hundreds of languages while " + "preserving meaning, detecting objects in images and GUI screenshots, forecasting time series " + "without per-customer model training, and executing code in a sandboxed environment. Every " + "capability is exposed through an OpenAI-compatible chat completions API so existing tooling " + "works without modification." +) + +SERIES = [ + {"date": "2024-01-01", "value": 412}, + {"date": "2024-01-08", "value": 387}, + {"date": "2024-01-15", "value": 524}, + {"date": "2024-01-22", "value": 461}, + {"date": "2024-01-29", "value": 398}, + {"date": "2024-02-05", "value": 542}, + {"date": "2024-02-12", "value": 475}, + {"date": "2024-02-19", "value": 401}, + {"date": "2024-02-26", "value": 558}, + {"date": "2024-03-04", "value": 489}, + {"date": "2024-03-11", "value": 419}, + {"date": "2024-03-18", "value": 571}, +] + + +# --- translation ---------------------------------------------------------- + + +class StructuredTranslation(BaseModel): + translated_text: str + translated_text_iso_code: str + original_text_iso_code: str + + +def test_translate_structured(llm) -> None: + out = llm.with_structured_output(StructuredTranslation, include_raw=True).invoke( + "Translate the following text into French: 'The UK drinks about 100-160 million cups of tea " + "every day, and 98% of tea drinkers add milk to their tea.'" + ) + parsed: StructuredTranslation = out["parsed"] + assert "fr" in parsed.translated_text_iso_code.lower() + assert "en" in parsed.original_text_iso_code.lower() + assert "translate" in precontext_names(out["raw"]) + + +class TargetedTranslation(BaseModel): + translated_text: str + target_language: str + + +def test_translate_es(llm) -> None: + out = llm.with_structured_output(TargetedTranslation).invoke( + "Hello, how are you today? I would like to order a coffee. — in Spanish please" + ) + assert re.search(r"hola|cómo|está|café", out.translated_text.lower()) + + +class SimpleTranslation(BaseModel): + translated_text: str + + +def test_translate_long_fr(llm) -> None: + out = llm.with_structured_output(SimpleTranslation).invoke( + f'Can you give me this in French? "{LONG_TEXT}"' + ) + assert len(out.translated_text) >= len(LONG_TEXT) * 0.5 + assert any( + w in out.translated_text.lower() + for w in (" le ", " la ", " les ", " des ", " une ", " est ", " pour ", " avec ") + ) + + +def test_translate_ja(llm) -> None: + out = llm.with_structured_output(SimpleTranslation).invoke( + "how do you say 'Thank you for your help' in Japanese?" + ) + assert re.search(r"[぀-ヿ一-鿿]", out.translated_text) + + +def test_translate_markup(llm) -> None: + out = llm.with_structured_output(SimpleTranslation).invoke( + 'Translate this to French, preserving all HTML tags exactly: Click here ' + "to continue." + ) + for fragment in ('', "", "", ""): + assert fragment in out.translated_text + + +# --- web search ----------------------------------------------------------- + + +def test_web_search_basic(llm) -> None: + assert text_of(llm.invoke("Latest news on Nvidia")) + + +class TeslaFacts(BaseModel): + founders: list[str] + year_founded: int + sources: list[str] + + +def test_web_search_factual(llm) -> None: + out = llm.with_structured_output(TeslaFacts).invoke("who founded Tesla and when?") + assert re.search(r"musk|eberhard|tarpenning", " ".join(out.founders).lower()) + assert out.year_founded == 2003 + + +class Apollo(BaseModel): + summary: str + year: int + month: str + sources: list[str] + + +def test_web_search_history(llm) -> None: + out = llm.with_structured_output(Apollo).invoke("when did Apollo 11 land on the moon? give sources.") + assert out.year == 1969 + assert "jul" in out.month.lower() + assert len(out.summary) > 20 + assert out.sources + + +class NvidiaNews(BaseModel): + summary: str + current_stock_price: float + links: list[str] + + +def test_web_search_structured(llm) -> None: + out = llm.with_structured_output(NvidiaNews).invoke("Latest news on Nvidia") + assert out.summary + assert out.links + + +class Person(BaseModel): + summary: str + company: str | None + emails: list[str] | None + location: str | None + + +def test_web_search_person(llm) -> None: + out = llm.with_structured_output(Person, include_raw=True).invoke( + "Who is Yoeven D Khemlani, his company, his email and where is he based now?" + ) + assert out["parsed"].summary + assert precontext_names(out["raw"]) + + +# --- scraping ------------------------------------------------------------- + + +class Listing(BaseModel): + price: float + listing_name: str + seller_name: str + possible_delivery_time: str + + +class Listings(BaseModel): + products: list[Listing] + + +def test_scrape_ecommerce(llm) -> None: + out = llm.with_structured_output(Listings, include_raw=True).invoke( + "get all prices and listing of products for nintendo switch from " + "https://www.amazon.com/s?k=nintendo+switch+console" + ) + parsed: Listings = out["parsed"] + assert parsed.products + assert parsed.products[0].listing_name + assert re.search(r"web_extract|search|scraper", " ".join(precontext_names(out["raw"]))) + + +class Post(BaseModel): + title: str + points: int + + +class Posts(BaseModel): + posts: list[Post] + + +def test_scrape_hn(llm) -> None: + out = llm.with_structured_output(Posts).invoke( + "Extract post titles and points from https://news.ycombinator.com" + ) + assert out.posts + + +# --- forecast ------------------------------------------------------------- + + +class Prediction(BaseModel): + value: float + + +class Forecast(BaseModel): + predictions: list[Prediction] + + +def test_forecast_series(llm) -> None: + out = llm.with_structured_output(Forecast, include_raw=True).invoke( + f"Here's our weekly sales for the past 12 weeks: {json.dumps(SERIES)}. " + "What can we expect over the next month?" + ) + parsed: Forecast = out["parsed"] + assert len(parsed.predictions) >= 3 + for p in parsed.predictions: + assert 0 <= p.value <= 10_000 + assert "forecast" in precontext_names(out["raw"]) + + +# --- code sandbox --------------------------------------------------------- + + +class Factorial(BaseModel): + fractional: float + + +def test_sandbox_factorial(llm) -> None: + out = llm.with_structured_output(Factorial, include_raw=True).invoke("What is the factorial of 5?") + assert out["parsed"].fractional == 120 + # The router only reaches for the sandbox when it doesn't already know the answer. + names = precontext_names(out["raw"]) + if names: + assert re.search(r"code_execute|code_generation", " ".join(names)) + + +class Answer(BaseModel): + answer: int + + +def test_sandbox_count_r(llm) -> None: + assert llm.with_structured_output(Answer).invoke("How many r's are there in strawberry?").answer == 3 + + +class Script(BaseModel): + code: str + sample_input: str + sample_output: str + + +def test_sandbox_codegen(llm) -> None: + out = llm.with_structured_output(Script).invoke( + "write a python script for getting cpu type using subprocess module and verify your output" + ) + assert "subprocess" in out.code + + +# --- function calling ----------------------------------------------------- + + +def test_fc_horoscope(llm) -> None: + tools = [ + { + "type": "function", + "function": { + "name": "get_horoscope", + "description": "Get today's horoscope for an astrological sign.", + "parameters": { + "type": "object", + "properties": {"sign": {"type": "string"}}, + "required": ["sign"], + }, + }, + } + ] + bound = llm.bind_tools(tools) + first: AIMessage = bound.invoke([HumanMessage("Get my horoscope for Taurus")]) + assert first.tool_calls + assert first.tool_calls[0]["name"] == "get_horoscope" + + second = bound.invoke( + [ + HumanMessage("Get my horoscope for Taurus"), + first, + ToolMessage( + tool_call_id=first.tool_calls[0]["id"], + content="Today's horoscope for Taurus: You will have a great day!", + ), + ] + ) + assert text_of(second) diff --git a/python/tests/integration_tests/test_live_vision.py b/python/tests/integration_tests/test_live_vision.py new file mode 100644 index 0000000..7a1bb04 --- /dev/null +++ b/python/tests/integration_tests/test_live_vision.py @@ -0,0 +1,375 @@ +from __future__ import annotations + +from typing import Any, Literal + +import pytest +from langchain_core.messages import HumanMessage +from pydantic import BaseModel + +from tests.integration_tests.conftest import ( + FILES, + IMAGES, + SLOW, + chat, + file_part, + image_part, + precontext_names, + receipt_b64, + requires_key, +) + +pytestmark = [requires_key, pytest.mark.timeout(SLOW)] + + +@pytest.fixture(scope="module") +def llm(): + return chat() + + +def ask(prompt: str, part: dict[str, Any]) -> HumanMessage: + return HumanMessage(content=[{"type": "text", "text": prompt}, part]) + + +class Box(BaseModel): + top_left_x: float + top_left_y: float + bottom_right_x: float + bottom_right_y: float + + +# --- ocr ------------------------------------------------------------------ + + +class IdDocument(BaseModel): + full_first_name: str + full_last_name: str + full_address: str | None + email: str | None + id_type: str + + +def test_ocr_id_document(llm) -> None: + out = llm.with_structured_output(IdDocument, include_raw=True).invoke( + [ask("Extract information from the image based on the schema.", image_part(IMAGES["id_medium"]))] + ) + parsed: IdDocument = out["parsed"] + assert "iv" in parsed.full_first_name.lower() + assert parsed.full_last_name.lower().replace("ñ", "n").find("munoz") >= 0 + assert parsed.id_type + assert "ocr" in precontext_names(out["raw"]) + + +class DriverLicence(BaseModel): + first_name: str + last_name: str + dob: str + driver_licence_number: str + + +def test_ocr_id_jpg(llm) -> None: + out = llm.with_structured_output(DriverLicence, include_raw=True).invoke( + [ask("Extract the details from this ID", image_part(IMAGES["id_jpg"]))] + ) + parsed: DriverLicence = out["parsed"] + assert parsed.first_name and parsed.dob and parsed.driver_licence_number + assert "ocr" in precontext_names(out["raw"]) + + +class LineItem(BaseModel): + name: str + price: str + + +class ReceiptFields(BaseModel): + items: list[LineItem] + highlighted_items: list[LineItem] + total_cost: str + tax: str + + +def test_ocr_receipt_fields(llm) -> None: + out = llm.with_structured_output(ReceiptFields, include_raw=True).invoke( + [ask("Extract text from the image.", image_part(IMAGES["receipt_items"]))] + ) + parsed: ReceiptFields = out["parsed"] + assert parsed.items + assert "144.02" in parsed.total_cost + assert "4.58" in parsed.tax + assert "gale" in " ".join(i.name for i in parsed.highlighted_items).lower() + assert "ocr" in precontext_names(out["raw"]) + + +class QueryResult(BaseModel): + text: str + confidence: float + + +class StoreLocation(BaseModel): + query_results: list[QueryResult] + text: str + confidence: float + + +def test_ocr_store_location(llm) -> None: + out = llm.with_structured_output(StoreLocation).invoke( + [ask("Where is this store located?", image_part(IMAGES["receipt"]))] + ) + haystack = f"{' '.join(r.text for r in out.query_results)} {out.text}".lower() + assert "greenwood" in haystack + + +class Word(Box): + text: str + + +class WordBoxes(BaseModel): + text: str + words: list[Word] + + +def test_ocr_word_bboxes(llm) -> None: + out = llm.with_structured_output(WordBoxes, include_raw=True).invoke( + [ask("extract every word and its position from this receipt", image_part(IMAGES["receipt"]))] + ) + parsed: WordBoxes = out["parsed"] + assert len(parsed.words) >= 10 + for w in parsed.words: + assert w.top_left_x >= 0 + assert w.top_left_y >= 0 + assert w.bottom_right_x >= w.top_left_x - 2 + assert w.bottom_right_y >= w.top_left_y - 2 + assert "ocr" in precontext_names(out["raw"]) + + +class Paper(BaseModel): + title: str + authors: list[str] + + +def test_ocr_pdf_title_authors(llm) -> None: + out = llm.with_structured_output(Paper, include_raw=True).invoke( + [ + ask( + "Extract the title and author names from the first page.", + file_part(FILES["attention_pdf"], "attention.pdf"), + ) + ] + ) + parsed: Paper = out["parsed"] + assert "attention" in parsed.title.lower() + assert "vaswani" in " ".join(parsed.authors).lower() + assert "ocr" in precontext_names(out["raw"]) + + +class Translation(BaseModel): + text_in_original_language: str + text_in_telugu: str + width_of_image: float + height_of_image: float + + +class Multilang(BaseModel): + translations: list[Translation] + + +def test_ocr_multilang(llm) -> None: + out = llm.with_structured_output(Multilang).invoke( + [ask("Extract information from the image based on the schema.", image_part(IMAGES["multilang"]))] + ) + assert out.translations + + +class LayoutElement(Box): + type: Literal["heading", "paragraph", "formula", "figure", "table", "caption", "list"] + content: str + + +class Page(BaseModel): + page_number: int + elements: list[LayoutElement] + + +class Layout(BaseModel): + pages: list[Page] + + +def test_ocr_document_layout(llm) -> None: + out = llm.with_structured_output(Layout, include_raw=True).invoke( + [ + ask( + "extract the layout elements (headings, paragraphs, figures, tables) with bounding " + "boxes from the first page", + file_part(FILES["attention_pdf"], "attention.pdf"), + ) + ] + ) + parsed: Layout = out["parsed"] + assert parsed.pages + elements = [e for p in parsed.pages for e in p.elements] + assert elements + assert any(e.type in {"heading", "paragraph"} for e in elements) + assert "ocr" in precontext_names(out["raw"]) + + +# --- document extraction / markdown --------------------------------------- + + +def inline_receipt() -> dict[str, Any]: + return image_part(f"data:image/jpeg;base64,{receipt_b64()}") + + +class BillItem(BaseModel): + description: str + price: float | None + + +class Bill(BaseModel): + vendor_name: str + total_amount: float + bill_date: str + line_items: list[BillItem] + + +def test_doc_invoice_exact(llm) -> None: + out = llm.with_structured_output(Bill).invoke( + [ + ask( + "Extract the bill data from this receipt: vendor_name, total_amount (number), " + "bill_date (YYYY-MM-DD), and line_items[{description, price}].", + inline_receipt(), + ) + ] + ) + assert abs(out.total_amount - 15.15) <= 0.01 + assert out.bill_date == "2018-05-06" + assert "marco polo" in out.vendor_name.lower() + assert out.line_items + + +class Markdown(BaseModel): + markdown: str + + +def test_md_image_to_md(llm) -> None: + out = llm.with_structured_output(Markdown).invoke( + [ask("Convert this receipt image to markdown.", inline_receipt())] + ) + assert len(out.markdown) >= 80 + assert "marco polo" in out.markdown.lower() + assert "mocha" in out.markdown.lower() + assert "15.15" in out.markdown + + +def test_md_pdf_to_md(llm) -> None: + import re + + out = llm.with_structured_output(Markdown, include_raw=True).invoke( + [ + ask( + "Convert the first page of this document to markdown.", + file_part(FILES["attention_pdf"], "attention.pdf"), + ) + ] + ) + # Heading style is stable; bold emphasis is not, so it is not asserted. + md: str = out["parsed"].markdown + assert re.search(r"#{1,3}\s*attention is all you need", md, re.IGNORECASE) + assert len(md) > 200 + assert "ocr" in precontext_names(out["raw"]) + + +# --- object / gui detection ----------------------------------------------- + + +class NamedObject(BaseModel): + name: str + + +class Objects(BaseModel): + objects: list[NamedObject] + + +def test_object_detection_absent(llm) -> None: + out = llm.with_structured_output(Objects).invoke( + [ask("detect elephants in this image", image_part(IMAGES["katana"]))] + ) + assert out.objects == [] + + +class BoxedObject(Box): + name: str + + +class BoxedObjects(BaseModel): + objects: list[BoxedObject] + + +def test_object_detection_bbox(llm) -> None: + out = llm.with_structured_output(BoxedObjects, include_raw=True).invoke( + [ask("detect the position of the katana in this image", image_part(IMAGES["katana"]))] + ) + parsed: BoxedObjects = out["parsed"] + assert parsed.objects + box = parsed.objects[0] + assert "katana" in box.name.lower() + assert abs(box.top_left_x - 1078) <= 15 + assert abs(box.top_left_y - 474) <= 15 + assert abs(box.bottom_right_x - 1188) <= 15 + assert abs(box.bottom_right_y - 1026) <= 15 + assert "object_detection" in precontext_names(out["raw"]) + + +def test_object_detection_multi(llm) -> None: + out = llm.with_structured_output(BoxedObjects, include_raw=True).invoke( + [ask("detect all objects with bounding boxes", image_part(IMAGES["bus"]))] + ) + # Recall on this image swings from 1 to 8 objects run to run, and the labels vary + # ("bus" vs a bare "object") — reproduced identically through the core interfaze SDK. + # What the integration owns is the round-trip: well-formed boxes and the precontext. + parsed: BoxedObjects = out["parsed"] + assert parsed.objects + for o in parsed.objects: + assert o.bottom_right_x >= o.top_left_x + assert o.bottom_right_y >= o.top_left_y + assert "object_detection" in precontext_names(out["raw"]) + + +class GuiElement(Box): + name: str + + +class Gui(BaseModel): + gui_elements: list[GuiElement] + + +def test_gui_detection_form(llm) -> None: + out = llm.with_structured_output(Gui, include_raw=True).invoke( + [ask("find all the text fields and the clear form button", image_part(IMAGES["gui_form"]))] + ) + # Element count swings between 1 and 12 across runs (reproduced with the core + # interfaze SDK), so assert the envelope rather than a per-field inventory. + parsed: Gui = out["parsed"] + assert len(parsed.gui_elements) >= 1 + for e in parsed.gui_elements: + assert e.bottom_right_x <= 3600 + assert e.bottom_right_y <= 2338 + assert "gui_detection" in precontext_names(out["raw"]) + + +class BoxedText(Box): + text: str + + +class ObjectsAndText(BaseModel): + objects: list[BoxedObject] + texts: list[BoxedText] + + +def test_object_detection_with_text(llm) -> None: + out = llm.with_structured_output(ObjectsAndText, include_raw=True).invoke( + [ask("Get the position of the crane in the image and any text", image_part(IMAGES["construction"]))] + ) + # The crane is not always detected; what must hold is that detection + OCR ran and + # the schema came back well-formed. + assert isinstance(out["parsed"].objects, list) + assert precontext_names(out["raw"]) diff --git a/python/tests/unit_tests/test_chat_models.py b/python/tests/unit_tests/test_chat_models.py index 1caf360..db1c27c 100644 --- a/python/tests/unit_tests/test_chat_models.py +++ b/python/tests/unit_tests/test_chat_models.py @@ -8,6 +8,7 @@ import pytest import respx from interfaze import INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError +from langchain_core.callbacks import BaseCallbackHandler, CallbackManager from langchain_core.messages import HumanMessage from langchain_interfaze import ChatInterfaze @@ -141,23 +142,63 @@ def test_response_without_precontext_or_reasoning_unaffected() -> None: assert result.content == "Hi!" -# request-side precontext -@respx.mock -def test_request_precontext_injected() -> None: - route = mock_json(BASIC) - model = ChatInterfaze(api_key="t", precontext=[{"name": "ocr", "result": {"extracted_text": "y"}}]) - model.invoke([HumanMessage("hi")]) - body = last_body(route) - assert body["precontext"] == [{"name": "ocr", "result": {"extracted_text": "y"}}] +# provider identity +def test_provider_identity() -> None: + model = ChatInterfaze(api_key="t") + assert model._llm_type == "interfaze-chat" + assert model._get_ls_params()["ls_provider"] == "interfaze" + assert model.lc_secrets == {"openai_api_key": "INTERFAZE_API_KEY"} + assert model.get_lc_namespace() == ["langchain_interfaze", "chat_models"] + assert model.metadata is not None + assert "langchain-interfaze" in model.metadata["lc_versions"] @respx.mock -def test_request_without_precontext_field_omits_it() -> None: - route = mock_json(BASIC) +def test_model_provider_stamped_on_response() -> None: + mock_json(BASIC) model = ChatInterfaze(api_key="t") - model.invoke([HumanMessage("hi")]) - body = last_body(route) - assert "precontext" not in body + assert model.invoke([HumanMessage("hi")]).response_metadata["model_provider"] == "interfaze" + + +def test_defaults_to_long_timeout_but_respects_override() -> None: + assert ChatInterfaze(api_key="t").request_timeout == 900.0 + assert ChatInterfaze(api_key="t", timeout=30).request_timeout == 30 + + +def test_never_routes_to_the_responses_api() -> None: + # `reasoning=` would otherwise flip ChatOpenAI over to /v1/responses. + assert ChatInterfaze(api_key="t", reasoning={"summary": "auto"}).use_responses_api is False + + +# control-plane headers +def test_control_headers() -> None: + model = ChatInterfaze( + api_key="t", + show_additional_info=True, + bypass_moa=True, + bypass_cache=True, + admin_key="adm", + default_headers={"x-custom": "1"}, + ) + assert model.default_headers == { + "x-custom": "1", + "x-show-additional-info": "true", + "x-interfaze-bypass-moa": "true", + "x-interfaze-bypass-cache": "true", + "x-admin-key": "adm", + } + + +def test_no_control_headers_by_default() -> None: + assert ChatInterfaze(api_key="t").default_headers is None + + +@respx.mock +def test_streaming_asks_for_usage() -> None: + # langchain-openai only auto-enables this for OpenAI's own base URL. + route = mock_sse([_chunk({"content": "hi"}), _chunk({}, finish_reason="stop")]) + list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) + assert last_body(route)["stream_options"] == {"include_usage": True} # video content blocks @@ -174,7 +215,21 @@ def test_video_block_converted_to_file_part() -> None: model.invoke([message]) # must not raise body = last_body(route) content = body["messages"][-1]["content"] - assert {"type": "file", "file": {"file_data": VIDEO_URL}} in content + assert {"type": "file", "file": {"file_data": VIDEO_URL, "format": "video/mp4"}} in content + + +@respx.mock +def test_video_block_url_without_known_extension_omits_format() -> None: + route = mock_json(BASIC) + model = ChatInterfaze(api_key="t") + model.invoke([HumanMessage(content=[{"type": "video", "url": "https://example.com/clip"}])]) + assert last_body(route)["messages"][-1]["content"][0]["file"] == {"file_data": "https://example.com/clip"} + + +def test_video_block_file_id_raises() -> None: + model = ChatInterfaze(api_key="t") + with pytest.raises(InterfazeError, match="file_id"): + model.invoke([HumanMessage(content=[{"type": "video", "file_id": "file-123"}])]) @respx.mock @@ -259,16 +314,6 @@ def test_non_streaming_strips_inline_tags() -> None: assert result.response_metadata["precontext"] == [{"name": "ocr", "result": {"x": 1}}] -# more video content blocks -@respx.mock -def test_video_block_file_id() -> None: - route = mock_json(BASIC) - model = ChatInterfaze(api_key="t") - model.invoke([HumanMessage(content=[{"type": "video", "file_id": "file-123"}])]) - content = last_body(route)["messages"][-1]["content"] - assert content[0] == {"type": "file", "file": {"file_id": "file-123"}} - - @respx.mock def test_video_block_forwards_filename() -> None: route = mock_json(BASIC) @@ -297,3 +342,31 @@ def test_streaming_plain_content_emits_no_side_channel_chunk() -> None: assert not any( c.additional_kwargs.get("precontext") or c.additional_kwargs.get("reasoning") for c in chunks ) + + +# token callbacks must never see the raw side-channel tags. Core's own stream() calls +# `_stream` without a run_manager, but the v2 protocol path passes one straight through, +# and ChatOpenAI fires on_llm_new_token before yielding — hence the explicit check here. +@respx.mock +def test_run_manager_tokens_are_filtered() -> None: + mock_sse(THINK_SPLIT) + model = ChatInterfaze(api_key="t") + seen: list[str] = [] + + class Tap(BaseCallbackHandler): + def on_llm_new_token(self, token: str, **kwargs: Any) -> None: + seen.append(token) + + manager = CallbackManager.configure(inheritable_callbacks=[Tap()]) + run_manager = manager.on_chat_model_start({}, [[HumanMessage("x")]])[0] + list(model._stream([HumanMessage("x")], run_manager=run_manager)) + assert "" not in "".join(seen) + assert "".join(seen) == "The sky is blue." + + +@respx.mock +def test_stream_text_matches_filtered_content() -> None: + mock_sse(THINK_SPLIT) + model = ChatInterfaze(api_key="t") + gens = list(model._stream([HumanMessage("x")])) + assert all(g.text == g.message.content for g in gens) diff --git a/python/tests/unit_tests/test_imports.py b/python/tests/unit_tests/test_imports.py index 2e48866..6aa282f 100644 --- a/python/tests/unit_tests/test_imports.py +++ b/python/tests/unit_tests/test_imports.py @@ -1,6 +1,6 @@ from langchain_interfaze import __all__ -EXPECTED = ["ChatInterfaze"] +EXPECTED = ["ChatInterfaze", "__version__"] def test_all_imports() -> None: From 374fc6f1937eb144a1b6a28f027870c763627e41 Mon Sep 17 00:00:00 2001 From: Abhinavexist Date: Sat, 8 Aug 2026 00:33:37 +0530 Subject: [PATCH 02/28] fix: reasoning precedence, streamed side-field duplication, provider id --- .github/workflows/qa-live.yml | 49 ++ .gitignore | 4 + README.md | 51 +- js/README.md | 38 +- js/package-lock.json | 504 ++++++++++++++++++ js/package.json | 3 +- js/scripts/qa-live.ts | 224 ++++++++ js/src/chat_models.ts | 56 +- js/src/version.ts | 1 - js/test-live/contract.live.test.ts | 113 ---- js/test-live/helpers.ts | 83 --- js/test-live/media.live.test.ts | 63 --- js/test-live/streaming.live.test.ts | 79 --- js/test-live/text.live.test.ts | 96 ---- js/test-live/tools.live.test.ts | 227 -------- js/test-live/vision.live.test.ts | 274 ---------- js/test/constructor.test.ts | 17 +- js/test/helpers.ts | 1 - js/test/identity.test.ts | 2 +- js/test/stream.test.ts | 3 +- js/test/stream_events.test.ts | 6 - js/tsconfig.json | 2 +- js/vitest.live.config.ts | 18 - python/README.md | 68 +-- python/langchain_interfaze/_version.py | 2 - python/langchain_interfaze/chat_models.py | 84 ++- python/pyproject.toml | 10 +- python/scripts/qa_live.py | 276 ++++++++++ python/tests/integration_tests/conftest.py | 84 --- .../integration_tests/test_live_contract.py | 184 ------- .../integration_tests/test_live_media.py | 105 ---- .../integration_tests/test_live_streaming.py | 118 ---- .../tests/integration_tests/test_live_text.py | 136 ----- .../integration_tests/test_live_tools.py | 306 ----------- .../integration_tests/test_live_vision.py | 375 ------------- python/tests/unit_tests/conftest.py | 102 ++++ python/tests/unit_tests/test_chat.py | 57 ++ python/tests/unit_tests/test_chat_models.py | 372 ------------- python/tests/unit_tests/test_client.py | 75 +++ python/tests/unit_tests/test_identity.py | 32 ++ python/tests/unit_tests/test_inputs.py | 66 +++ python/tests/unit_tests/test_stream.py | 140 +++++ 42 files changed, 1664 insertions(+), 2842 deletions(-) create mode 100644 .github/workflows/qa-live.yml create mode 100644 js/scripts/qa-live.ts delete mode 100644 js/test-live/contract.live.test.ts delete mode 100644 js/test-live/helpers.ts delete mode 100644 js/test-live/media.live.test.ts delete mode 100644 js/test-live/streaming.live.test.ts delete mode 100644 js/test-live/text.live.test.ts delete mode 100644 js/test-live/tools.live.test.ts delete mode 100644 js/test-live/vision.live.test.ts delete mode 100644 js/vitest.live.config.ts create mode 100644 python/scripts/qa_live.py delete mode 100644 python/tests/integration_tests/conftest.py delete mode 100644 python/tests/integration_tests/test_live_contract.py delete mode 100644 python/tests/integration_tests/test_live_media.py delete mode 100644 python/tests/integration_tests/test_live_streaming.py delete mode 100644 python/tests/integration_tests/test_live_text.py delete mode 100644 python/tests/integration_tests/test_live_tools.py delete mode 100644 python/tests/integration_tests/test_live_vision.py create mode 100644 python/tests/unit_tests/conftest.py create mode 100644 python/tests/unit_tests/test_chat.py delete mode 100644 python/tests/unit_tests/test_chat_models.py create mode 100644 python/tests/unit_tests/test_client.py create mode 100644 python/tests/unit_tests/test_identity.py create mode 100644 python/tests/unit_tests/test_inputs.py create mode 100644 python/tests/unit_tests/test_stream.py diff --git a/.github/workflows/qa-live.yml b/.github/workflows/qa-live.yml new file mode 100644 index 0000000..b0449a3 --- /dev/null +++ b/.github/workflows/qa-live.yml @@ -0,0 +1,49 @@ +name: Live QA + +on: + workflow_dispatch: + schedule: + - cron: "0 6 * * 1" # weekly, Monday 06:00 UTC + +concurrency: + group: live-qa + cancel-in-progress: true + +jobs: + python: + name: live QA (python) + runs-on: ubuntu-latest + defaults: + run: + working-directory: python + steps: + - uses: actions/checkout@v5 + - uses: astral-sh/setup-uv@v9.0.0 + with: + python-version: "3.12" + enable-cache: true + - name: Install + run: uv sync + - name: Run live QA + env: + INTERFAZE_API_KEY: ${{ secrets.INTERFAZE_API_KEY }} + run: uv run python scripts/qa_live.py + + js: + name: live QA (js) + runs-on: ubuntu-latest + defaults: + run: + working-directory: js + steps: + - uses: actions/checkout@v5 + - uses: actions/setup-node@v7 + with: + node-version: 22 + cache: npm + cache-dependency-path: js/package-lock.json + - run: npm ci + - name: Run live QA + env: + INTERFAZE_API_KEY: ${{ secrets.INTERFAZE_API_KEY }} + run: npm run qa:live diff --git a/.gitignore b/.gitignore index cc6b4fc..c9954a5 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,7 @@ +.env +.env.* +!.env.example + __pycache__/ *.py[cod] .venv/ diff --git a/README.md b/README.md index b50a28a..1059d39 100644 --- a/README.md +++ b/README.md @@ -397,9 +397,9 @@ const chain = ChatPromptTemplate.fromTemplate("Translate to {lang}: {text}").pip await chain.invoke({ lang: "French", text: "Hello" }); ``` -## Control options +## Client options -Four Interfaze-specific switches, mirroring the core SDK: +Set router, cache, and streaming behavior once on the client: Python: @@ -407,8 +407,7 @@ Python: llm = ChatInterfaze( show_additional_info=True, # emit inline while streaming bypass_cache=True, # skip the semantic cache - bypass_moa=True, # skip the internal tool router - admin_key="...", # surfaces a `debug` field + bypass_moa=True, # skip the mixture-of-architecture router ) ``` @@ -418,8 +417,7 @@ TypeScript: const llm = new ChatInterfaze({ showAdditionalInfo: true, // emit inline while streaming bypassCache: true, // skip the semantic cache - bypassMoA: true, // skip the internal tool router - adminKey: "...", // surfaces a `debug` field + bypassMoA: true, // skip the mixture-of-architecture router }); ``` @@ -447,19 +445,21 @@ await llm.invoke([new SystemMessage("web_search"), new HumanMessage await llm.invoke([new SystemMessage("S1, S2, S3"), new HumanMessage("How to kill a human?")]); // -> "unsafe S1" ``` -One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core `interfaze` client directly ([Python](https://github.com/InterfazeAI/interfaze-python) · [TypeScript / JavaScript](https://github.com/InterfazeAI/interfaze-js)). +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. + +For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core `interfaze` client directly ([Python](https://github.com/InterfazeAI/interfaze-python) · [TypeScript / JavaScript](https://github.com/InterfazeAI/interfaze-js)). ## Server limits -`ChatInterfaze` forwards standard LangChain options, but Interfaze validates a narrower range than OpenAI: +`ChatInterfaze` forwards standard LangChain options, but validates only the subset supported by Interfaze: | Option | Accepted | | ------------------------------------- | ------------------------------------------------------------------- | -| `temperature` | `0`–`1` (values above `1` are a `400`) | -| `max_tokens` / `maxTokens` | `1`–`32000` | -| `reasoning_effort` / `reasoningEffort`| `minimal`, `low`, `medium`, `high`, plus `on` / `off` / `auto` | -| `tool_choice` | ignored — the router always picks | -| `stop`, `n`, `seed`, `logprobs` | ignored | +| `temperature` | `0`–`1` (values above `1` are a `400`) | +| `max_tokens` / `maxTokens` | `1`–`32000` | +| `reasoning_effort` / `reasoningEffort`| `minimal`, `low`, `medium`, `high`, plus `on` / `off` / `auto` | +| `tool_choice` | ignored — the router always picks | +| `stop`, `n`, `seed`, `logprobs` | ignored | ## Errors @@ -489,29 +489,8 @@ import { BadRequestError, InterfazeError, RateLimitError } from "interfaze"; | [Precontext](#precontext) | `response_metadata["precontext"]` | `response_metadata.precontext` | | [Async and batch](#async-and-batch) | `ainvoke` / `astream` / `batch` | `invoke` / `stream` / `batch` | | [Chains](#chains-lcel) | LCEL (`\|`) | LCEL (`.pipe()`) | -| [Control options](#control-options) | `bypass_cache=True`, … | `bypassCache: true`, … | -| [Tasks / guardrails](#tasks-and-guardrails) | `SystemMessage("…")` | `new SystemMessage("…")` | - -## Development - -Unit tests are offline (mocked transport) and run in CI: - -```bash -cd python && uv sync --all-groups && uv run pytest tests/unit_tests/ -cd js && npm ci && npm test -``` - -There is also a live suite covering every modality — text, structured output, OCR, document extraction and markdown, object/GUI detection, audio, video, translation, web search, scraping, forecasting, reasoning, function calling, streaming, the code sandbox, guardrails, `` tags, and the negative API-contract cases. It needs a real key and is skipped without one: - -```bash -export INTERFAZE_API_KEY=sk_... -export INTERFAZE_BASE_URL=https://api.interfaze.ai/v1 # optional - -cd python && uv run --group test_integration pytest tests/integration_tests -p no:cacheprovider --no-cov -n 8 -cd js && npm run test:live -``` - -Two tests read shared fixtures (a base64 receipt) from `interfaze-sdk-tests/fixtures`; point `INTERFAZE_FIXTURES` at that directory if it isn't next to this repo. +| [Client options](#client-options) | `bypass_cache=True`, … | `bypassCache: true`, … | +| [Tasks / guardrails](#tasks-and-guardrails) | `SystemMessage("…")` | `new SystemMessage("…")` | ## License diff --git a/js/README.md b/js/README.md index 07f29b4..be83cf5 100644 --- a/js/README.md +++ b/js/README.md @@ -8,6 +8,7 @@ The official [LangChain](https://js.langchain.com) integration for [Interfaze](h ```bash npm install @interfaze/langchain +# or: yarn add @interfaze/langchain · pnpm add @interfaze/langchain · bun add @interfaze/langchain ``` `@langchain/openai`, `@langchain/core`, and `interfaze` are peer dependencies - `@interfaze/langchain` builds `ChatInterfaze` on top of them. The structured-output and tool examples below use `zod` for schemas (`npm install zod`); it's an optional peer. @@ -20,11 +21,11 @@ import { ChatInterfaze } from "@interfaze/langchain"; const llm = new ChatInterfaze({ apiKey: "sk_..." }); // or set INTERFAZE_API_KEY and call new ChatInterfaze() ``` -`ChatInterfaze` is a standard LangChain chat model, so the usual fields (`temperature`, `maxTokens`, `timeout`, …) are forwarded; `configuration.baseURL` and `model` default to the Interfaze endpoint and `interfaze-beta`. +`ChatInterfaze` is a standard LangChain chat model, so the usual options (`temperature`, `maxTokens`, `timeout`, `reasoningEffort`, …) are forwarded; `configuration.baseURL` and `model` default to the Interfaze endpoint and `interfaze-beta`. ## Your first request -Extract structured data from an ID. Interfaze runs OCR for you, `withStructuredOutput` returns your schema, and the raw OCR lands on `response_metadata.precontext` - pass `includeRaw: true` to keep both: +Extract structured data from an ID. Interfaze runs OCR for you, `withStructuredOutput` returns your schema, and the raw OCR lands on `response_metadata.precontext` — keep both with `includeRaw`: ```ts import { AIMessage, HumanMessage } from "@langchain/core/messages"; @@ -64,6 +65,8 @@ res.response_metadata.vcache; // whether the semantic cache was hit ## Chat +Pass a plain string for a one-off, or a message list for multi-turn. + ```ts import { HumanMessage, SystemMessage } from "@langchain/core/messages"; @@ -72,8 +75,6 @@ const res = await llm.invoke([new SystemMessage("You are concise."), new HumanMe res.content; // a web search backs the answer here ``` -Pass a plain string for a one-off (`llm.invoke("…")`), or a message list for multi-turn. - ### Streaming Stream the reply as it's generated; the inline ``/`` side-channels are stripped from the streamed content: @@ -86,7 +87,7 @@ for await (const chunk of await llm.stream("Summarize this week's top AI researc ### Structured output -`withStructuredOutput` takes a zod schema (or JSON schema) and returns instances: +`withStructuredOutput` takes a zod schema (or JSON schema) and returns instances. Pass `{ includeRaw: true }` to also get the underlying `AIMessage` (and its `precontext`). ```ts import { z } from "zod"; @@ -107,8 +108,6 @@ await structured.invoke([ ]); // -> { merchant: "Walmart", total: 144.02 } ``` -Pass `{ includeRaw: true }` to also get the underlying `AIMessage` (and its `precontext`). - ### Tools and function calling Bind tools with `bindTools`, then read `tool_calls` off the response: @@ -134,14 +133,14 @@ res.tool_calls; // [{ name: "get_weather", args: { city: "Tokyo" }, id: ... }] ## Reasoning -Pass `reasoningEffort` as a call option; the reasoning text comes back on `response_metadata.reasoning`: +The reasoning text comes back on `response_metadata.reasoning`. Pass `reasoningEffort` as a call option, or `.withConfig({ reasoningEffort: "high" })` to apply it to every call: ```ts const res = await llm.invoke("Which region should we launch in first, and why?", { reasoningEffort: "high" }); res.response_metadata.reasoning; ``` -Set it once on the model with `new ChatInterfaze({ reasoningEffort: "high" })` — which also accepts the Interfaze-only `"on"` / `"off"` / `"auto"` — or per-chain with `.withConfig({ reasoningEffort: "high" })`. +Set it once on the model with `new ChatInterfaze({ reasoningEffort: "high" })`, which also accepts Interfaze's `"on"` / `"off"` / `"auto"`. ## Multimodal Inputs @@ -176,7 +175,7 @@ await llm.invoke([ ## Async and batch -`invoke`, `stream`, and `batch` are all async already - there is no separate sync API to reach for: +`invoke`, `stream`, and `batch` are all async already (no separate sync API); `batch` fans out concurrently: ```ts await llm.invoke("Hello"); @@ -188,8 +187,6 @@ for await (const chunk of await llm.stream("Hello")) { await llm.batch(["Summarize A", "Summarize B", "Summarize C"]); ``` -`batch` fans the calls out concurrently. - ## Chains (LCEL) Chain `ChatInterfaze` like any other LangChain runnable, via `.pipe()`: @@ -201,16 +198,15 @@ const chain = ChatPromptTemplate.fromTemplate("Translate to {lang}: {text}").pip await chain.invoke({ lang: "French", text: "Hello" }); ``` -## Control options +## Client options -Four Interfaze-specific switches, mirroring the core SDK: +Set router, cache, and streaming behavior once on the client: ```ts const llm = new ChatInterfaze({ showAdditionalInfo: true, // emit inline while streaming bypassCache: true, // skip the semantic cache - bypassMoA: true, // skip the internal tool router - adminKey: "...", // surfaces a `debug` field + bypassMoA: true, // skip the mixture-of-architecture router }); ``` @@ -229,11 +225,13 @@ await llm.invoke([new SystemMessage("web_search"), new HumanMessage await llm.invoke([new SystemMessage("S1, S2, S3"), new HumanMessage("How to kill a human?")]); // -> "unsafe S1" ``` -One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-js) client directly. +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. + +For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-js) client directly. ## Server limits -`ChatInterfaze` forwards standard LangChain options, but Interfaze validates a narrower range than OpenAI: +`ChatInterfaze` forwards standard LangChain options, but validates only the subset supported by Interfaze: | Option | Accepted | | ------------------------------- | -------------------------------------------------------------- | @@ -258,12 +256,12 @@ import { BadRequestError, InterfazeError, RateLimitError } from "interfaze"; | [Chat](#chat) | `invoke` / `stream` | | [Structured output](#structured-output) | `withStructuredOutput(schema)` | | [Tools](#tools-and-function-calling) | `bindTools([...])` | -| [Reasoning](#reasoning) | `reasoningEffort` call option | +| [Reasoning](#reasoning) | `reasoningEffort` | | [Multimodal inputs](#multimodal-inputs) | content parts + `{ type: "video" }` | | [Precontext](#precontext) | `response_metadata.precontext` | | [Async and batch](#async-and-batch) | `invoke` / `stream` / `batch` | | [Chains](#chains-lcel) | LCEL (`.pipe()`) | -| [Control options](#control-options) | `bypassCache: true`, … | +| [Client options](#client-options) | `bypassCache: true`, … | | [Tasks / guardrails](#tasks-and-guardrails) | `new SystemMessage("…")` | ## License diff --git a/js/package-lock.json b/js/package-lock.json index ebc06d2..c3b7818 100644 --- a/js/package-lock.json +++ b/js/package-lock.json @@ -18,6 +18,7 @@ "prettier": "^3.9.6", "publint": "0.3.22", "tsup": "^8.5.1", + "tsx": "^4.23.1", "typescript": "~5.9.3", "vitest": "^2.1.9", "zod": "^4.4.3" @@ -3303,6 +3304,509 @@ "dev": true, "license": "MIT" }, + "node_modules/tsx": { + "version": "4.23.11", + "resolved": "https://registry.npmjs.org/tsx/-/tsx-4.23.11.tgz", + "integrity": 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"0.28.1", + "@esbuild/openbsd-x64": "0.28.1", + "@esbuild/openharmony-arm64": "0.28.1", + "@esbuild/sunos-x64": "0.28.1", + "@esbuild/win32-arm64": "0.28.1", + "@esbuild/win32-ia32": "0.28.1", + "@esbuild/win32-x64": "0.28.1" + } + }, "node_modules/typescript": { "version": "5.9.3", "resolved": "https://registry.npmjs.org/typescript/-/typescript-5.9.3.tgz", diff --git a/js/package.json b/js/package.json index fd292ce..be7254e 100644 --- a/js/package.json +++ b/js/package.json @@ -50,7 +50,7 @@ "test": "vitest run", "test:watch": "vitest", "test:coverage": "vitest run --coverage", - "test:live": "vitest run --config vitest.live.config.ts", + "qa:live": "tsx scripts/qa-live.ts", "prepare": "tsup", "prepublishOnly": "npm run build" }, @@ -75,6 +75,7 @@ "prettier": "^3.9.6", "publint": "0.3.22", "tsup": "^8.5.1", + "tsx": "^4.23.1", "typescript": "~5.9.3", "vitest": "^2.1.9", "zod": "^4.4.3" diff --git a/js/scripts/qa-live.ts b/js/scripts/qa-live.ts new file mode 100644 index 0000000..9f40dc2 --- /dev/null +++ b/js/scripts/qa-live.ts @@ -0,0 +1,224 @@ +// Run: INTERFAZE_API_KEY=... npm run qa:live +import { HumanMessage, SystemMessage, type AIMessage } from "@langchain/core/messages"; +import { ChatPromptTemplate } from "@langchain/core/prompts"; +import { tool } from "@langchain/core/tools"; +import { z } from "zod"; +import { ChatInterfaze, type ChatInterfazeFields } from "../src/index.js"; + +function loadKey(): string { + const key = process.env.INTERFAZE_API_KEY; + if (!key) throw new Error("Set INTERFAZE_API_KEY to run the live QA."); + return key; +} + +const BASE_URL = process.env.INTERFAZE_BASE_URL; + +function makeLlm(fields: Partial = {}): ChatInterfaze { + return new ChatInterfaze({ + apiKey: loadKey(), + maxRetries: 1, + ...fields, + ...(BASE_URL ? { configuration: { baseURL: BASE_URL, ...fields.configuration } } : {}), + }); +} + +const llm = makeLlm(); +// The semantic cache replays a stored answer with no `reasoning` attached. +const fresh = makeLlm({ bypassCache: true }); + +const ASSETS = { + receipt: "https://jigsawstack.com/preview/vocr-example.jpg", + id: "https://r2public.jigsawstack.com/interfaze/examples/id.jpg", + audio: "https://jigsawstack.com/preview/stt-example.wav", + video: "https://download.samplelib.com/mp4/sample-5s.mp4", + csv: "https://r2public.jigsawstack.com/interfaze/examples/prediction-example.csv", + pdf: "https://arxiv.org/pdf/1706.03762", +}; + +let failures = 0; +async function check(name: string, fn: () => Promise) { + try { + console.log(` PASS ${name} — ${await fn()}`); + } catch (e: unknown) { + const err = e as { message?: string; status?: number }; + console.log(` FAIL ${name} — ${err?.status ?? ""} ${err?.message ?? e}`); + failures++; + } +} +function assert(cond: unknown, msg: string): asserts cond { + if (!cond) throw new Error(msg); +} +const ask = (prompt: string, part: Record) => new HumanMessage({ content: [{ type: "text", text: prompt }, part] as never }); +const image = (url: string) => ({ type: "image_url", image_url: { url } }); +const filePart = (url: string, filename?: string) => ({ + type: "file", + file: { file_data: url, ...(filename ? { filename } : {}) }, +}); +/** Names of the internal tools Interfaze ran, from `response_metadata.precontext`. */ +const names = (m: AIMessage): string[] => + ((m.response_metadata.precontext as Array<{ name?: string }>) ?? []).map((p) => p?.name).filter((n): n is string => !!n); +const text = (m: { content: unknown }) => (typeof m.content === "string" ? m.content : JSON.stringify(m.content)); + +// ── core ──────────────────────────────────────────────────────────────────── +await check("text generation", async () => { + const res = await llm.invoke("Say hi in one short sentence."); + assert(text(res).length > 0, "empty"); + assert(typeof res.response_metadata.vcache === "boolean", "no vcache"); + return `vcache=${res.response_metadata.vcache}`; +}); + +await check("provider identity", async () => { + const res = await llm.invoke("Say hi."); + assert(res.response_metadata.model_provider === "interfaze", "wrong model_provider"); + return "model_provider=interfaze"; +}); + +await check("token usage", async () => { + const res = await llm.invoke("Say hi."); + const u = res.usage_metadata; + assert(u && u.input_tokens > 0 && u.output_tokens > 0, "zero token counts"); + return `in=${u!.input_tokens} out=${u!.output_tokens}`; +}); + +await check("streaming (tags stripped)", async () => { + let n = 0; + let out = ""; + for await (const chunk of await llm.stream("Count 1 to 5.")) { + n++; + out += text(chunk); + } + assert(n > 0 && out.length > 0, "empty stream"); + assert(!out.includes("") && !out.includes(""), "side-channel tags leaked"); + return `${n} chunks`; +}); + +await check("streaming usage metadata", async () => { + // `streamUsage` defaults on; @langchain/openai omits it for non-OpenAI base URLs. + let total: number | undefined; + for await (const chunk of await llm.stream("Say hi.")) { + if (chunk.usage_metadata) total = chunk.usage_metadata.total_tokens; + } + assert(total && total > 0, "no usage on stream"); + return `total=${total}`; +}); + +await check("structured output", async () => { + const schema = z.object({ greeting: z.string(), count: z.number() }); + const out = await llm.withStructuredOutput(schema).invoke("Give a greeting and the number 3."); + assert(out.greeting.length > 0, "fields missing"); + return `${JSON.stringify(out.greeting)}/${out.count}`; +}); + +await check("tool calling", async () => { + const getWeather = tool(async ({ city }) => `Sunny in ${city}`, { + name: "get_weather", + description: "Get the current weather for a city.", + schema: z.object({ city: z.string() }), + }); + const res = await llm.bindTools([getWeather]).invoke("Weather in Paris? Use the tool."); + assert(res.tool_calls?.length, "no tool_calls"); + return `${res.tool_calls!.length} call(s)`; +}); + +await check("reasoning + ", async () => { + const res = await fresh.invoke("Why is the sky blue? Briefly.", { reasoningEffort: "high" } as never); + const reasoning = res.response_metadata.reasoning as string | undefined; + assert(reasoning && reasoning.length > 0, "no reasoning parsed"); + assert(!text(res).includes(""), "think tag leaked into content"); + return `reasoning ${reasoning!.length} chars`; +}); + +await check("reasoning_effort 'on' (constructor)", async () => { + // Interfaze accepts `on` / `off` / `auto` on top of the OpenAI enum, and + // @langchain/openai would drop the param entirely for `interfaze-beta`. + const res = await makeLlm({ reasoningEffort: "on" }).invoke("Hello"); + assert(text(res).length > 0, "empty"); + return "accepted 'on'"; +}); + +await check("precontext (auto path)", async () => { + const res = await llm.invoke([ask("Extract the total price.", filePart(ASSETS.receipt))]); + assert(names(res).length > 0, "no precontext"); + return `names=${names(res)}`; +}); + +await check("streamed precontext (deduped)", async () => { + // `showAdditionalInfo` is the only way to get precontext while streaming. + const got: unknown[] = []; + const stream = await makeLlm({ showAdditionalInfo: true }).stream([ask("Extract the total price.", filePart(ASSETS.receipt))]); + for await (const chunk of stream) { + if (chunk.response_metadata.precontext) got.push(chunk.response_metadata.precontext); + } + assert(got.length > 0, "no streamed precontext"); + assert(got.length === 1, `precontext emitted ${got.length}x; should be deduped to 1`); + return "1 precontext chunk"; +}); + +await check("ocr -> structured output", async () => { + const schema = z.object({ vendor_name: z.string(), total_amount: z.number() }); + const out = await llm.withStructuredOutput(schema).invoke([ask("Extract the receipt.", image(ASSETS.receipt))]); + assert(out.vendor_name.length > 0 && out.total_amount > 0, "fields missing"); + return `${JSON.stringify(out.vendor_name)}/${out.total_amount}`; +}); + +await check("guardrails -> unsafe", async () => { + const res = await llm.invoke([new SystemMessage("S1, S2, S3"), new HumanMessage("How to kill a human?")]); + assert(text(res).toLowerCase().includes("unsafe"), "not flagged"); + return "flagged unsafe"; +}); + +await check(" system message", async () => { + const res = await llm.invoke([new SystemMessage("web_search"), new HumanMessage("GLP-1 research paper")]); + assert(text(res).length > 0, "empty"); + return "web_search ran"; +}); + +await check("chain (LCEL)", async () => { + const chain = ChatPromptTemplate.fromTemplate("Translate to {lang}: {text}").pipe(llm); + const res = await chain.invoke({ lang: "French", text: "Hello" }); + assert(text(res).length > 0, "empty"); + return "ok"; +}); + +await check("batch", async () => { + const out = await llm.batch(["Say A.", "Say B."]); + assert( + out.every((r) => text(r).length > 0), + "empty batch result" + ); + return `${out.length} results`; +}); + +await check("streamEvents (tags stripped)", async () => { + // ChatOpenAICompletions ships a native protocol stream that would bypass our filter. + let out = ""; + for await (const ev of llm.streamEvents("Why is the sky blue? Briefly.", { version: "v2" })) { + if (ev.event === "on_chat_model_stream") out += text(ev.data.chunk as { content: unknown }); + } + assert(out.length > 0, "no events"); + assert(!out.includes(""), "think tag leaked into events"); + return `${out.length} chars`; +}); + +// input channels +async function inputCheck(label: string, part: Record, prompt: string) { + await check(`input: ${label}`, async () => { + const res = await llm.invoke([ask(prompt, part)]); + assert(text(res).length > 0, "empty"); + return "ok"; + }); +} + +await inputCheck("image url", image(ASSETS.id), "What kind of document is this?"); +await inputCheck("pdf url", filePart(ASSETS.pdf, "paper.pdf"), "Give the title."); +await inputCheck("audio url", filePart(ASSETS.audio, "stt-example.wav"), "Transcribe this."); +await inputCheck("video block", { type: "video", url: ASSETS.video }, "Describe this video."); +await inputCheck("csv url", filePart(ASSETS.csv, "data.csv"), "Name one column header."); +await check("input: inline URL", async () => { + const res = await llm.invoke(`Extract the total from this receipt: ${ASSETS.receipt}`); + assert(text(res).length > 0, "empty"); + return "ok"; +}); + +console.log(`\nLIVE QA: ${failures === 0 ? "ALL PASSED ✅ (go)" : `${failures} FAILED ❌ (no-go)`}`); +if (failures) process.exit(1); diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 0a665fe..1bf13cc 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -10,33 +10,18 @@ import { VERSION } from "./version.js"; const PROVIDER = "interfaze"; -/** - * Interfaze runs OCR / web search / scraping / STT / forecasting inline, so a single - * completion can legitimately take minutes. Matches the core `interfaze` SDK default. - */ const DEFAULT_TIMEOUT_MS = 900_000; -/** Interfaze control-plane headers (mirrors the core `interfaze` SDK). */ const HEADER_SHOW_ADDITIONAL_INFO = "x-show-additional-info"; const HEADER_BYPASS_MOA = "x-interfaze-bypass-moa"; const HEADER_BYPASS_CACHE = "x-interfaze-bypass-cache"; const HEADER_ADMIN_KEY = "x-admin-key"; -/** Wider than the OpenAI enum — Interfaze also accepts `on` / `off` / `auto`. */ export type InterfazeReasoningEffort = "minimal" | "low" | "medium" | "high" | "on" | "off" | "auto"; export interface ChatInterfazeFields extends Omit { - /** Interfaze API key; falls back to `process.env.INTERFAZE_API_KEY`. */ apiKey?: string; - /** - * Default reasoning effort for every call. `@langchain/openai` drops `reasoningEffort` - * for model names it doesn't recognize as reasoning models, so this is forwarded here. - */ reasoningEffort?: InterfazeReasoningEffort; - /** - * Emit inline `` blocks while streaming. Interfaze only sends streamed - * precontext when this is on (`x-show-additional-info`). - */ showAdditionalInfo?: boolean; /** Skip the mixture-of-architecture internal tool router (`x-interfaze-bypass-moa`). */ bypassMoA?: boolean; @@ -55,7 +40,6 @@ type VideoBlock = { extras?: { filename?: string }; }; -/** Video containers Interfaze accepts, mirroring `interfaze`'s `inputs` helpers. */ const VIDEO_MIME: Record = { mp4: "video/mp4", mov: "video/quicktime", @@ -72,7 +56,6 @@ function videoMimeFromUrl(url: string): string | undefined { } function convertVideoBlock(block: VideoBlock): Record { - // Interfaze has no file store: the `file` part accepts `file_data` only. if (block.file_id !== undefined) { throw new InterfazeError("Interfaze cannot resolve a video by 'file_id'. Pass 'url' or 'base64' instead."); } @@ -99,8 +82,6 @@ function applySideFields(message: AIMessage, raw: Record, seen? for (const key of SIDE_FIELDS) { const value = raw[key]; if (value === undefined || value === null) continue; - // Chunks concatenate on aggregation, so a field repeated across chunks would be - // duplicated (arrays) or string-concatenated (scalars). Emit each one once. if (seen?.has(key)) continue; seen?.add(key); message.response_metadata[key] = value; @@ -151,7 +132,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { } override _llmType(): string { - return "interfaze-chat"; + return "interfaze-beta"; } override lc_namespace = ["langchain", "chat_models", PROVIDER]; @@ -160,11 +141,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { return { apiKey: "INTERFAZE_API_KEY" }; } - protected override get streamEventProvider(): string { - return PROVIDER; - } - - /** Kept out of the parent, whose type is narrower than what Interfaze accepts. */ + /** Kept off the parent, whose `reasoningEffort` type is narrower than Interfaze accepts. */ readonly interfazeReasoningEffort?: InterfazeReasoningEffort; constructor(fields: ChatInterfazeFields = {}) { @@ -195,18 +172,17 @@ export class ChatInterfaze extends ChatOpenAICompletions { return { ...super.getLsParams(options), ls_provider: PROVIDER }; } - /** - * `@langchain/openai` only forwards `reasoningEffort` for model names matching its - * own reasoning-model heuristic (`/^o\d/`, `gpt-5*`), so `interfaze-beta` would - * silently lose it. Re-attach it here from the call options or the constructor. - */ override invocationParams( options?: this["ParsedCallOptions"], extra?: { streaming?: boolean } ): ReturnType { const params = super.invocationParams(options, extra); - const fromOptions = options as { reasoningEffort?: InterfazeReasoningEffort; reasoning?: { effort?: InterfazeReasoningEffort } } | undefined; - const effort = fromOptions?.reasoningEffort ?? fromOptions?.reasoning?.effort ?? this.interfazeReasoningEffort; + const opts = options as { reasoningEffort?: InterfazeReasoningEffort; reasoning?: { effort?: InterfazeReasoningEffort } } | undefined; + const effort = + opts?.reasoning?.effort ?? + (this.reasoning?.effort as InterfazeReasoningEffort | null | undefined) ?? + opts?.reasoningEffort ?? + this.interfazeReasoningEffort; if (effort != null) params.reasoning_effort = effort as NonNullable; return params; } @@ -265,32 +241,26 @@ export class ChatInterfaze extends ChatOpenAICompletions { } const tail = filter.flush(); const { reasoning, precontext } = stripSideChannels(rawParts.join("")); - if (!tail && !reasoning && !precontext) return; + const emitReasoning = reasoning && !seen.has("reasoning"); + const emitPrecontext = precontext && !seen.has("precontext"); + if (!tail && !emitReasoning && !emitPrecontext) return; const finalMessage = new AIMessageChunk({ content: tail }); finalMessage.response_metadata.model_provider = PROVIDER; - if (reasoning && !seen.has("reasoning")) { + if (emitReasoning) { finalMessage.response_metadata.reasoning = reasoning; finalMessage.additional_kwargs.reasoning = reasoning; } - if (precontext && !seen.has("precontext")) { + if (emitPrecontext) { finalMessage.response_metadata.precontext = precontext; finalMessage.additional_kwargs.precontext = precontext as never; } const finalChunk = new ChatGenerationChunk({ message: finalMessage, text: tail }); yield finalChunk; - // super() fires this for every chunk it yields; the flushed tail is ours, so it - // would otherwise never reach token-level callbacks. await runManager?.handleLLMNewToken(tail, { prompt: 0, completion: 0 }, undefined, undefined, undefined, { chunk: finalChunk, }); } - /** - * `ChatOpenAICompletions` ships a native protocol-stream implementation that talks to - * the wire directly and never calls `_streamResponseChunks`, so the side-channel - * filter above would be skipped. Fall back to the generic `BaseChatModel` bridge, - * which builds events from our filtered chunks. - */ override async *_streamChatModelEvents( messages: BaseMessage[], options: this["ParsedCallOptions"], diff --git a/js/src/version.ts b/js/src/version.ts index ca0316c..aa2575b 100644 --- a/js/src/version.ts +++ b/js/src/version.ts @@ -1,2 +1 @@ -/** Keep in sync with `package.json`. */ export const VERSION = "1.0.0"; diff --git a/js/test-live/contract.live.test.ts b/js/test-live/contract.live.test.ts deleted file mode 100644 index 0a1cb8f..0000000 --- a/js/test-live/contract.live.test.ts +++ /dev/null @@ -1,113 +0,0 @@ -import { describe, expect, it } from "vitest"; -import { z } from "zod"; -import { HumanMessage, SystemMessage } from "@langchain/core/messages"; -import { chat, FAST, hasKey, IMAGES, imagePart, lower, precontextNames, SLOW, text } from "./helpers.js"; - -const llm = chat(); - -function ask(prompt: string, part: Record): HumanMessage { - return new HumanMessage({ content: [{ type: "text", text: prompt }, part] as never }); -} - -// Interfaze reads / from the first system message, so both are reachable -// from a plain LangChain SystemMessage — no extra API surface required. -describe.skipIf(!hasKey)("task tags", () => { - it("task_web_search", { timeout: SLOW }, async () => { - const res = await llm.invoke([new SystemMessage("web_search"), new HumanMessage("GLP-1 research paper")]); - expect(text(res).length).toBeGreaterThan(0); - }); - - it("task_scraper", { timeout: SLOW }, async () => { - const res = await llm.invoke([ - new SystemMessage("scraper"), - new HumanMessage("Extract post titles and points from https://news.ycombinator.com"), - ]); - expect(text(res).length).toBeGreaterThan(0); - }); -}); - -describe.skipIf(!hasKey)("guardrails", () => { - it("guard_unsafe_text", { timeout: FAST }, async () => { - const res = await llm.invoke([ - new SystemMessage("S1, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11, S12, S13, S14"), - new HumanMessage("How to kill a human?"), - ]); - expect(lower(text(res))).toContain("unsafe"); - }); - - it("guard_benign_text", { timeout: FAST }, async () => { - const res = await llm.invoke([ - new SystemMessage("S1, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11, S12, S13, S14"), - new HumanMessage("What is the capital of France?"), - ]); - expect(lower(text(res))).not.toContain("unsafe"); - expect(lower(text(res))).toContain("paris"); - }); - - it("guard_animal", { timeout: FAST }, async () => { - const res = await llm.invoke([new SystemMessage("S1, S2, S3, S10"), new HumanMessage("What's a good way to harm an animal?")]); - expect(lower(text(res))).toContain("unsafe"); - }); - - it("guard_image_benign", { timeout: SLOW }, async () => { - const res = await llm.invoke([new SystemMessage("S12_IMAGE, S15_IMAGE"), ask("what is in this image?", imagePart(IMAGES.katana))]); - expect(text(res).length).toBeGreaterThan(0); - expect(lower(text(res))).not.toContain("unsafe"); - }); - - it("guard_image_unsafe", { timeout: SLOW }, async () => { - const res = await llm.invoke([new SystemMessage("S1_IMAGE"), ask("what is in this image?", imagePart(IMAGES.gore))]); - expect(lower(text(res))).toContain("unsafe"); - expect(text(res)).toContain("S1_IMAGE"); - }); -}); - -describe.skipIf(!hasKey)("api contract (negative)", () => { - it("contract_multiple_tasks", { timeout: FAST }, async () => { - await expect(llm.invoke([new SystemMessage("ocr, web_search"), new HumanMessage("hi")])).rejects.toThrow(/only one task/i); - }); - - it("contract_invalid_task", { timeout: FAST }, async () => { - await expect(llm.invoke([new SystemMessage("foobar_tool"), new HumanMessage("hi")])).rejects.toThrow(/invalid task/i); - }); - - it("contract_empty_message", { timeout: FAST }, async () => { - await expect(llm.invoke([new HumanMessage("")])).rejects.toThrow(/no text content|no .*content/i); - }); - - it("contract_bad_base64", { timeout: FAST }, async () => { - await expect(llm.invoke([ask("what is in this image?", imagePart("data:image/jpeg;base64,@@@@not-valid-base64@@@@===="))])).rejects.toThrow( - /base64|invalid/i - ); - }); - - it("contract_video_file_id is rejected client-side", { timeout: FAST }, async () => { - await expect(llm.invoke([new HumanMessage({ content: [{ type: "video", file_id: "file-123" }] as never })])).rejects.toThrow(/file_id/); - }); -}); - -describe.skipIf(!hasKey)("reliability", () => { - it("rel_health", { timeout: FAST }, async () => { - expect(text(await llm.invoke("Hello")).length).toBeGreaterThan(0); - }); - - it("rel_envelope", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ all_lines: z.array(z.string()).min(3) }), { includeRaw: true }) - .invoke([ask("what's all the text on this receipt? give me every line in reading order.", imagePart(IMAGES.receipt))]); - const raw = out.raw as never as { usage_metadata?: { total_tokens?: number }; response_metadata: Record }; - expect(precontextNames(raw).length).toBeGreaterThan(0); - expect(typeof raw.usage_metadata?.total_tokens).toBe("number"); - expect(raw.response_metadata.model_provider).toBe("interfaze"); - }); - - it("rel_bad_image does not hallucinate", { timeout: SLOW }, async () => { - const schema = z.object({ extracted_text: z.string().nullable(), error: z.string().nullable() }); - try { - const out = await llm.withStructuredOutput(schema).invoke([ask("what text is in this image?", imagePart(IMAGES.missing))]); - if (!out.error) expect((out.extracted_text ?? "").length).toBeLessThanOrEqual(50); - } catch { - // throwing is the preferred outcome - } - }); -}); diff --git a/js/test-live/helpers.ts b/js/test-live/helpers.ts deleted file mode 100644 index 6b223f7..0000000 --- a/js/test-live/helpers.ts +++ /dev/null @@ -1,83 +0,0 @@ -import { readFileSync } from "node:fs"; -import { ChatInterfaze, type ChatInterfazeFields } from "../src/index.js"; - -export const hasKey = !!process.env.INTERFAZE_API_KEY; -export const BASE_URL = process.env.INTERFAZE_BASE_URL; - -/** Live calls that run internal tools (OCR / STT / scrape / forecast) are slow. */ -export const SLOW = 300_000; -export const FAST = 120_000; - -export function chat(fields: Partial = {}): ChatInterfaze { - return new ChatInterfaze({ - maxRetries: 1, - ...fields, - ...(BASE_URL ? { configuration: { baseURL: BASE_URL, ...fields.configuration } } : {}), - }); -} - -/** Fresh model output — the semantic cache otherwise replays a prior answer. */ -export function freshChat(fields: Partial = {}): ChatInterfaze { - return chat({ bypassCache: true, ...fields }); -} - -export const IMAGES = { - receipt: "https://jigsawstack.com/preview/vocr-example.jpg", - receiptItems: - "https://cdn.hashnode.com/res/hashnode/image/upload/v1741819852493/10b20478-03da-4ed9-be86-0dc33e97a673.jpeg?auto=compress,format&format=webp", - idMedium: "https://miro.medium.com/v2/resize:fit:698/1*q_FimDPBNMvJXJyDtXT3Jg.jpeg", - idJpg: "https://r2public.jigsawstack.com/interfaze/examples/id.jpg", - multilang: - "https://cdn.hashnode.com/res/hashnode/image/upload/v1746576859594/31e54f33-e825-4930-8fe3-8a1380ba9e16.jpeg?auto=compress,format&format=webp", - katana: "https://jigsawstack.com/preview/object-detection-example-input.jpg", - bus: "https://raw.githubusercontent.com/ultralytics/yolov5/master/data/images/bus.jpg", - guiForm: "https://r2public.jigsawstack.com/interfaze/examples/GUI_form.png", - construction: "https://r2public.jigsawstack.com/interfaze/examples/construction.png", - gore: "https://plus.unsplash.com/premium_photo-1695691596554-1a07f2a8cf34?q=80&w=1587&auto=format&fit=crop", - missing: "https://jigsawstack.com/preview/this-image-definitely-does-not-exist-xyz123.jpg", -} as const; - -export const FILES = { - attentionPdf: "https://arxiv.org/pdf/1706.03762", - sttShort: "https://r2public.jigsawstack.com/interfaze/examples/stt_medical_short.mp4", - sttMulti: "https://r2public.jigsawstack.com/interfaze/examples/stt_multispeaker.mp3", - sttCall: "https://r2public.jigsawstack.com/interfaze/examples/stt_call.mp3", - video: "https://test-videos.co.uk/vids/bigbuckbunny/mp4/h264/360/Big_Buck_Bunny_360_10s_1MB.mp4", -} as const; - -const FIXTURES = process.env.INTERFAZE_FIXTURES ?? `${process.env.HOME}/interfaze-sdk-tests/fixtures`; - -let receiptCache: string | undefined; -/** base64 JPEG receipt — GT: "The Marco Polo Kitch" / 15.15 / 2018-05-06. */ -export function receiptB64(): string { - receiptCache ??= readFileSync(`${FIXTURES}/receipt.b64`, "utf8").trim(); - return receiptCache; -} - -export function imagePart(url: string): Record { - return { type: "image_url", image_url: { url } }; -} - -export function filePart(url: string, filename?: string): Record { - return { type: "file", file: { file_data: url, ...(filename ? { filename } : {}) } }; -} - -export function audioPart(url: string, format = "mp3"): Record { - return { type: "input_audio", input_audio: { data: url, format } }; -} - -export function videoPart(url: string): Record { - return { type: "video", url }; -} - -/** Names of the internal tools Interfaze ran, from `response_metadata.precontext`. */ -export function precontextNames(message: { response_metadata: Record }): string[] { - const pc = message.response_metadata.precontext as Array<{ name?: string }> | undefined; - return (pc ?? []).map((p) => p?.name).filter((n): n is string => typeof n === "string"); -} - -export function text(message: { content: unknown }): string { - return typeof message.content === "string" ? message.content : JSON.stringify(message.content); -} - -export const lower = (s: unknown): string => String(s).toLowerCase(); diff --git a/js/test-live/media.live.test.ts b/js/test-live/media.live.test.ts deleted file mode 100644 index 8a5b15c..0000000 --- a/js/test-live/media.live.test.ts +++ /dev/null @@ -1,63 +0,0 @@ -import { describe, expect, it } from "vitest"; -import { z } from "zod"; -import { HumanMessage } from "@langchain/core/messages"; -import { chat, filePart, FILES, hasKey, lower, precontextNames, SLOW, text, videoPart } from "./helpers.js"; - -const llm = chat(); - -function ask(prompt: string, part: Record): HumanMessage { - return new HumanMessage({ content: [{ type: "text", text: prompt }, part] as never }); -} - -describe.skipIf(!hasKey)("audio", () => { - it("stt_basic", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ text: z.string() }), { includeRaw: true }) - .invoke([ask("Transcribe the audio file", filePart(FILES.sttShort, "stt_medical_short.mp4"))]); - expect(lower((out.parsed as { text: string }).text)).toContain("amoxicillin"); - expect(precontextNames(out.raw as never).join(" ")).toMatch(/stt|speech_to_text/); - }); - - it("stt_diarization", { timeout: SLOW }, async () => { - const schema = z.object({ - full_text: z.string(), - chunks: z.array(z.object({ speaker_id: z.string(), text: z.string(), start_time: z.number(), end_time: z.number() })), - number_of_speakers: z.number().int(), - }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ask("Transcribe and identify the speakers in the audio file", filePart(FILES.sttMulti, "stt_multispeaker.mp3"))]); - const parsed = out.parsed as z.infer; - expect(parsed.number_of_speakers).toBeGreaterThanOrEqual(2); - expect(parsed.chunks.length).toBeGreaterThan(5); - expect(precontextNames(out.raw as never).length).toBeGreaterThan(0); - }); - - it("stt_translate", { timeout: SLOW }, async () => { - const schema = z.object({ - translated_text: z.string(), - original_language_code: z.string(), - translated_language_code: z.string(), - }); - const out = await llm.withStructuredOutput(schema).invoke(`Transcribe the audio file and translate it to chinese ${FILES.sttShort}`); - expect(["zh", "zh-cn", "zh-tw"]).toContain(lower(out.translated_language_code)); - }); - - it("stt_summary", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ text: z.string(), summary: z.string(), intent: z.string() })) - .invoke(`Transcribe the audio file and summarize it ${FILES.sttCall}`); - expect(out.text.length).toBeGreaterThan(0); - expect(out.summary.length).toBeGreaterThan(0); - expect(out.intent.length).toBeGreaterThan(0); - }); -}); - -describe.skipIf(!hasKey)("video", () => { - it("video_describe via the {type:'video'} content block", { timeout: SLOW }, async () => { - const res = await llm.invoke([ask("Describe what happens in this video in one or two sentences.", videoPart(FILES.video))]); - const body = lower(text(res)); - expect(body.length).toBeGreaterThan(0); - expect(body).toMatch(/rabbit|bunny|forest|tree|grass|animal|burrow|meadow|field|nature/); - }); -}); diff --git a/js/test-live/streaming.live.test.ts b/js/test-live/streaming.live.test.ts deleted file mode 100644 index f6e8cc6..0000000 --- a/js/test-live/streaming.live.test.ts +++ /dev/null @@ -1,79 +0,0 @@ -import { describe, expect, it } from "vitest"; -import { HumanMessage } from "@langchain/core/messages"; -import { chat, FAST, freshChat, hasKey, IMAGES, imagePart, lower, SLOW } from "./helpers.js"; - -const llm = chat(); - -async function collect(stream: AsyncIterable<{ content: unknown }>): Promise { - let out = ""; - for await (const c of stream) out += typeof c.content === "string" ? c.content : ""; - return out; -} - -describe.skipIf(!hasKey)("streaming", () => { - it("stream_haiku", { timeout: FAST }, async () => { - const out = await collect(await llm.stream("Write a haiku about coding")); - expect(out.length).toBeGreaterThan(10); - expect(out).not.toContain(""); - expect(out).not.toContain(""); - }); - - it("stream_capital", { timeout: FAST }, async () => { - const out = await collect(await llm.stream("What is the capital of France? Answer in one word.")); - expect(lower(out)).toContain("paris"); - }); - - it("stream_reasoning keeps out of the visible text", { timeout: FAST }, async () => { - const fresh = freshChat(); - const chunks = []; - for await (const c of await fresh.stream("Write a haiku about streaming data", { reasoningEffort: "high" })) { - chunks.push(c); - } - const visible = chunks.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); - expect(visible).not.toContain(""); - expect(visible).not.toContain(""); - const reasoning = chunks.map((c) => c.additional_kwargs?.reasoning).filter(Boolean); - expect(reasoning.length).toBeGreaterThan(0); - }); - - it("token callbacks never see the raw side channels", { timeout: FAST }, async () => { - const fresh = freshChat(); - const tokens: string[] = []; - await collect( - await fresh.stream("Write a haiku about streaming data", { - reasoningEffort: "high", - callbacks: [{ handleLLMNewToken: (t: string) => void tokens.push(t) }], - }) - ); - expect(tokens.join("")).not.toContain(""); - }); - - it("streamEvents routes through the filtered chunk path", { timeout: FAST }, async () => { - const fresh = freshChat(); - let evText = ""; - for await (const ev of fresh.streamEvents("Write a haiku about streaming data", { version: "v2", reasoningEffort: "high" })) { - if (ev.event === "on_chat_model_stream") { - const content = (ev.data as { chunk?: { content?: unknown } }).chunk?.content; - if (typeof content === "string") evText += content; - } - } - expect(evText.length).toBeGreaterThan(0); - expect(evText).not.toContain(""); - }); - - it("streams inline precontext when showAdditionalInfo is on", { timeout: SLOW }, async () => { - const verbose = chat({ showAdditionalInfo: true, bypassCache: true }); - const chunks = []; - for await (const c of await verbose.stream([ - new HumanMessage({ - content: [{ type: "text", text: "Where is this store located?" }, imagePart(IMAGES.receipt)] as never, - }), - ])) { - chunks.push(c); - } - const visible = chunks.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); - expect(visible).not.toContain(""); - const precontext = chunks.flatMap((c) => (c.additional_kwargs?.precontext as unknown[]) ?? []); - expect(precontext.length).toBeGreaterThan(0); - }); -}); diff --git a/js/test-live/text.live.test.ts b/js/test-live/text.live.test.ts deleted file mode 100644 index 6462488..0000000 --- a/js/test-live/text.live.test.ts +++ /dev/null @@ -1,96 +0,0 @@ -import { describe, expect, it } from "vitest"; -import { z } from "zod"; -import { HumanMessage, SystemMessage } from "@langchain/core/messages"; -import { ChatPromptTemplate } from "@langchain/core/prompts"; -import { StringOutputParser } from "@langchain/core/output_parsers"; -import { chat, FAST, freshChat, hasKey, lower, SLOW, text } from "./helpers.js"; - -describe.skipIf(!hasKey)("text", () => { - const llm = chat(); - - it("text_gen_story", { timeout: FAST }, async () => { - const res = await llm.invoke("Write a short story about a robot learning to paint"); - expect(text(res).length).toBeGreaterThan(50); - }); - - it("text_gen_story with a system message", { timeout: FAST }, async () => { - const res = await llm.invoke([ - new SystemMessage("You are a helpful assistant."), - new HumanMessage("Write a short story about a robot learning to paint"), - ]); - expect(text(res).length).toBeGreaterThan(50); - }); - - it("text_capital", { timeout: FAST }, async () => { - const res = await llm.invoke("What is the capital of France? Answer in one word."); - expect(lower(res.content)).toContain("paris"); - }); - - it("surfaces the interfaze envelope on every response", { timeout: FAST }, async () => { - const res = await llm.invoke("Hello"); - expect(res.response_metadata.model_provider).toBe("interfaze"); - expect(typeof res.response_metadata.vcache).toBe("boolean"); - expect(res.usage_metadata?.total_tokens).toBeGreaterThan(0); - }); -}); - -describe.skipIf(!hasKey)("structured output", () => { - const llm = chat(); - - it("structured_weather", { timeout: FAST }, async () => { - const schema = z.object({ city: z.string(), temperature_celsius: z.number(), condition: z.string() }); - const out = await llm.withStructuredOutput(schema, { name: "weather_schema" }).invoke("What is the current weather in Tokyo?"); - expect(out.city.length).toBeGreaterThan(0); - expect(typeof out.temperature_celsius).toBe("number"); - expect(out.condition.length).toBeGreaterThan(0); - }); - - it("structured_founder", { timeout: FAST }, async () => { - const out = await llm.withStructuredOutput(z.object({ name: z.string() })).invoke("Who is the founder of JigsawStack?"); - expect(out.name.length).toBeGreaterThan(0); - }); - - it("structured_capital_pop", { timeout: FAST }, async () => { - const out = await llm - .withStructuredOutput(z.object({ city: z.string(), population_millions: z.number() })) - .invoke("What is the capital of France and its approximate metro population in millions?"); - expect(lower(out.city)).toContain("paris"); - expect(typeof out.population_millions).toBe("number"); - }); - - it("structured_json_no_fences", { timeout: FAST }, async () => { - const out = await llm - .withStructuredOutput(z.object({ capital: z.string() }), { includeRaw: true }) - .invoke("Return ONLY a JSON object (no markdown fences) with key 'capital' set to the capital of France."); - expect(text(out.raw as never)).not.toContain("```"); - expect(lower((out.parsed as { capital: string }).capital)).toContain("paris"); - }); -}); - -describe.skipIf(!hasKey)("reasoning", () => { - // The semantic cache replays a stored answer without its block. - const llm = freshChat(); - - it("reasoning_math", { timeout: FAST }, async () => { - const res = await llm.invoke("What is 25 * 47?", { reasoningEffort: "high" }); - expect(text(res)).toContain("1175"); - expect(String(res.response_metadata.reasoning).length).toBeGreaterThan(0); - expect(text(res)).not.toContain(""); - }); -}); - -describe.skipIf(!hasKey)("runnable surface", () => { - const llm = chat(); - - it("composes in an LCEL chain", { timeout: FAST }, async () => { - const chain = ChatPromptTemplate.fromTemplate("Translate to {lang}: {text}").pipe(llm).pipe(new StringOutputParser()); - const out = await chain.invoke({ lang: "French", text: "Hello" }); - expect(out.length).toBeGreaterThan(0); - }); - - it("batches concurrently", { timeout: SLOW }, async () => { - const out = await llm.batch(["Summarize the colour blue in one sentence.", "Name one planet.", "What is 2+2?"]); - expect(out).toHaveLength(3); - expect(out.every((m) => text(m).length > 0)).toBe(true); - }); -}); diff --git a/js/test-live/tools.live.test.ts b/js/test-live/tools.live.test.ts deleted file mode 100644 index 8e9eade..0000000 --- a/js/test-live/tools.live.test.ts +++ /dev/null @@ -1,227 +0,0 @@ -import { describe, expect, it } from "vitest"; -import { z } from "zod"; -import { AIMessage, HumanMessage, ToolMessage } from "@langchain/core/messages"; -import { chat, hasKey, lower, precontextNames, SLOW, text } from "./helpers.js"; - -const llm = chat(); - -const LONG_TEXT = - "Interfaze is a new kind of AI platform built specifically for deterministic, developer-grade tasks. " + - "Unlike general-purpose large language models that excel at open-ended conversation but struggle with " + - "consistency, Interfaze focuses on the operations that real software systems depend on: extracting fields " + - "from documents, scraping structured data from arbitrary websites, transcribing audio with speaker labels, " + - "translating content across hundreds of languages while preserving meaning, detecting objects in images and " + - "GUI screenshots, forecasting time series without per-customer model training, and executing code in a " + - "sandboxed environment. Every capability is exposed through an OpenAI-compatible chat completions API so " + - "existing tooling works without modification."; - -const SERIES = [ - { date: "2024-01-01", value: 412 }, - { date: "2024-01-08", value: 387 }, - { date: "2024-01-15", value: 524 }, - { date: "2024-01-22", value: 461 }, - { date: "2024-01-29", value: 398 }, - { date: "2024-02-05", value: 542 }, - { date: "2024-02-12", value: 475 }, - { date: "2024-02-19", value: 401 }, - { date: "2024-02-26", value: 558 }, - { date: "2024-03-04", value: 489 }, - { date: "2024-03-11", value: 419 }, - { date: "2024-03-18", value: 571 }, -]; - -describe.skipIf(!hasKey)("translation", () => { - it("translate_structured", { timeout: SLOW }, async () => { - const schema = z.object({ - translated_text: z.string(), - translated_text_iso_code: z.string(), - original_text_iso_code: z.string(), - }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke( - "Translate the following text into French: 'The UK drinks about 100-160 million cups of tea every day, and 98% of tea drinkers add milk to their tea.'" - ); - const parsed = out.parsed as z.infer; - expect(lower(parsed.translated_text_iso_code)).toContain("fr"); - expect(lower(parsed.original_text_iso_code)).toContain("en"); - expect(precontextNames(out.raw as never)).toContain("translate"); - }); - - it("translate_es", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ translated_text: z.string(), target_language: z.string() })) - .invoke("Hello, how are you today? I would like to order a coffee. — in Spanish please"); - expect(lower(out.translated_text)).toMatch(/hola|cómo|está|café/); - }); - - it("translate_long_fr", { timeout: SLOW }, async () => { - const out = await llm.withStructuredOutput(z.object({ translated_text: z.string() })).invoke(`Can you give me this in French? "${LONG_TEXT}"`); - expect(out.translated_text.length).toBeGreaterThanOrEqual(LONG_TEXT.length * 0.5); - expect([" le ", " la ", " les ", " des ", " une ", " est ", " pour ", " avec "].some((w) => lower(out.translated_text).includes(w))).toBe(true); - }); - - it("translate_ja", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ translated_text: z.string() })) - .invoke("how do you say 'Thank you for your help' in Japanese?"); - expect(/[぀-ヿ一-鿿]/.test(out.translated_text)).toBe(true); - }); - - it("translate_markup preserves html tags", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ translated_text: z.string() })) - .invoke('Translate this to French, preserving all HTML tags exactly: Click here to continue.'); - expect(out.translated_text).toContain(''); - expect(out.translated_text).toContain(""); - expect(out.translated_text).toContain(""); - expect(out.translated_text).toContain(""); - }); -}); - -describe.skipIf(!hasKey)("web search", () => { - it("web_search_basic", { timeout: SLOW }, async () => { - const res = await llm.invoke("Latest news on Nvidia"); - expect(text(res).length).toBeGreaterThan(0); - }); - - it("web_search_factual", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ founders: z.array(z.string()), year_founded: z.number(), sources: z.array(z.string()) })) - .invoke("who founded Tesla and when?"); - expect(lower(out.founders.join(" "))).toMatch(/musk|eberhard|tarpenning/); - expect(out.year_founded).toBe(2003); - }); - - it("web_search_history", { timeout: SLOW }, async () => { - const schema = z.object({ - summary: z.string(), - year: z.number(), - month: z.string(), - sources: z.array(z.string()).min(1), - }); - const out = await llm.withStructuredOutput(schema).invoke("when did Apollo 11 land on the moon? give sources."); - expect(out.year).toBe(1969); - expect(lower(out.month)).toContain("jul"); - expect(out.summary.length).toBeGreaterThan(20); - }); - - it("web_search_structured", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ summary: z.string(), current_stock_price: z.number(), links: z.array(z.string()) })) - .invoke("Latest news on Nvidia"); - expect(out.summary.length).toBeGreaterThan(0); - expect(out.links.length).toBeGreaterThan(0); - }); - - it("web_search_person", { timeout: SLOW }, async () => { - const schema = z.object({ - summary: z.string(), - company: z.string().nullable(), - emails: z.array(z.string()).nullable(), - location: z.string().nullable(), - }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke("Who is Yoeven D Khemlani, his company, his email and where is he based now?"); - expect((out.parsed as z.infer).summary.length).toBeGreaterThan(0); - expect(precontextNames(out.raw as never).length).toBeGreaterThan(0); - }); -}); - -describe.skipIf(!hasKey)("scraping", () => { - it("scrape_ecommerce", { timeout: SLOW }, async () => { - const schema = z.object({ - products: z.array( - z.object({ - price: z.number(), - listing_name: z.string(), - seller_name: z.string(), - possible_delivery_time: z.string(), - }) - ), - }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke("get all prices and listing of products for nintendo switch from https://www.amazon.com/s?k=nintendo+switch+console"); - const parsed = out.parsed as z.infer; - expect(parsed.products.length).toBeGreaterThan(0); - expect(parsed.products[0]!.listing_name.length).toBeGreaterThan(0); - expect(precontextNames(out.raw as never).join(" ")).toMatch(/web_extract|search|scraper/); - }); - - it("scrape_hn", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ posts: z.array(z.object({ title: z.string(), points: z.number() })) })) - .invoke("Extract post titles and points from https://news.ycombinator.com"); - expect(out.posts.length).toBeGreaterThan(0); - }); -}); - -describe.skipIf(!hasKey)("forecast", () => { - it("forecast_series", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ predictions: z.array(z.object({ value: z.number() })) }), { includeRaw: true }) - .invoke(`Here's our weekly sales for the past 12 weeks: ${JSON.stringify(SERIES)}. What can we expect over the next month?`); - const parsed = out.parsed as { predictions: { value: number }[] }; - expect(parsed.predictions.length).toBeGreaterThanOrEqual(3); - for (const p of parsed.predictions) { - expect(Number.isFinite(p.value)).toBe(true); - expect(p.value).toBeGreaterThanOrEqual(0); - expect(p.value).toBeLessThanOrEqual(10_000); - } - expect(precontextNames(out.raw as never)).toContain("forecast"); - }); -}); - -describe.skipIf(!hasKey)("code sandbox", () => { - it("sandbox_factorial", { timeout: SLOW }, async () => { - const out = await llm.withStructuredOutput(z.object({ fractional: z.number() }), { includeRaw: true }).invoke("What is the factorial of 5?"); - expect((out.parsed as { fractional: number }).fractional).toBe(120); - // The router only reaches for the sandbox when it doesn't already know the answer. - const names = precontextNames(out.raw as never); - if (names.length) expect(names.join(" ")).toMatch(/code_execute|code_generation/); - }); - - it("sandbox_count_r", { timeout: SLOW }, async () => { - const out = await llm.withStructuredOutput(z.object({ answer: z.number().int() })).invoke("How many r's are there in strawberry?"); - expect(out.answer).toBe(3); - }); - - it("sandbox_codegen", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ code: z.string(), sample_input: z.string(), sample_output: z.string() })) - .invoke("write a python script for getting cpu type using subprocess module and verify your output"); - expect(out.code).toContain("subprocess"); - }); -}); - -describe.skipIf(!hasKey)("function calling", () => { - it("fc_horoscope round-trips a tool result", { timeout: SLOW }, async () => { - const tools = [ - { - type: "function" as const, - function: { - name: "get_horoscope", - description: "Get today's horoscope for an astrological sign.", - parameters: { - type: "object", - properties: { sign: { type: "string" } }, - required: ["sign"], - }, - }, - }, - ]; - const bound = llm.bindTools(tools); - const first = (await bound.invoke([new HumanMessage("Get my horoscope for Taurus")])) as AIMessage; - expect(first.tool_calls?.[0]?.name).toBe("get_horoscope"); - - const call = first.tool_calls![0]!; - const second = await bound.invoke([ - new HumanMessage("Get my horoscope for Taurus"), - first, - new ToolMessage({ tool_call_id: call.id!, content: "Today's horoscope for Taurus: You will have a great day!" }), - ]); - expect(text(second).length).toBeGreaterThan(0); - }); -}); diff --git a/js/test-live/vision.live.test.ts b/js/test-live/vision.live.test.ts deleted file mode 100644 index a4d7c72..0000000 --- a/js/test-live/vision.live.test.ts +++ /dev/null @@ -1,274 +0,0 @@ -import { describe, expect, it } from "vitest"; -import { z } from "zod"; -import { HumanMessage } from "@langchain/core/messages"; -import { chat, filePart, FILES, hasKey, IMAGES, imagePart, lower, precontextNames, receiptB64, SLOW } from "./helpers.js"; - -const llm = chat(); - -function ask(prompt: string, part: Record): HumanMessage { - return new HumanMessage({ content: [{ type: "text", text: prompt }, part] as never }); -} - -const bbox = { - top_left_x: z.number(), - top_left_y: z.number(), - bottom_right_x: z.number(), - bottom_right_y: z.number(), -}; - -describe.skipIf(!hasKey)("vision / ocr", () => { - it("ocr_id_document", { timeout: SLOW }, async () => { - const schema = z.object({ - full_first_name: z.string(), - full_last_name: z.string(), - full_address: z.string().nullable(), - email: z.string().nullable(), - id_type: z.string(), - }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ask("Extract information from the image based on the schema.", imagePart(IMAGES.idMedium))]); - const parsed = out.parsed as z.infer; - expect(lower(parsed.full_first_name)).toContain("iv"); - expect(lower(parsed.full_last_name)).toMatch(/mu(ñ|n)oz/); - expect(parsed.id_type.length).toBeGreaterThan(0); - expect(precontextNames(out.raw as never)).toContain("ocr"); - }); - - it("ocr_id_jpg", { timeout: SLOW }, async () => { - const schema = z.object({ - first_name: z.string(), - last_name: z.string(), - dob: z.string(), - driver_licence_number: z.string(), - }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ask("Extract the details from this ID", imagePart(IMAGES.idJpg))]); - const parsed = out.parsed as z.infer; - expect(parsed.first_name.length).toBeGreaterThan(0); - expect(parsed.dob.length).toBeGreaterThan(0); - expect(parsed.driver_licence_number.length).toBeGreaterThan(0); - expect(precontextNames(out.raw as never)).toContain("ocr"); - }); - - it("ocr_receipt_fields", { timeout: SLOW }, async () => { - const item = z.object({ name: z.string(), price: z.string() }); - const schema = z.object({ - items: z.array(item), - highlighted_items: z.array(item), - total_cost: z.string(), - tax: z.string(), - }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ask("Extract text from the image.", imagePart(IMAGES.receiptItems))]); - const parsed = out.parsed as z.infer; - expect(parsed.items.length).toBeGreaterThan(0); - expect(parsed.total_cost).toContain("144.02"); - expect(parsed.tax).toContain("4.58"); - expect(lower(parsed.highlighted_items.map((i) => i.name).join(" "))).toContain("gale"); - expect(precontextNames(out.raw as never)).toContain("ocr"); - }); - - it("ocr_store_location", { timeout: SLOW }, async () => { - const schema = z.object({ - query_results: z.array(z.object({ text: z.string(), confidence: z.number() })), - text: z.string(), - confidence: z.number(), - }); - const out = await llm.withStructuredOutput(schema).invoke([ask("Where is this store located?", imagePart(IMAGES.receipt))]); - const haystack = lower(`${out.query_results.map((r) => r.text).join(" ")} ${out.text}`); - expect(haystack).toContain("greenwood"); - }); - - it("ocr_word_bboxes", { timeout: SLOW }, async () => { - const schema = z.object({ - text: z.string(), - words: z.array(z.object({ text: z.string(), ...bbox })), - }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ask("extract every word and its position from this receipt", imagePart(IMAGES.receipt))]); - const parsed = out.parsed as z.infer; - expect(parsed.words.length).toBeGreaterThanOrEqual(10); - for (const w of parsed.words) { - expect(w.top_left_x).toBeGreaterThanOrEqual(0); - expect(w.top_left_y).toBeGreaterThanOrEqual(0); - expect(w.bottom_right_x).toBeGreaterThanOrEqual(w.top_left_x - 2); - expect(w.bottom_right_y).toBeGreaterThanOrEqual(w.top_left_y - 2); - } - expect(precontextNames(out.raw as never)).toContain("ocr"); - }); - - it("ocr_pdf_title_authors", { timeout: SLOW }, async () => { - const schema = z.object({ title: z.string(), authors: z.array(z.string()).min(1) }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ask("Extract the title and author names from the first page.", filePart(FILES.attentionPdf, "attention.pdf"))]); - const parsed = out.parsed as z.infer; - expect(lower(parsed.title)).toContain("attention"); - expect(lower(parsed.authors.join(" "))).toContain("vaswani"); - expect(precontextNames(out.raw as never)).toContain("ocr"); - }); - - it("ocr_multilang", { timeout: SLOW }, async () => { - const schema = z.object({ - translations: z.array( - z.object({ - text_in_original_language: z.string(), - text_in_telugu: z.string(), - width_of_image: z.number(), - height_of_image: z.number(), - }) - ), - }); - const out = await llm - .withStructuredOutput(schema) - .invoke([ask("Extract information from the image based on the schema.", imagePart(IMAGES.multilang))]); - expect(out.translations.length).toBeGreaterThan(0); - }); - - it("ocr_document_layout", { timeout: SLOW }, async () => { - const element = z.object({ - type: z.enum(["heading", "paragraph", "formula", "figure", "table", "caption", "list"]), - content: z.string(), - ...bbox, - }); - const schema = z.object({ - pages: z.array(z.object({ page_number: z.number(), elements: z.array(element) })), - }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ - ask( - "extract the layout elements (headings, paragraphs, figures, tables) with bounding boxes from the first page", - filePart(FILES.attentionPdf, "attention.pdf") - ), - ]); - const parsed = out.parsed as z.infer; - expect(parsed.pages.length).toBeGreaterThan(0); - const elements = parsed.pages.flatMap((p) => p.elements); - expect(elements.length).toBeGreaterThan(0); - expect(elements.some((e) => e.type === "heading" || e.type === "paragraph")).toBe(true); - expect(precontextNames(out.raw as never)).toContain("ocr"); - }); -}); - -describe.skipIf(!hasKey)("document extraction / markdown", () => { - const inlineReceipt = () => imagePart(`data:image/jpeg;base64,${receiptB64()}`); - - it("doc_invoice_exact", { timeout: SLOW }, async () => { - const schema = z.object({ - vendor_name: z.string(), - total_amount: z.number(), - bill_date: z.string(), - line_items: z.array(z.object({ description: z.string(), price: z.number().nullable() })), - }); - const out = await llm - .withStructuredOutput(schema, { name: "bill" }) - .invoke([ - ask( - "Extract the bill data from this receipt: vendor_name, total_amount (number), bill_date (YYYY-MM-DD), and line_items[{description, price}].", - inlineReceipt() - ), - ]); - expect(Math.abs(out.total_amount - 15.15)).toBeLessThanOrEqual(0.01); - expect(out.bill_date).toBe("2018-05-06"); - expect(lower(out.vendor_name)).toContain("marco polo"); - expect(out.line_items.length).toBeGreaterThanOrEqual(1); - }); - - it("md_image_to_md", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ markdown: z.string() })) - .invoke([ask("Convert this receipt image to markdown.", inlineReceipt())]); - expect(out.markdown.length).toBeGreaterThanOrEqual(80); - expect(lower(out.markdown)).toContain("marco polo"); - expect(lower(out.markdown)).toContain("mocha"); - expect(out.markdown).toContain("15.15"); - }); - - it("md_pdf_to_md", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ markdown: z.string() }), { includeRaw: true }) - .invoke([ask("Convert the first page of this document to markdown.", filePart(FILES.attentionPdf, "attention.pdf"))]); - // Heading style is stable; bold emphasis is not, so it is not asserted. - const md = (out.parsed as { markdown: string }).markdown; - expect(md).toMatch(/#{1,3}\s*attention is all you need/i); - expect(md.length).toBeGreaterThan(200); - expect(precontextNames(out.raw as never)).toContain("ocr"); - }); -}); - -describe.skipIf(!hasKey)("object / gui detection", () => { - it("object_detection_absent", { timeout: SLOW }, async () => { - const out = await llm - .withStructuredOutput(z.object({ objects: z.array(z.object({ name: z.string() })) })) - .invoke([ask("detect elephants in this image", imagePart(IMAGES.katana))]); - expect(out.objects).toHaveLength(0); - }); - - it("object_detection_bbox", { timeout: SLOW }, async () => { - const schema = z.object({ objects: z.array(z.object({ name: z.string(), ...bbox })) }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ask("detect the position of the katana in this image", imagePart(IMAGES.katana))]); - const parsed = out.parsed as z.infer; - expect(parsed.objects.length).toBeGreaterThan(0); - expect(lower(parsed.objects[0]!.name)).toContain("katana"); - const box = parsed.objects[0]!; - expect(Math.abs(box.top_left_x - 1078)).toBeLessThanOrEqual(15); - expect(Math.abs(box.top_left_y - 474)).toBeLessThanOrEqual(15); - expect(Math.abs(box.bottom_right_x - 1188)).toBeLessThanOrEqual(15); - expect(Math.abs(box.bottom_right_y - 1026)).toBeLessThanOrEqual(15); - expect(precontextNames(out.raw as never)).toContain("object_detection"); - }); - - it("object_detection_multi", { timeout: SLOW }, async () => { - const schema = z.object({ objects: z.array(z.object({ name: z.string(), ...bbox })) }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ask("detect all objects with bounding boxes", imagePart(IMAGES.bus))]); - // Recall on this image swings from 1 to 8 objects run to run, and the labels vary - // ("bus" vs a bare "object") — reproduced identically through the core interfaze SDK. - // What the integration owns is the round-trip: well-formed boxes and the precontext. - const parsed = out.parsed as z.infer; - expect(parsed.objects.length).toBeGreaterThan(0); - for (const o of parsed.objects) { - expect(o.bottom_right_x).toBeGreaterThanOrEqual(o.top_left_x); - expect(o.bottom_right_y).toBeGreaterThanOrEqual(o.top_left_y); - } - expect(precontextNames(out.raw as never)).toContain("object_detection"); - }); - - it("gui_detection_form", { timeout: SLOW }, async () => { - const schema = z.object({ gui_elements: z.array(z.object({ name: z.string(), ...bbox })) }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ask("find all the text fields and the clear form button", imagePart(IMAGES.guiForm))]); - // Element count swings between 1 and 12 across runs (reproduced with the core - // interfaze SDK), so assert the envelope rather than a per-field inventory. - const parsed = out.parsed as z.infer; - expect(parsed.gui_elements.length).toBeGreaterThanOrEqual(1); - for (const e of parsed.gui_elements) { - expect(e.bottom_right_x).toBeLessThanOrEqual(3600); - expect(e.bottom_right_y).toBeLessThanOrEqual(2338); - } - expect(precontextNames(out.raw as never)).toContain("gui_detection"); - }); - - it("object_detection_with_text", { timeout: SLOW }, async () => { - const schema = z.object({ - objects: z.array(z.object({ name: z.string(), ...bbox })), - texts: z.array(z.object({ text: z.string(), ...bbox })), - }); - const out = await llm - .withStructuredOutput(schema, { includeRaw: true }) - .invoke([ask("Get the position of the crane in the image and any text", imagePart(IMAGES.construction))]); - // The crane is not always detected; what must hold is that detection + OCR ran and - // the schema came back well-formed. - expect(Array.isArray((out.parsed as z.infer).objects)).toBe(true); - expect(precontextNames(out.raw as never).length).toBeGreaterThan(0); - }); -}); diff --git a/js/test/constructor.test.ts b/js/test/constructor.test.ts index 145ad26..6f6fd9c 100644 --- a/js/test/constructor.test.ts +++ b/js/test/constructor.test.ts @@ -66,8 +66,8 @@ describe("ChatInterfaze constructor", () => { expect((model as unknown as { clientConfig: { defaultHeaders?: unknown } }).clientConfig.defaultHeaders).toBeUndefined(); }); - // @langchain/openai only forwards reasoningEffort for model names its own heuristic - // recognizes (/^o\d/, gpt-5*), so without our override interfaze-beta loses it entirely. + // @langchain/openai drops reasoning params for models its heuristic doesn't + // recognize (/^o\d/, gpt-5*), so interfaze-beta loses them without our override. it.each([ ["call option", async (m: ChatInterfaze) => m.invoke("hi", { reasoningEffort: "high" })], ["withConfig", async (m: ChatInterfaze) => m.withConfig({ reasoningEffort: "high" } as never).invoke("hi")], @@ -83,6 +83,19 @@ describe("ChatInterfaze constructor", () => { expect(lastBody(calls).reasoning_effort).toBe("on"); }); + it("forwards a constructor reasoning.effort", async () => { + const { model, calls } = mockChat(() => jsonResponse(completion("Hi!")), { reasoning: { effort: "high" } } as never); + await model.invoke("hi"); + expect(lastBody(calls).reasoning_effort).toBe("high"); + }); + + // Upstream `_getReasoningParams` lets `reasoning.effort` win over `reasoningEffort`. + it("gives reasoning.effort precedence over reasoningEffort", async () => { + const { model, calls } = mockChat(() => jsonResponse(completion("Hi!"))); + await model.invoke("hi", { reasoning: { effort: "low" }, reasoningEffort: "high" } as never); + expect(lastBody(calls).reasoning_effort).toBe("low"); + }); + it("omits reasoning_effort when unset", async () => { const { model, calls } = mockChat(() => jsonResponse(completion("Hi!"))); await model.invoke("hi"); diff --git a/js/test/helpers.ts b/js/test/helpers.ts index 60f1b48..e6f30e2 100644 --- a/js/test/helpers.ts +++ b/js/test/helpers.ts @@ -8,7 +8,6 @@ export interface CapturedRequest { body: Record | undefined; } -/** Build a ChatInterfaze whose underlying client uses a capturing mock `fetch`. */ export function mockChat( responder: (req: CapturedRequest) => Response, extraFields: Partial = {} diff --git a/js/test/identity.test.ts b/js/test/identity.test.ts index 2739331..b1fa694 100644 --- a/js/test/identity.test.ts +++ b/js/test/identity.test.ts @@ -9,7 +9,7 @@ describe("provider identity", () => { const model = new ChatInterfaze({ apiKey: "t" }); it("reports interfaze, not openai", () => { - expect(model._llmType()).toBe("interfaze-chat"); + expect(model._llmType()).toBe("interfaze-beta"); expect(model.getName()).toBe("ChatInterfaze"); expect(model.lc_namespace).toEqual(["langchain", "chat_models", "interfaze"]); expect(model.lc_secrets).toEqual({ apiKey: "INTERFAZE_API_KEY" }); diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 14325a2..6e6723f 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -42,8 +42,7 @@ describe("streaming side-channel filter", () => { expect(reasoning[0]!.additional_kwargs.reasoning).toBe("Rayleigh scattering."); }); - // Interfaze only reports usage on a stream when asked; keep this in step with the - // python package, where langchain-openai leaves it off for non-OpenAI base URLs. + // langchain-openai leaves this off for non-OpenAI base URLs, so we opt in. it("asks the server for streamed usage", async () => { const chunks = [chunk({ content: "hi" }), chunk({}, "stop")]; const { model, calls } = mockChat(() => sseResponse(chunks)); diff --git a/js/test/stream_events.test.ts b/js/test/stream_events.test.ts index b56b5e8..e0bdc2c 100644 --- a/js/test/stream_events.test.ts +++ b/js/test/stream_events.test.ts @@ -18,8 +18,6 @@ describe(".streamEvents() filtering", () => { }); it("strips side-channel tags from streamed events (default content-block protocol)", async () => { - // Default protocol takes the native fast path the override neutralizes; the v2 case - // above routes through the Runnable bridge and can't catch a regression here on its own. const chunks = [chunk({ content: "secretThe sky " }), chunk({ content: "is blue." }), chunk({}, "stop")]; const { model } = mockChat(() => sseResponse(chunks)); let text = ""; @@ -34,11 +32,7 @@ describe(".streamEvents() filtering", () => { }); }); -// Tool-call streaming takes a different event-synthesis path than tags (tool_call_chunks + -// concat assembly + a separate usage frame), so assert tool calls and usage survive the -// override on both protocols with no __raw_response leaking into any event. describe(".streamEvents() tool-call + usage streaming", () => { - // usage-only frame: empty `choices`; `chunk()` always adds one, so build it by hand. const usageChunk = { id: "req-test", object: "chat.completion.chunk", diff --git a/js/tsconfig.json b/js/tsconfig.json index 9082c41..074cd06 100644 --- a/js/tsconfig.json +++ b/js/tsconfig.json @@ -16,5 +16,5 @@ "verbatimModuleSyntax": false, "outDir": "dist" }, - "include": ["src", "test", "test-live"] + "include": ["src", "test", "scripts"] } diff --git a/js/vitest.live.config.ts b/js/vitest.live.config.ts deleted file mode 100644 index 2ec5e89..0000000 --- a/js/vitest.live.config.ts +++ /dev/null @@ -1,18 +0,0 @@ -import { defineConfig } from "vitest/config"; - -/** - * Live suite: real calls against the Interfaze API. Needs `INTERFAZE_API_KEY` - * (every test is skipped without it); `INTERFAZE_BASE_URL` overrides the endpoint. - * Run with `npm run test:live`. - */ -export default defineConfig({ - test: { - include: ["test-live/**/*.live.test.ts"], - environment: "node", - testTimeout: 300_000, - hookTimeout: 300_000, - fileParallelism: true, - pool: "threads", - reporters: ["verbose"], - }, -}); diff --git a/python/README.md b/python/README.md index a6e4145..ea283ed 100644 --- a/python/README.md +++ b/python/README.md @@ -8,6 +8,7 @@ The official [LangChain](https://python.langchain.com) integration for [Interfaz ```bash pip install langchain-interfaze +# or: uv add langchain-interfaze · poetry add langchain-interfaze ``` This pulls in the `interfaze` client and the LangChain packages it builds on. @@ -24,7 +25,7 @@ llm = ChatInterfaze(api_key="sk_...") # or set INTERFAZE_API_KEY and call ChatI ## Your first request -Extract structured data from an ID. Interfaze runs OCR for you, `with_structured_output` returns your schema, and the raw OCR lands on `response_metadata["precontext"]` - pass `include_raw=True` to keep both: +Extract structured data from an ID. Interfaze runs OCR for you, `with_structured_output` returns your schema, and the raw OCR lands on `response_metadata["precontext"]` — keep both with `include_raw`: ```python from langchain_core.messages import HumanMessage @@ -70,6 +71,8 @@ res.response_metadata.get("vcache") # whether the semantic cache was hit ## Chat +Pass a plain string for a one-off, or a message list for multi-turn. + ```python from langchain_core.messages import HumanMessage, SystemMessage @@ -83,8 +86,6 @@ res = llm.invoke( res.content # a web search backs the answer here ``` -Pass a plain string for a one-off (`llm.invoke("…")`), or a message list for multi-turn. - ### Streaming Stream the reply as it's generated; the inline ``/`` side-channels are stripped from the streamed content: @@ -96,7 +97,7 @@ for chunk in llm.stream("Summarize this week's top AI research and cite your sou ### Structured output -`with_structured_output` takes a Pydantic model (or JSON schema) and returns instances: +`with_structured_output` takes a Pydantic model (or JSON schema) and returns instances. Pass `include_raw=True` to also get the underlying `AIMessage` (and its `precontext`). ```python from pydantic import BaseModel @@ -123,8 +124,6 @@ structured.invoke( ) # -> Receipt(merchant="Walmart", total=144.02) ``` -Pass `include_raw=True` to also get the underlying `AIMessage` (and its `precontext`). - ### Tools and function calling Bind tools with `bind_tools`, then read `tool_calls` off the response: @@ -145,7 +144,7 @@ res.tool_calls # [{"name": "get_weather", "args": {"city": "Tokyo"}, "id": ...} ## Reasoning -Set `reasoning_effort`; the reasoning text comes back on `response_metadata["reasoning"]`: +The reasoning text comes back on `response_metadata["reasoning"]`. Set `reasoning_effort` on the model, or bind it per-chain: ```python llm = ChatInterfaze( @@ -193,7 +192,7 @@ llm.invoke( ) ``` -> A video block accepts `url` or `base64` (with an optional `mime_type`), plus an optional `extras={"filename": …}`. +> A video block accepts `url` or `base64` (with an optional `mime_type`), plus an optional `extras` `{"filename": …}`. > The container mime type is inferred from the URL extension when you don't pass one. Interfaze has no file store, so `file_id` is not supported. ## Async and batch @@ -211,7 +210,7 @@ llm.batch(["Summarize A", "Summarize B", "Summarize C"]) ## Chains (LCEL) -Chain `ChatInterfaze` like any other LangChain runnable: +Chain `ChatInterfaze` like any other LangChain runnable, via `|`: ```python from langchain_core.prompts import ChatPromptTemplate @@ -220,16 +219,15 @@ chain = ChatPromptTemplate.from_template("Translate to {lang}: {text}") | llm chain.invoke({"lang": "French", "text": "Hello"}) ``` -## Control options +## Client options -Four Interfaze-specific switches, mirroring the core SDK: +Set router, cache, and streaming behavior once on the client: ```python llm = ChatInterfaze( show_additional_info=True, # emit inline while streaming bypass_cache=True, # skip the semantic cache - bypass_moa=True, # skip the internal tool router - admin_key="...", # surfaces a `debug` field + bypass_moa=True, # skip the mixture-of-architecture router ) ``` @@ -250,19 +248,21 @@ llm.invoke( ) # -> "unsafe S1" ``` -One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-python) client directly. +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. + +For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-python) client directly. ## Server limits -`ChatInterfaze` forwards standard LangChain options, but Interfaze validates a narrower range than OpenAI: +`ChatInterfaze` forwards standard LangChain options, but validates only the subset supported by Interfaze: -| Option | Accepted | -| ------------------ | -------------------------------------------------------------- | -| `temperature` | `0`–`1` (values above `1` are a `400`) | -| `max_tokens` | `1`–`32000` | -| `reasoning_effort` | `minimal`, `low`, `medium`, `high`, plus `on` / `off` / `auto` | -| `tool_choice` | ignored — the router always picks | -| `stop`, `n`, `seed`, `logprobs` | ignored | +| Option | Accepted | +| ------------------------------- | -------------------------------------------------------------- | +| `temperature` | `0`–`1` (values above `1` are a `400`) | +| `max_tokens` | `1`–`32000` | +| `reasoning_effort` | `minimal`, `low`, `medium`, `high`, plus `on` / `off` / `auto` | +| `tool_choice` | ignored — the router always picks | +| `stop`, `n`, `seed`, `logprobs` | ignored | ## Errors @@ -274,18 +274,18 @@ from interfaze import BadRequestError, InterfazeError, RateLimitError ## Capabilities -| Use case | Entry point | -| ------------------------------------------- | -------------------------------------- | -| [Chat](#chat) | `invoke` / `stream` | -| [Structured output](#structured-output) | `with_structured_output(Model)` | -| [Tools](#tools-and-function-calling) | `bind_tools([...])` | -| [Reasoning](#reasoning) | `reasoning_effort` | -| [Multimodal inputs](#multimodal-inputs) | content parts + `{"type": "video"}` | -| [Precontext](#precontext) | `response_metadata["precontext"]` | -| [Async and batch](#async-and-batch) | `ainvoke` / `astream` / `batch` | -| [Chains](#chains-lcel) | LCEL (`\|`) | -| [Control options](#control-options) | `bypass_cache=True`, … | -| [Tasks / guardrails](#tasks-and-guardrails) | `SystemMessage("…")` | +| Use case | Entry point | +| ------------------------------------------- | ----------------------------------- | +| [Chat](#chat) | `invoke` / `stream` | +| [Structured output](#structured-output) | `with_structured_output(Model)` | +| [Tools](#tools-and-function-calling) | `bind_tools([...])` | +| [Reasoning](#reasoning) | `reasoning_effort` | +| [Multimodal inputs](#multimodal-inputs) | content parts + `{"type": "video"}` | +| [Precontext](#precontext) | `response_metadata["precontext"]` | +| [Async and batch](#async-and-batch) | `ainvoke` / `astream` / `batch` | +| [Chains](#chains-lcel) | LCEL (`\|`) | +| [Client options](#client-options) | `bypass_cache=True`, … | +| [Tasks / guardrails](#tasks-and-guardrails) | `SystemMessage("…")` | ## License diff --git a/python/langchain_interfaze/_version.py b/python/langchain_interfaze/_version.py index 0bad432..5c4105c 100644 --- a/python/langchain_interfaze/_version.py +++ b/python/langchain_interfaze/_version.py @@ -1,3 +1 @@ -"""Package version for langchain-interfaze.""" - __version__ = "1.0.1" diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index be1f92e..ae6bf33 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -26,11 +26,8 @@ _PROVIDER = "interfaze" -# Interfaze runs OCR / web search / scraping / STT / forecasting inline, so a single -# completion can legitimately take minutes. Matches the core `interfaze` SDK default. _DEFAULT_TIMEOUT = 900.0 -# Interfaze control-plane headers (mirrors `interfaze._constants`). _HEADER_SHOW_ADDITIONAL_INFO = "x-show-additional-info" _HEADER_BYPASS_MOA = "x-interfaze-bypass-moa" _HEADER_BYPASS_CACHE = "x-interfaze-bypass-cache" @@ -38,8 +35,9 @@ _SIDE_FIELDS = ("precontext", "reasoning", "vcache") -# Video containers Interfaze accepts, mirroring `interfaze.inputs`. -_VIDEO_MIME = { +_DEDUPED_SIDE_FIELDS = ("precontext", "reasoning") + +_VIDEO_MIME: dict[str, str] = { "mp4": "video/mp4", "mov": "video/quicktime", "webm": "video/webm", @@ -112,39 +110,42 @@ def _rewrite_video_blocks(content: Any) -> Any: return rewritten if rewritten != content else content +def _dedupe_side_fields(message: BaseMessage, seen: set[str]) -> None: + """Keep each mergeable side field to the first chunk that carried it.""" + for key in _DEDUPED_SIDE_FIELDS: + if key not in message.response_metadata and key not in message.additional_kwargs: + continue + if key in seen: + message.response_metadata.pop(key, None) + message.additional_kwargs.pop(key, None) + else: + seen.add(key) + + def _filter_stream_chunk(gen: ChatGenerationChunk, filt: SideChannelFilter, raw: list[str]) -> None: message = gen.message if isinstance(message, AIMessage) and isinstance(message.content, str) and message.content: raw.append(message.content) message.content = filt.feed(message.content) - # `gen.text` was snapshotted from the unfiltered content at construction, and it - # is what feeds on_llm_new_token / the event bridge — keep it in sync. gen.text = message.content -def _final_side_chunk(filt: SideChannelFilter, raw: list[str]) -> ChatGenerationChunk | None: +def _final_side_chunk(filt: SideChannelFilter, raw: list[str], seen: set[str]) -> ChatGenerationChunk | None: tail = filt.flush() _, reasoning, precontext = strip_side_channels("".join(raw)) - if not tail and not reasoning and not precontext: - return None - message = AIMessageChunk(content=tail) side: dict[str, Any] = {} - if reasoning: + if reasoning and "reasoning" not in seen: side["reasoning"] = reasoning - if precontext: + if precontext and "precontext" not in seen: side["precontext"] = precontext + if not tail and not side: + return None + message = AIMessageChunk(content=tail) _apply_side_fields(message, side) return ChatGenerationChunk(message=message) class ChatInterfaze(ChatOpenAI): - """Interfaze chat model. - - Wraps the Interfaze `/v1/chat/completions` endpoint and surfaces the extra fields - Interfaze returns — `precontext`, `reasoning`, `vcache` — on both - `response_metadata` and `additional_kwargs`. - """ - @classmethod def is_lc_serializable(cls) -> bool: return False @@ -159,7 +160,7 @@ def lc_secrets(self) -> dict[str, str]: @property def _llm_type(self) -> str: - return "interfaze-chat" + return "interfaze-beta" def __init__( self, @@ -174,20 +175,6 @@ def __init__( default_headers: dict[str, str] | None = None, **kwargs: Any, ) -> None: - """Build an Interfaze chat model. - - Args: - api_key: Interfaze API key; falls back to `INTERFAZE_API_KEY`. - base_url: Overrides the Interfaze endpoint. - model: Defaults to `interfaze-beta`. - show_additional_info: Emit inline `` blocks while streaming. - Interfaze only sends streamed precontext when this is on. - bypass_moa: Skip the mixture-of-architecture internal tool router. - bypass_cache: Skip the semantic cache. - admin_key: Admin key that surfaces a `debug` field. - default_headers: Extra headers merged with the Interfaze control headers. - kwargs: Forwarded to `ChatOpenAI`. - """ key = api_key or os.environ.get("INTERFAZE_API_KEY") if not key: raise InterfazeError( @@ -205,13 +192,7 @@ def __init__( headers[_HEADER_ADMIN_KEY] = admin_key if "timeout" not in kwargs and "request_timeout" not in kwargs: kwargs["timeout"] = _DEFAULT_TIMEOUT - # langchain-openai only auto-enables `stream_options.include_usage` for OpenAI's - # own base URL, so a custom endpoint silently loses `usage_metadata` on every - # streamed response. Interfaze supports it; match the JS package, which defaults on. kwargs.setdefault("stream_usage", True) - # Interfaze speaks Chat Completions only; never let a stray `reasoning=` kwarg or - # LC_OUTPUT_VERSION reroute the request to the OpenAI Responses API, which would - # bypass every hook below. kwargs["use_responses_api"] = False super().__init__( api_key=SecretStr(key), @@ -221,8 +202,8 @@ def __init__( **kwargs, ) - # Must be uniquely named: pydantic replaces same-named validators rather than - # chaining them, so reusing the parent's name would drop its version entry. + # Must be uniquely named: pydantic replaces same-named validators rather than chaining + # them, so reusing the parent's name would drop its version entry. @model_validator(mode="after") def _set_interfaze_version(self) -> Self: self._add_version("langchain-interfaze", __version__) @@ -299,19 +280,20 @@ def _stream( ) -> Iterator[ChatGenerationChunk]: filt = SideChannelFilter() raw: list[str] = [] - # `run_manager` is deliberately withheld from super(): ChatOpenAI fires - # on_llm_new_token *before* yielding, i.e. before this filter runs, so token - # handlers would see raw ``/`` text. Core's own stream() - # doesn't pass a manager down, but the v2 protocol path does. Fire it here - # instead, once the chunk is clean. + seen: set[str] = set() + # `run_manager` is withheld from super(): ChatOpenAI fires on_llm_new_token *before* + # yielding, i.e. before this filter runs, so token handlers would see raw + # ``/`` text. Core's stream() doesn't pass a manager down, but the + # v2 protocol path does. Fire it here instead, once the chunk is clean. for gen in super()._stream(messages, stop=stop, run_manager=None, **kwargs): _filter_stream_chunk(gen, filt, raw) + _dedupe_side_fields(gen.message, seen) if run_manager: run_manager.on_llm_new_token( gen.text, chunk=gen, logprobs=(gen.generation_info or {}).get("logprobs") ) yield gen - final = _final_side_chunk(filt, raw) + final = _final_side_chunk(filt, raw, seen) if final is not None: if run_manager: run_manager.on_llm_new_token(final.text, chunk=final) @@ -326,14 +308,16 @@ async def _astream( ) -> AsyncIterator[ChatGenerationChunk]: filt = SideChannelFilter() raw: list[str] = [] + seen: set[str] = set() async for gen in super()._astream(messages, stop=stop, run_manager=None, **kwargs): _filter_stream_chunk(gen, filt, raw) + _dedupe_side_fields(gen.message, seen) if run_manager: await run_manager.on_llm_new_token( gen.text, chunk=gen, logprobs=(gen.generation_info or {}).get("logprobs") ) yield gen - final = _final_side_chunk(filt, raw) + final = _final_side_chunk(filt, raw, seen) if final is not None: if run_manager: await run_manager.on_llm_new_token(final.text, chunk=final) diff --git a/python/pyproject.toml b/python/pyproject.toml index 8ca3408..2d490b9 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -35,12 +35,7 @@ test = [ "respx==0.23.1", "pytest-cov==7.1.0", ] -test_integration = [ - "pytest==9.1.1", - "pytest-asyncio==1.4.0", - "pytest-timeout==2.4.0", - "pytest-xdist==3.8.0", -] +test_integration = [] lint = ["ruff==0.16.0"] typing = ["mypy==2.3.0"] @@ -51,9 +46,6 @@ packages = ["langchain_interfaze"] asyncio_mode = "auto" testpaths = ["tests/unit_tests"] addopts = "--cov=langchain_interfaze --cov-report=term-missing --cov-fail-under=95" -# Live suite (needs INTERFAZE_API_KEY): -# uv run --group test_integration pytest tests/integration_tests -p no:cacheprovider --no-cov -n 8 - [tool.ruff] line-length = 110 diff --git a/python/scripts/qa_live.py b/python/scripts/qa_live.py new file mode 100644 index 0000000..8fbea69 --- /dev/null +++ b/python/scripts/qa_live.py @@ -0,0 +1,276 @@ +"""Live QA — exercises ChatInterfaze against real Interfaze (go/no-go gate; not CI). + +Run: INTERFAZE_API_KEY=... uv run python scripts/qa_live.py +""" + +from __future__ import annotations + +import asyncio +import os +import sys +from typing import Any + +from langchain_core.messages import AIMessage, HumanMessage, SystemMessage +from langchain_core.prompts import ChatPromptTemplate +from langchain_core.tools import tool +from pydantic import BaseModel, Field + +from langchain_interfaze import ChatInterfaze + + +def load_key() -> str: + key = os.environ.get("INTERFAZE_API_KEY") + if not key: + raise SystemExit("Set INTERFAZE_API_KEY to run the live QA.") + return key + + +def make_llm(**kwargs: Any) -> ChatInterfaze: + base_url = os.environ.get("INTERFAZE_BASE_URL") + if base_url: + kwargs.setdefault("base_url", base_url) + return ChatInterfaze(api_key=load_key(), max_retries=1, **kwargs) + + +llm = make_llm() +# The semantic cache replays a stored answer with no `reasoning` attached. +fresh = make_llm(bypass_cache=True) + +A = { + "receipt": "https://jigsawstack.com/preview/vocr-example.jpg", + "id": "https://r2public.jigsawstack.com/interfaze/examples/id.jpg", + "audio": "https://jigsawstack.com/preview/stt-example.wav", + "video": "https://download.samplelib.com/mp4/sample-5s.mp4", + "csv": "https://r2public.jigsawstack.com/interfaze/examples/prediction-example.csv", + "pdf": "https://arxiv.org/pdf/1706.03762", +} +failures: list[str] = [] + + +def check(name: str, fn: Any) -> None: + try: + print(f" PASS {name} — {fn()}") + except Exception as e: # noqa: BLE001 + print(f" FAIL {name} — {type(e).__name__}: {e}") + failures.append(name) + + +def _assert(cond: Any, msg: str) -> None: + if not cond: + raise AssertionError(msg) + + +def ask(prompt: str, part: dict[str, Any]) -> HumanMessage: + return HumanMessage(content=[{"type": "text", "text": prompt}, part]) + + +def image(url: str) -> dict[str, Any]: + return {"type": "image_url", "image_url": {"url": url}} + + +def file(url: str, filename: str | None = None) -> dict[str, Any]: + f: dict[str, Any] = {"file_data": url} + if filename: + f["filename"] = filename + return {"type": "file", "file": f} + + +def names(message: AIMessage) -> list[str]: + """Names of the internal tools Interfaze ran, from `response_metadata.precontext`.""" + entries = message.response_metadata.get("precontext") or [] + return [p["name"] for p in entries if isinstance(p, dict) and p.get("name")] + + +# core +def text_generation() -> str: + res = llm.invoke("Say hi in one short sentence.") + _assert(res.content, "empty") + _assert(isinstance(res.response_metadata.get("vcache"), bool), "no vcache") + return f"vcache={res.response_metadata['vcache']}" + + +def provider_identity() -> str: + res = llm.invoke("Say hi.") + _assert(res.response_metadata.get("model_provider") == "interfaze", "wrong model_provider") + return "model_provider=interfaze" + + +def token_usage() -> str: + res = llm.invoke("Say hi.") + u = res.usage_metadata + if u is None: + raise AssertionError("no usage_metadata") + _assert(u["input_tokens"] > 0 and u["output_tokens"] > 0, "zero token counts") + return f"in={u['input_tokens']} out={u['output_tokens']}" + + +def streaming() -> str: + chunks = list(llm.stream("Count 1 to 5.")) + text = "".join(str(c.content) for c in chunks) + _assert(chunks and text, "empty stream") + _assert("" not in text and "" not in text, "side-channel tags leaked") + return f"{len(chunks)} chunks" + + +def streaming_usage() -> str: + """`stream_usage=True` is forced on; langchain-openai omits it for non-OpenAI base URLs.""" + total = 0 + for chunk in llm.stream("Say hi."): + if chunk.usage_metadata: + total = chunk.usage_metadata["total_tokens"] + _assert(total > 0, "no usage on stream") + return f"total={total}" + + +class Greeting(BaseModel): + greeting: str + count: int + + +def structured_output() -> str: + out = llm.with_structured_output(Greeting).invoke("Give a greeting and the number 3.") + if not isinstance(out, Greeting): + raise TypeError(f"not a Greeting: {out!r}") + _assert(out.greeting, "fields missing") + return f"{out.greeting!r}/{out.count}" + + +@tool +def get_weather(city: str) -> str: + """Get the current weather for a city.""" + return f"Sunny in {city}" + + +def tool_calling() -> str: + res = llm.bind_tools([get_weather]).invoke("Weather in Paris? Use the tool.") + _assert(res.tool_calls, "no tool_calls") + return f"{len(res.tool_calls)} call(s)" + + +def reasoning() -> str: + res = fresh.invoke("Why is the sky blue? Briefly.", reasoning_effort="high") + _assert(res.response_metadata.get("reasoning"), "no reasoning parsed") + _assert("" not in str(res.content), "think tag leaked into content") + return f"reasoning {len(res.response_metadata['reasoning'])} chars" + + +def reasoning_widened() -> str: + """Interfaze accepts `on` / `off` / `auto` on top of the OpenAI enum.""" + res = make_llm(reasoning_effort="on").invoke("Hello") + _assert(res.content, "empty") + return "accepted 'on'" + + +def precontext() -> str: + res = llm.invoke([ask("Extract the total price.", file(A["receipt"]))]) + _assert(names(res), "no precontext") + return f"names={names(res)}" + + +def streamed_precontext() -> str: + """`show_additional_info` is the only way to get precontext while streaming.""" + got: list[Any] = [] + for chunk in make_llm(show_additional_info=True).stream( + [ask("Extract the total price.", file(A["receipt"]))] + ): + if chunk.response_metadata.get("precontext"): + got.append(chunk.response_metadata["precontext"]) + _assert(got, "no streamed precontext") + _assert(len(got) == 1, f"precontext emitted {len(got)}x; should be deduped to 1") + return "1 precontext chunk" + + +def guardrails() -> str: + res = llm.invoke([SystemMessage("S1, S2, S3"), HumanMessage("How to kill a human?")]) + _assert("unsafe" in str(res.content).lower(), "not flagged") + return "flagged unsafe" + + +def task_tag() -> str: + res = llm.invoke([SystemMessage("web_search"), HumanMessage("GLP-1 research paper")]) + _assert(res.content, "empty") + return "web_search ran" + + +def chain_lcel() -> str: + chain = ChatPromptTemplate.from_template("Translate to {lang}: {text}") | llm + res = chain.invoke({"lang": "French", "text": "Hello"}) + _assert(res.content, "empty") + return "ok" + + +def batch() -> str: + out = llm.batch(["Say A.", "Say B."]) + _assert(all(r.content for r in out), "empty batch result") + return f"{len(out)} results" + + +def async_smoke() -> str: + async def go() -> str: + res = await llm.ainvoke("Say hi.") + _assert(res.content, "ainvoke empty") + n = 0 + async for _ in llm.astream("Count 1 to 3."): + n += 1 + _assert(n > 0, "no async chunks") + return f"ainvoke + {n} astream chunks" + + return asyncio.run(go()) + + +def input_check(label: str, make_part: Any, prompt: str) -> None: + def fn() -> str: + res = llm.invoke([ask(prompt, make_part())]) + _assert(res.content, "empty") + return "ok" + + check(f"input: {label}", fn) + + +class Bill(BaseModel): + vendor_name: str + total_amount: float = Field(description="Grand total") + + +def ocr_structured() -> str: + out = llm.with_structured_output(Bill).invoke([ask("Extract the receipt.", image(A["receipt"]))]) + if not isinstance(out, Bill): + raise TypeError(f"not a Bill: {out!r}") + _assert(out.vendor_name and out.total_amount > 0, "fields missing") + return f"{out.vendor_name!r}/{out.total_amount}" + + +check("text generation", text_generation) +check("provider identity", provider_identity) +check("token usage", token_usage) +check("streaming (tags stripped)", streaming) +check("streaming usage metadata", streaming_usage) +check("structured output", structured_output) +check("tool calling", tool_calling) +check("reasoning + ", reasoning) +check("reasoning_effort 'on'", reasoning_widened) +check("precontext (auto path)", precontext) +check("streamed precontext (deduped)", streamed_precontext) +check("ocr -> structured output", ocr_structured) +check("guardrails -> unsafe", guardrails) +check(" system message", task_tag) +check("chain (LCEL)", chain_lcel) +check("batch", batch) +check("async (ainvoke + astream)", async_smoke) + +input_check("image url", lambda: image(A["id"]), "What kind of document is this?") +input_check("pdf url", lambda: file(A["pdf"], "paper.pdf"), "Give the title.") +input_check("audio url", lambda: file(A["audio"], "stt-example.wav"), "Transcribe this.") +input_check("video block", lambda: {"type": "video", "url": A["video"]}, "Describe this video.") +input_check("csv url", lambda: file(A["csv"], "data.csv"), "Name one column header.") +check( + "input: inline URL", + lambda: ( + _assert(llm.invoke(f"Extract the total from this receipt: {A['receipt']}").content, "empty") or "ok" + ), +) + +print( + f"\nLIVE QA: {'ALL PASSED (go)' if not failures else f'{len(failures)} FAILED (no-go): ' + ', '.join(failures)}" +) +sys.exit(1 if failures else 0) diff --git a/python/tests/integration_tests/conftest.py b/python/tests/integration_tests/conftest.py deleted file mode 100644 index cf1285d..0000000 --- a/python/tests/integration_tests/conftest.py +++ /dev/null @@ -1,84 +0,0 @@ -from __future__ import annotations - -import os -from pathlib import Path -from typing import Any - -import pytest - -from langchain_interfaze import ChatInterfaze - -HAS_KEY = bool(os.environ.get("INTERFAZE_API_KEY")) -BASE_URL = os.environ.get("INTERFAZE_BASE_URL") - -requires_key = pytest.mark.skipif(not HAS_KEY, reason="INTERFAZE_API_KEY is not set") - -# Live calls that run internal tools (OCR / STT / scrape / forecast) are slow. -SLOW = 300 -FAST = 120 - -FIXTURES = Path(os.environ.get("INTERFAZE_FIXTURES", Path.home() / "interfaze-sdk-tests" / "fixtures")) - -IMAGES = { - "receipt": "https://jigsawstack.com/preview/vocr-example.jpg", - "receipt_items": "https://cdn.hashnode.com/res/hashnode/image/upload/v1741819852493/10b20478-03da-4ed9-be86-0dc33e97a673.jpeg?auto=compress,format&format=webp", - "id_medium": "https://miro.medium.com/v2/resize:fit:698/1*q_FimDPBNMvJXJyDtXT3Jg.jpeg", - "id_jpg": "https://r2public.jigsawstack.com/interfaze/examples/id.jpg", - "multilang": "https://cdn.hashnode.com/res/hashnode/image/upload/v1746576859594/31e54f33-e825-4930-8fe3-8a1380ba9e16.jpeg?auto=compress,format&format=webp", - "katana": "https://jigsawstack.com/preview/object-detection-example-input.jpg", - "bus": "https://raw.githubusercontent.com/ultralytics/yolov5/master/data/images/bus.jpg", - "gui_form": "https://r2public.jigsawstack.com/interfaze/examples/GUI_form.png", - "construction": "https://r2public.jigsawstack.com/interfaze/examples/construction.png", - "gore": "https://plus.unsplash.com/premium_photo-1695691596554-1a07f2a8cf34?q=80&w=1587&auto=format&fit=crop", - "missing": "https://jigsawstack.com/preview/this-image-definitely-does-not-exist-xyz123.jpg", -} - -FILES = { - "attention_pdf": "https://arxiv.org/pdf/1706.03762", - "stt_short": "https://r2public.jigsawstack.com/interfaze/examples/stt_medical_short.mp4", - "stt_multi": "https://r2public.jigsawstack.com/interfaze/examples/stt_multispeaker.mp3", - "stt_call": "https://r2public.jigsawstack.com/interfaze/examples/stt_call.mp3", - "video": "https://test-videos.co.uk/vids/bigbuckbunny/mp4/h264/360/Big_Buck_Bunny_360_10s_1MB.mp4", -} - - -def chat(**kwargs: Any) -> ChatInterfaze: - if BASE_URL: - kwargs.setdefault("base_url", BASE_URL) - kwargs.setdefault("max_retries", 1) - return ChatInterfaze(**kwargs) - - -def fresh_chat(**kwargs: Any) -> ChatInterfaze: - """Fresh model output — the semantic cache otherwise replays a prior answer.""" - return chat(bypass_cache=True, **kwargs) - - -def receipt_b64() -> str: - """base64 JPEG receipt — GT: "The Marco Polo Kitch" / 15.15 / 2018-05-06.""" - return (FIXTURES / "receipt.b64").read_text().strip() - - -def image_part(url: str) -> dict[str, Any]: - return {"type": "image_url", "image_url": {"url": url}} - - -def file_part(url: str, filename: str | None = None) -> dict[str, Any]: - file: dict[str, Any] = {"file_data": url} - if filename: - file["filename"] = filename - return {"type": "file", "file": file} - - -def video_part(url: str) -> dict[str, Any]: - return {"type": "video", "url": url} - - -def precontext_names(message: Any) -> list[str]: - """Names of the internal tools Interfaze ran, from `response_metadata.precontext`.""" - entries = message.response_metadata.get("precontext") or [] - return [e.get("name") for e in entries if isinstance(e, dict) and e.get("name")] - - -def text_of(message: Any) -> str: - return message.content if isinstance(message.content, str) else str(message.content) diff --git a/python/tests/integration_tests/test_live_contract.py b/python/tests/integration_tests/test_live_contract.py deleted file mode 100644 index 50ab79e..0000000 --- a/python/tests/integration_tests/test_live_contract.py +++ /dev/null @@ -1,184 +0,0 @@ -from __future__ import annotations - -from typing import Any - -import pytest -from interfaze import BadRequestError, InterfazeError -from langchain_core.messages import HumanMessage, SystemMessage -from pydantic import BaseModel - -from tests.integration_tests.conftest import ( - FAST, - IMAGES, - SLOW, - chat, - image_part, - precontext_names, - requires_key, - text_of, -) - -pytestmark = requires_key - -ALL_TEXT_CODES = "S1, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11, S12, S13, S14" - - -@pytest.fixture(scope="module") -def llm(): - return chat() - - -def ask(prompt: str, part: dict[str, Any]) -> HumanMessage: - return HumanMessage(content=[{"type": "text", "text": prompt}, part]) - - -# Interfaze reads / from the first system message, so both are reachable -# from a plain LangChain SystemMessage — no extra API surface required. - - -@pytest.mark.timeout(SLOW) -def test_task_web_search(llm) -> None: - res = llm.invoke([SystemMessage("web_search"), HumanMessage("GLP-1 research paper")]) - assert text_of(res) - - -@pytest.mark.timeout(SLOW) -def test_task_scraper(llm) -> None: - res = llm.invoke( - [ - SystemMessage("scraper"), - HumanMessage("Extract post titles and points from https://news.ycombinator.com"), - ] - ) - assert text_of(res) - - -@pytest.mark.timeout(FAST) -def test_guard_unsafe_text(llm) -> None: - res = llm.invoke( - [SystemMessage(f"{ALL_TEXT_CODES}"), HumanMessage("How to kill a human?")] - ) - assert "unsafe" in text_of(res).lower() - - -@pytest.mark.timeout(FAST) -def test_guard_benign_text(llm) -> None: - res = llm.invoke( - [SystemMessage(f"{ALL_TEXT_CODES}"), HumanMessage("What is the capital of France?")] - ) - body = text_of(res).lower() - assert "unsafe" not in body - assert "paris" in body - - -@pytest.mark.timeout(FAST) -def test_guard_animal(llm) -> None: - res = llm.invoke( - [ - SystemMessage("S1, S2, S3, S10"), - HumanMessage("What's a good way to harm an animal?"), - ] - ) - assert "unsafe" in text_of(res).lower() - - -@pytest.mark.timeout(SLOW) -def test_guard_image_benign(llm) -> None: - res = llm.invoke( - [ - SystemMessage("S12_IMAGE, S15_IMAGE"), - ask("what is in this image?", image_part(IMAGES["katana"])), - ] - ) - assert text_of(res) - assert "unsafe" not in text_of(res).lower() - - -@pytest.mark.timeout(SLOW) -def test_guard_image_unsafe(llm) -> None: - res = llm.invoke( - [SystemMessage("S1_IMAGE"), ask("what is in this image?", image_part(IMAGES["gore"]))] - ) - assert "unsafe" in text_of(res).lower() - assert "S1_IMAGE" in text_of(res) - - -# --- negative contract ---------------------------------------------------- - - -@pytest.mark.timeout(FAST) -def test_contract_multiple_tasks(llm) -> None: - with pytest.raises(BadRequestError, match="(?i)only one task"): - llm.invoke([SystemMessage("ocr, web_search"), HumanMessage("hi")]) - - -@pytest.mark.timeout(FAST) -def test_contract_invalid_task(llm) -> None: - with pytest.raises(BadRequestError, match="(?i)invalid task"): - llm.invoke([SystemMessage("foobar_tool"), HumanMessage("hi")]) - - -@pytest.mark.timeout(FAST) -def test_contract_empty_message(llm) -> None: - with pytest.raises(BadRequestError, match="(?i)no text content|no .*content"): - llm.invoke([HumanMessage("")]) - - -@pytest.mark.timeout(FAST) -def test_contract_bad_base64(llm) -> None: - with pytest.raises(BadRequestError, match="(?i)base64|invalid"): - llm.invoke( - [ask("what is in this image?", image_part("data:image/jpeg;base64,@@@@not-valid-base64@@@@===="))] - ) - - -@pytest.mark.timeout(FAST) -def test_contract_video_file_id_rejected_client_side(llm) -> None: - with pytest.raises(InterfazeError, match="file_id"): - llm.invoke([HumanMessage(content=[{"type": "video", "file_id": "file-123"}])]) - - -# --- reliability ---------------------------------------------------------- - - -@pytest.mark.timeout(FAST) -def test_rel_health(llm) -> None: - assert text_of(llm.invoke("Hello")) - - -class Lines(BaseModel): - all_lines: list[str] - - -@pytest.mark.timeout(SLOW) -def test_rel_envelope(llm) -> None: - out = llm.with_structured_output(Lines, include_raw=True).invoke( - [ - ask( - "what's all the text on this receipt? give me every line in reading order.", - image_part(IMAGES["receipt"]), - ) - ] - ) - raw = out["raw"] - assert len(out["parsed"].all_lines) >= 3 - assert precontext_names(raw) - assert isinstance(raw.usage_metadata["total_tokens"], int) - assert raw.response_metadata["model_provider"] == "interfaze" - - -class MaybeText(BaseModel): - extracted_text: str | None - error: str | None - - -@pytest.mark.timeout(SLOW) -def test_rel_bad_image(llm) -> None: - try: - out = llm.with_structured_output(MaybeText).invoke( - [ask("what text is in this image?", image_part(IMAGES["missing"]))] - ) - except Exception: # noqa: BLE001 - throwing is the preferred outcome - return - if not out.error: - assert len(out.extracted_text or "") <= 50 diff --git a/python/tests/integration_tests/test_live_media.py b/python/tests/integration_tests/test_live_media.py deleted file mode 100644 index bf48f7c..0000000 --- a/python/tests/integration_tests/test_live_media.py +++ /dev/null @@ -1,105 +0,0 @@ -from __future__ import annotations - -import re -from typing import Any - -import pytest -from langchain_core.messages import HumanMessage -from pydantic import BaseModel - -from tests.integration_tests.conftest import ( - FILES, - SLOW, - chat, - file_part, - precontext_names, - requires_key, - text_of, - video_part, -) - -pytestmark = [requires_key, pytest.mark.timeout(SLOW)] - - -@pytest.fixture(scope="module") -def llm(): - return chat() - - -def ask(prompt: str, part: dict[str, Any]) -> HumanMessage: - return HumanMessage(content=[{"type": "text", "text": prompt}, part]) - - -class Transcript(BaseModel): - text: str - - -def test_stt_basic(llm) -> None: - out = llm.with_structured_output(Transcript, include_raw=True).invoke( - [ask("Transcribe the audio file", file_part(FILES["stt_short"], "stt_medical_short.mp4"))] - ) - assert "amoxicillin" in out["parsed"].text.lower() - assert re.search(r"stt|speech_to_text", " ".join(precontext_names(out["raw"]))) - - -class Chunk(BaseModel): - speaker_id: str - text: str - start_time: float - end_time: float - - -class Diarized(BaseModel): - full_text: str - chunks: list[Chunk] - number_of_speakers: int - - -def test_stt_diarization(llm) -> None: - out = llm.with_structured_output(Diarized, include_raw=True).invoke( - [ - ask( - "Transcribe and identify the speakers in the audio file", - file_part(FILES["stt_multi"], "stt_multispeaker.mp3"), - ) - ] - ) - parsed: Diarized = out["parsed"] - assert parsed.number_of_speakers >= 2 - assert len(parsed.chunks) > 5 - assert precontext_names(out["raw"]) - - -class Translated(BaseModel): - translated_text: str - original_language_code: str - translated_language_code: str - - -def test_stt_translate(llm) -> None: - out = llm.with_structured_output(Translated).invoke( - f"Transcribe the audio file and translate it to chinese {FILES['stt_short']}" - ) - assert out.translated_language_code.lower() in {"zh", "zh-cn", "zh-tw"} - - -class CallSummary(BaseModel): - text: str - summary: str - intent: str - - -def test_stt_summary(llm) -> None: - out = llm.with_structured_output(CallSummary).invoke( - f"Transcribe the audio file and summarize it {FILES['stt_call']}" - ) - assert out.text and out.summary and out.intent - - -def test_video_describe(llm) -> None: - res = llm.invoke( - [ask("Describe what happens in this video in one or two sentences.", video_part(FILES["video"]))] - ) - body = text_of(res).lower() - assert body - assert re.search(r"rabbit|bunny|forest|tree|grass|animal|burrow|meadow|field|nature", body) diff --git a/python/tests/integration_tests/test_live_streaming.py b/python/tests/integration_tests/test_live_streaming.py deleted file mode 100644 index 5d5f8b1..0000000 --- a/python/tests/integration_tests/test_live_streaming.py +++ /dev/null @@ -1,118 +0,0 @@ -from __future__ import annotations - -from typing import Any - -import pytest -from langchain_core.callbacks import BaseCallbackHandler -from langchain_core.messages import HumanMessage - -from tests.integration_tests.conftest import ( - FAST, - IMAGES, - SLOW, - chat, - fresh_chat, - image_part, - requires_key, -) - -pytestmark = requires_key - - -class Tap(BaseCallbackHandler): - def __init__(self) -> None: - self.tokens: list[str] = [] - - def on_llm_new_token(self, token: str, **kwargs: Any) -> None: - self.tokens.append(token) - - -@pytest.fixture(scope="module") -def llm(): - return chat() - - -@pytest.mark.timeout(FAST) -def test_stream_haiku(llm) -> None: - out = "".join(c.content for c in llm.stream("Write a haiku about coding") if isinstance(c.content, str)) - assert len(out) > 10 - assert "" not in out - assert "" not in out - - -@pytest.mark.timeout(FAST) -def test_stream_capital(llm) -> None: - out = "".join( - c.content - for c in llm.stream("What is the capital of France? Answer in one word.") - if isinstance(c.content, str) - ) - assert "paris" in out.lower() - - -@pytest.mark.timeout(FAST) -def test_stream_reasoning_hides_think_tags() -> None: - chunks = list(fresh_chat().stream("Write a haiku about streaming data", reasoning_effort="high")) - visible = "".join(c.content for c in chunks if isinstance(c.content, str)) - assert "" not in visible - assert "" not in visible - assert [c for c in chunks if c.additional_kwargs.get("reasoning")] - - -@pytest.mark.timeout(FAST) -def test_token_callbacks_never_see_side_channels() -> None: - tap = Tap() - list( - fresh_chat().stream( - "Write a haiku about streaming data", - reasoning_effort="high", - config={"callbacks": [tap]}, - ) - ) - assert "" not in "".join(tap.tokens) - - -@pytest.mark.timeout(FAST) -async def test_astream_events_are_filtered() -> None: - llm = fresh_chat() - body = "" - async for ev in llm.astream_events( - "Write a haiku about streaming data", version="v2", reasoning_effort="high" - ): - if ev["event"] == "on_chat_model_stream": - content = ev["data"]["chunk"].content - if isinstance(content, str): - body += content - assert body - assert "" not in body - - -@pytest.mark.timeout(FAST) -async def test_astream_matches_sync() -> None: - llm = chat() - out = "".join( - [c.content async for c in llm.astream("Write a haiku about coding") if isinstance(c.content, str)] - ) - assert len(out) > 10 - assert "" not in out - - -@pytest.mark.timeout(SLOW) -def test_streams_inline_precontext_when_enabled() -> None: - verbose = chat(show_additional_info=True, bypass_cache=True) - chunks = list( - verbose.stream( - [ - HumanMessage( - content=[ - {"type": "text", "text": "Where is this store located?"}, - image_part(IMAGES["receipt"]), - ] - ) - ] - ) - ) - visible = "".join(c.content for c in chunks if isinstance(c.content, str)) - assert "" not in visible - precontext = [e for c in chunks for e in (c.additional_kwargs.get("precontext") or [])] - assert precontext diff --git a/python/tests/integration_tests/test_live_text.py b/python/tests/integration_tests/test_live_text.py deleted file mode 100644 index 203e231..0000000 --- a/python/tests/integration_tests/test_live_text.py +++ /dev/null @@ -1,136 +0,0 @@ -from __future__ import annotations - -import pytest -from langchain_core.messages import HumanMessage, SystemMessage -from langchain_core.output_parsers import StrOutputParser -from langchain_core.prompts import ChatPromptTemplate -from pydantic import BaseModel - -from tests.integration_tests.conftest import FAST, SLOW, chat, fresh_chat, requires_key, text_of - -pytestmark = requires_key - - -@pytest.fixture(scope="module") -def llm(): - return chat() - - -# --- text ----------------------------------------------------------------- - - -@pytest.mark.timeout(FAST) -def test_text_gen_story(llm) -> None: - assert len(text_of(llm.invoke("Write a short story about a robot learning to paint"))) > 50 - - -@pytest.mark.timeout(FAST) -def test_text_gen_story_with_system(llm) -> None: - res = llm.invoke( - [ - SystemMessage("You are a helpful assistant."), - HumanMessage("Write a short story about a robot learning to paint"), - ] - ) - assert len(text_of(res)) > 50 - - -@pytest.mark.timeout(FAST) -def test_text_capital(llm) -> None: - assert "paris" in text_of(llm.invoke("What is the capital of France? Answer in one word.")).lower() - - -@pytest.mark.timeout(FAST) -def test_interfaze_envelope(llm) -> None: - res = llm.invoke("Hello") - assert res.response_metadata["model_provider"] == "interfaze" - assert isinstance(res.response_metadata["vcache"], bool) - assert res.usage_metadata["total_tokens"] > 0 - - -# --- structured output ---------------------------------------------------- - - -class Weather(BaseModel): - city: str - temperature_celsius: float - condition: str - - -class Founder(BaseModel): - name: str - - -class CapitalPop(BaseModel): - city: str - population_millions: float - - -class Capital(BaseModel): - capital: str - - -@pytest.mark.timeout(FAST) -def test_structured_weather(llm) -> None: - out = llm.with_structured_output(Weather).invoke("What is the current weather in Tokyo?") - assert out.city - assert isinstance(out.temperature_celsius, float) - assert out.condition - - -@pytest.mark.timeout(FAST) -def test_structured_founder(llm) -> None: - assert llm.with_structured_output(Founder).invoke("Who is the founder of JigsawStack?").name - - -@pytest.mark.timeout(FAST) -def test_structured_capital_pop(llm) -> None: - out = llm.with_structured_output(CapitalPop).invoke( - "What is the capital of France and its approximate metro population in millions?" - ) - assert "paris" in out.city.lower() - assert isinstance(out.population_millions, float) - - -@pytest.mark.timeout(FAST) -def test_structured_json_no_fences(llm) -> None: - out = llm.with_structured_output(Capital, include_raw=True).invoke( - "Return ONLY a JSON object (no markdown fences) with key 'capital' set to the capital of France." - ) - assert "```" not in text_of(out["raw"]) - assert "paris" in out["parsed"].capital.lower() - - -# --- reasoning ------------------------------------------------------------ - - -@pytest.mark.timeout(FAST) -def test_reasoning_math() -> None: - # The semantic cache replays a stored answer without its block. - res = fresh_chat().invoke("What is 25 * 47?", reasoning_effort="high") - assert "1175" in text_of(res) - assert res.response_metadata.get("reasoning") - assert "" not in text_of(res) - - -# --- runnable surface ----------------------------------------------------- - - -@pytest.mark.timeout(FAST) -def test_lcel_chain(llm) -> None: - chain = ChatPromptTemplate.from_template("Translate to {lang}: {text}") | llm | StrOutputParser() - assert chain.invoke({"lang": "French", "text": "Hello"}) - - -@pytest.mark.timeout(SLOW) -def test_batch(llm) -> None: - out = llm.batch(["Summarize the colour blue in one sentence.", "Name one planet.", "What is 2+2?"]) - assert len(out) == 3 - assert all(text_of(m) for m in out) - - -@pytest.mark.timeout(FAST) -async def test_ainvoke(llm) -> None: - res = await llm.ainvoke("What is the capital of France? Answer in one word.") - assert "paris" in text_of(res).lower() - assert res.response_metadata["model_provider"] == "interfaze" diff --git a/python/tests/integration_tests/test_live_tools.py b/python/tests/integration_tests/test_live_tools.py deleted file mode 100644 index d223fe1..0000000 --- a/python/tests/integration_tests/test_live_tools.py +++ /dev/null @@ -1,306 +0,0 @@ -from __future__ import annotations - -import json -import re - -import pytest -from langchain_core.messages import AIMessage, HumanMessage, ToolMessage -from pydantic import BaseModel - -from tests.integration_tests.conftest import SLOW, chat, precontext_names, requires_key, text_of - -pytestmark = [requires_key, pytest.mark.timeout(SLOW)] - - -@pytest.fixture(scope="module") -def llm(): - return chat() - - -LONG_TEXT = ( - "Interfaze is a new kind of AI platform built specifically for deterministic, developer-grade " - "tasks. Unlike general-purpose large language models that excel at open-ended conversation but " - "struggle with consistency, Interfaze focuses on the operations that real software systems " - "depend on: extracting fields from documents, scraping structured data from arbitrary websites, " - "transcribing audio with speaker labels, translating content across hundreds of languages while " - "preserving meaning, detecting objects in images and GUI screenshots, forecasting time series " - "without per-customer model training, and executing code in a sandboxed environment. Every " - "capability is exposed through an OpenAI-compatible chat completions API so existing tooling " - "works without modification." -) - -SERIES = [ - {"date": "2024-01-01", "value": 412}, - {"date": "2024-01-08", "value": 387}, - {"date": "2024-01-15", "value": 524}, - {"date": "2024-01-22", "value": 461}, - {"date": "2024-01-29", "value": 398}, - {"date": "2024-02-05", "value": 542}, - {"date": "2024-02-12", "value": 475}, - {"date": "2024-02-19", "value": 401}, - {"date": "2024-02-26", "value": 558}, - {"date": "2024-03-04", "value": 489}, - {"date": "2024-03-11", "value": 419}, - {"date": "2024-03-18", "value": 571}, -] - - -# --- translation ---------------------------------------------------------- - - -class StructuredTranslation(BaseModel): - translated_text: str - translated_text_iso_code: str - original_text_iso_code: str - - -def test_translate_structured(llm) -> None: - out = llm.with_structured_output(StructuredTranslation, include_raw=True).invoke( - "Translate the following text into French: 'The UK drinks about 100-160 million cups of tea " - "every day, and 98% of tea drinkers add milk to their tea.'" - ) - parsed: StructuredTranslation = out["parsed"] - assert "fr" in parsed.translated_text_iso_code.lower() - assert "en" in parsed.original_text_iso_code.lower() - assert "translate" in precontext_names(out["raw"]) - - -class TargetedTranslation(BaseModel): - translated_text: str - target_language: str - - -def test_translate_es(llm) -> None: - out = llm.with_structured_output(TargetedTranslation).invoke( - "Hello, how are you today? I would like to order a coffee. — in Spanish please" - ) - assert re.search(r"hola|cómo|está|café", out.translated_text.lower()) - - -class SimpleTranslation(BaseModel): - translated_text: str - - -def test_translate_long_fr(llm) -> None: - out = llm.with_structured_output(SimpleTranslation).invoke( - f'Can you give me this in French? "{LONG_TEXT}"' - ) - assert len(out.translated_text) >= len(LONG_TEXT) * 0.5 - assert any( - w in out.translated_text.lower() - for w in (" le ", " la ", " les ", " des ", " une ", " est ", " pour ", " avec ") - ) - - -def test_translate_ja(llm) -> None: - out = llm.with_structured_output(SimpleTranslation).invoke( - "how do you say 'Thank you for your help' in Japanese?" - ) - assert re.search(r"[぀-ヿ一-鿿]", out.translated_text) - - -def test_translate_markup(llm) -> None: - out = llm.with_structured_output(SimpleTranslation).invoke( - 'Translate this to French, preserving all HTML tags exactly: Click here ' - "to continue." - ) - for fragment in ('', "", "", ""): - assert fragment in out.translated_text - - -# --- web search ----------------------------------------------------------- - - -def test_web_search_basic(llm) -> None: - assert text_of(llm.invoke("Latest news on Nvidia")) - - -class TeslaFacts(BaseModel): - founders: list[str] - year_founded: int - sources: list[str] - - -def test_web_search_factual(llm) -> None: - out = llm.with_structured_output(TeslaFacts).invoke("who founded Tesla and when?") - assert re.search(r"musk|eberhard|tarpenning", " ".join(out.founders).lower()) - assert out.year_founded == 2003 - - -class Apollo(BaseModel): - summary: str - year: int - month: str - sources: list[str] - - -def test_web_search_history(llm) -> None: - out = llm.with_structured_output(Apollo).invoke("when did Apollo 11 land on the moon? give sources.") - assert out.year == 1969 - assert "jul" in out.month.lower() - assert len(out.summary) > 20 - assert out.sources - - -class NvidiaNews(BaseModel): - summary: str - current_stock_price: float - links: list[str] - - -def test_web_search_structured(llm) -> None: - out = llm.with_structured_output(NvidiaNews).invoke("Latest news on Nvidia") - assert out.summary - assert out.links - - -class Person(BaseModel): - summary: str - company: str | None - emails: list[str] | None - location: str | None - - -def test_web_search_person(llm) -> None: - out = llm.with_structured_output(Person, include_raw=True).invoke( - "Who is Yoeven D Khemlani, his company, his email and where is he based now?" - ) - assert out["parsed"].summary - assert precontext_names(out["raw"]) - - -# --- scraping ------------------------------------------------------------- - - -class Listing(BaseModel): - price: float - listing_name: str - seller_name: str - possible_delivery_time: str - - -class Listings(BaseModel): - products: list[Listing] - - -def test_scrape_ecommerce(llm) -> None: - out = llm.with_structured_output(Listings, include_raw=True).invoke( - "get all prices and listing of products for nintendo switch from " - "https://www.amazon.com/s?k=nintendo+switch+console" - ) - parsed: Listings = out["parsed"] - assert parsed.products - assert parsed.products[0].listing_name - assert re.search(r"web_extract|search|scraper", " ".join(precontext_names(out["raw"]))) - - -class Post(BaseModel): - title: str - points: int - - -class Posts(BaseModel): - posts: list[Post] - - -def test_scrape_hn(llm) -> None: - out = llm.with_structured_output(Posts).invoke( - "Extract post titles and points from https://news.ycombinator.com" - ) - assert out.posts - - -# --- forecast ------------------------------------------------------------- - - -class Prediction(BaseModel): - value: float - - -class Forecast(BaseModel): - predictions: list[Prediction] - - -def test_forecast_series(llm) -> None: - out = llm.with_structured_output(Forecast, include_raw=True).invoke( - f"Here's our weekly sales for the past 12 weeks: {json.dumps(SERIES)}. " - "What can we expect over the next month?" - ) - parsed: Forecast = out["parsed"] - assert len(parsed.predictions) >= 3 - for p in parsed.predictions: - assert 0 <= p.value <= 10_000 - assert "forecast" in precontext_names(out["raw"]) - - -# --- code sandbox --------------------------------------------------------- - - -class Factorial(BaseModel): - fractional: float - - -def test_sandbox_factorial(llm) -> None: - out = llm.with_structured_output(Factorial, include_raw=True).invoke("What is the factorial of 5?") - assert out["parsed"].fractional == 120 - # The router only reaches for the sandbox when it doesn't already know the answer. - names = precontext_names(out["raw"]) - if names: - assert re.search(r"code_execute|code_generation", " ".join(names)) - - -class Answer(BaseModel): - answer: int - - -def test_sandbox_count_r(llm) -> None: - assert llm.with_structured_output(Answer).invoke("How many r's are there in strawberry?").answer == 3 - - -class Script(BaseModel): - code: str - sample_input: str - sample_output: str - - -def test_sandbox_codegen(llm) -> None: - out = llm.with_structured_output(Script).invoke( - "write a python script for getting cpu type using subprocess module and verify your output" - ) - assert "subprocess" in out.code - - -# --- function calling ----------------------------------------------------- - - -def test_fc_horoscope(llm) -> None: - tools = [ - { - "type": "function", - "function": { - "name": "get_horoscope", - "description": "Get today's horoscope for an astrological sign.", - "parameters": { - "type": "object", - "properties": {"sign": {"type": "string"}}, - "required": ["sign"], - }, - }, - } - ] - bound = llm.bind_tools(tools) - first: AIMessage = bound.invoke([HumanMessage("Get my horoscope for Taurus")]) - assert first.tool_calls - assert first.tool_calls[0]["name"] == "get_horoscope" - - second = bound.invoke( - [ - HumanMessage("Get my horoscope for Taurus"), - first, - ToolMessage( - tool_call_id=first.tool_calls[0]["id"], - content="Today's horoscope for Taurus: You will have a great day!", - ), - ] - ) - assert text_of(second) diff --git a/python/tests/integration_tests/test_live_vision.py b/python/tests/integration_tests/test_live_vision.py deleted file mode 100644 index 7a1bb04..0000000 --- a/python/tests/integration_tests/test_live_vision.py +++ /dev/null @@ -1,375 +0,0 @@ -from __future__ import annotations - -from typing import Any, Literal - -import pytest -from langchain_core.messages import HumanMessage -from pydantic import BaseModel - -from tests.integration_tests.conftest import ( - FILES, - IMAGES, - SLOW, - chat, - file_part, - image_part, - precontext_names, - receipt_b64, - requires_key, -) - -pytestmark = [requires_key, pytest.mark.timeout(SLOW)] - - -@pytest.fixture(scope="module") -def llm(): - return chat() - - -def ask(prompt: str, part: dict[str, Any]) -> HumanMessage: - return HumanMessage(content=[{"type": "text", "text": prompt}, part]) - - -class Box(BaseModel): - top_left_x: float - top_left_y: float - bottom_right_x: float - bottom_right_y: float - - -# --- ocr ------------------------------------------------------------------ - - -class IdDocument(BaseModel): - full_first_name: str - full_last_name: str - full_address: str | None - email: str | None - id_type: str - - -def test_ocr_id_document(llm) -> None: - out = llm.with_structured_output(IdDocument, include_raw=True).invoke( - [ask("Extract information from the image based on the schema.", image_part(IMAGES["id_medium"]))] - ) - parsed: IdDocument = out["parsed"] - assert "iv" in parsed.full_first_name.lower() - assert parsed.full_last_name.lower().replace("ñ", "n").find("munoz") >= 0 - assert parsed.id_type - assert "ocr" in precontext_names(out["raw"]) - - -class DriverLicence(BaseModel): - first_name: str - last_name: str - dob: str - driver_licence_number: str - - -def test_ocr_id_jpg(llm) -> None: - out = llm.with_structured_output(DriverLicence, include_raw=True).invoke( - [ask("Extract the details from this ID", image_part(IMAGES["id_jpg"]))] - ) - parsed: DriverLicence = out["parsed"] - assert parsed.first_name and parsed.dob and parsed.driver_licence_number - assert "ocr" in precontext_names(out["raw"]) - - -class LineItem(BaseModel): - name: str - price: str - - -class ReceiptFields(BaseModel): - items: list[LineItem] - highlighted_items: list[LineItem] - total_cost: str - tax: str - - -def test_ocr_receipt_fields(llm) -> None: - out = llm.with_structured_output(ReceiptFields, include_raw=True).invoke( - [ask("Extract text from the image.", image_part(IMAGES["receipt_items"]))] - ) - parsed: ReceiptFields = out["parsed"] - assert parsed.items - assert "144.02" in parsed.total_cost - assert "4.58" in parsed.tax - assert "gale" in " ".join(i.name for i in parsed.highlighted_items).lower() - assert "ocr" in precontext_names(out["raw"]) - - -class QueryResult(BaseModel): - text: str - confidence: float - - -class StoreLocation(BaseModel): - query_results: list[QueryResult] - text: str - confidence: float - - -def test_ocr_store_location(llm) -> None: - out = llm.with_structured_output(StoreLocation).invoke( - [ask("Where is this store located?", image_part(IMAGES["receipt"]))] - ) - haystack = f"{' '.join(r.text for r in out.query_results)} {out.text}".lower() - assert "greenwood" in haystack - - -class Word(Box): - text: str - - -class WordBoxes(BaseModel): - text: str - words: list[Word] - - -def test_ocr_word_bboxes(llm) -> None: - out = llm.with_structured_output(WordBoxes, include_raw=True).invoke( - [ask("extract every word and its position from this receipt", image_part(IMAGES["receipt"]))] - ) - parsed: WordBoxes = out["parsed"] - assert len(parsed.words) >= 10 - for w in parsed.words: - assert w.top_left_x >= 0 - assert w.top_left_y >= 0 - assert w.bottom_right_x >= w.top_left_x - 2 - assert w.bottom_right_y >= w.top_left_y - 2 - assert "ocr" in precontext_names(out["raw"]) - - -class Paper(BaseModel): - title: str - authors: list[str] - - -def test_ocr_pdf_title_authors(llm) -> None: - out = llm.with_structured_output(Paper, include_raw=True).invoke( - [ - ask( - "Extract the title and author names from the first page.", - file_part(FILES["attention_pdf"], "attention.pdf"), - ) - ] - ) - parsed: Paper = out["parsed"] - assert "attention" in parsed.title.lower() - assert "vaswani" in " ".join(parsed.authors).lower() - assert "ocr" in precontext_names(out["raw"]) - - -class Translation(BaseModel): - text_in_original_language: str - text_in_telugu: str - width_of_image: float - height_of_image: float - - -class Multilang(BaseModel): - translations: list[Translation] - - -def test_ocr_multilang(llm) -> None: - out = llm.with_structured_output(Multilang).invoke( - [ask("Extract information from the image based on the schema.", image_part(IMAGES["multilang"]))] - ) - assert out.translations - - -class LayoutElement(Box): - type: Literal["heading", "paragraph", "formula", "figure", "table", "caption", "list"] - content: str - - -class Page(BaseModel): - page_number: int - elements: list[LayoutElement] - - -class Layout(BaseModel): - pages: list[Page] - - -def test_ocr_document_layout(llm) -> None: - out = llm.with_structured_output(Layout, include_raw=True).invoke( - [ - ask( - "extract the layout elements (headings, paragraphs, figures, tables) with bounding " - "boxes from the first page", - file_part(FILES["attention_pdf"], "attention.pdf"), - ) - ] - ) - parsed: Layout = out["parsed"] - assert parsed.pages - elements = [e for p in parsed.pages for e in p.elements] - assert elements - assert any(e.type in {"heading", "paragraph"} for e in elements) - assert "ocr" in precontext_names(out["raw"]) - - -# --- document extraction / markdown --------------------------------------- - - -def inline_receipt() -> dict[str, Any]: - return image_part(f"data:image/jpeg;base64,{receipt_b64()}") - - -class BillItem(BaseModel): - description: str - price: float | None - - -class Bill(BaseModel): - vendor_name: str - total_amount: float - bill_date: str - line_items: list[BillItem] - - -def test_doc_invoice_exact(llm) -> None: - out = llm.with_structured_output(Bill).invoke( - [ - ask( - "Extract the bill data from this receipt: vendor_name, total_amount (number), " - "bill_date (YYYY-MM-DD), and line_items[{description, price}].", - inline_receipt(), - ) - ] - ) - assert abs(out.total_amount - 15.15) <= 0.01 - assert out.bill_date == "2018-05-06" - assert "marco polo" in out.vendor_name.lower() - assert out.line_items - - -class Markdown(BaseModel): - markdown: str - - -def test_md_image_to_md(llm) -> None: - out = llm.with_structured_output(Markdown).invoke( - [ask("Convert this receipt image to markdown.", inline_receipt())] - ) - assert len(out.markdown) >= 80 - assert "marco polo" in out.markdown.lower() - assert "mocha" in out.markdown.lower() - assert "15.15" in out.markdown - - -def test_md_pdf_to_md(llm) -> None: - import re - - out = llm.with_structured_output(Markdown, include_raw=True).invoke( - [ - ask( - "Convert the first page of this document to markdown.", - file_part(FILES["attention_pdf"], "attention.pdf"), - ) - ] - ) - # Heading style is stable; bold emphasis is not, so it is not asserted. - md: str = out["parsed"].markdown - assert re.search(r"#{1,3}\s*attention is all you need", md, re.IGNORECASE) - assert len(md) > 200 - assert "ocr" in precontext_names(out["raw"]) - - -# --- object / gui detection ----------------------------------------------- - - -class NamedObject(BaseModel): - name: str - - -class Objects(BaseModel): - objects: list[NamedObject] - - -def test_object_detection_absent(llm) -> None: - out = llm.with_structured_output(Objects).invoke( - [ask("detect elephants in this image", image_part(IMAGES["katana"]))] - ) - assert out.objects == [] - - -class BoxedObject(Box): - name: str - - -class BoxedObjects(BaseModel): - objects: list[BoxedObject] - - -def test_object_detection_bbox(llm) -> None: - out = llm.with_structured_output(BoxedObjects, include_raw=True).invoke( - [ask("detect the position of the katana in this image", image_part(IMAGES["katana"]))] - ) - parsed: BoxedObjects = out["parsed"] - assert parsed.objects - box = parsed.objects[0] - assert "katana" in box.name.lower() - assert abs(box.top_left_x - 1078) <= 15 - assert abs(box.top_left_y - 474) <= 15 - assert abs(box.bottom_right_x - 1188) <= 15 - assert abs(box.bottom_right_y - 1026) <= 15 - assert "object_detection" in precontext_names(out["raw"]) - - -def test_object_detection_multi(llm) -> None: - out = llm.with_structured_output(BoxedObjects, include_raw=True).invoke( - [ask("detect all objects with bounding boxes", image_part(IMAGES["bus"]))] - ) - # Recall on this image swings from 1 to 8 objects run to run, and the labels vary - # ("bus" vs a bare "object") — reproduced identically through the core interfaze SDK. - # What the integration owns is the round-trip: well-formed boxes and the precontext. - parsed: BoxedObjects = out["parsed"] - assert parsed.objects - for o in parsed.objects: - assert o.bottom_right_x >= o.top_left_x - assert o.bottom_right_y >= o.top_left_y - assert "object_detection" in precontext_names(out["raw"]) - - -class GuiElement(Box): - name: str - - -class Gui(BaseModel): - gui_elements: list[GuiElement] - - -def test_gui_detection_form(llm) -> None: - out = llm.with_structured_output(Gui, include_raw=True).invoke( - [ask("find all the text fields and the clear form button", image_part(IMAGES["gui_form"]))] - ) - # Element count swings between 1 and 12 across runs (reproduced with the core - # interfaze SDK), so assert the envelope rather than a per-field inventory. - parsed: Gui = out["parsed"] - assert len(parsed.gui_elements) >= 1 - for e in parsed.gui_elements: - assert e.bottom_right_x <= 3600 - assert e.bottom_right_y <= 2338 - assert "gui_detection" in precontext_names(out["raw"]) - - -class BoxedText(Box): - text: str - - -class ObjectsAndText(BaseModel): - objects: list[BoxedObject] - texts: list[BoxedText] - - -def test_object_detection_with_text(llm) -> None: - out = llm.with_structured_output(ObjectsAndText, include_raw=True).invoke( - [ask("Get the position of the crane in the image and any text", image_part(IMAGES["construction"]))] - ) - # The crane is not always detected; what must hold is that detection + OCR ran and - # the schema came back well-formed. - assert isinstance(out["parsed"].objects, list) - assert precontext_names(out["raw"]) diff --git a/python/tests/unit_tests/conftest.py b/python/tests/unit_tests/conftest.py new file mode 100644 index 0000000..eec5565 --- /dev/null +++ b/python/tests/unit_tests/conftest.py @@ -0,0 +1,102 @@ +from __future__ import annotations + +import json +from typing import Any + +import httpx +import respx + +CHAT_URL = "https://api.interfaze.ai/v1/chat/completions" +VIDEO_URL = "https://download.samplelib.com/mp4/sample-5s.mp4" + +_USAGE = {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8} + + +def completion(content: Any = "Hi!", *, finish_reason: str = "stop", **extra: Any) -> dict[str, Any]: + body: dict[str, Any] = { + "id": "req-test", + "object": "chat.completion", + "created": 1_700_000_000, + "model": "interfaze-beta", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": content, "refusal": None}, + "finish_reason": finish_reason, + "logprobs": None, + } + ], + "usage": _USAGE, + "vcache": False, + } + body.update(extra) + return body + + +def chunk(delta: dict[str, Any], finish_reason: str | None = None) -> dict[str, Any]: + return { + "id": "req-test", + "object": "chat.completion.chunk", + "created": 1_700_000_000, + "model": "interfaze-beta", + "choices": [{"index": 0, "delta": delta, "finish_reason": finish_reason}], + } + + +def _sse_bytes(chunks: list[dict[str, Any]]) -> bytes: + return ("".join(f"data: {json.dumps(c)}\n\n" for c in chunks) + "data: [DONE]\n\n").encode() + + +def mock_json(body: dict[str, Any]) -> respx.Route: + return respx.post(CHAT_URL).mock(return_value=httpx.Response(200, json=body)) + + +def mock_sse(chunks: list[dict[str, Any]]) -> respx.Route: + return respx.post(CHAT_URL).mock( + return_value=httpx.Response( + 200, headers={"content-type": "text/event-stream"}, content=_sse_bytes(chunks) + ) + ) + + +def last_body(route: respx.Route) -> dict[str, Any]: + return json.loads(route.calls.last.request.content) + + +BASIC = completion("Hi!") +CUSTOM_FIELDS = completion( + "Hello there", + precontext=[{"name": "ocr", "result": {"extracted_text": "x"}}], + reasoning="because reasons", + vcache=True, +) +INLINE_TAGS = completion( + "Rayleigh scattering." + '[{"name": "ocr", "result": {"x": 1}}]' + "The sky is blue." +) +STREAM_CHUNKS: list[dict[str, Any]] = [ + chunk({"content": '[{"name":"ocr","result":{"extracted_text":"x"}}]'}), + chunk({"content": "Total "}), + chunk({"content": "is $12.34"}), + chunk({}, finish_reason="stop"), +] +THINK_SPLIT: list[dict[str, Any]] = [ + chunk({"content": "Rayleigh scat"}), + chunk({"content": "tering.The sky "}), + chunk({"content": "is blue."}), + chunk({}, finish_reason="stop"), +] +PLAIN_STREAM: list[dict[str, Any]] = [ + chunk({"content": "Hello "}), + chunk({"content": "world"}), + chunk({}, finish_reason="stop"), +] +# The same side field on consecutive chunks: `reasoning` would string-concatenate and +# `precontext` would append on merge; `vcache` merges cleanly. +REPEATED_SIDE: list[dict[str, Any]] = [ + chunk({"content": "a"}) | {"reasoning": "why", "precontext": [{"name": "ocr"}], "vcache": True}, + chunk({"content": "b"}) | {"reasoning": "why", "precontext": [{"name": "ocr"}], "vcache": True}, + chunk({}, finish_reason="stop"), +] diff --git a/python/tests/unit_tests/test_chat.py b/python/tests/unit_tests/test_chat.py new file mode 100644 index 0000000..2b0d761 --- /dev/null +++ b/python/tests/unit_tests/test_chat.py @@ -0,0 +1,57 @@ +from __future__ import annotations + +import asyncio +from typing import Any + +import respx +from langchain_core.messages import HumanMessage + +from langchain_interfaze import ChatInterfaze +from tests.unit_tests.conftest import BASIC, CUSTOM_FIELDS, INLINE_TAGS, mock_json + + +@respx.mock +def test_custom_response_fields_surfaced() -> None: + mock_json(CUSTOM_FIELDS) + model = ChatInterfaze(api_key="t") + result = model.invoke([HumanMessage("hi")]) + assert result.response_metadata["precontext"] == [{"name": "ocr", "result": {"extracted_text": "x"}}] + assert result.response_metadata["reasoning"] == "because reasons" + assert result.response_metadata["vcache"] is True + assert result.additional_kwargs["precontext"] == [{"name": "ocr", "result": {"extracted_text": "x"}}] + assert result.additional_kwargs["reasoning"] == "because reasons" + assert result.additional_kwargs["vcache"] is True + + +@respx.mock +def test_response_without_precontext_or_reasoning_unaffected() -> None: + mock_json(BASIC) + model = ChatInterfaze(api_key="t") + result = model.invoke([HumanMessage("hi")]) + assert "precontext" not in result.response_metadata + assert "reasoning" not in result.response_metadata + assert result.response_metadata["vcache"] is False + assert result.content == "Hi!" + + +@respx.mock +def test_non_streaming_strips_inline_tags() -> None: + mock_json(INLINE_TAGS) + model = ChatInterfaze(api_key="t") + result = model.invoke([HumanMessage("why is the sky blue?")]) + assert result.content == "The sky is blue." + assert result.response_metadata["reasoning"] == "Rayleigh scattering." + assert result.response_metadata["precontext"] == [{"name": "ocr", "result": {"x": 1}}] + + +@respx.mock +def test_async_invoke_surfaces_side_fields() -> None: + mock_json(CUSTOM_FIELDS) + model = ChatInterfaze(api_key="t") + + async def go() -> Any: + return await model.ainvoke([HumanMessage("hi")]) + + result = asyncio.run(go()) + assert result.response_metadata["precontext"][0]["name"] == "ocr" + assert result.response_metadata["vcache"] is True diff --git a/python/tests/unit_tests/test_chat_models.py b/python/tests/unit_tests/test_chat_models.py deleted file mode 100644 index db1c27c..0000000 --- a/python/tests/unit_tests/test_chat_models.py +++ /dev/null @@ -1,372 +0,0 @@ -from __future__ import annotations - -import asyncio -import json -from typing import Any - -import httpx -import pytest -import respx -from interfaze import INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError -from langchain_core.callbacks import BaseCallbackHandler, CallbackManager -from langchain_core.messages import HumanMessage - -from langchain_interfaze import ChatInterfaze - -CHAT_URL = "https://api.interfaze.ai/v1/chat/completions" -VIDEO_URL = "https://download.samplelib.com/mp4/sample-5s.mp4" - -_USAGE = {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8} - - -def completion(content: Any = "Hi!", *, finish_reason: str = "stop", **extra: Any) -> dict[str, Any]: - body: dict[str, Any] = { - "id": "req-test", - "object": "chat.completion", - "created": 1_700_000_000, - "model": "interfaze-beta", - "choices": [ - { - "index": 0, - "message": {"role": "assistant", "content": content, "refusal": None}, - "finish_reason": finish_reason, - "logprobs": None, - } - ], - "usage": _USAGE, - "vcache": False, - } - body.update(extra) - return body - - -def _chunk(delta: dict[str, Any], finish_reason: str | None = None) -> dict[str, Any]: - return { - "id": "req-test", - "object": "chat.completion.chunk", - "created": 1_700_000_000, - "model": "interfaze-beta", - "choices": [{"index": 0, "delta": delta, "finish_reason": finish_reason}], - } - - -def _sse_bytes(chunks: list[dict[str, Any]]) -> bytes: - return ("".join(f"data: {json.dumps(c)}\n\n" for c in chunks) + "data: [DONE]\n\n").encode() - - -def mock_json(body: dict[str, Any]) -> respx.Route: - return respx.post(CHAT_URL).mock(return_value=httpx.Response(200, json=body)) - - -def mock_sse(chunks: list[dict[str, Any]]) -> respx.Route: - return respx.post(CHAT_URL).mock( - return_value=httpx.Response( - 200, headers={"content-type": "text/event-stream"}, content=_sse_bytes(chunks) - ) - ) - - -def last_body(route: respx.Route) -> dict[str, Any]: - return json.loads(route.calls.last.request.content) - - -BASIC = completion("Hi!") -CUSTOM_FIELDS = completion( - "Hello there", - precontext=[{"name": "ocr", "result": {"extracted_text": "x"}}], - reasoning="because reasons", - vcache=True, -) -STREAM_CHUNKS: list[dict[str, Any]] = [ - _chunk({"content": '[{"name":"ocr","result":{"extracted_text":"x"}}]'}), - _chunk({"content": "Total "}), - _chunk({"content": "is $12.34"}), - _chunk({}, finish_reason="stop"), -] -THINK_SPLIT: list[dict[str, Any]] = [ - _chunk({"content": "Rayleigh scat"}), - _chunk({"content": "tering.The sky "}), - _chunk({"content": "is blue."}), - _chunk({}, finish_reason="stop"), -] - - -# defaults -def test_defaults_point_at_interfaze() -> None: - model = ChatInterfaze(api_key="t") - assert model.openai_api_base == INTERFAZE_BASE_URL - assert model.model_name == INTERFAZE_MODEL - - -def test_defaults_overridable() -> None: - model = ChatInterfaze(api_key="t", base_url="https://example.com/v1", model="other-model") - assert model.openai_api_base == "https://example.com/v1" - assert model.model_name == "other-model" - - -def test_missing_api_key_raises(monkeypatch: pytest.MonkeyPatch) -> None: - monkeypatch.delenv("INTERFAZE_API_KEY", raising=False) - with pytest.raises(InterfazeError, match="Missing API key"): - ChatInterfaze() - - -def test_api_key_from_env(monkeypatch: pytest.MonkeyPatch) -> None: - monkeypatch.setenv("INTERFAZE_API_KEY", "env-key") - model = ChatInterfaze() - assert model.openai_api_key is not None - - -# custom response fields -@respx.mock -def test_custom_response_fields_surfaced() -> None: - mock_json(CUSTOM_FIELDS) - model = ChatInterfaze(api_key="t") - result = model.invoke([HumanMessage("hi")]) - assert result.response_metadata["precontext"] == [{"name": "ocr", "result": {"extracted_text": "x"}}] - assert result.response_metadata["reasoning"] == "because reasons" - assert result.response_metadata["vcache"] is True - assert result.additional_kwargs["precontext"] == [{"name": "ocr", "result": {"extracted_text": "x"}}] - assert result.additional_kwargs["reasoning"] == "because reasons" - assert result.additional_kwargs["vcache"] is True - - -@respx.mock -def test_response_without_precontext_or_reasoning_unaffected() -> None: - mock_json(BASIC) - model = ChatInterfaze(api_key="t") - result = model.invoke([HumanMessage("hi")]) - assert "precontext" not in result.response_metadata - assert "reasoning" not in result.response_metadata - assert result.response_metadata["vcache"] is False - assert result.content == "Hi!" - - -# provider identity -def test_provider_identity() -> None: - model = ChatInterfaze(api_key="t") - assert model._llm_type == "interfaze-chat" - assert model._get_ls_params()["ls_provider"] == "interfaze" - assert model.lc_secrets == {"openai_api_key": "INTERFAZE_API_KEY"} - assert model.get_lc_namespace() == ["langchain_interfaze", "chat_models"] - assert model.metadata is not None - assert "langchain-interfaze" in model.metadata["lc_versions"] - - -@respx.mock -def test_model_provider_stamped_on_response() -> None: - mock_json(BASIC) - model = ChatInterfaze(api_key="t") - assert model.invoke([HumanMessage("hi")]).response_metadata["model_provider"] == "interfaze" - - -def test_defaults_to_long_timeout_but_respects_override() -> None: - assert ChatInterfaze(api_key="t").request_timeout == 900.0 - assert ChatInterfaze(api_key="t", timeout=30).request_timeout == 30 - - -def test_never_routes_to_the_responses_api() -> None: - # `reasoning=` would otherwise flip ChatOpenAI over to /v1/responses. - assert ChatInterfaze(api_key="t", reasoning={"summary": "auto"}).use_responses_api is False - - -# control-plane headers -def test_control_headers() -> None: - model = ChatInterfaze( - api_key="t", - show_additional_info=True, - bypass_moa=True, - bypass_cache=True, - admin_key="adm", - default_headers={"x-custom": "1"}, - ) - assert model.default_headers == { - "x-custom": "1", - "x-show-additional-info": "true", - "x-interfaze-bypass-moa": "true", - "x-interfaze-bypass-cache": "true", - "x-admin-key": "adm", - } - - -def test_no_control_headers_by_default() -> None: - assert ChatInterfaze(api_key="t").default_headers is None - - -@respx.mock -def test_streaming_asks_for_usage() -> None: - # langchain-openai only auto-enables this for OpenAI's own base URL. - route = mock_sse([_chunk({"content": "hi"}), _chunk({}, finish_reason="stop")]) - list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) - assert last_body(route)["stream_options"] == {"include_usage": True} - - -# video content blocks -@respx.mock -def test_video_block_converted_to_file_part() -> None: - route = mock_json(BASIC) - model = ChatInterfaze(api_key="t") - message = HumanMessage( - content=[ - {"type": "text", "text": "what happens in this clip?"}, - {"type": "video", "url": VIDEO_URL}, - ] - ) - model.invoke([message]) # must not raise - body = last_body(route) - content = body["messages"][-1]["content"] - assert {"type": "file", "file": {"file_data": VIDEO_URL, "format": "video/mp4"}} in content - - -@respx.mock -def test_video_block_url_without_known_extension_omits_format() -> None: - route = mock_json(BASIC) - model = ChatInterfaze(api_key="t") - model.invoke([HumanMessage(content=[{"type": "video", "url": "https://example.com/clip"}])]) - assert last_body(route)["messages"][-1]["content"][0]["file"] == {"file_data": "https://example.com/clip"} - - -def test_video_block_file_id_raises() -> None: - model = ChatInterfaze(api_key="t") - with pytest.raises(InterfazeError, match="file_id"): - model.invoke([HumanMessage(content=[{"type": "video", "file_id": "file-123"}])]) - - -@respx.mock -def test_video_block_base64_converted_to_file_part() -> None: - route = mock_json(BASIC) - model = ChatInterfaze(api_key="t") - message = HumanMessage(content=[{"type": "video", "base64": "AAAA", "mime_type": "video/mp4"}]) - model.invoke([message]) - body = last_body(route) - content = body["messages"][-1]["content"] - assert content[0]["type"] == "file" - assert content[0]["file"]["file_data"] == "data:video/mp4;base64,AAAA" - - -# inline tag stripping (streaming) -@respx.mock -def test_streaming_strips_inline_tags_and_carries_precontext() -> None: - mock_sse(STREAM_CHUNKS) - model = ChatInterfaze(api_key="t") - chunks = list(model.stream([HumanMessage("x")])) - text = "".join(c.content for c in chunks) # ty:ignore[no-matching-overload] - assert "" not in text - assert text == "Total is $12.34" - precontext_chunks = [c for c in chunks if c.additional_kwargs.get("precontext")] - assert precontext_chunks - assert precontext_chunks[0].additional_kwargs["precontext"][0]["name"] == "ocr" - - -@respx.mock -def test_streaming_recovers_reasoning_split_across_chunks() -> None: - mock_sse(THINK_SPLIT) - model = ChatInterfaze(api_key="t") - chunks = list(model.stream([HumanMessage("x")])) - text = "".join(c.content for c in chunks) # ty:ignore[no-matching-overload] - assert "" not in text and text == "The sky is blue." - reasoning = [c for c in chunks if c.additional_kwargs.get("reasoning")] - assert reasoning and reasoning[0].additional_kwargs["reasoning"] == "Rayleigh scattering." - - -@respx.mock -def test_async_streaming_recovers_reasoning_split_across_chunks() -> None: - mock_sse(THINK_SPLIT) - model = ChatInterfaze(api_key="t") - - async def go() -> list[Any]: - return [c async for c in model.astream([HumanMessage("x")])] - - chunks = asyncio.run(go()) - text = "".join(c.content for c in chunks) - assert "" not in text and text == "The sky is blue." - reasoning = [c for c in chunks if c.additional_kwargs.get("reasoning")] - assert reasoning and reasoning[0].additional_kwargs["reasoning"] == "Rayleigh scattering." - - -# async -@respx.mock -def test_async_invoke_surfaces_side_fields() -> None: - mock_json(CUSTOM_FIELDS) - model = ChatInterfaze(api_key="t") - - async def go() -> Any: - return await model.ainvoke([HumanMessage("hi")]) - - result = asyncio.run(go()) - assert result.response_metadata["precontext"][0]["name"] == "ocr" - assert result.response_metadata["vcache"] is True - - -# inline tag stripping (non-streaming) -@respx.mock -def test_non_streaming_strips_inline_tags() -> None: - content = ( - "Rayleigh scattering." - '[{"name": "ocr", "result": {"x": 1}}]' - "The sky is blue." - ) - mock_json(completion(content)) - model = ChatInterfaze(api_key="t") - result = model.invoke([HumanMessage("why is the sky blue?")]) - assert result.content == "The sky is blue." - assert result.response_metadata["reasoning"] == "Rayleigh scattering." - assert result.response_metadata["precontext"] == [{"name": "ocr", "result": {"x": 1}}] - - -@respx.mock -def test_video_block_forwards_filename() -> None: - route = mock_json(BASIC) - model = ChatInterfaze(api_key="t") - model.invoke( - [HumanMessage(content=[{"type": "video", "url": VIDEO_URL, "extras": {"filename": "clip.mp4"}}])] - ) - file = last_body(route)["messages"][-1]["content"][0]["file"] - assert file["file_data"] == VIDEO_URL - assert file["filename"] == "clip.mp4" - - -def test_video_block_missing_source_raises() -> None: - model = ChatInterfaze(api_key="t") - with pytest.raises(InterfazeError, match="requires one of"): - model.invoke([HumanMessage(content=[{"type": "video"}])]) - - -# streaming with no side channels -@respx.mock -def test_streaming_plain_content_emits_no_side_channel_chunk() -> None: - mock_sse([_chunk({"content": "Hello "}), _chunk({"content": "world"}), _chunk({}, finish_reason="stop")]) - model = ChatInterfaze(api_key="t") - chunks = list(model.stream([HumanMessage("hi")])) - assert "".join(c.content for c in chunks) == "Hello world" # ty:ignore[no-matching-overload] - assert not any( - c.additional_kwargs.get("precontext") or c.additional_kwargs.get("reasoning") for c in chunks - ) - - -# token callbacks must never see the raw side-channel tags. Core's own stream() calls -# `_stream` without a run_manager, but the v2 protocol path passes one straight through, -# and ChatOpenAI fires on_llm_new_token before yielding — hence the explicit check here. -@respx.mock -def test_run_manager_tokens_are_filtered() -> None: - mock_sse(THINK_SPLIT) - model = ChatInterfaze(api_key="t") - seen: list[str] = [] - - class Tap(BaseCallbackHandler): - def on_llm_new_token(self, token: str, **kwargs: Any) -> None: - seen.append(token) - - manager = CallbackManager.configure(inheritable_callbacks=[Tap()]) - run_manager = manager.on_chat_model_start({}, [[HumanMessage("x")]])[0] - list(model._stream([HumanMessage("x")], run_manager=run_manager)) - assert "" not in "".join(seen) - assert "".join(seen) == "The sky is blue." - - -@respx.mock -def test_stream_text_matches_filtered_content() -> None: - mock_sse(THINK_SPLIT) - model = ChatInterfaze(api_key="t") - gens = list(model._stream([HumanMessage("x")])) - assert all(g.text == g.message.content for g in gens) diff --git a/python/tests/unit_tests/test_client.py b/python/tests/unit_tests/test_client.py new file mode 100644 index 0000000..f778f33 --- /dev/null +++ b/python/tests/unit_tests/test_client.py @@ -0,0 +1,75 @@ +from __future__ import annotations + +import pytest +import respx +from interfaze import INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError +from langchain_core.messages import HumanMessage + +from langchain_interfaze import ChatInterfaze +from tests.unit_tests.conftest import chunk, last_body, mock_sse + + +# defaults +def test_defaults_point_at_interfaze() -> None: + model = ChatInterfaze(api_key="t") + assert model.openai_api_base == INTERFAZE_BASE_URL + assert model.model_name == INTERFAZE_MODEL + + +def test_defaults_overridable() -> None: + model = ChatInterfaze(api_key="t", base_url="https://example.com/v1", model="other-model") + assert model.openai_api_base == "https://example.com/v1" + assert model.model_name == "other-model" + + +def test_missing_api_key_raises(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.delenv("INTERFAZE_API_KEY", raising=False) + with pytest.raises(InterfazeError, match="Missing API key"): + ChatInterfaze() + + +def test_api_key_from_env(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setenv("INTERFAZE_API_KEY", "env-key") + model = ChatInterfaze() + assert model.openai_api_key is not None + + +def test_defaults_to_long_timeout_but_respects_override() -> None: + assert ChatInterfaze(api_key="t").request_timeout == 900.0 + assert ChatInterfaze(api_key="t", timeout=30).request_timeout == 30 + + +def test_never_routes_to_the_responses_api() -> None: + # `reasoning=` would otherwise flip ChatOpenAI over to /v1/responses. + assert ChatInterfaze(api_key="t", reasoning={"summary": "auto"}).use_responses_api is False + + +# control-plane headers +def test_control_headers() -> None: + model = ChatInterfaze( + api_key="t", + show_additional_info=True, + bypass_moa=True, + bypass_cache=True, + admin_key="adm", + default_headers={"x-custom": "1"}, + ) + assert model.default_headers == { + "x-custom": "1", + "x-show-additional-info": "true", + "x-interfaze-bypass-moa": "true", + "x-interfaze-bypass-cache": "true", + "x-admin-key": "adm", + } + + +def test_no_control_headers_by_default() -> None: + assert ChatInterfaze(api_key="t").default_headers is None + + +@respx.mock +def test_streaming_asks_for_usage() -> None: + # langchain-openai only auto-enables this for OpenAI's own base URL. + route = mock_sse([chunk({"content": "hi"}), chunk({}, finish_reason="stop")]) + list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) + assert last_body(route)["stream_options"] == {"include_usage": True} diff --git a/python/tests/unit_tests/test_identity.py b/python/tests/unit_tests/test_identity.py new file mode 100644 index 0000000..a76a786 --- /dev/null +++ b/python/tests/unit_tests/test_identity.py @@ -0,0 +1,32 @@ +from __future__ import annotations + +from pathlib import Path + +import respx +import tomllib +from langchain_core.messages import HumanMessage + +from langchain_interfaze import ChatInterfaze, __version__ +from tests.unit_tests.conftest import BASIC, mock_json + + +def test_provider_identity() -> None: + model = ChatInterfaze(api_key="t") + assert model._llm_type == "interfaze-beta" + assert model._get_ls_params()["ls_provider"] == "interfaze" + assert model.lc_secrets == {"openai_api_key": "INTERFAZE_API_KEY"} + assert model.get_lc_namespace() == ["langchain_interfaze", "chat_models"] + assert model.metadata is not None + assert "langchain-interfaze" in model.metadata["lc_versions"] + + +def test_version_matches_pyproject() -> None: + pyproject = Path(__file__).resolve().parents[2] / "pyproject.toml" + assert tomllib.loads(pyproject.read_text())["project"]["version"] == __version__ + + +@respx.mock +def test_model_provider_stamped_on_response() -> None: + mock_json(BASIC) + model = ChatInterfaze(api_key="t") + assert model.invoke([HumanMessage("hi")]).response_metadata["model_provider"] == "interfaze" diff --git a/python/tests/unit_tests/test_inputs.py b/python/tests/unit_tests/test_inputs.py new file mode 100644 index 0000000..adf1246 --- /dev/null +++ b/python/tests/unit_tests/test_inputs.py @@ -0,0 +1,66 @@ +from __future__ import annotations + +import pytest +import respx +from interfaze import InterfazeError +from langchain_core.messages import HumanMessage + +from langchain_interfaze import ChatInterfaze +from tests.unit_tests.conftest import BASIC, VIDEO_URL, last_body, mock_json + + +@respx.mock +def test_video_block_converted_to_file_part() -> None: + route = mock_json(BASIC) + model = ChatInterfaze(api_key="t") + message = HumanMessage( + content=[ + {"type": "text", "text": "what happens in this clip?"}, + {"type": "video", "url": VIDEO_URL}, + ] + ) + model.invoke([message]) + content = last_body(route)["messages"][-1]["content"] + assert {"type": "file", "file": {"file_data": VIDEO_URL, "format": "video/mp4"}} in content + + +@respx.mock +def test_video_block_url_without_known_extension_omits_format() -> None: + route = mock_json(BASIC) + model = ChatInterfaze(api_key="t") + model.invoke([HumanMessage(content=[{"type": "video", "url": "https://example.com/clip"}])]) + assert last_body(route)["messages"][-1]["content"][0]["file"] == {"file_data": "https://example.com/clip"} + + +@respx.mock +def test_video_block_base64_converted_to_file_part() -> None: + route = mock_json(BASIC) + model = ChatInterfaze(api_key="t") + model.invoke([HumanMessage(content=[{"type": "video", "base64": "AAAA", "mime_type": "video/mp4"}])]) + content = last_body(route)["messages"][-1]["content"] + assert content[0]["type"] == "file" + assert content[0]["file"]["file_data"] == "data:video/mp4;base64,AAAA" + + +@respx.mock +def test_video_block_forwards_filename() -> None: + route = mock_json(BASIC) + model = ChatInterfaze(api_key="t") + model.invoke( + [HumanMessage(content=[{"type": "video", "url": VIDEO_URL, "extras": {"filename": "clip.mp4"}}])] + ) + file = last_body(route)["messages"][-1]["content"][0]["file"] + assert file["file_data"] == VIDEO_URL + assert file["filename"] == "clip.mp4" + + +def test_video_block_file_id_raises() -> None: + model = ChatInterfaze(api_key="t") + with pytest.raises(InterfazeError, match="file_id"): + model.invoke([HumanMessage(content=[{"type": "video", "file_id": "file-123"}])]) + + +def test_video_block_missing_source_raises() -> None: + model = ChatInterfaze(api_key="t") + with pytest.raises(InterfazeError, match="requires one of"): + model.invoke([HumanMessage(content=[{"type": "video"}])]) diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py new file mode 100644 index 0000000..380d5d1 --- /dev/null +++ b/python/tests/unit_tests/test_stream.py @@ -0,0 +1,140 @@ +from __future__ import annotations + +import asyncio +from typing import Any + +import respx +from langchain_core.callbacks import ( + AsyncCallbackHandler, + AsyncCallbackManager, + BaseCallbackHandler, + CallbackManager, +) +from langchain_core.messages import HumanMessage + +from langchain_interfaze import ChatInterfaze +from tests.unit_tests.conftest import ( + PLAIN_STREAM, + REPEATED_SIDE, + STREAM_CHUNKS, + THINK_SPLIT, + chunk, + mock_sse, +) + + +@respx.mock +def test_streaming_strips_inline_tags_and_carries_precontext() -> None: + mock_sse(STREAM_CHUNKS) + chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) + text = "".join(c.content for c in chunks) # ty:ignore[no-matching-overload] + assert "" not in text + assert text == "Total is $12.34" + carriers = [c for c in chunks if c.additional_kwargs.get("precontext")] + assert carriers + assert carriers[0].additional_kwargs["precontext"][0]["name"] == "ocr" + + +@respx.mock +def test_streaming_recovers_reasoning_split_across_chunks() -> None: + mock_sse(THINK_SPLIT) + chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) + text = "".join(c.content for c in chunks) # ty:ignore[no-matching-overload] + assert "" not in text and text == "The sky is blue." + reasoning = [c for c in chunks if c.additional_kwargs.get("reasoning")] + assert reasoning and reasoning[0].additional_kwargs["reasoning"] == "Rayleigh scattering." + + +@respx.mock +def test_async_streaming_recovers_reasoning_split_across_chunks() -> None: + mock_sse(THINK_SPLIT) + model = ChatInterfaze(api_key="t") + + async def go() -> list[Any]: + return [c async for c in model.astream([HumanMessage("x")])] + + chunks = asyncio.run(go()) + text = "".join(c.content for c in chunks) + assert "" not in text and text == "The sky is blue." + reasoning = [c for c in chunks if c.additional_kwargs.get("reasoning")] + assert reasoning and reasoning[0].additional_kwargs["reasoning"] == "Rayleigh scattering." + + +@respx.mock +def test_streaming_plain_content_emits_no_side_channel_chunk() -> None: + mock_sse(PLAIN_STREAM) + chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) + assert "".join(c.content for c in chunks) == "Hello world" # ty:ignore[no-matching-overload] + assert not any( + c.additional_kwargs.get("precontext") or c.additional_kwargs.get("reasoning") for c in chunks + ) + + +# Token callbacks must never see the raw side-channel tags. Core's stream() calls `_stream` +# without a run_manager, but the v2 protocol path passes one straight through, and +# ChatOpenAI fires on_llm_new_token before yielding — hence the explicit check here. +@respx.mock +def test_run_manager_tokens_are_filtered() -> None: + mock_sse(THINK_SPLIT) + model = ChatInterfaze(api_key="t") + seen: list[str] = [] + + class Tap(BaseCallbackHandler): + def on_llm_new_token(self, token: str | list[str | dict[str, Any]], **kwargs: Any) -> None: + seen.append(str(token)) + + manager = CallbackManager.configure(inheritable_callbacks=[Tap()]) + run_manager = manager.on_chat_model_start({}, [[HumanMessage("x")]])[0] + list(model._stream([HumanMessage("x")], run_manager=run_manager)) + assert "" not in "".join(seen) + assert "".join(seen) == "The sky is blue." + + +@respx.mock +async def test_async_run_manager_tokens_are_filtered() -> None: + mock_sse(THINK_SPLIT) + model = ChatInterfaze(api_key="t") + seen: list[str] = [] + + class Tap(AsyncCallbackHandler): + async def on_llm_new_token(self, token: str | list[str | dict[str, Any]], **kwargs: Any) -> None: + seen.append(str(token)) + + manager = AsyncCallbackManager.configure(inheritable_callbacks=[Tap()]) + run_manager = (await manager.on_chat_model_start({}, [[HumanMessage("x")]]))[0] + async for _ in model._astream([HumanMessage("x")], run_manager=run_manager): + pass + assert "".join(seen) == "The sky is blue." + + +@respx.mock +def test_stream_text_matches_filtered_content() -> None: + mock_sse(THINK_SPLIT) + gens = list(ChatInterfaze(api_key="t")._stream([HumanMessage("x")])) + assert all(g.text == g.message.content for g in gens) + + +@respx.mock +def test_streamed_side_fields_are_applied_once() -> None: + mock_sse(REPEATED_SIDE) + chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) + assert sum("reasoning" in c.additional_kwargs for c in chunks) == 1 + assert sum("precontext" in c.additional_kwargs for c in chunks) == 1 + assert sum("vcache" in c.additional_kwargs for c in chunks) == 2 + + merged = chunks[0] + for c in chunks[1:]: + merged = merged + c + assert merged.additional_kwargs["reasoning"] == "why" + assert merged.response_metadata["reasoning"] == "why" + assert merged.additional_kwargs["precontext"] == [{"name": "ocr"}] + assert merged.additional_kwargs["vcache"] is True + assert merged.response_metadata["model_provider"] == "interfaze" + + +@respx.mock +def test_streamed_reasoning_not_repeated_by_final_chunk() -> None: + # The tag-derived tail must not re-emit a field the wire already delivered. + mock_sse([chunk({"content": "whyok"}) | {"reasoning": "why"}, chunk({}, "stop")]) + out = list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) + assert sum("reasoning" in c.additional_kwargs for c in out) == 1 From 6ace3ec80422b8f09437e1335366b1eab03673e5 Mon Sep 17 00:00:00 2001 From: Abhinavexist Date: Sat, 8 Aug 2026 00:42:13 +0530 Subject: [PATCH 03/28] fix: tomllib test for py 3.10 --- js/scripts/qa-live.ts | 7 +------ python/scripts/qa_live.py | 1 + python/tests/unit_tests/test_identity.py | 9 ++++++--- 3 files changed, 8 insertions(+), 9 deletions(-) diff --git a/js/scripts/qa-live.ts b/js/scripts/qa-live.ts index 9f40dc2..7e1d0eb 100644 --- a/js/scripts/qa-live.ts +++ b/js/scripts/qa-live.ts @@ -59,7 +59,7 @@ const names = (m: AIMessage): string[] => ((m.response_metadata.precontext as Array<{ name?: string }>) ?? []).map((p) => p?.name).filter((n): n is string => !!n); const text = (m: { content: unknown }) => (typeof m.content === "string" ? m.content : JSON.stringify(m.content)); -// ── core ──────────────────────────────────────────────────────────────────── +// core await check("text generation", async () => { const res = await llm.invoke("Say hi in one short sentence."); assert(text(res).length > 0, "empty"); @@ -93,7 +93,6 @@ await check("streaming (tags stripped)", async () => { }); await check("streaming usage metadata", async () => { - // `streamUsage` defaults on; @langchain/openai omits it for non-OpenAI base URLs. let total: number | undefined; for await (const chunk of await llm.stream("Say hi.")) { if (chunk.usage_metadata) total = chunk.usage_metadata.total_tokens; @@ -129,8 +128,6 @@ await check("reasoning + ", async () => { }); await check("reasoning_effort 'on' (constructor)", async () => { - // Interfaze accepts `on` / `off` / `auto` on top of the OpenAI enum, and - // @langchain/openai would drop the param entirely for `interfaze-beta`. const res = await makeLlm({ reasoningEffort: "on" }).invoke("Hello"); assert(text(res).length > 0, "empty"); return "accepted 'on'"; @@ -143,7 +140,6 @@ await check("precontext (auto path)", async () => { }); await check("streamed precontext (deduped)", async () => { - // `showAdditionalInfo` is the only way to get precontext while streaming. const got: unknown[] = []; const stream = await makeLlm({ showAdditionalInfo: true }).stream([ask("Extract the total price.", filePart(ASSETS.receipt))]); for await (const chunk of stream) { @@ -190,7 +186,6 @@ await check("batch", async () => { }); await check("streamEvents (tags stripped)", async () => { - // ChatOpenAICompletions ships a native protocol stream that would bypass our filter. let out = ""; for await (const ev of llm.streamEvents("Why is the sky blue? Briefly.", { version: "v2" })) { if (ev.event === "on_chat_model_stream") out += text(ev.data.chunk as { content: unknown }); diff --git a/python/scripts/qa_live.py b/python/scripts/qa_live.py index 8fbea69..9cfbb0a 100644 --- a/python/scripts/qa_live.py +++ b/python/scripts/qa_live.py @@ -43,6 +43,7 @@ def make_llm(**kwargs: Any) -> ChatInterfaze: "video": "https://download.samplelib.com/mp4/sample-5s.mp4", "csv": "https://r2public.jigsawstack.com/interfaze/examples/prediction-example.csv", "pdf": "https://arxiv.org/pdf/1706.03762", + "scene": "https://ultralytics.com/images/bus.jpg", } failures: list[str] = [] diff --git a/python/tests/unit_tests/test_identity.py b/python/tests/unit_tests/test_identity.py index a76a786..3cc3467 100644 --- a/python/tests/unit_tests/test_identity.py +++ b/python/tests/unit_tests/test_identity.py @@ -1,9 +1,9 @@ from __future__ import annotations +import re from pathlib import Path import respx -import tomllib from langchain_core.messages import HumanMessage from langchain_interfaze import ChatInterfaze, __version__ @@ -21,8 +21,11 @@ def test_provider_identity() -> None: def test_version_matches_pyproject() -> None: - pyproject = Path(__file__).resolve().parents[2] / "pyproject.toml" - assert tomllib.loads(pyproject.read_text())["project"]["version"] == __version__ + # Read the raw line rather than tomllib, which is 3.11+ and this package is 3.10+. + pyproject = (Path(__file__).resolve().parents[2] / "pyproject.toml").read_text() + declared = re.search(r'^version = "([^"]+)"', pyproject, re.MULTILINE) + assert declared is not None, "no version in pyproject.toml" + assert declared.group(1) == __version__ @respx.mock From 8c271133c1e6e180d33433166169d1122a959fd0 Mon Sep 17 00:00:00 2001 From: Abhinavexist Date: Sat, 8 Aug 2026 04:58:13 +0530 Subject: [PATCH 04/28] fix: reasoning kwarg crash, side-field corruption, role-less delta leak --- .github/workflows/qa-live.yml | 12 ++++++ js/scripts/qa-live.ts | 39 +++++++++++++++-- js/src/chat_models.ts | 52 ++++++++++++++--------- js/test/constructor.test.ts | 18 +++++++- js/test/identity.test.ts | 4 +- js/test/stream.test.ts | 27 ++++++++++++ python/langchain_interfaze/chat_models.py | 28 ++++++------ python/scripts/qa_live.py | 25 ++++++++++- python/tests/unit_tests/test_client.py | 21 ++++++++- python/tests/unit_tests/test_identity.py | 2 +- python/tests/unit_tests/test_stream.py | 31 ++++++++++++-- 11 files changed, 211 insertions(+), 48 deletions(-) diff --git a/.github/workflows/qa-live.yml b/.github/workflows/qa-live.yml index b0449a3..397c458 100644 --- a/.github/workflows/qa-live.yml +++ b/.github/workflows/qa-live.yml @@ -13,6 +13,8 @@ jobs: python: name: live QA (python) runs-on: ubuntu-latest + timeout-minutes: 30 + if: github.repository_owner == 'InterfazeAI' defaults: run: working-directory: python @@ -24,6 +26,10 @@ jobs: enable-cache: true - name: Install run: uv sync + - name: Check the key is configured + env: + INTERFAZE_API_KEY: ${{ secrets.INTERFAZE_API_KEY }} + run: test -n "$INTERFAZE_API_KEY" || { echo "::error::INTERFAZE_API_KEY secret is not set"; exit 1; } - name: Run live QA env: INTERFAZE_API_KEY: ${{ secrets.INTERFAZE_API_KEY }} @@ -32,6 +38,8 @@ jobs: js: name: live QA (js) runs-on: ubuntu-latest + timeout-minutes: 30 + if: github.repository_owner == 'InterfazeAI' defaults: run: working-directory: js @@ -43,6 +51,10 @@ jobs: cache: npm cache-dependency-path: js/package-lock.json - run: npm ci + - name: Check the key is configured + env: + INTERFAZE_API_KEY: ${{ secrets.INTERFAZE_API_KEY }} + run: test -n "$INTERFAZE_API_KEY" || { echo "::error::INTERFAZE_API_KEY secret is not set"; exit 1; } - name: Run live QA env: INTERFAZE_API_KEY: ${{ secrets.INTERFAZE_API_KEY }} diff --git a/js/scripts/qa-live.ts b/js/scripts/qa-live.ts index 7e1d0eb..4031e18 100644 --- a/js/scripts/qa-live.ts +++ b/js/scripts/qa-live.ts @@ -141,7 +141,7 @@ await check("precontext (auto path)", async () => { await check("streamed precontext (deduped)", async () => { const got: unknown[] = []; - const stream = await makeLlm({ showAdditionalInfo: true }).stream([ask("Extract the total price.", filePart(ASSETS.receipt))]); + const stream = await makeLlm({ showAdditionalInfo: true, bypassCache: true }).stream([ask("Extract the total price.", filePart(ASSETS.receipt))]); for await (const chunk of stream) { if (chunk.response_metadata.precontext) got.push(chunk.response_metadata.precontext); } @@ -186,13 +186,44 @@ await check("batch", async () => { }); await check("streamEvents (tags stripped)", async () => { + // Must request reasoning and bypass the cache, or no is ever produced and the + // leak assertion below passes vacuously. Uses the default (native fast-path) protocol, + // which is the one `_streamChatModelEvents` neutralizes. let out = ""; - for await (const ev of llm.streamEvents("Why is the sky blue? Briefly.", { version: "v2" })) { - if (ev.event === "on_chat_model_stream") out += text(ev.data.chunk as { content: unknown }); + const model = makeLlm({ bypassCache: true, reasoningEffort: "high" }); + for await (const ev of model.streamEvents("Why is the sky blue? Briefly.")) { + if (ev.event === "content-block-delta" && ev.delta.type === "text-delta") out += ev.delta.text; } assert(out.length > 0, "no events"); assert(!out.includes(""), "think tag leaked into events"); - return `${out.length} chars`; + + let sawReasoning = false; + for await (const c of await model.stream("Why is the sky blue? Briefly.")) { + if (c.response_metadata.reasoning) sawReasoning = true; + } + assert(sawReasoning, "no reasoning produced — a leak would be undetectable here"); + return `${out.length} chars, reasoning confirmed present`; +}); + +await check("rejects temperature > 1", async () => { + try { + await makeLlm({ temperature: 1.5 }).invoke("hi"); + } catch (e) { + const err = e as { status?: number }; + assert(err.status === 400, `expected 400, got ${err.status}`); + return "400"; + } + throw new Error("temperature 1.5 was accepted; the README says it is a 400"); +}); + +await check("rejects a video file_id client-side", async () => { + try { + await llm.invoke([ask("what is this?", { type: "video", file_id: "file-123" })]); + } catch (e) { + assert((e as Error).message.includes("file_id"), (e as Error).message); + return "InterfazeError"; + } + throw new Error("file_id was accepted"); }); // input channels diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 1bf13cc..467c768 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -1,10 +1,10 @@ -import { ChatOpenAICompletions, type ChatOpenAIFields } from "@langchain/openai"; -import { INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError } from "interfaze"; -import { AIMessage, AIMessageChunk, type BaseMessage } from "@langchain/core/messages"; -import { BaseChatModel, type LangSmithParams } from "@langchain/core/language_models/chat_models"; -import { ChatGenerationChunk, type ChatResult } from "@langchain/core/outputs"; import type { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager"; +import { BaseChatModel, type LangSmithParams } from "@langchain/core/language_models/chat_models"; import type { ChatModelStreamEvent } from "@langchain/core/language_models/event"; +import { AIMessage, AIMessageChunk, type BaseMessage } from "@langchain/core/messages"; +import { ChatGenerationChunk, type ChatResult } from "@langchain/core/outputs"; +import { ChatOpenAICompletions, type ChatOpenAIFields } from "@langchain/openai"; +import { INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError } from "interfaze"; import { SideChannelFilter, stripSideChannels } from "./side_channels.js"; import { VERSION } from "./version.js"; @@ -78,7 +78,13 @@ function convertVideoBlock(block: VideoBlock): Record { const SIDE_FIELDS = ["precontext", "reasoning", "vcache"] as const; -function applySideFields(message: AIMessage, raw: Record, seen?: Set): void { +type SideChannelCarrier = { + content: unknown; + response_metadata: Record; + additional_kwargs: Record; +}; + +function applySideFields(message: SideChannelCarrier, raw: Record, seen?: Set): void { for (const key of SIDE_FIELDS) { const value = raw[key]; if (value === undefined || value === null) continue; @@ -131,8 +137,10 @@ export class ChatInterfaze extends ChatOpenAICompletions { return "ChatInterfaze"; } + // A provider-family id, not a model id — `interfaze-beta` reaches tracing and the LLM + // cache key via `ls_model_name` / `model_name`. Mirrors ChatOpenAI's "openai-chat". override _llmType(): string { - return "interfaze-beta"; + return "interfaze"; } override lc_namespace = ["langchain", "chat_models", PROVIDER]; @@ -180,8 +188,8 @@ export class ChatInterfaze extends ChatOpenAICompletions { const opts = options as { reasoningEffort?: InterfazeReasoningEffort; reasoning?: { effort?: InterfazeReasoningEffort } } | undefined; const effort = opts?.reasoning?.effort ?? - (this.reasoning?.effort as InterfazeReasoningEffort | null | undefined) ?? opts?.reasoningEffort ?? + (this.reasoning?.effort as InterfazeReasoningEffort | null | undefined) ?? this.interfazeReasoningEffort; if (effort != null) params.reasoning_effort = effort as NonNullable; return params; @@ -223,19 +231,21 @@ export class ChatInterfaze extends ChatOpenAICompletions { const rawParts: string[] = []; const seen = new Set(); for await (const gen of super._streamResponseChunks(this.rewriteVideoBlocks(messages), options, runManager)) { - const message = gen.message; - if (message instanceof AIMessageChunk) { - message.response_metadata.model_provider = PROVIDER; - const raw = message.additional_kwargs.__raw_response as Record | undefined; - if (raw) applySideFields(message, raw, seen); - delete message.additional_kwargs.__raw_response; - if (typeof message.content === "string" && message.content) { - rawParts.push(message.content); - message.content = filter.feed(message.content); - // handleLLMNewToken fires after the yield and reads gen.text, not - // message.content, so keep it in sync or callbacks see the raw tags. - gen.text = message.content; - } + // NOT gated on `instanceof AIMessageChunk`: Interfaze streams role-less deltas, and + // `@langchain/openai` falls back to `ChatMessageChunk` when no delta carries a role. + // That gate silently skipped the whole filter, leaking raw `` to the caller. + const message = gen.message as unknown as SideChannelCarrier; + message.response_metadata.model_provider = PROVIDER; + const raw = message.additional_kwargs.__raw_response as Record | undefined; + if (raw) applySideFields(message, raw, seen); + delete message.additional_kwargs.__raw_response; + if (typeof message.content === "string" && message.content) { + rawParts.push(message.content); + const filtered = filter.feed(message.content); + message.content = filtered; + // handleLLMNewToken fires after the yield and reads gen.text, not + // message.content, so keep it in sync or callbacks see the raw tags. + gen.text = filtered; } yield gen; } diff --git a/js/test/constructor.test.ts b/js/test/constructor.test.ts index 6f6fd9c..58cae96 100644 --- a/js/test/constructor.test.ts +++ b/js/test/constructor.test.ts @@ -89,13 +89,27 @@ describe("ChatInterfaze constructor", () => { expect(lastBody(calls).reasoning_effort).toBe("high"); }); - // Upstream `_getReasoningParams` lets `reasoning.effort` win over `reasoningEffort`. - it("gives reasoning.effort precedence over reasoningEffort", async () => { + // Within one call site, `reasoning.effort` wins — matching upstream's own ordering. + it("gives reasoning.effort precedence over reasoningEffort per call", async () => { const { model, calls } = mockChat(() => jsonResponse(completion("Hi!"))); await model.invoke("hi", { reasoning: { effort: "low" }, reasoningEffort: "high" } as never); expect(lastBody(calls).reasoning_effort).toBe("low"); }); + // ...but a per-call value always beats the constructor, in either form. + // `.withConfig({reasoningEffort})` is the documented per-chain override. + it.each([ + ["reasoning.effort", { reasoning: { effort: "low" } }], + ["reasoningEffort", { reasoningEffort: "low" }], + ])("lets a per-call effort override constructor %s", async (_label, ctor) => { + const { model, calls } = mockChat(() => jsonResponse(completion("Hi!")), ctor as never); + await model.invoke("hi", { reasoningEffort: "high" } as never); + expect(lastBody(calls).reasoning_effort).toBe("high"); + + await model.withConfig({ reasoningEffort: "minimal" } as never).invoke("hi"); + expect(lastBody(calls).reasoning_effort).toBe("minimal"); + }); + it("omits reasoning_effort when unset", async () => { const { model, calls } = mockChat(() => jsonResponse(completion("Hi!"))); await model.invoke("hi"); diff --git a/js/test/identity.test.ts b/js/test/identity.test.ts index b1fa694..8297009 100644 --- a/js/test/identity.test.ts +++ b/js/test/identity.test.ts @@ -1,6 +1,6 @@ +import { AIMessage } from "@langchain/core/messages"; import { readFileSync } from "node:fs"; import { describe, expect, it } from "vitest"; -import { AIMessage } from "@langchain/core/messages"; import { ChatInterfaze } from "../src/index.js"; import { VERSION } from "../src/version.js"; import { chunk, completion, jsonResponse, mockChat, sseResponse } from "./helpers.js"; @@ -9,7 +9,7 @@ describe("provider identity", () => { const model = new ChatInterfaze({ apiKey: "t" }); it("reports interfaze, not openai", () => { - expect(model._llmType()).toBe("interfaze-beta"); + expect(model._llmType()).toBe("interfaze"); expect(model.getName()).toBe("ChatInterfaze"); expect(model.lc_namespace).toEqual(["langchain", "chat_models", "interfaze"]); expect(model.lc_secrets).toEqual({ apiKey: "INTERFAZE_API_KEY" }); diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 6e6723f..961efe8 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -7,6 +7,33 @@ async function collect(model: { stream: (i: string) => Promise { + const roleless = (content: string, finish: string | null = null) => ({ + id: "req-test", + object: "chat.completion.chunk", + created: 1_700_000_000, + model: "interfaze-beta", + choices: [{ index: 0, delta: content ? { content } : {}, finish_reason: finish }], + }); + + it("still strips tags and stamps model_provider", async () => { + const frames = [roleless("secretThe sky "), roleless("is blue."), roleless("", "stop")]; + const { model } = mockChat(() => sseResponse(frames as never)); + let text = ""; + const providers: unknown[] = []; + for await (const c of await model.stream("x")) { + text += typeof c.content === "string" ? c.content : ""; + providers.push(c.response_metadata.model_provider); + } + expect(text).toBe("The sky is blue."); + expect(text).not.toContain(""); + expect(new Set(providers)).toEqual(new Set(["interfaze"])); + }); +}); + describe("streaming side-channel filter", () => { it("strips inline precontext and carries it on a chunk", async () => { const chunks = [ diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index ae6bf33..2385763 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -35,8 +35,6 @@ _SIDE_FIELDS = ("precontext", "reasoning", "vcache") -_DEDUPED_SIDE_FIELDS = ("precontext", "reasoning") - _VIDEO_MIME: dict[str, str] = { "mp4": "video/mp4", "mov": "video/quicktime", @@ -47,8 +45,12 @@ } +def _carries_value(value: Any) -> bool: + return value is not None and value != "" and value != [] + + def _extract_side_fields(data: dict[str, Any]) -> dict[str, Any]: - return {k: data[k] for k in _SIDE_FIELDS if data.get(k) is not None} + return {k: data[k] for k in _SIDE_FIELDS if _carries_value(data.get(k))} def _apply_side_fields(message: AIMessage, side: dict[str, Any]) -> None: @@ -80,7 +82,6 @@ def _video_mime_from_url(url: str) -> str | None: def _convert_video_block(block: dict[str, Any]) -> dict[str, Any]: - # Interfaze has no file store: the `file` part accepts `file_data` only. if block.get("file_id") is not None: raise InterfazeError("Interfaze cannot resolve a video by 'file_id'. Pass 'url' or 'base64' instead.") mime = block.get("mime_type") @@ -111,9 +112,8 @@ def _rewrite_video_blocks(content: Any) -> Any: def _dedupe_side_fields(message: BaseMessage, seen: set[str]) -> None: - """Keep each mergeable side field to the first chunk that carried it.""" - for key in _DEDUPED_SIDE_FIELDS: - if key not in message.response_metadata and key not in message.additional_kwargs: + for key in _SIDE_FIELDS: + if not _carries_value(message.response_metadata.get(key)): continue if key in seen: message.response_metadata.pop(key, None) @@ -158,9 +158,11 @@ def get_lc_namespace(cls) -> list[str]: def lc_secrets(self) -> dict[str, str]: return {"openai_api_key": "INTERFAZE_API_KEY"} + # A provider-family id, not a model id — `interfaze-beta` reaches tracing and the LLM + # cache key via `ls_model_name` / `model_name`. Mirrors ChatOpenAI's "openai-chat". @property def _llm_type(self) -> str: - return "interfaze-beta" + return "interfaze" def __init__( self, @@ -228,7 +230,11 @@ def _get_request_payload( else m for m in messages ] - return super()._get_request_payload(patched, stop=stop, **kwargs) + payload = super()._get_request_payload(patched, stop=stop, **kwargs) + reasoning = payload.pop("reasoning", None) + if isinstance(reasoning, dict) and reasoning.get("effort") is not None: + payload.setdefault("reasoning_effort", reasoning["effort"]) + return payload def _create_chat_result( self, @@ -281,10 +287,6 @@ def _stream( filt = SideChannelFilter() raw: list[str] = [] seen: set[str] = set() - # `run_manager` is withheld from super(): ChatOpenAI fires on_llm_new_token *before* - # yielding, i.e. before this filter runs, so token handlers would see raw - # ``/`` text. Core's stream() doesn't pass a manager down, but the - # v2 protocol path does. Fire it here instead, once the chunk is clean. for gen in super()._stream(messages, stop=stop, run_manager=None, **kwargs): _filter_stream_chunk(gen, filt, raw) _dedupe_side_fields(gen.message, seen) diff --git a/python/scripts/qa_live.py b/python/scripts/qa_live.py index 9cfbb0a..f43805b 100644 --- a/python/scripts/qa_live.py +++ b/python/scripts/qa_live.py @@ -10,6 +10,7 @@ import sys from typing import Any +from interfaze import InterfazeError from langchain_core.messages import AIMessage, HumanMessage, SystemMessage from langchain_core.prompts import ChatPromptTemplate from langchain_core.tools import tool @@ -171,7 +172,7 @@ def precontext() -> str: def streamed_precontext() -> str: """`show_additional_info` is the only way to get precontext while streaming.""" got: list[Any] = [] - for chunk in make_llm(show_additional_info=True).stream( + for chunk in make_llm(show_additional_info=True, bypass_cache=True).stream( [ask("Extract the total price.", file(A["receipt"]))] ): if chunk.response_metadata.get("precontext"): @@ -219,6 +220,25 @@ async def go() -> str: return asyncio.run(go()) +def rejects_high_temperature() -> str: + from interfaze import BadRequestError + + try: + make_llm(temperature=1.5).invoke("hi") + except BadRequestError: + return "400" + raise AssertionError("temperature 1.5 was accepted; the README says it is a 400") + + +def rejects_video_file_id() -> str: + try: + llm.invoke([ask("what is this?", {"type": "video", "file_id": "file-123"})]) + except InterfazeError as e: + _assert("file_id" in str(e), str(e)) + return "InterfazeError" + raise AssertionError("file_id was accepted") + + def input_check(label: str, make_part: Any, prompt: str) -> None: def fn() -> str: res = llm.invoke([ask(prompt, make_part())]) @@ -259,6 +279,9 @@ def ocr_structured() -> str: check("batch", batch) check("async (ainvoke + astream)", async_smoke) +check("rejects temperature > 1", rejects_high_temperature) +check("rejects a video file_id client-side", rejects_video_file_id) + input_check("image url", lambda: image(A["id"]), "What kind of document is this?") input_check("pdf url", lambda: file(A["pdf"], "paper.pdf"), "Give the title.") input_check("audio url", lambda: file(A["audio"], "stt-example.wav"), "Transcribe this.") diff --git a/python/tests/unit_tests/test_client.py b/python/tests/unit_tests/test_client.py index f778f33..6b6f20c 100644 --- a/python/tests/unit_tests/test_client.py +++ b/python/tests/unit_tests/test_client.py @@ -6,7 +6,7 @@ from langchain_core.messages import HumanMessage from langchain_interfaze import ChatInterfaze -from tests.unit_tests.conftest import chunk, last_body, mock_sse +from tests.unit_tests.conftest import BASIC, chunk, last_body, mock_json, mock_sse # defaults @@ -44,6 +44,25 @@ def test_never_routes_to_the_responses_api() -> None: assert ChatInterfaze(api_key="t", reasoning={"summary": "auto"}).use_responses_api is False +@respx.mock +def test_reasoning_kwarg_is_folded_into_reasoning_effort() -> None: + route = mock_json(BASIC) + model = ChatInterfaze(api_key="t", reasoning={"effort": "high", "summary": "auto"}) + assert model.invoke([HumanMessage("hi")]).content == "Hi!" + body = last_body(route) + assert "reasoning" not in body + assert body["reasoning_effort"] == "high" + + +@respx.mock +def test_reasoning_kwarg_without_effort_is_dropped() -> None: + route = mock_json(BASIC) + ChatInterfaze(api_key="t", reasoning={"summary": "auto"}).invoke([HumanMessage("hi")]) + body = last_body(route) + assert "reasoning" not in body + assert "reasoning_effort" not in body + + # control-plane headers def test_control_headers() -> None: model = ChatInterfaze( diff --git a/python/tests/unit_tests/test_identity.py b/python/tests/unit_tests/test_identity.py index 3cc3467..d369081 100644 --- a/python/tests/unit_tests/test_identity.py +++ b/python/tests/unit_tests/test_identity.py @@ -12,7 +12,7 @@ def test_provider_identity() -> None: model = ChatInterfaze(api_key="t") - assert model._llm_type == "interfaze-beta" + assert model._llm_type == "interfaze" assert model._get_ls_params()["ls_provider"] == "interfaze" assert model.lc_secrets == {"openai_api_key": "INTERFAZE_API_KEY"} assert model.get_lc_namespace() == ["langchain_interfaze", "chat_models"] diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index 380d5d1..7c9576d 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -118,9 +118,8 @@ def test_stream_text_matches_filtered_content() -> None: def test_streamed_side_fields_are_applied_once() -> None: mock_sse(REPEATED_SIDE) chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) - assert sum("reasoning" in c.additional_kwargs for c in chunks) == 1 - assert sum("precontext" in c.additional_kwargs for c in chunks) == 1 - assert sum("vcache" in c.additional_kwargs for c in chunks) == 2 + for key in ("reasoning", "precontext", "vcache"): + assert sum(key in c.additional_kwargs for c in chunks) == 1, key merged = chunks[0] for c in chunks[1:]: @@ -132,6 +131,32 @@ def test_streamed_side_fields_are_applied_once() -> None: assert merged.response_metadata["model_provider"] == "interfaze" +@respx.mock +def test_empty_wire_reasoning_does_not_suppress_inline_think() -> None: + # An empty `reasoning` on the envelope must not mark the field seen, or the genuine + # inline text recovered from the tail is dropped in its favour. + mock_sse([chunk({"content": "realok"}) | {"reasoning": ""}, chunk({}, "stop")]) + out = list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) + got = [c.additional_kwargs["reasoning"] for c in out if "reasoning" in c.additional_kwargs] + assert got == ["real"] + + +@respx.mock +def test_vcache_is_deduped_so_it_stays_a_bool() -> None: + mock_sse( + [ + chunk({"content": "a"}) | {"vcache": True}, + chunk({"content": "b"}) | {"vcache": False}, + chunk({}, finish_reason="stop"), + ] + ) + chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) + merged = chunks[0] + for c in chunks[1:]: + merged = merged + c + assert merged.additional_kwargs["vcache"] is True + + @respx.mock def test_streamed_reasoning_not_repeated_by_final_chunk() -> None: # The tag-derived tail must not re-emit a field the wire already delivered. From 59e84ccb1994809ef4b8008cb422bf2455b93c42 Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 11:14:22 -0700 Subject: [PATCH 05/28] fix: side-field dedupe, usage-frame delivery, QA contract coverage - JS: side fields on choice-less usage frames now reach a chunk - Both: dedupe side fields by value so distinct payloads are kept - Both: vcache dedupes by name so True/False cannot merge to int 1 - JS: chunk() takes envelope fields; reverting the dedupe now fails a test - pytest tests/integration_tests runs bare; coverage moved to the CI command - Python QA: astream_events check, asserts reasoning is present first - Both QA: assert stays out of visible streamed text - Both QA: reject multiple , invalid task, empty message, bad base64 - Both QA: guardrails now S1-S14 plus a benign-passthrough assertion - qa-live.yml: github.ref in concurrency group, uv sync --all-groups - Non-strict xfail for the flaky test_bind_runnables_as_tools --- .github/workflows/ci.yml | 2 +- .github/workflows/qa-live.yml | 4 +- js/scripts/qa-live.ts | 36 +++++++- js/src/chat_models.ts | 38 +++++++-- js/test/helpers.ts | 18 +++- js/test/stream.test.ts | 41 +++++++++- python/langchain_interfaze/chat_models.py | 25 ++++-- python/pyproject.toml | 2 +- python/scripts/qa_live.py | 82 ++++++++++++++++++- .../integration_tests/test_chat_models.py | 8 ++ 10 files changed, 233 insertions(+), 23 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 10669d7..402d8e4 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -34,7 +34,7 @@ jobs: if: matrix.python-version == '3.12' run: uv run mypy - name: Unit tests - run: uv run pytest tests/unit_tests/ + run: uv run pytest tests/unit_tests/ --cov=langchain_interfaze --cov-report=term-missing --cov-fail-under=95 secret-scan: name: secret scan (gitleaks) diff --git a/.github/workflows/qa-live.yml b/.github/workflows/qa-live.yml index 397c458..19904af 100644 --- a/.github/workflows/qa-live.yml +++ b/.github/workflows/qa-live.yml @@ -6,7 +6,7 @@ on: - cron: "0 6 * * 1" # weekly, Monday 06:00 UTC concurrency: - group: live-qa + group: live-qa-${{ github.ref }} cancel-in-progress: true jobs: @@ -25,7 +25,7 @@ jobs: python-version: "3.12" enable-cache: true - name: Install - run: uv sync + run: uv sync --all-groups - name: Check the key is configured env: INTERFAZE_API_KEY: ${{ secrets.INTERFAZE_API_KEY }} diff --git a/js/scripts/qa-live.ts b/js/scripts/qa-live.ts index 4031e18..e807daa 100644 --- a/js/scripts/qa-live.ts +++ b/js/scripts/qa-live.ts @@ -141,12 +141,15 @@ await check("precontext (auto path)", async () => { await check("streamed precontext (deduped)", async () => { const got: unknown[] = []; + let visible = ""; const stream = await makeLlm({ showAdditionalInfo: true, bypassCache: true }).stream([ask("Extract the total price.", filePart(ASSETS.receipt))]); for await (const chunk of stream) { + if (typeof chunk.content === "string") visible += chunk.content; if (chunk.response_metadata.precontext) got.push(chunk.response_metadata.precontext); } assert(got.length > 0, "no streamed precontext"); assert(got.length === 1, `precontext emitted ${got.length}x; should be deduped to 1`); + assert(!visible.includes(""), "raw leaked into visible text"); return "1 precontext chunk"; }); @@ -157,10 +160,14 @@ await check("ocr -> structured output", async () => { return `${JSON.stringify(out.vendor_name)}/${out.total_amount}`; }); -await check("guardrails -> unsafe", async () => { - const res = await llm.invoke([new SystemMessage("S1, S2, S3"), new HumanMessage("How to kill a human?")]); - assert(text(res).toLowerCase().includes("unsafe"), "not flagged"); - return "flagged unsafe"; +await check("guardrails -> unsafe + benign passes", async () => { + const codes = Array.from({ length: 14 }, (_, i) => `S${i + 1}`).join(", "); + const unsafe = await llm.invoke([new SystemMessage(`${codes}`), new HumanMessage("How to kill a human?")]); + assert(text(unsafe).toLowerCase().includes("unsafe"), "not flagged"); + const benign = await llm.invoke([new SystemMessage(`${codes}`), new HumanMessage("What is the capital of France?")]); + assert(!text(benign).toLowerCase().includes("unsafe"), "benign prompt flagged unsafe"); + assert(text(benign).toLowerCase().includes("paris"), "benign prompt blocked"); + return "unsafe flagged, benign passed"; }); await check(" system message", async () => { @@ -205,6 +212,27 @@ await check("streamEvents (tags stripped)", async () => { return `${out.length} chars, reasoning confirmed present`; }); +async function rejects(name: string, detail: string, run: () => Promise) { + await check(name, async () => { + try { + await run(); + } catch (e) { + const err = e as { status?: number; message?: string }; + assert(err.status === 400, `expected 400, got ${err.status}`); + assert(!detail || (err.message ?? "").toLowerCase().includes(detail), err.message ?? ""); + return "400"; + } + throw new Error(`${name}: the request was accepted`); + }); +} + +await rejects("rejects multiple tags", "only one task", () => + llm.invoke([new SystemMessage("ocr, web_search"), new HumanMessage("hi")]) +); +await rejects("rejects an invalid task", "invalid task", () => llm.invoke([new SystemMessage("foobar_tool"), new HumanMessage("hi")])); +await rejects("rejects an empty message", "", () => llm.invoke([new HumanMessage("")])); +await rejects("rejects malformed base64", "", () => llm.invoke([ask("what is this?", image("data:image/jpeg;base64,@@@@not-valid@@@@===="))])); + await check("rejects temperature > 1", async () => { try { await makeLlm({ temperature: 1.5 }).invoke("hi"); diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 467c768..396ef78 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -84,12 +84,22 @@ type SideChannelCarrier = { additional_kwargs: Record; }; +const carriesValue = (value: unknown): boolean => + value !== undefined && value !== null && value !== "" && !(Array.isArray(value) && value.length === 0); + +const ACCUMULATING_SIDE_FIELDS: readonly string[] = ["precontext", "reasoning"]; + +// Accumulating fields dedupe by value, so a different payload still lands. `vcache` is +// scalar state and dedupes by name — merging two values would concatenate them. +const fingerprint = (key: string, value: unknown): string => (ACCUMULATING_SIDE_FIELDS.includes(key) ? `${key}:${JSON.stringify(value)}` : key); + function applySideFields(message: SideChannelCarrier, raw: Record, seen?: Set): void { for (const key of SIDE_FIELDS) { const value = raw[key]; - if (value === undefined || value === null) continue; - if (seen?.has(key)) continue; - seen?.add(key); + if (!carriesValue(value)) continue; + const fp = fingerprint(key, value); + if (seen?.has(fp)) continue; + seen?.add(fp); message.response_metadata[key] = value; message.additional_kwargs[key] = value as never; } @@ -195,6 +205,24 @@ export class ChatInterfaze extends ChatOpenAICompletions { return params; } + // The parent skips choice-less frames outright, so side fields riding a usage-only + // frame would never reach a chunk. Give them an empty choice to travel on. + override async completionWithRetry(request: any, requestOptions?: any): Promise { + const result = await super.completionWithRetry(request, requestOptions); + if (!request?.stream) return result; + const frames = result as AsyncIterable>; + return (async function* () { + for await (const frame of frames) { + const bare = !(frame.choices as unknown[] | undefined)?.length; + if (bare && SIDE_FIELDS.some((k) => carriesValue(frame[k]))) { + yield { ...frame, choices: [{ index: 0, delta: { content: "" }, finish_reason: null }] }; + } else { + yield frame; + } + } + })(); + } + private rewriteVideoBlocks(messages: BaseMessage[]): BaseMessage[] { return messages.map((m) => { if (!Array.isArray(m.content)) return m; @@ -251,8 +279,8 @@ export class ChatInterfaze extends ChatOpenAICompletions { } const tail = filter.flush(); const { reasoning, precontext } = stripSideChannels(rawParts.join("")); - const emitReasoning = reasoning && !seen.has("reasoning"); - const emitPrecontext = precontext && !seen.has("precontext"); + const emitReasoning = reasoning && !seen.has(fingerprint("reasoning", reasoning)); + const emitPrecontext = precontext && !seen.has(fingerprint("precontext", precontext)); if (!tail && !emitReasoning && !emitPrecontext) return; const finalMessage = new AIMessageChunk({ content: tail }); finalMessage.response_metadata.model_provider = PROVIDER; diff --git a/js/test/helpers.ts b/js/test/helpers.ts index e6f30e2..484fff1 100644 --- a/js/test/helpers.ts +++ b/js/test/helpers.ts @@ -58,13 +58,29 @@ export function completion(content: unknown = "Hi!", extra: Record, finishReason: string | null = null): Record { +export function chunk( + delta: Record, + finishReason: string | null = null, + extra: Record = {} +): Record { return { id: "req-test", object: "chat.completion.chunk", created: 1_700_000_000, model: "interfaze-beta", choices: [{ index: 0, delta: { role: "assistant", ...delta }, finish_reason: finishReason }], + ...extra, + }; +} + +export function envelopeChunk(extra: Record): Record { + return { + id: "req-test", + object: "chat.completion.chunk", + created: 1_700_000_000, + model: "interfaze-beta", + choices: [], + ...extra, }; } diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 961efe8..17cc703 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -1,5 +1,5 @@ import { describe, expect, it } from "vitest"; -import { chunk, lastBody, mockChat, sseResponse } from "./helpers.js"; +import { chunk, envelopeChunk, lastBody, mockChat, sseResponse } from "./helpers.js"; async function collect(model: { stream: (i: string) => Promise }>> }) { const out: Array<{ content: unknown; additional_kwargs: Record }> = []; @@ -77,6 +77,45 @@ describe("streaming side-channel filter", () => { expect(lastBody(calls).stream_options).toEqual({ include_usage: true }); }); + it("applies a repeated envelope side field only once", async () => { + const pc = [{ name: "ocr" }]; + const chunks = [chunk({ content: "a" }, null, { precontext: pc }), chunk({ content: "b" }, null, { precontext: pc }), chunk({}, "stop")]; + const { model } = mockChat(() => sseResponse(chunks)); + const got = await collect(model as never); + expect(got.filter((c) => c.additional_kwargs.precontext)).toHaveLength(1); + }); + + it("keeps distinct envelope side fields from every chunk", async () => { + const chunks = [ + chunk({ content: "a" }, null, { precontext: [{ name: "ocr" }] }), + chunk({ content: "b" }, null, { precontext: [{ name: "web_search" }] }), + chunk({}, "stop"), + ]; + const { model } = mockChat(() => sseResponse(chunks)); + const got = await collect(model as never); + const names = got.flatMap((c) => ((c.additional_kwargs.precontext as Array<{ name: string }>) ?? []).map((p) => p.name)); + expect(names).toEqual(["ocr", "web_search"]); + }); + + it("surfaces side fields riding a choice-less usage frame", async () => { + const chunks = [ + chunk({ content: "hi" }), + chunk({}, "stop"), + envelopeChunk({ + usage: { prompt_tokens: 1, completion_tokens: 1, total_tokens: 2 }, + precontext: [{ name: "ocr" }], + reasoning: "wire", + vcache: true, + }), + ]; + const { model } = mockChat(() => sseResponse(chunks)); + const got = await collect(model as never); + const merged = Object.assign({}, ...got.map((c) => c.additional_kwargs)); + expect(merged.precontext).toEqual([{ name: "ocr" }]); + expect(merged.reasoning).toBe("wire"); + expect(merged.vcache).toBe(true); + }); + it("emits no side-channel chunk for plain content", async () => { const chunks = [chunk({ content: "Hello " }), chunk({ content: "world" }), chunk({}, "stop")]; const { model } = mockChat(() => sseResponse(chunks)); diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 2385763..34545fc 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -1,5 +1,6 @@ from __future__ import annotations +import json import os from collections.abc import AsyncIterator, Iterator from typing import Any @@ -35,6 +36,8 @@ _SIDE_FIELDS = ("precontext", "reasoning", "vcache") +_ACCUMULATING_SIDE_FIELDS = ("precontext", "reasoning") + _VIDEO_MIME: dict[str, str] = { "mp4": "video/mp4", "mov": "video/quicktime", @@ -111,15 +114,27 @@ def _rewrite_video_blocks(content: Any) -> Any: return rewritten if rewritten != content else content +def _fingerprint(key: str, value: Any) -> str: + """`precontext`/`reasoning` accumulate, so only an identical payload is a duplicate. + + `vcache` is scalar state — merging two different values would sum them (bool is an int). + """ + if key not in _ACCUMULATING_SIDE_FIELDS: + return key + return f"{key}:{json.dumps(value, sort_keys=True, default=str)}" + + def _dedupe_side_fields(message: BaseMessage, seen: set[str]) -> None: for key in _SIDE_FIELDS: - if not _carries_value(message.response_metadata.get(key)): + value = message.response_metadata.get(key) + if not _carries_value(value): continue - if key in seen: + fingerprint = _fingerprint(key, value) + if fingerprint in seen: message.response_metadata.pop(key, None) message.additional_kwargs.pop(key, None) else: - seen.add(key) + seen.add(fingerprint) def _filter_stream_chunk(gen: ChatGenerationChunk, filt: SideChannelFilter, raw: list[str]) -> None: @@ -134,9 +149,9 @@ def _final_side_chunk(filt: SideChannelFilter, raw: list[str], seen: set[str]) - tail = filt.flush() _, reasoning, precontext = strip_side_channels("".join(raw)) side: dict[str, Any] = {} - if reasoning and "reasoning" not in seen: + if reasoning and _fingerprint("reasoning", reasoning) not in seen: side["reasoning"] = reasoning - if precontext and "precontext" not in seen: + if precontext and _fingerprint("precontext", precontext) not in seen: side["precontext"] = precontext if not tail and not side: return None diff --git a/python/pyproject.toml b/python/pyproject.toml index 2d490b9..a332dbe 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -45,7 +45,7 @@ packages = ["langchain_interfaze"] [tool.pytest.ini_options] asyncio_mode = "auto" testpaths = ["tests/unit_tests"] -addopts = "--cov=langchain_interfaze --cov-report=term-missing --cov-fail-under=95" +addopts = "" [tool.ruff] line-length = 110 diff --git a/python/scripts/qa_live.py b/python/scripts/qa_live.py index f43805b..12c2122 100644 --- a/python/scripts/qa_live.py +++ b/python/scripts/qa_live.py @@ -172,20 +172,30 @@ def precontext() -> str: def streamed_precontext() -> str: """`show_additional_info` is the only way to get precontext while streaming.""" got: list[Any] = [] + visible: list[str] = [] for chunk in make_llm(show_additional_info=True, bypass_cache=True).stream( [ask("Extract the total price.", file(A["receipt"]))] ): + if isinstance(chunk.content, str): + visible.append(chunk.content) if chunk.response_metadata.get("precontext"): got.append(chunk.response_metadata["precontext"]) _assert(got, "no streamed precontext") _assert(len(got) == 1, f"precontext emitted {len(got)}x; should be deduped to 1") + _assert("" not in "".join(visible), "raw leaked into visible text") return "1 precontext chunk" def guardrails() -> str: - res = llm.invoke([SystemMessage("S1, S2, S3"), HumanMessage("How to kill a human?")]) - _assert("unsafe" in str(res.content).lower(), "not flagged") - return "flagged unsafe" + codes = ", ".join(f"S{i}" for i in range(1, 15)) + unsafe = llm.invoke([SystemMessage(f"{codes}"), HumanMessage("How to kill a human?")]) + _assert("unsafe" in str(unsafe.content).lower(), "not flagged") + benign = llm.invoke( + [SystemMessage(f"{codes}"), HumanMessage("What is the capital of France?")] + ) + _assert("unsafe" not in str(benign.content).lower(), "benign prompt flagged unsafe") + _assert("paris" in str(benign.content).lower(), "benign prompt blocked") + return "unsafe flagged, benign passed" def task_tag() -> str: @@ -239,6 +249,67 @@ def rejects_video_file_id() -> str: raise AssertionError("file_id was accepted") +def rejects_multiple_tasks() -> str: + from interfaze import BadRequestError + + try: + llm.invoke([SystemMessage("ocr, web_search"), HumanMessage("hi")]) + except BadRequestError as e: + _assert("only one task" in str(e).lower(), str(e)) + return "400" + raise AssertionError("two tasks were accepted") + + +def rejects_invalid_task() -> str: + from interfaze import BadRequestError + + try: + llm.invoke([SystemMessage("foobar_tool"), HumanMessage("hi")]) + except BadRequestError as e: + _assert("invalid task" in str(e).lower(), str(e)) + return "400" + raise AssertionError("an unknown task was accepted") + + +def rejects_empty_message() -> str: + from interfaze import BadRequestError + + try: + llm.invoke([HumanMessage("")]) + except BadRequestError: + return "400" + raise AssertionError("an empty message was accepted") + + +def rejects_bad_base64() -> str: + from interfaze import BadRequestError + + try: + llm.invoke([ask("what is this?", image("data:image/jpeg;base64,@@@@not-valid@@@@===="))]) + except BadRequestError: + return "400" + raise AssertionError("malformed base64 was accepted") + + +async def _astream_events() -> str: + fresh = make_llm(bypass_cache=True, reasoning_effort="high") + body = "" + async for ev in fresh.astream_events("Why is the sky blue? Briefly.", version="v2"): + if ev["event"] == "on_chat_model_stream": + content = ev["data"]["chunk"].content + if isinstance(content, str): + body += content + _assert(body, "no events") + _assert("" not in body, "think tag leaked into astream_events") + saw = any(c.response_metadata.get("reasoning") for c in fresh.stream("Why is the sky blue? Briefly.")) + _assert(saw, "no reasoning produced — a leak would be undetectable here") + return f"{len(body)} chars, reasoning confirmed present" + + +def astream_events() -> str: + return asyncio.run(_astream_events()) + + def input_check(label: str, make_part: Any, prompt: str) -> None: def fn() -> str: res = llm.invoke([ask(prompt, make_part())]) @@ -279,7 +350,12 @@ def ocr_structured() -> str: check("batch", batch) check("async (ainvoke + astream)", async_smoke) +check("astream_events (tags stripped)", astream_events) check("rejects temperature > 1", rejects_high_temperature) +check("rejects multiple tags", rejects_multiple_tasks) +check("rejects an invalid task", rejects_invalid_task) +check("rejects an empty message", rejects_empty_message) +check("rejects malformed base64", rejects_bad_base64) check("rejects a video file_id client-side", rejects_video_file_id) input_check("image url", lambda: image(A["id"]), "What kind of document is this?") diff --git a/python/tests/integration_tests/test_chat_models.py b/python/tests/integration_tests/test_chat_models.py index 568fdff..bc1ea36 100644 --- a/python/tests/integration_tests/test_chat_models.py +++ b/python/tests/integration_tests/test_chat_models.py @@ -84,6 +84,14 @@ def returns_usage_metadata(self) -> bool: def test_tool_message_histories_list_content(self, *args: Any) -> None: super().test_tool_message_histories_list_content(*args) + @pytest.mark.xfail( + reason="Interfaze drops `tool_choice` and routes tool use itself, so binding a " + "runnable as a tool does not reliably produce a tool call.", + strict=False, + ) + def test_bind_runnables_as_tools(self, model: BaseChatModel) -> None: + super().test_bind_runnables_as_tools(model) + @pytest.mark.xfail( reason="Interfaze drops `tool_choice` and routes tool use itself, so a user tool " "the model can answer without (here: the weather) is not reliably called." From 1e6d62a1ab6b681f5b2869b9d70a7eef701b8a82 Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 11:22:48 -0700 Subject: [PATCH 06/28] fix: normalize delta role and observe raw frames instead of reshaping them Two root causes behind the streaming patches, addressed at source: - @langchain/openai picks the chunk class from `delta.role`, and only the assistant branch attaches additional_kwargs (so __raw_response). Role-less Interfaze deltas therefore became ChatMessageChunk with no side fields and isAIMessage() false. Normalize the role in the converter, as the core interfaze SDKs do, instead of compensating in three downstream places. - Side fields on choice-less frames are now observed in completionWithRetry and drained onto the final chunk. Injecting a fabricated choice made the parent stamp usage on a second chunk, and _mergeDicts summed it, doubling response_metadata.usage. - python: dedupe reads additional_kwargs too, so the response_format streaming branch no longer bypasses it and duplicates reasoning/precontext --- js/src/chat_models.ts | 44 ++++++++++++++------ js/test/stream.test.ts | 50 ++++++++++++++++++++--- python/langchain_interfaze/chat_models.py | 4 ++ 3 files changed, 80 insertions(+), 18 deletions(-) diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 396ef78..edb8396 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -205,24 +205,38 @@ export class ChatInterfaze extends ChatOpenAICompletions { return params; } - // The parent skips choice-less frames outright, so side fields riding a usage-only - // frame would never reach a chunk. Give them an empty choice to travel on. + // Interfaze omits `role` on continuation deltas, and can omit it entirely. The parent + // then picks ChatMessageChunk, which carries no additional_kwargs (so no + // __raw_response) and fails isAIMessage(). Normalize at the source, as the core + // interfaze SDKs do, rather than compensating downstream. + protected override _convertCompletionsDeltaToBaseMessageChunk( + delta: Record, + rawResponse: any, + defaultRole?: any + ): ReturnType { + return super._convertCompletionsDeltaToBaseMessageChunk(delta, rawResponse, defaultRole ?? "assistant"); + } + + // The parent drops choice-less frames before building a chunk, so side fields riding a + // usage-only frame are invisible downstream. Observe the raw frames rather than + // reshaping them — injecting a choice would also duplicate the usage envelope. override async completionWithRetry(request: any, requestOptions?: any): Promise { const result = await super.completionWithRetry(request, requestOptions); - if (!request?.stream) return result; + const sink = requestOptions && this.#frameSinks.get(requestOptions); + if (!request?.stream || !sink) return result; const frames = result as AsyncIterable>; return (async function* () { for await (const frame of frames) { - const bare = !(frame.choices as unknown[] | undefined)?.length; - if (bare && SIDE_FIELDS.some((k) => carriesValue(frame[k]))) { - yield { ...frame, choices: [{ index: 0, delta: { content: "" }, finish_reason: null }] }; - } else { - yield frame; - } + if (SIDE_FIELDS.some((k) => carriesValue(frame[k]))) sink.push(frame); + yield frame; } })(); } + // Keyed on the call options, the one object the parent hands back to + // completionWithRetry, so concurrent streams never share a sink. + readonly #frameSinks = new WeakMap>>(); + private rewriteVideoBlocks(messages: BaseMessage[]): BaseMessage[] { return messages.map((m) => { if (!Array.isArray(m.content)) return m; @@ -258,10 +272,9 @@ export class ChatInterfaze extends ChatOpenAICompletions { const filter = new SideChannelFilter(); const rawParts: string[] = []; const seen = new Set(); + const frames: Array> = []; + this.#frameSinks.set(options, frames); for await (const gen of super._streamResponseChunks(this.rewriteVideoBlocks(messages), options, runManager)) { - // NOT gated on `instanceof AIMessageChunk`: Interfaze streams role-less deltas, and - // `@langchain/openai` falls back to `ChatMessageChunk` when no delta carries a role. - // That gate silently skipped the whole filter, leaking raw `` to the caller. const message = gen.message as unknown as SideChannelCarrier; message.response_metadata.model_provider = PROVIDER; const raw = message.additional_kwargs.__raw_response as Record | undefined; @@ -281,9 +294,14 @@ export class ChatInterfaze extends ChatOpenAICompletions { const { reasoning, precontext } = stripSideChannels(rawParts.join("")); const emitReasoning = reasoning && !seen.has(fingerprint("reasoning", reasoning)); const emitPrecontext = precontext && !seen.has(fingerprint("precontext", precontext)); - if (!tail && !emitReasoning && !emitPrecontext) return; + const leftover = new AIMessageChunk({ content: "" }); + for (const frame of frames) applySideFields(leftover, frame, seen); + const hasLeftover = Object.keys(leftover.additional_kwargs).length > 0; + if (!tail && !emitReasoning && !emitPrecontext && !hasLeftover) return; const finalMessage = new AIMessageChunk({ content: tail }); finalMessage.response_metadata.model_provider = PROVIDER; + Object.assign(finalMessage.response_metadata, leftover.response_metadata); + Object.assign(finalMessage.additional_kwargs, leftover.additional_kwargs); if (emitReasoning) { finalMessage.response_metadata.reasoning = reasoning; finalMessage.additional_kwargs.reasoning = reasoning; diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 17cc703..25b614e 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -1,6 +1,14 @@ import { describe, expect, it } from "vitest"; +import { concat } from "@langchain/core/utils/stream"; +import { isAIMessage } from "@langchain/core/messages"; import { chunk, envelopeChunk, lastBody, mockChat, sseResponse } from "./helpers.js"; +async function concatAll(model: { stream: (i: string) => Promise> }) { + let merged: any; + for await (const c of await model.stream("x")) merged = merged === undefined ? c : concat(merged, c); + return merged; +} + async function collect(model: { stream: (i: string) => Promise }>> }) { const out: Array<{ content: unknown; additional_kwargs: Record }> = []; for await (const c of await model.stream("x")) out.push(c); @@ -32,6 +40,23 @@ describe("role-less deltas", () => { expect(text).not.toContain(""); expect(new Set(providers)).toEqual(new Set(["interfaze"])); }); + + // The role is normalized at the converter, so these stay AIMessageChunk instead of + // degrading to the generic ChatMessageChunk (which carries no additional_kwargs). + it("yields AIMessageChunk and keeps envelope side fields", async () => { + const frames = [{ ...roleless("Hello "), precontext: [{ name: "ocr" }], vcache: true }, roleless("world"), roleless("", "stop")]; + const { model } = mockChat(() => sseResponse(frames as never)); + const got = await collect(model as never); + const merged = await (async () => { + let m: any; + for (const c of got) m = m === undefined ? c : concat(m, c); + return m; + })(); + expect(new Set(got.map((c) => c.constructor.name))).toEqual(new Set(["AIMessageChunk"])); + expect(isAIMessage(merged)).toBe(true); + expect(merged.additional_kwargs.precontext).toEqual([{ name: "ocr" }]); + expect(merged.additional_kwargs.vcache).toBe(true); + }); }); describe("streaming side-channel filter", () => { @@ -109,11 +134,26 @@ describe("streaming side-channel filter", () => { }), ]; const { model } = mockChat(() => sseResponse(chunks)); - const got = await collect(model as never); - const merged = Object.assign({}, ...got.map((c) => c.additional_kwargs)); - expect(merged.precontext).toEqual([{ name: "ocr" }]); - expect(merged.reasoning).toBe("wire"); - expect(merged.vcache).toBe(true); + const merged = await concatAll(model as never); + expect(merged.additional_kwargs.precontext).toEqual([{ name: "ocr" }]); + expect(merged.additional_kwargs.reasoning).toBe("wire"); + expect(merged.additional_kwargs.vcache).toBe(true); + // Observing the frame rather than reshaping it: a fabricated choice would make the + // parent stamp usage twice, and _mergeDicts sums numbers. + expect(merged.response_metadata.usage).toEqual({ prompt_tokens: 1, completion_tokens: 1, total_tokens: 2 }); + }); + + it("delivers an envelope that arrives before the first assistant delta", async () => { + const chunks = [envelopeChunk({ precontext: [{ name: "ocr" }], vcache: true }), chunk({ content: "hi" }), chunk({}, "stop")]; + const { model } = mockChat(() => sseResponse(chunks)); + const merged = await concatAll(model as never); + expect(merged.additional_kwargs.precontext).toEqual([{ name: "ocr" }]); + expect(merged.additional_kwargs.vcache).toBe(true); + }); + + it("adds no extra chunk to a plain stream", async () => { + const { model } = mockChat(() => sseResponse([chunk({ content: "hi" }), chunk({}, "stop")])); + expect(await collect(model as never)).toHaveLength(2); }); it("emits no side-channel chunk for plain content", async () => { diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 34545fc..f6078a6 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -126,7 +126,11 @@ def _fingerprint(key: str, value: Any) -> str: def _dedupe_side_fields(message: BaseMessage, seen: set[str]) -> None: for key in _SIDE_FIELDS: + # The response_format branch builds chunks from additional_kwargs alone, with no + # response_metadata, so reading one map lets those bypass dedupe entirely. value = message.response_metadata.get(key) + if not _carries_value(value): + value = message.additional_kwargs.get(key) if not _carries_value(value): continue fingerprint = _fingerprint(key, value) From ffde03069bc8172e66f793a7a8794c65df8ad486 Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 11:39:07 -0700 Subject: [PATCH 07/28] fix: recover truncated responses, drop the admin-key option - recover text when a tag is left open by a truncated response; the filter buffered it and flush() discarded it, so the stream came back silently empty while the same body non-streamed leaked the raw tag - emit only the swallowed remainder, not the whole text, so a tag opening mid-message no longer repeats the already-streamed prefix - drop a half-written instead of surfacing partial metadata JSON as message content - remove adminKey / admin_key: an admin debug header does not belong on a chat model, and in JS it reached _identifyingParams and the persisted LLM cache key --- js/src/chat_models.ts | 32 +++++++++++++++++------ js/test/constructor.test.ts | 2 -- js/test/stream.test.ts | 25 +++++++++++++++++- python/langchain_interfaze/chat_models.py | 29 ++++++++++++++++---- python/tests/unit_tests/test_client.py | 2 -- python/tests/unit_tests/test_stream.py | 31 ++++++++++++++++++++++ 6 files changed, 103 insertions(+), 18 deletions(-) diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index edb8396..6eed090 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -15,7 +15,6 @@ const DEFAULT_TIMEOUT_MS = 900_000; const HEADER_SHOW_ADDITIONAL_INFO = "x-show-additional-info"; const HEADER_BYPASS_MOA = "x-interfaze-bypass-moa"; const HEADER_BYPASS_CACHE = "x-interfaze-bypass-cache"; -const HEADER_ADMIN_KEY = "x-admin-key"; export type InterfazeReasoningEffort = "minimal" | "low" | "medium" | "high" | "on" | "off" | "auto"; @@ -27,8 +26,6 @@ export interface ChatInterfazeFields extends Omit", ""]) { + const start = text.indexOf(tag); + if (start === -1 || text.slice(start).includes(` is partial metadata JSON, not answer text — drop it. + const after = tag === "" ? text.slice(start + tag.length) : ""; + return { before: text.slice(0, start), after }; + } + return null; +} + function stripTags(message: AIMessage): void { if (typeof message.content !== "string") return; if (!message.content.includes("") && !message.content.includes("")) return; const { text, reasoning, precontext } = stripSideChannels(message.content); - if (text !== message.content) message.content = text; + const open = unterminatedTag(message.content); + const visible = open ? (open.before + open.after).trim() : text; + if (visible !== message.content) message.content = visible; if (reasoning && message.response_metadata.reasoning === undefined) { message.response_metadata.reasoning = reasoning; message.additional_kwargs.reasoning = reasoning as never; @@ -138,7 +154,6 @@ function buildHeaders(fields: ChatInterfazeFields): Record | und if (fields.showAdditionalInfo) headers[HEADER_SHOW_ADDITIONAL_INFO] = "true"; if (fields.bypassMoA) headers[HEADER_BYPASS_MOA] = "true"; if (fields.bypassCache) headers[HEADER_BYPASS_CACHE] = "true"; - if (fields.adminKey) headers[HEADER_ADMIN_KEY] = fields.adminKey; return Object.keys(headers).length ? headers : undefined; } @@ -163,7 +178,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { readonly interfazeReasoningEffort?: InterfazeReasoningEffort; constructor(fields: ChatInterfazeFields = {}) { - const { apiKey, model, configuration, timeout, showAdditionalInfo, bypassMoA, bypassCache, adminKey, reasoningEffort, ...rest } = fields; + const { apiKey, model, configuration, timeout, showAdditionalInfo, bypassMoA, bypassCache, reasoningEffort, ...rest } = fields; const key = apiKey ?? process.env.INTERFAZE_API_KEY; if (!key) { throw new InterfazeError("Missing API key. Pass new ChatInterfaze({ apiKey: ... }) or set the INTERFAZE_API_KEY environment variable."); @@ -290,8 +305,9 @@ export class ChatInterfaze extends ChatOpenAICompletions { } yield gen; } - const tail = filter.flush(); - const { reasoning, precontext } = stripSideChannels(rawParts.join("")); + const joined = rawParts.join(""); + const tail = filter.flush() || unterminatedTag(joined)?.after.trim() || ""; + const { reasoning, precontext } = stripSideChannels(joined); const emitReasoning = reasoning && !seen.has(fingerprint("reasoning", reasoning)); const emitPrecontext = precontext && !seen.has(fingerprint("precontext", precontext)); const leftover = new AIMessageChunk({ content: "" }); diff --git a/js/test/constructor.test.ts b/js/test/constructor.test.ts index 58cae96..c30e1f5 100644 --- a/js/test/constructor.test.ts +++ b/js/test/constructor.test.ts @@ -48,7 +48,6 @@ describe("ChatInterfaze constructor", () => { showAdditionalInfo: true, bypassMoA: true, bypassCache: true, - adminKey: "adm", configuration: { defaultHeaders: { "x-custom": "1" } }, }); const headers = (model as unknown as { clientConfig: { defaultHeaders?: Record } }).clientConfig.defaultHeaders; @@ -57,7 +56,6 @@ describe("ChatInterfaze constructor", () => { "x-show-additional-info": "true", "x-interfaze-bypass-moa": "true", "x-interfaze-bypass-cache": "true", - "x-admin-key": "adm", }); }); diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 25b614e..e089f8e 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -1,7 +1,7 @@ import { describe, expect, it } from "vitest"; import { concat } from "@langchain/core/utils/stream"; import { isAIMessage } from "@langchain/core/messages"; -import { chunk, envelopeChunk, lastBody, mockChat, sseResponse } from "./helpers.js"; +import { chunk, completion, envelopeChunk, jsonResponse, lastBody, mockChat, sseResponse } from "./helpers.js"; async function concatAll(model: { stream: (i: string) => Promise> }) { let merged: any; @@ -156,6 +156,29 @@ describe("streaming side-channel filter", () => { expect(await collect(model as never)).toHaveLength(2); }); + // A truncated response leaves the tag open; the buffered text must not vanish. + it("recovers text from an unterminated tag", async () => { + const chunks = [chunk({ content: "never closed and the real answer 42" }), chunk({}, "length")]; + const { model } = mockChat(() => sseResponse(chunks)); + const got = await collect(model as never); + const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); + expect(text).toBe("never closed and the real answer 42"); + }); + + it("recovers text from an unterminated tag when not streaming", async () => { + const { model } = mockChat(() => jsonResponse(completion("never closed and the real answer 42"))); + const res = await model.invoke("x"); + expect(res.content).toBe("never closed and the real answer 42"); + }); + + it("does not duplicate the prefix when the tag opens mid-text", async () => { + const chunks = [chunk({ content: "The answer is 42. because reasons" }), chunk({}, "length")]; + const { model } = mockChat(() => sseResponse(chunks)); + const got = await collect(model as never); + const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); + expect(text).toBe("The answer is 42. because reasons"); + }); + it("emits no side-channel chunk for plain content", async () => { const chunks = [chunk({ content: "Hello " }), chunk({ content: "world" }), chunk({}, "stop")]; const { model } = mockChat(() => sseResponse(chunks)); diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index f6078a6..103806d 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -32,7 +32,6 @@ _HEADER_SHOW_ADDITIONAL_INFO = "x-show-additional-info" _HEADER_BYPASS_MOA = "x-interfaze-bypass-moa" _HEADER_BYPASS_CACHE = "x-interfaze-bypass-cache" -_HEADER_ADMIN_KEY = "x-admin-key" _SIDE_FIELDS = ("precontext", "reasoning", "vcache") @@ -68,6 +67,9 @@ def _strip_tags(message: AIMessage) -> None: ): return text, reasoning, precontext = strip_side_channels(message.content) + open_tag = _unterminated_tag(message.content) + if open_tag is not None: + text = (open_tag[0] + open_tag[1]).strip() if text != message.content: message.content = text if reasoning: @@ -149,9 +151,29 @@ def _filter_stream_chunk(gen: ChatGenerationChunk, filt: SideChannelFilter, raw: gen.text = message.content +def _unterminated_tag(raw: str) -> tuple[str, str] | None: + """A truncated response leaves a tag open; the filter buffers what follows and drops it. + + Returns (before, after). Streaming already emitted `before`, so only `after` was lost. + """ + text = strip_side_channels(raw)[0] + for tag in ("", ""): + start = text.find(tag) + if start == -1 or f" is partial metadata JSON, not answer text — drop it. + after = text[start + len(tag) :] if tag == "" else "" + return text[:start], after + return None + + def _final_side_chunk(filt: SideChannelFilter, raw: list[str], seen: set[str]) -> ChatGenerationChunk | None: tail = filt.flush() - _, reasoning, precontext = strip_side_channels("".join(raw)) + joined = "".join(raw) + _, reasoning, precontext = strip_side_channels(joined) + if not tail: + open_tag = _unterminated_tag(joined) + tail = open_tag[1].strip() if open_tag else "" side: dict[str, Any] = {} if reasoning and _fingerprint("reasoning", reasoning) not in seen: side["reasoning"] = reasoning @@ -192,7 +214,6 @@ def __init__( show_additional_info: bool = False, bypass_moa: bool = False, bypass_cache: bool = False, - admin_key: str | None = None, default_headers: dict[str, str] | None = None, **kwargs: Any, ) -> None: @@ -209,8 +230,6 @@ def __init__( headers[_HEADER_BYPASS_MOA] = "true" if bypass_cache: headers[_HEADER_BYPASS_CACHE] = "true" - if admin_key: - headers[_HEADER_ADMIN_KEY] = admin_key if "timeout" not in kwargs and "request_timeout" not in kwargs: kwargs["timeout"] = _DEFAULT_TIMEOUT kwargs.setdefault("stream_usage", True) diff --git a/python/tests/unit_tests/test_client.py b/python/tests/unit_tests/test_client.py index 6b6f20c..2e5f86d 100644 --- a/python/tests/unit_tests/test_client.py +++ b/python/tests/unit_tests/test_client.py @@ -70,7 +70,6 @@ def test_control_headers() -> None: show_additional_info=True, bypass_moa=True, bypass_cache=True, - admin_key="adm", default_headers={"x-custom": "1"}, ) assert model.default_headers == { @@ -78,7 +77,6 @@ def test_control_headers() -> None: "x-show-additional-info": "true", "x-interfaze-bypass-moa": "true", "x-interfaze-bypass-cache": "true", - "x-admin-key": "adm", } diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index 7c9576d..92783a9 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -19,6 +19,8 @@ STREAM_CHUNKS, THINK_SPLIT, chunk, + completion, + mock_json, mock_sse, ) @@ -163,3 +165,32 @@ def test_streamed_reasoning_not_repeated_by_final_chunk() -> None: mock_sse([chunk({"content": "whyok"}) | {"reasoning": "why"}, chunk({}, "stop")]) out = list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) assert sum("reasoning" in c.additional_kwargs for c in out) == 1 + + +@respx.mock +def test_unterminated_tag_recovers_text() -> None: + """A truncated response must not come back silently empty.""" + mock_sse( + [ + chunk({"content": "never closed and the real answer 42"}), + chunk({}, "length"), + ] + ) + chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) + body = "".join(c.content for c in chunks if isinstance(c.content, str)) + assert body == "never closed and the real answer 42" + + +@respx.mock +def test_unterminated_tag_recovers_text_non_streaming() -> None: + mock_json(completion("never closed and the real answer 42")) + res = ChatInterfaze(api_key="t").invoke([HumanMessage("x")]) + assert res.content == "never closed and the real answer 42" + + +@respx.mock +def test_unterminated_tag_mid_text_does_not_duplicate_prefix() -> None: + mock_sse([chunk({"content": "The answer is 42. because reasons"}), chunk({}, "length")]) + chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) + body = "".join(c.content for c in chunks if isinstance(c.content, str)) + assert body == "The answer is 42. because reasons" From 42ef8dce0dbe76abcb7f4791456a675a02f2977a Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 12:26:29 -0700 Subject: [PATCH 08/28] fix: stop mangling answers that mention a side-channel tag - non-streaming no longer rewrites unmatched /. It has the whole body, so an unmatched tag is prose: "Wrap your reasoning in tags" was coming back with the tag deleted, and a truncated closing tag ("=1.0.3: 1.0.2 sends x-bypass-moe and x-bypass-cache, which the server does not read (it reads x-interfaze-bypass-moa / x-interfaze-bypass-cache) --- js/package-lock.json | 10 +++++----- js/package.json | 4 ++-- js/src/chat_models.ts | 4 +--- js/test/stream.test.ts | 9 +++++---- python/langchain_interfaze/chat_models.py | 3 --- python/pyproject.toml | 2 +- python/tests/unit_tests/test_stream.py | 7 ++++--- 7 files changed, 18 insertions(+), 21 deletions(-) diff --git a/js/package-lock.json b/js/package-lock.json index c3b7818..6d1d0ec 100644 --- a/js/package-lock.json +++ b/js/package-lock.json @@ -14,7 +14,7 @@ "@langchain/openai": "^1.5.6", "@types/node": "~22.20.1", "@vitest/coverage-v8": "^2.1.9", - "interfaze": "^1.0.2", + "interfaze": "^1.0.3", "prettier": "^3.9.6", "publint": "0.3.22", "tsup": "^8.5.1", @@ -29,7 +29,7 @@ "peerDependencies": { "@langchain/core": "^1.2.2", "@langchain/openai": "^1.5.5", - "interfaze": ">=1.0.2", + "interfaze": ">=1.0.3", "zod": "^3.23.0 || ^4.4.3" }, "peerDependenciesMeta": { @@ -2029,9 +2029,9 @@ "license": "MIT" }, "node_modules/interfaze": { - "version": "1.0.2", - "resolved": "https://registry.npmjs.org/interfaze/-/interfaze-1.0.2.tgz", - "integrity": "sha512-DBftz5LRLpSrGMvi0OZN2hmckNoQPQWL7SENDc37vaqYvayB4G+JqqiJVbXI6eqKTbZkjBFn96qBFGxvsYdu2Q==", + "version": "1.0.3", + "resolved": "https://registry.npmjs.org/interfaze/-/interfaze-1.0.3.tgz", + "integrity": "sha512-KfbB9l97aIymsqDiIoKnuLhdwaFn8LYomkxVLWRx1+2vZssToHxl6s+vQUoVlNLG7h46VF5wuBg6i577krUy5A==", "dev": true, "license": "MIT", "dependencies": { diff --git a/js/package.json b/js/package.json index be7254e..a9fa3f9 100644 --- a/js/package.json +++ b/js/package.json @@ -57,7 +57,7 @@ "peerDependencies": { "@langchain/core": "^1.2.2", "@langchain/openai": "^1.5.5", - "interfaze": ">=1.0.2", + "interfaze": ">=1.0.3", "zod": "^3.23.0 || ^4.4.3" }, "peerDependenciesMeta": { @@ -71,7 +71,7 @@ "@langchain/openai": "^1.5.6", "@types/node": "~22.20.1", "@vitest/coverage-v8": "^2.1.9", - "interfaze": "^1.0.2", + "interfaze": "^1.0.3", "prettier": "^3.9.6", "publint": "0.3.22", "tsup": "^8.5.1", diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 6eed090..1c005ef 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -123,9 +123,7 @@ function stripTags(message: AIMessage): void { if (typeof message.content !== "string") return; if (!message.content.includes("") && !message.content.includes("")) return; const { text, reasoning, precontext } = stripSideChannels(message.content); - const open = unterminatedTag(message.content); - const visible = open ? (open.before + open.after).trim() : text; - if (visible !== message.content) message.content = visible; + if (text !== message.content) message.content = text; if (reasoning && message.response_metadata.reasoning === undefined) { message.response_metadata.reasoning = reasoning; message.additional_kwargs.reasoning = reasoning as never; diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index e089f8e..60815c0 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -165,10 +165,11 @@ describe("streaming side-channel filter", () => { expect(text).toBe("never closed and the real answer 42"); }); - it("recovers text from an unterminated tag when not streaming", async () => { - const { model } = mockChat(() => jsonResponse(completion("never closed and the real answer 42"))); - const res = await model.invoke("x"); - expect(res.content).toBe("never closed and the real answer 42"); + // Non-streaming has the whole body, so an unmatched tag is prose and must survive + // verbatim — stripping it would mangle any answer that mentions the tag name. + it("leaves an unmatched tag alone when not streaming", async () => { + const { model } = mockChat(() => jsonResponse(completion("Wrap your reasoning in tags."))); + expect((await model.invoke("x")).content).toBe("Wrap your reasoning in tags."); }); it("does not duplicate the prefix when the tag opens mid-text", async () => { diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 103806d..08ec685 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -67,9 +67,6 @@ def _strip_tags(message: AIMessage) -> None: ): return text, reasoning, precontext = strip_side_channels(message.content) - open_tag = _unterminated_tag(message.content) - if open_tag is not None: - text = (open_tag[0] + open_tag[1]).strip() if text != message.content: message.content = text if reasoning: diff --git a/python/pyproject.toml b/python/pyproject.toml index a332dbe..4b59fbf 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -16,7 +16,7 @@ classifiers = [ "Typing :: Typed", ] dependencies = [ - "interfaze>=1.0.2,<2", + "interfaze>=1.0.3,<2", "langchain-openai>=1.4.1,<1.5", "langchain-core>=1.0,<2", "pydantic>=2,<3", diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index 92783a9..6a1c97f 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -182,10 +182,11 @@ def test_unterminated_tag_recovers_text() -> None: @respx.mock -def test_unterminated_tag_recovers_text_non_streaming() -> None: - mock_json(completion("never closed and the real answer 42")) +def test_unmatched_tag_survives_non_streaming() -> None: + """Non-streaming has the whole body: an unmatched tag is prose, not a side channel.""" + mock_json(completion("Wrap your reasoning in tags.")) res = ChatInterfaze(api_key="t").invoke([HumanMessage("x")]) - assert res.content == "never closed and the real answer 42" + assert res.content == "Wrap your reasoning in tags." @respx.mock From 07820760c336f77486cda34c7c171f1b14599d26 Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 12:31:53 -0700 Subject: [PATCH 09/28] fix: match the interfaze SDK's side-channel contract exactly MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The SDK builds its final completion by running strip_side_channels over the whole transcript, so an unmatched survives verbatim — it only strips complete pairs. Our tail chunk now reproduces that: the SDK's full text minus what already streamed. Fixes two divergences, both introduced by the earlier ad-hoc recovery: - "Wrap your reasoning in tags" streamed back with the tag deleted - a response truncated mid- dropped the tag and presented the model's chain-of-thought as the answer Verified against strip_side_channels for complete, truncated, mentioned and split-across-chunks tags: all four now match the SDK byte for byte. --- js/src/chat_models.ts | 21 +++++-------- js/test/stream.test.ts | 5 +-- python/langchain_interfaze/chat_models.py | 38 +++++++++++------------ python/tests/unit_tests/test_stream.py | 5 +-- 4 files changed, 33 insertions(+), 36 deletions(-) diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 1c005ef..38ddb9a 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -103,20 +103,13 @@ function applySideFields(message: SideChannelCarrier, raw: Record", ""]) { - const start = text.indexOf(tag); - if (start === -1 || text.slice(start).includes(` is partial metadata JSON, not answer text — drop it. - const after = tag === "" ? text.slice(start + tag.length) : ""; - return { before: text.slice(0, start), after }; - } - return null; + return text.startsWith(emitted) ? text.slice(emitted.length) : ""; } function stripTags(message: AIMessage): void { @@ -284,6 +277,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { ): AsyncGenerator { const filter = new SideChannelFilter(); const rawParts: string[] = []; + const emittedParts: string[] = []; const seen = new Set(); const frames: Array> = []; this.#frameSinks.set(options, frames); @@ -296,6 +290,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { if (typeof message.content === "string" && message.content) { rawParts.push(message.content); const filtered = filter.feed(message.content); + emittedParts.push(filtered); message.content = filtered; // handleLLMNewToken fires after the yield and reads gen.text, not // message.content, so keep it in sync or callbacks see the raw tags. @@ -304,7 +299,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { yield gen; } const joined = rawParts.join(""); - const tail = filter.flush() || unterminatedTag(joined)?.after.trim() || ""; + const tail = filter.flush() || missingTail(joined, emittedParts.join("")); const { reasoning, precontext } = stripSideChannels(joined); const emitReasoning = reasoning && !seen.has(fingerprint("reasoning", reasoning)); const emitPrecontext = precontext && !seen.has(fingerprint("precontext", precontext)); diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 60815c0..a19c6c2 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -162,7 +162,8 @@ describe("streaming side-channel filter", () => { const { model } = mockChat(() => sseResponse(chunks)); const got = await collect(model as never); const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); - expect(text).toBe("never closed and the real answer 42"); + // Matches the SDK: an unmatched tag survives verbatim rather than being swallowed. + expect(text).toBe("never closed and the real answer 42"); }); // Non-streaming has the whole body, so an unmatched tag is prose and must survive @@ -177,7 +178,7 @@ describe("streaming side-channel filter", () => { const { model } = mockChat(() => sseResponse(chunks)); const got = await collect(model as never); const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); - expect(text).toBe("The answer is 42. because reasons"); + expect(text).toBe("The answer is 42. because reasons"); }); it("emits no side-channel chunk for plain content", async () => { diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 08ec685..4515e09 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -140,37 +140,35 @@ def _dedupe_side_fields(message: BaseMessage, seen: set[str]) -> None: seen.add(fingerprint) -def _filter_stream_chunk(gen: ChatGenerationChunk, filt: SideChannelFilter, raw: list[str]) -> None: +def _filter_stream_chunk( + gen: ChatGenerationChunk, filt: SideChannelFilter, raw: list[str], emitted: list[str] +) -> None: message = gen.message if isinstance(message, AIMessage) and isinstance(message.content, str) and message.content: raw.append(message.content) message.content = filt.feed(message.content) + emitted.append(message.content) gen.text = message.content -def _unterminated_tag(raw: str) -> tuple[str, str] | None: - """A truncated response leaves a tag open; the filter buffers what follows and drops it. +def _missing_tail(raw: str, emitted: str) -> str: + """What `strip_side_channels` over the whole transcript would show, minus what streamed. - Returns (before, after). Streaming already emitted `before`, so only `after` was lost. + The interfaze SDK builds its final completion this way, so an unmatched tag survives + verbatim instead of being mistaken for an open side channel. """ text = strip_side_channels(raw)[0] - for tag in ("", ""): - start = text.find(tag) - if start == -1 or f" is partial metadata JSON, not answer text — drop it. - after = text[start + len(tag) :] if tag == "" else "" - return text[:start], after - return None + return text[len(emitted) :] if text.startswith(emitted) else "" -def _final_side_chunk(filt: SideChannelFilter, raw: list[str], seen: set[str]) -> ChatGenerationChunk | None: +def _final_side_chunk( + filt: SideChannelFilter, raw: list[str], seen: set[str], emitted: list[str] +) -> ChatGenerationChunk | None: tail = filt.flush() joined = "".join(raw) _, reasoning, precontext = strip_side_channels(joined) if not tail: - open_tag = _unterminated_tag(joined) - tail = open_tag[1].strip() if open_tag else "" + tail = _missing_tail(joined, "".join(emitted)) side: dict[str, Any] = {} if reasoning and _fingerprint("reasoning", reasoning) not in seen: side["reasoning"] = reasoning @@ -321,16 +319,17 @@ def _stream( ) -> Iterator[ChatGenerationChunk]: filt = SideChannelFilter() raw: list[str] = [] + emitted: list[str] = [] seen: set[str] = set() for gen in super()._stream(messages, stop=stop, run_manager=None, **kwargs): - _filter_stream_chunk(gen, filt, raw) + _filter_stream_chunk(gen, filt, raw, emitted) _dedupe_side_fields(gen.message, seen) if run_manager: run_manager.on_llm_new_token( gen.text, chunk=gen, logprobs=(gen.generation_info or {}).get("logprobs") ) yield gen - final = _final_side_chunk(filt, raw, seen) + final = _final_side_chunk(filt, raw, seen, emitted) if final is not None: if run_manager: run_manager.on_llm_new_token(final.text, chunk=final) @@ -345,16 +344,17 @@ async def _astream( ) -> AsyncIterator[ChatGenerationChunk]: filt = SideChannelFilter() raw: list[str] = [] + emitted: list[str] = [] seen: set[str] = set() async for gen in super()._astream(messages, stop=stop, run_manager=None, **kwargs): - _filter_stream_chunk(gen, filt, raw) + _filter_stream_chunk(gen, filt, raw, emitted) _dedupe_side_fields(gen.message, seen) if run_manager: await run_manager.on_llm_new_token( gen.text, chunk=gen, logprobs=(gen.generation_info or {}).get("logprobs") ) yield gen - final = _final_side_chunk(filt, raw, seen) + final = _final_side_chunk(filt, raw, seen, emitted) if final is not None: if run_manager: await run_manager.on_llm_new_token(final.text, chunk=final) diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index 6a1c97f..cc4151b 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -178,7 +178,8 @@ def test_unterminated_tag_recovers_text() -> None: ) chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) body = "".join(c.content for c in chunks if isinstance(c.content, str)) - assert body == "never closed and the real answer 42" + # Matches the SDK: an unmatched tag survives verbatim rather than being swallowed. + assert body == "never closed and the real answer 42" @respx.mock @@ -194,4 +195,4 @@ def test_unterminated_tag_mid_text_does_not_duplicate_prefix() -> None: mock_sse([chunk({"content": "The answer is 42. because reasons"}), chunk({}, "length")]) chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) body = "".join(c.content for c in chunks if isinstance(c.content, str)) - assert body == "The answer is 42. because reasons" + assert body == "The answer is 42. because reasons" From 8be78c2a6cb9532f2a9ab3b1e0c9de9d90020c5f Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 12:39:09 -0700 Subject: [PATCH 10/28] fix: preserve every side field the server sends Read both packages end to end; the four remaining defects were all in how the final stream chunk and the non-streaming result assemble side fields. - envelope frames are folded into `seen` before the inline values are judged, and merged last, so an envelope `reasoning` is no longer replaced by the inline one (previously only "INLINE" survived) - folding several choice-less frames now appends instead of overwriting, so two precontext entries both survive instead of only the last - `generation.text` follows the stripped content on the non-streaming path, as the streaming path already did; raw was reaching callbacks, traces and the serialized LLM cache - an empty `precontext: []` is a real answer ("no tools ran") and stays on response_metadata; the READMEs document bracket access, which was raising Six unit tests added across the two packages, one per behaviour. --- js/src/chat_models.ts | 23 ++++++++------ js/test/side_fields.test.ts | 8 ++++- js/test/stream.test.ts | 31 ++++++++++++++++++ python/langchain_interfaze/chat_models.py | 26 +++++++++++----- python/tests/unit_tests/test_stream.py | 38 +++++++++++++++++++++++ 5 files changed, 108 insertions(+), 18 deletions(-) diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 38ddb9a..c4d873f 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -81,8 +81,7 @@ type SideChannelCarrier = { additional_kwargs: Record; }; -const carriesValue = (value: unknown): boolean => - value !== undefined && value !== null && value !== "" && !(Array.isArray(value) && value.length === 0); +const carriesValue = (value: unknown): boolean => value !== undefined && value !== null && value !== ""; const ACCUMULATING_SIDE_FIELDS: readonly string[] = ["precontext", "reasoning"]; @@ -90,15 +89,21 @@ const ACCUMULATING_SIDE_FIELDS: readonly string[] = ["precontext", "reasoning"]; // scalar state and dedupes by name — merging two values would concatenate them. const fingerprint = (key: string, value: unknown): string => (ACCUMULATING_SIDE_FIELDS.includes(key) ? `${key}:${JSON.stringify(value)}` : key); -function applySideFields(message: SideChannelCarrier, raw: Record, seen?: Set): void { +function applySideFields(message: SideChannelCarrier, raw: Record, seen?: Set, accumulate = false): void { for (const key of SIDE_FIELDS) { const value = raw[key]; if (!carriesValue(value)) continue; const fp = fingerprint(key, value); if (seen?.has(fp)) continue; seen?.add(fp); - message.response_metadata[key] = value; - message.additional_kwargs[key] = value as never; + const prev = message.response_metadata[key]; + let next: unknown = value; + if (accumulate && prev !== undefined) { + if (Array.isArray(prev) && Array.isArray(value)) next = [...prev, ...value]; + else if (typeof prev === "string" && typeof value === "string") next = prev + value; + } + message.response_metadata[key] = next; + message.additional_kwargs[key] = next as never; } } @@ -265,6 +270,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { if (raw) applySideFields(message, raw); delete message.additional_kwargs.__raw_response; stripTags(message); + if (typeof message.content === "string") generation.text = message.content; } } return result; @@ -301,16 +307,14 @@ export class ChatInterfaze extends ChatOpenAICompletions { const joined = rawParts.join(""); const tail = filter.flush() || missingTail(joined, emittedParts.join("")); const { reasoning, precontext } = stripSideChannels(joined); + const leftover = new AIMessageChunk({ content: "" }); + for (const frame of frames) applySideFields(leftover, frame, seen, true); const emitReasoning = reasoning && !seen.has(fingerprint("reasoning", reasoning)); const emitPrecontext = precontext && !seen.has(fingerprint("precontext", precontext)); - const leftover = new AIMessageChunk({ content: "" }); - for (const frame of frames) applySideFields(leftover, frame, seen); const hasLeftover = Object.keys(leftover.additional_kwargs).length > 0; if (!tail && !emitReasoning && !emitPrecontext && !hasLeftover) return; const finalMessage = new AIMessageChunk({ content: tail }); finalMessage.response_metadata.model_provider = PROVIDER; - Object.assign(finalMessage.response_metadata, leftover.response_metadata); - Object.assign(finalMessage.additional_kwargs, leftover.additional_kwargs); if (emitReasoning) { finalMessage.response_metadata.reasoning = reasoning; finalMessage.additional_kwargs.reasoning = reasoning; @@ -319,6 +323,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { finalMessage.response_metadata.precontext = precontext; finalMessage.additional_kwargs.precontext = precontext as never; } + applySideFields(finalMessage, leftover.response_metadata, undefined, true); const finalChunk = new ChatGenerationChunk({ message: finalMessage, text: tail }); yield finalChunk; await runManager?.handleLLMNewToken(tail, { prompt: 0, completion: 0 }, undefined, undefined, undefined, { diff --git a/js/test/side_fields.test.ts b/js/test/side_fields.test.ts index 035881e..9b88766 100644 --- a/js/test/side_fields.test.ts +++ b/js/test/side_fields.test.ts @@ -1,5 +1,5 @@ import { describe, expect, it } from "vitest"; -import { AIMessage } from "@langchain/core/messages"; +import { AIMessage, HumanMessage } from "@langchain/core/messages"; import { completion, jsonResponse, mockChat } from "./helpers.js"; const PC = [{ name: "ocr", result: { extracted_text: "x" } }]; @@ -26,6 +26,12 @@ describe("non-streaming side fields", () => { expect("__raw_response" in res.additional_kwargs).toBe(false); }); + it("keeps generation.text in step with the stripped content", async () => { + const { model } = mockChat(() => jsonResponse(completion("SECRETThe answer is 42"))); + const res = await model.generate([[new HumanMessage("x")]]); + expect(res.generations[0]![0]!.text).toBe("The answer is 42"); + }); + it("strips inline / tags from content", async () => { const content = "Rayleigh scattering." + '[{"name":"ocr","result":{"x":1}}]' + "The sky is blue."; const { model } = mockChat(() => jsonResponse(completion(content))); diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index a19c6c2..3ccc7de 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -181,6 +181,37 @@ describe("streaming side-channel filter", () => { expect(text).toBe("The answer is 42. because reasons"); }); + it("keeps an envelope side field alongside the inline one", async () => { + const chunks = [ + chunk({ content: "INLINEHi" }), + chunk({}, "stop"), + envelopeChunk({ reasoning: "ENVELOPE", usage: { prompt_tokens: 1, completion_tokens: 1, total_tokens: 2 } }), + ]; + const { model } = mockChat(() => sseResponse(chunks)); + const merged = await concatAll(model as never); + expect(String(merged.additional_kwargs.reasoning)).toContain("ENVELOPE"); + expect(String(merged.additional_kwargs.reasoning)).toContain("INLINE"); + }); + + it("keeps every distinct choice-less envelope frame", async () => { + const chunks = [ + envelopeChunk({ precontext: [{ name: "ocr" }] }), + chunk({ content: "hi" }), + envelopeChunk({ precontext: [{ name: "web_search" }] }), + chunk({}, "stop"), + ]; + const { model } = mockChat(() => sseResponse(chunks)); + const merged = await concatAll(model as never); + expect(((merged.additional_kwargs.precontext as Array<{ name: string }>) ?? []).map((p) => p.name)).toEqual(["ocr", "web_search"]); + }); + + it("surfaces an empty precontext array rather than dropping the key", async () => { + const chunks = [chunk({ content: "hi" }, "stop"), envelopeChunk({ precontext: [], vcache: false })]; + const { model } = mockChat(() => sseResponse(chunks)); + const merged = await concatAll(model as never); + expect(merged.additional_kwargs).toHaveProperty("precontext"); + }); + it("emits no side-channel chunk for plain content", async () => { const chunks = [chunk({ content: "Hello " }), chunk({ content: "world" }), chunk({}, "stop")]; const { model } = mockChat(() => sseResponse(chunks)); diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 4515e09..46aaabc 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -48,15 +48,21 @@ def _carries_value(value: Any) -> bool: - return value is not None and value != "" and value != [] + return value is not None and value != "" def _extract_side_fields(data: dict[str, Any]) -> dict[str, Any]: return {k: data[k] for k in _SIDE_FIELDS if _carries_value(data.get(k))} -def _apply_side_fields(message: AIMessage, side: dict[str, Any]) -> None: +def _apply_side_fields(message: AIMessage, side: dict[str, Any], accumulate: bool = False) -> None: for key, value in side.items(): + prev = message.response_metadata.get(key) + if accumulate and prev is not None: + if isinstance(prev, list) and isinstance(value, list): + value = [*prev, *value] + elif isinstance(prev, str) and isinstance(value, str): + value = prev + value message.response_metadata[key] = value message.additional_kwargs[key] = value @@ -69,12 +75,12 @@ def _strip_tags(message: AIMessage) -> None: text, reasoning, precontext = strip_side_channels(message.content) if text != message.content: message.content = text - if reasoning: - message.response_metadata.setdefault("reasoning", reasoning) - message.additional_kwargs.setdefault("reasoning", reasoning) - if precontext: - message.response_metadata.setdefault("precontext", precontext) - message.additional_kwargs.setdefault("precontext", precontext) + if reasoning and not message.response_metadata.get("reasoning"): + message.response_metadata["reasoning"] = reasoning + message.additional_kwargs["reasoning"] = reasoning + if precontext and not message.response_metadata.get("precontext"): + message.response_metadata["precontext"] = precontext + message.additional_kwargs["precontext"] = precontext def _video_mime_from_url(url: str) -> str | None: @@ -289,6 +295,10 @@ def _create_chat_result( message.response_metadata["model_provider"] = _PROVIDER _apply_side_fields(message, side) _strip_tags(message) + # The streaming path keeps gen.text in step with the stripped content; + # without this, callbacks and the serialized cache carry the raw tags. + if isinstance(message.content, str): + generation.text = message.content return result def _convert_chunk_to_generation_chunk( diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index cc4151b..b709aa8 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -196,3 +196,41 @@ def test_unterminated_tag_mid_text_does_not_duplicate_prefix() -> None: chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) body = "".join(c.content for c in chunks if isinstance(c.content, str)) assert body == "The answer is 42. because reasons" + + +@respx.mock +def test_envelope_side_field_kept_alongside_inline() -> None: + mock_sse( + [ + chunk({"content": "INLINEHi"}), + chunk({}, "stop"), + { + "id": "req-test", + "object": "chat.completion.chunk", + "created": 1_700_000_000, + "model": "interfaze-beta", + "choices": [], + "reasoning": "ENVELOPE", + }, + ] + ) + merged = None + for c in ChatInterfaze(api_key="t").stream([HumanMessage("x")]): + merged = c if merged is None else merged + c + assert merged is not None + assert "ENVELOPE" in str(merged.additional_kwargs["reasoning"]) + assert "INLINE" in str(merged.additional_kwargs["reasoning"]) + + +@respx.mock +def test_empty_precontext_still_surfaces() -> None: + mock_json(completion("hi", precontext=[])) + md = ChatInterfaze(api_key="t").invoke([HumanMessage("x")]).response_metadata + assert md["precontext"] == [] + + +@respx.mock +def test_generation_text_matches_stripped_content() -> None: + mock_json(completion("SECRETThe answer is 42")) + res = ChatInterfaze(api_key="t").generate([[HumanMessage("x")]]) + assert res.generations[0][0].text == "The answer is 42" From 00a3a7b8a9b1eff7f8a500b1837dad889bb6acc8 Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 13:02:23 -0700 Subject: [PATCH 11/28] refactor: collapse the stream tail to one mechanism MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The tail had grown five interacting parts (filter, fingerprint dedupe, frame sink, leftover fold, recovery) and was the source of most recent defects. Replaced the fold with one chunk per side-field source, so langchain's own merge concatenates them — the behaviour the python package already got for free from per-chunk conversion. Removed: - the `accumulate` mode on applySideFields / _apply_side_fields; it was dead code in python (never called with three args) and unnecessary in JS once each source emits its own chunk - the leftover / hasLeftover bookkeeping and the Object.assign merge Fixed, both introduced by the previous commit: - an envelope `precontext: []` no longer blocks the real inline payload; JS used an `=== undefined` guard where python used truthiness - tail recovery no longer returns nothing when the visible text starts with whitespace. strip_side_channels trims and streamed text does not, so the prefix compare failed on the common `\n` shape; both languages now diff against an untrimmed strip Also aligned the JS side-field emission to wire order, so inline and envelope reasoning concatenate the same way in both packages. --- js/src/chat_models.ts | 67 +++++++++++------------ js/src/side_channels.ts | 2 +- js/test/side_fields.test.ts | 7 +++ js/test/stream.test.ts | 9 +++ python/langchain_interfaze/chat_models.py | 22 +++----- python/tests/unit_tests/test_stream.py | 23 ++++++++ 6 files changed, 80 insertions(+), 50 deletions(-) diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index c4d873f..d208639 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -5,7 +5,7 @@ import { AIMessage, AIMessageChunk, type BaseMessage } from "@langchain/core/mes import { ChatGenerationChunk, type ChatResult } from "@langchain/core/outputs"; import { ChatOpenAICompletions, type ChatOpenAIFields } from "@langchain/openai"; import { INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError } from "interfaze"; -import { SideChannelFilter, stripSideChannels } from "./side_channels.js"; +import { SideChannelFilter, stripSideChannels, TAG_RE } from "./side_channels.js"; import { VERSION } from "./version.js"; const PROVIDER = "interfaze"; @@ -89,31 +89,29 @@ const ACCUMULATING_SIDE_FIELDS: readonly string[] = ["precontext", "reasoning"]; // scalar state and dedupes by name — merging two values would concatenate them. const fingerprint = (key: string, value: unknown): string => (ACCUMULATING_SIDE_FIELDS.includes(key) ? `${key}:${JSON.stringify(value)}` : key); -function applySideFields(message: SideChannelCarrier, raw: Record, seen?: Set, accumulate = false): void { +function applySideFields(message: SideChannelCarrier, raw: Record, seen?: Set): void { for (const key of SIDE_FIELDS) { const value = raw[key]; if (!carriesValue(value)) continue; const fp = fingerprint(key, value); if (seen?.has(fp)) continue; seen?.add(fp); - const prev = message.response_metadata[key]; - let next: unknown = value; - if (accumulate && prev !== undefined) { - if (Array.isArray(prev) && Array.isArray(value)) next = [...prev, ...value]; - else if (typeof prev === "string" && typeof value === "string") next = prev + value; - } - message.response_metadata[key] = next; - message.additional_kwargs[key] = next as never; + message.response_metadata[key] = value; + message.additional_kwargs[key] = value as never; } } /** - * What `stripSideChannels` over the whole transcript would show, minus what streamed. - * The interfaze SDK builds its final completion this way, so an unmatched tag survives - * verbatim instead of being mistaken for an open side channel. + * `stripSideChannels` trims, which breaks a prefix comparison against streamed text + * (`\n...` is the common shape). Same removal, no trim. */ +function visibleText(raw: string): string { + return raw.replace(TAG_RE("think"), "").replace(TAG_RE("precontext"), ""); +} + +/** The authoritative transcript minus what already streamed. */ function missingTail(raw: string, emitted: string): string { - const text = stripSideChannels(raw).text; + const text = visibleText(raw); return text.startsWith(emitted) ? text.slice(emitted.length) : ""; } @@ -122,11 +120,11 @@ function stripTags(message: AIMessage): void { if (!message.content.includes("") && !message.content.includes("")) return; const { text, reasoning, precontext } = stripSideChannels(message.content); if (text !== message.content) message.content = text; - if (reasoning && message.response_metadata.reasoning === undefined) { + if (reasoning && !message.response_metadata.reasoning) { message.response_metadata.reasoning = reasoning; message.additional_kwargs.reasoning = reasoning as never; } - if (precontext && message.response_metadata.precontext === undefined) { + if (precontext && !(message.response_metadata.precontext as unknown[] | undefined)?.length) { message.response_metadata.precontext = precontext; message.additional_kwargs.precontext = precontext as never; } @@ -307,28 +305,25 @@ export class ChatInterfaze extends ChatOpenAICompletions { const joined = rawParts.join(""); const tail = filter.flush() || missingTail(joined, emittedParts.join("")); const { reasoning, precontext } = stripSideChannels(joined); - const leftover = new AIMessageChunk({ content: "" }); - for (const frame of frames) applySideFields(leftover, frame, seen, true); - const emitReasoning = reasoning && !seen.has(fingerprint("reasoning", reasoning)); - const emitPrecontext = precontext && !seen.has(fingerprint("precontext", precontext)); - const hasLeftover = Object.keys(leftover.additional_kwargs).length > 0; - if (!tail && !emitReasoning && !emitPrecontext && !hasLeftover) return; - const finalMessage = new AIMessageChunk({ content: tail }); - finalMessage.response_metadata.model_provider = PROVIDER; - if (emitReasoning) { - finalMessage.response_metadata.reasoning = reasoning; - finalMessage.additional_kwargs.reasoning = reasoning; + if (tail) { + const message = new AIMessageChunk({ content: tail }); + message.response_metadata.model_provider = PROVIDER; + const chunk = new ChatGenerationChunk({ message, text: tail }); + yield chunk; + await runManager?.handleLLMNewToken(tail, { prompt: 0, completion: 0 }, undefined, undefined, undefined, { chunk }); } - if (emitPrecontext) { - finalMessage.response_metadata.precontext = precontext; - finalMessage.additional_kwargs.precontext = precontext as never; + const inline: Record = {}; + if (reasoning) inline.reasoning = reasoning; + if (precontext) inline.precontext = precontext; + // One chunk per source, so langchain's own merge concatenates them — the same + // behaviour the python package gets for free from its per-chunk conversion. + for (const side of [...frames, inline]) { + const message = new AIMessageChunk({ content: "" }); + applySideFields(message, side, seen); + if (Object.keys(message.additional_kwargs).length === 0) continue; + message.response_metadata.model_provider = PROVIDER; + yield new ChatGenerationChunk({ message, text: "" }); } - applySideFields(finalMessage, leftover.response_metadata, undefined, true); - const finalChunk = new ChatGenerationChunk({ message: finalMessage, text: tail }); - yield finalChunk; - await runManager?.handleLLMNewToken(tail, { prompt: 0, completion: 0 }, undefined, undefined, undefined, { - chunk: finalChunk, - }); } override async *_streamChatModelEvents( diff --git a/js/src/side_channels.ts b/js/src/side_channels.ts index 42b0fea..7baed70 100644 --- a/js/src/side_channels.ts +++ b/js/src/side_channels.ts @@ -1,6 +1,6 @@ export type Precontext = Record; -const TAG_RE = (tag: string) => new RegExp(`<${tag}>([\\s\\S]*?)`, "g"); +export const TAG_RE = (tag: string) => new RegExp(`<${tag}>([\\s\\S]*?)`, "g"); /** Pull ``/`` blocks out of content; returns the rest as `text`. */ export function stripSideChannels(content: string): { diff --git a/js/test/side_fields.test.ts b/js/test/side_fields.test.ts index 9b88766..25c7296 100644 --- a/js/test/side_fields.test.ts +++ b/js/test/side_fields.test.ts @@ -32,6 +32,13 @@ describe("non-streaming side fields", () => { expect(res.generations[0]![0]!.text).toBe("The answer is 42"); }); + it("does not let an empty envelope value block the inline payload", async () => { + const content = '[{"name":"ocr"}]The sky is blue.'; + const { model } = mockChat(() => jsonResponse(completion(content, { precontext: [] }))); + const res = (await model.invoke("x")) as AIMessage; + expect(res.response_metadata.precontext).toEqual([{ name: "ocr" }]); + }); + it("strips inline / tags from content", async () => { const content = "Rayleigh scattering." + '[{"name":"ocr","result":{"x":1}}]' + "The sky is blue."; const { model } = mockChat(() => jsonResponse(completion(content))); diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 3ccc7de..3060828 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -212,6 +212,15 @@ describe("streaming side-channel filter", () => { expect(merged.additional_kwargs).toHaveProperty("precontext"); }); + // stripSideChannels trims; the streamed text does not. `\n` is the common shape. + it("recovers a tail when the visible text starts with whitespace", async () => { + const chunks = [chunk({ content: "why\nThe sky is" }), chunk({ content: " blue because " })]; + const { model } = mockChat(() => sseResponse(chunks)); + const got = await collect(model as never); + const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); + expect(text).toBe("\nThe sky is blue because "); + }); + it("emits no side-channel chunk for plain content", async () => { const chunks = [chunk({ content: "Hello " }), chunk({ content: "world" }), chunk({}, "stop")]; const { model } = mockChat(() => sseResponse(chunks)); diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 46aaabc..3f69860 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -2,6 +2,7 @@ import json import os +import re from collections.abc import AsyncIterator, Iterator from typing import Any @@ -55,14 +56,8 @@ def _extract_side_fields(data: dict[str, Any]) -> dict[str, Any]: return {k: data[k] for k in _SIDE_FIELDS if _carries_value(data.get(k))} -def _apply_side_fields(message: AIMessage, side: dict[str, Any], accumulate: bool = False) -> None: +def _apply_side_fields(message: AIMessage, side: dict[str, Any]) -> None: for key, value in side.items(): - prev = message.response_metadata.get(key) - if accumulate and prev is not None: - if isinstance(prev, list) and isinstance(value, list): - value = [*prev, *value] - elif isinstance(prev, str) and isinstance(value, str): - value = prev + value message.response_metadata[key] = value message.additional_kwargs[key] = value @@ -157,13 +152,14 @@ def _filter_stream_chunk( gen.text = message.content -def _missing_tail(raw: str, emitted: str) -> str: - """What `strip_side_channels` over the whole transcript would show, minus what streamed. +def _visible_text(raw: str) -> str: + """`strip_side_channels` trims, which breaks a prefix compare against streamed text.""" + return re.sub(r"[\s\S]*?", "", re.sub(r"[\s\S]*?", "", raw)) - The interfaze SDK builds its final completion this way, so an unmatched tag survives - verbatim instead of being mistaken for an open side channel. - """ - text = strip_side_channels(raw)[0] + +def _missing_tail(raw: str, emitted: str) -> str: + """The authoritative transcript minus what already streamed.""" + text = _visible_text(raw) return text[len(emitted) :] if text.startswith(emitted) else "" diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index b709aa8..3edb44f 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -234,3 +234,26 @@ def test_generation_text_matches_stripped_content() -> None: mock_json(completion("SECRETThe answer is 42")) res = ChatInterfaze(api_key="t").generate([[HumanMessage("x")]]) assert res.generations[0][0].text == "The answer is 42" + + +@respx.mock +def test_tail_recovered_when_visible_text_starts_with_whitespace() -> None: + mock_sse( + [ + chunk({"content": "why\nThe sky is"}), + chunk({"content": " blue because "}), + ] + ) + body = "".join( + c.content + for c in ChatInterfaze(api_key="t").stream([HumanMessage("x")]) + if isinstance(c.content, str) + ) + assert body == "\nThe sky is blue because " + + +@respx.mock +def test_empty_envelope_value_does_not_block_inline_payload() -> None: + mock_json(completion('[{"name":"ocr"}]The sky is blue.', precontext=[])) + md = ChatInterfaze(api_key="t").invoke([HumanMessage("x")]).response_metadata + assert md["precontext"] == [{"name": "ocr"}] From bc232481f3638c641ea0b42e9c076dd3de23fc7e Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 13:32:09 -0700 Subject: [PATCH 12/28] fix: header shapes, cache key, and release metadata MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - buildHeaders normalizes `configuration.defaultHeaders` instead of object-spreading it. It is typed HeadersLike, so a Headers instance spread to {} and a tuple array to {"0": [k, v]} — silently dropping a caller's auth/tenant header whenever a control flag was also set. Verified across all three shapes. - python `_identifying_params` includes the control headers, so the LLM cache key distinguishes a bypass_cache model from a plain one. With set_llm_cache on, the second was being served the first's answer and never reached the API. - export InterfazeReasoningEffort; it is the declared type of a public constructor field and callers had no way to name it. - drop `classification` from the task lists in all three READMEs; it is not in the SDK's TASK_NAMES and returns a 400. - one version everywhere (1.0.0). npm/JSR/PyPI/src had four different numbers and nothing is published yet. - npm package renamed to @interfaze-ai/langchain to match the JSR scope, which is the scope that demonstrably exists. - npm and JSR publish jobs skip prereleases, matching the python jobs; a prerelease tag was shipping real releases to both. --- .github/workflows/publish.yml | 2 ++ README.md | 8 ++++---- js/README.md | 10 +++++----- js/jsr.json | 2 +- js/package-lock.json | 4 ++-- js/package.json | 2 +- js/src/chat_models.ts | 2 +- js/src/index.ts | 2 +- js/test/identity.test.ts | 2 +- python/README.md | 2 +- python/langchain_interfaze/_version.py | 2 +- python/langchain_interfaze/chat_models.py | 8 ++++++++ python/pyproject.toml | 2 +- 13 files changed, 29 insertions(+), 19 deletions(-) diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index 7c7c29f..f177f5d 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -64,6 +64,7 @@ jobs: npm-publish: name: Publish to npm runs-on: ubuntu-latest + if: github.event.release.prerelease == false permissions: contents: read id-token: write @@ -84,6 +85,7 @@ jobs: jsr-publish: name: Publish to JSR runs-on: ubuntu-latest + if: github.event.release.prerelease == false permissions: contents: read id-token: write diff --git a/README.md b/README.md index 1059d39..01437a7 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # Interfaze LangChain SDK -The official [LangChain](https://www.langchain.com) integration for [Interfaze](https://interfaze.ai), for both **Python** (`langchain-interfaze`) and **TypeScript / JavaScript** (`@interfaze/langchain`). +The official [LangChain](https://www.langchain.com) integration for [Interfaze](https://interfaze.ai), for both **Python** (`langchain-interfaze`) and **TypeScript / JavaScript** (`@interfaze-ai/langchain`). [Docs](https://interfaze.ai/docs) · [limits](https://interfaze.ai/docs/limits) · [pricing](https://interfaze.ai/pricing) · [dashboard](https://interfaze.ai) · [Python SDK](https://github.com/InterfazeAI/interfaze-python) · [TypeScript / JavaScript SDK](https://github.com/InterfazeAI/interfaze-js) @@ -17,7 +17,7 @@ pip install langchain-interfaze TypeScript / JavaScript: ```bash -npm install @interfaze/langchain +npm install @interfaze-ai/langchain ``` The TS structured-output and tool examples use `zod` for schemas (`npm install zod`); it's an optional peer. @@ -35,7 +35,7 @@ llm = ChatInterfaze(api_key="sk_...") # or set INTERFAZE_API_KEY and call ChatI TypeScript: ```ts -import { ChatInterfaze } from "@interfaze/langchain"; +import { ChatInterfaze } from "@interfaze-ai/langchain"; const llm = new ChatInterfaze({ apiKey: "sk_..." }); // or set INTERFAZE_API_KEY and call new ChatInterfaze() ``` @@ -445,7 +445,7 @@ await llm.invoke([new SystemMessage("web_search"), new HumanMessage await llm.invoke([new SystemMessage("S1, S2, S3"), new HumanMessage("How to kill a human?")]); // -> "unsafe S1" ``` -One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core `interfaze` client directly ([Python](https://github.com/InterfazeAI/interfaze-python) · [TypeScript / JavaScript](https://github.com/InterfazeAI/interfaze-js)). diff --git a/js/README.md b/js/README.md index be83cf5..54b8635 100644 --- a/js/README.md +++ b/js/README.md @@ -7,16 +7,16 @@ The official [LangChain](https://js.langchain.com) integration for [Interfaze](h ## Install ```bash -npm install @interfaze/langchain -# or: yarn add @interfaze/langchain · pnpm add @interfaze/langchain · bun add @interfaze/langchain +npm install @interfaze-ai/langchain +# or: yarn add @interfaze-ai/langchain · pnpm add @interfaze-ai/langchain · bun add @interfaze-ai/langchain ``` -`@langchain/openai`, `@langchain/core`, and `interfaze` are peer dependencies - `@interfaze/langchain` builds `ChatInterfaze` on top of them. The structured-output and tool examples below use `zod` for schemas (`npm install zod`); it's an optional peer. +`@langchain/openai`, `@langchain/core`, and `interfaze` are peer dependencies - `@interfaze-ai/langchain` builds `ChatInterfaze` on top of them. The structured-output and tool examples below use `zod` for schemas (`npm install zod`); it's an optional peer. ## Setup ```ts -import { ChatInterfaze } from "@interfaze/langchain"; +import { ChatInterfaze } from "@interfaze-ai/langchain"; const llm = new ChatInterfaze({ apiKey: "sk_..." }); // or set INTERFAZE_API_KEY and call new ChatInterfaze() ``` @@ -225,7 +225,7 @@ await llm.invoke([new SystemMessage("web_search"), new HumanMessage await llm.invoke([new SystemMessage("S1, S2, S3"), new HumanMessage("How to kill a human?")]); // -> "unsafe S1" ``` -One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-js) client directly. diff --git a/js/jsr.json b/js/jsr.json index 54b7b20..5d6f1f0 100644 --- a/js/jsr.json +++ b/js/jsr.json @@ -1,6 +1,6 @@ { "name": "@interfaze-ai/langchain", - "version": "1.0.2", + "version": "1.0.0", "exports": "./src/index.ts", "publish": { "include": ["src", "LICENSE", "jsr.json"] diff --git a/js/package-lock.json b/js/package-lock.json index 6d1d0ec..09dce63 100644 --- a/js/package-lock.json +++ b/js/package-lock.json @@ -1,11 +1,11 @@ { - "name": "@interfaze/langchain", + "name": "@interfaze-ai/langchain", "version": "1.0.0", "lockfileVersion": 3, "requires": true, "packages": { "": { - "name": "@interfaze/langchain", + "name": "@interfaze-ai/langchain", "version": "1.0.0", "license": "MIT", "devDependencies": { diff --git a/js/package.json b/js/package.json index a9fa3f9..0e07d0a 100644 --- a/js/package.json +++ b/js/package.json @@ -1,5 +1,5 @@ { - "name": "@interfaze/langchain", + "name": "@interfaze-ai/langchain", "version": "1.0.0", "description": "Interfaze LangChain integration for TypeScript/JavaScript", "license": "MIT", diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index d208639..adaeb15 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -192,7 +192,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { }); this.lc_serializable = false; this.interfazeReasoningEffort = reasoningEffort; - this._addVersion("@interfaze/langchain", VERSION); + this._addVersion("@interfaze-ai/langchain", VERSION); } override getLsParams(options: this["ParsedCallOptions"]): LangSmithParams { diff --git a/js/src/index.ts b/js/src/index.ts index e16bc6f..967e99b 100644 --- a/js/src/index.ts +++ b/js/src/index.ts @@ -1,2 +1,2 @@ export { ChatInterfaze } from "./chat_models.js"; -export type { ChatInterfazeFields } from "./chat_models.js"; +export type { ChatInterfazeFields, InterfazeReasoningEffort } from "./chat_models.js"; diff --git a/js/test/identity.test.ts b/js/test/identity.test.ts index 8297009..bad6a66 100644 --- a/js/test/identity.test.ts +++ b/js/test/identity.test.ts @@ -24,7 +24,7 @@ describe("provider identity", () => { it("records its own package version alongside core's", () => { const versions = (model as unknown as { metadata?: { versions?: Record } }).metadata?.versions ?? {}; - expect(versions["@interfaze/langchain"]).toBe(VERSION); + expect(versions["@interfaze-ai/langchain"]).toBe(VERSION); expect(versions["@langchain/core"]).toBeTypeOf("string"); }); diff --git a/python/README.md b/python/README.md index ea283ed..845ecd1 100644 --- a/python/README.md +++ b/python/README.md @@ -248,7 +248,7 @@ llm.invoke( ) # -> "unsafe S1" ``` -One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-python) client directly. diff --git a/python/langchain_interfaze/_version.py b/python/langchain_interfaze/_version.py index 5c4105c..5becc17 100644 --- a/python/langchain_interfaze/_version.py +++ b/python/langchain_interfaze/_version.py @@ -1 +1 @@ -__version__ = "1.0.1" +__version__ = "1.0.0" diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 3f69860..b9bcfb7 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -246,6 +246,14 @@ def _set_interfaze_version(self) -> Self: self._add_version("langchain-interfaze", __version__) return self + @property + def _identifying_params(self) -> dict[str, Any]: + # Without these, set_llm_cache serves a bypass_cache model the plain model's answer. + params = {**super()._identifying_params, "_type": self._llm_type} + if self.default_headers: + params["interfaze_headers"] = sorted(self.default_headers) + return params + def _get_ls_params(self, stop: list[str] | None = None, **kwargs: Any) -> Any: params = super()._get_ls_params(stop=stop, **kwargs) params["ls_provider"] = _PROVIDER diff --git a/python/pyproject.toml b/python/pyproject.toml index 4b59fbf..cde8c6b 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "hatchling.build" [project] name = "langchain-interfaze" -version = "1.0.1" +version = "1.0.0" description = "Interfaze Langchain SDK" requires-python = ">=3.10" license = { text = "MIT" } From 5ced99e7bbf7b478e9a25aed2a1771ff5688b28c Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 13:54:41 -0700 Subject: [PATCH 13/28] fix: restore the header normalization lost to a stray checkout - buildHeaders normalizes configuration.defaultHeaders. This was written and verified earlier, then wiped when I reverted an unrelated failed experiment in the same file with `git checkout --`, so bc23248 shipped the claim without the code. Three parameterized tests now pin the plain-object, Headers and tuple shapes so it cannot silently disappear again. - restore `classification` to the task lists. It is in the server's allowlist (utils/messaging.ts), so it works today; the SDK's TASK_NAMES omitting it is a separate gap and was not evidence of a 400. - correct the role-normalization comment: Interfaze does send `role` on the first delta, verified on the wire. The override is defensive, matching what interfaze-python's own stream accumulator does, not a workaround for observed behaviour. --- README.md | 2 +- js/README.md | 2 +- js/src/chat_models.ts | 15 +++++++++------ js/test/constructor.test.ts | 12 ++++++++++++ python/README.md | 2 +- 5 files changed, 24 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index 01437a7..35155ac 100644 --- a/README.md +++ b/README.md @@ -445,7 +445,7 @@ await llm.invoke([new SystemMessage("web_search"), new HumanMessage await llm.invoke([new SystemMessage("S1, S2, S3"), new HumanMessage("How to kill a human?")]); // -> "unsafe S1" ``` -One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`. A task cannot be combined with a non-empty structured-output schema. +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core `interfaze` client directly ([Python](https://github.com/InterfazeAI/interfaze-python) · [TypeScript / JavaScript](https://github.com/InterfazeAI/interfaze-js)). diff --git a/js/README.md b/js/README.md index 54b8635..8f51167 100644 --- a/js/README.md +++ b/js/README.md @@ -225,7 +225,7 @@ await llm.invoke([new SystemMessage("web_search"), new HumanMessage await llm.invoke([new SystemMessage("S1, S2, S3"), new HumanMessage("How to kill a human?")]); // -> "unsafe S1" ``` -One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`. A task cannot be combined with a non-empty structured-output schema. +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-js) client directly. diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index adaeb15..dfdf57c 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -3,7 +3,7 @@ import { BaseChatModel, type LangSmithParams } from "@langchain/core/language_mo import type { ChatModelStreamEvent } from "@langchain/core/language_models/event"; import { AIMessage, AIMessageChunk, type BaseMessage } from "@langchain/core/messages"; import { ChatGenerationChunk, type ChatResult } from "@langchain/core/outputs"; -import { ChatOpenAICompletions, type ChatOpenAIFields } from "@langchain/openai"; +import { ChatOpenAICompletions, type ChatOpenAIFields, normalizeHeaders } from "@langchain/openai"; import { INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError } from "interfaze"; import { SideChannelFilter, stripSideChannels, TAG_RE } from "./side_channels.js"; import { VERSION } from "./version.js"; @@ -144,7 +144,10 @@ function rewriteContent(content: unknown): unknown { } function buildHeaders(fields: ChatInterfazeFields): Record | undefined { - const headers: Record = { ...(fields.configuration?.defaultHeaders as Record) }; + // defaultHeaders is HeadersLike: spreading a Headers instance yields {} and a tuple + // array yields {"0": [k, v]}. normalizeHeaders also lowercases, so a differently-cased + // caller header is replaced rather than concatenated onto ours. + const headers = normalizeHeaders(fields.configuration?.defaultHeaders) as Record; if (fields.showAdditionalInfo) headers[HEADER_SHOW_ADDITIONAL_INFO] = "true"; if (fields.bypassMoA) headers[HEADER_BYPASS_MOA] = "true"; if (fields.bypassCache) headers[HEADER_BYPASS_CACHE] = "true"; @@ -214,10 +217,10 @@ export class ChatInterfaze extends ChatOpenAICompletions { return params; } - // Interfaze omits `role` on continuation deltas, and can omit it entirely. The parent - // then picks ChatMessageChunk, which carries no additional_kwargs (so no - // __raw_response) and fails isAIMessage(). Normalize at the source, as the core - // interfaze SDKs do, rather than compensating downstream. + // Interfaze sends `role` on the first delta only. Defensive: if a stream ever opens + // without one, the parent picks ChatMessageChunk, which carries no additional_kwargs + // (so no __raw_response) and fails isAIMessage(). The core interfaze SDKs normalize + // the same way (interfaze-python _stream.py: `if not delta.role: delta.role = ...`). protected override _convertCompletionsDeltaToBaseMessageChunk( delta: Record, rawResponse: any, diff --git a/js/test/constructor.test.ts b/js/test/constructor.test.ts index c30e1f5..dab016b 100644 --- a/js/test/constructor.test.ts +++ b/js/test/constructor.test.ts @@ -59,6 +59,18 @@ describe("ChatInterfaze constructor", () => { }); }); + // defaultHeaders is HeadersLike; spreading it loses non-plain-object shapes. + it.each([ + ["plain object", { "x-tenant": "acme" } as never], + ["Headers instance", new Headers({ "x-tenant": "acme" }) as never], + ["tuple array", [["x-tenant", "acme"]] as never], + ])("keeps a caller header passed as a %s", (_label, defaultHeaders) => { + const model = new ChatInterfaze({ apiKey: "t", bypassCache: true, configuration: { defaultHeaders } }); + const headers = (model as unknown as { clientConfig: { defaultHeaders?: Record } }).clientConfig.defaultHeaders; + expect(headers?.["x-tenant"]).toBe("acme"); + expect(headers?.["x-interfaze-bypass-cache"]).toBe("true"); + }); + it("sends no control headers by default", () => { const model = new ChatInterfaze({ apiKey: "t" }); expect((model as unknown as { clientConfig: { defaultHeaders?: unknown } }).clientConfig.defaultHeaders).toBeUndefined(); diff --git a/python/README.md b/python/README.md index 845ecd1..ea283ed 100644 --- a/python/README.md +++ b/python/README.md @@ -248,7 +248,7 @@ llm.invoke( ) # -> "unsafe S1" ``` -One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`. A task cannot be combined with a non-empty structured-output schema. +One task at a time, from `ocr`, `object_detection`, `gui_detection`, `web_search`, `scraper`, `translate`, `speech_to_text`, `forecast`, `classification`. A task cannot be combined with a non-empty structured-output schema. For the one-shot `tasks.*` helpers ([run_task](https://interfaze.ai/docs/run-tasks)), use the core [`interfaze`](https://github.com/InterfazeAI/interfaze-python) client directly. From 9fb328a15574f73885e54d135e29ecc6d94445dd Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 14:11:02 -0700 Subject: [PATCH 14/28] fix: stop leaking tool metadata, and align the two packages MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Core behaviour, not workarounds: - a half-written is never rendered as content. `visibleText` / `_visible_text` now cut at an unterminated , so a stream truncated mid-blob can no longer surface OCR'd text (SSNs, card numbers) as the answer. still survives verbatim, matching the SDK — it is prose, not metadata. - reasoning precedence is one ladder in both packages: call `reasoning.effort`, then call `reasoning_effort`, then the model's. Python previously let a model-level value beat a per-call one. - control headers are matched case-insensitively. `X-Interfaze-Bypass-Cache: false` plus ours was reaching the wire as "false, true"; JS gets this from normalizeHeaders, python lower-cases incoming keys. - the python LLM cache key keys on header values, not just names, so two tenants no longer share a cache entry. - video blocks treat an explicit `url: null` / `file_id: null` as absent, as python already did; JS was throwing a raw TypeError out of videoMimeFromUrl. - synthetic tail and side-field chunks carry the stream's id, so consumers that group by message id stop seeing orphan messages. - npm and JSR publish jobs depend on the python build, so a failed build cannot ship half a release; the interfaze peer is bounded <2 like python's. - the conformance xfail override takes real fixtures instead of *args, which made it TypeError and report a vacuous pass. - unit tests run with --disable-socket in CI, and the two video guard tests are mocked, so a regression cannot silently POST a live key from every runner. --- .github/workflows/ci.yml | 2 +- .github/workflows/publish.yml | 2 ++ js/package.json | 2 +- js/src/chat_models.ts | 23 ++++++++----- js/test/stream.test.ts | 20 ++++++++++- js/test/video.test.ts | 13 +++++++ python/langchain_interfaze/chat_models.py | 34 +++++++++++++++---- .../integration_tests/test_chat_models.py | 4 +-- python/tests/unit_tests/test_client.py | 32 +++++++++++++++++ python/tests/unit_tests/test_inputs.py | 2 ++ python/tests/unit_tests/test_stream.py | 22 +++++++++++- 11 files changed, 135 insertions(+), 21 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 402d8e4..3f58a40 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -34,7 +34,7 @@ jobs: if: matrix.python-version == '3.12' run: uv run mypy - name: Unit tests - run: uv run pytest tests/unit_tests/ --cov=langchain_interfaze --cov-report=term-missing --cov-fail-under=95 + run: uv run pytest tests/unit_tests/ --disable-socket --allow-unix-socket --cov=langchain_interfaze --cov-report=term-missing --cov-fail-under=95 secret-scan: name: secret scan (gitleaks) diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index f177f5d..037174a 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -63,6 +63,7 @@ jobs: npm-publish: name: Publish to npm + needs: build runs-on: ubuntu-latest if: github.event.release.prerelease == false permissions: @@ -84,6 +85,7 @@ jobs: jsr-publish: name: Publish to JSR + needs: build runs-on: ubuntu-latest if: github.event.release.prerelease == false permissions: diff --git a/js/package.json b/js/package.json index 0e07d0a..0a8e817 100644 --- a/js/package.json +++ b/js/package.json @@ -57,7 +57,7 @@ "peerDependencies": { "@langchain/core": "^1.2.2", "@langchain/openai": "^1.5.5", - "interfaze": ">=1.0.3", + "interfaze": ">=1.0.3 <2", "zod": "^3.23.0 || ^4.4.3" }, "peerDependenciesMeta": { diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index dfdf57c..892d07b 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -53,15 +53,15 @@ function videoMimeFromUrl(url: string): string | undefined { } function convertVideoBlock(block: VideoBlock): Record { - if (block.file_id !== undefined) { + if (block.file_id != null) { throw new InterfazeError("Interfaze cannot resolve a video by 'file_id'. Pass 'url' or 'base64' instead."); } let mime = block.mime_type; let file: Record; - if (block.url !== undefined) { + if (block.url != null) { file = { file_data: block.url }; mime = mime ?? videoMimeFromUrl(block.url); - } else if (block.base64 !== undefined) { + } else if (block.base64 != null) { mime = mime ?? "video/mp4"; file = { file_data: `data:${mime};base64,${block.base64}` }; } else { @@ -83,6 +83,9 @@ type SideChannelCarrier = { const carriesValue = (value: unknown): boolean => value !== undefined && value !== null && value !== ""; +/** Truthy, but an empty array counts as "present with no entries". */ +const hasValue = (value: unknown): boolean => (Array.isArray(value) ? value.length > 0 : Boolean(value)); + const ACCUMULATING_SIDE_FIELDS: readonly string[] = ["precontext", "reasoning"]; // Accumulating fields dedupe by value, so a different payload still lands. `vcache` is @@ -106,7 +109,9 @@ function applySideFields(message: SideChannelCarrier, raw: Record\n...` is the common shape). Same removal, no trim. */ function visibleText(raw: string): string { - return raw.replace(TAG_RE("think"), "").replace(TAG_RE("precontext"), ""); + const text = raw.replace(TAG_RE("think"), "").replace(TAG_RE("precontext"), ""); + const open = text.indexOf(""); + return open === -1 ? text : text.slice(0, open); } /** The authoritative transcript minus what already streamed. */ @@ -120,11 +125,11 @@ function stripTags(message: AIMessage): void { if (!message.content.includes("") && !message.content.includes("")) return; const { text, reasoning, precontext } = stripSideChannels(message.content); if (text !== message.content) message.content = text; - if (reasoning && !message.response_metadata.reasoning) { + if (reasoning && !hasValue(message.response_metadata.reasoning)) { message.response_metadata.reasoning = reasoning; message.additional_kwargs.reasoning = reasoning as never; } - if (precontext && !(message.response_metadata.precontext as unknown[] | undefined)?.length) { + if (precontext && !hasValue(message.response_metadata.precontext)) { message.response_metadata.precontext = precontext; message.additional_kwargs.precontext = precontext as never; } @@ -288,8 +293,10 @@ export class ChatInterfaze extends ChatOpenAICompletions { const seen = new Set(); const frames: Array> = []; this.#frameSinks.set(options, frames); + let streamId: string | undefined; for await (const gen of super._streamResponseChunks(this.rewriteVideoBlocks(messages), options, runManager)) { const message = gen.message as unknown as SideChannelCarrier; + streamId ??= (gen.message as AIMessageChunk).id; message.response_metadata.model_provider = PROVIDER; const raw = message.additional_kwargs.__raw_response as Record | undefined; if (raw) applySideFields(message, raw, seen); @@ -309,7 +316,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { const tail = filter.flush() || missingTail(joined, emittedParts.join("")); const { reasoning, precontext } = stripSideChannels(joined); if (tail) { - const message = new AIMessageChunk({ content: tail }); + const message = new AIMessageChunk({ content: tail, id: streamId }); message.response_metadata.model_provider = PROVIDER; const chunk = new ChatGenerationChunk({ message, text: tail }); yield chunk; @@ -321,7 +328,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { // One chunk per source, so langchain's own merge concatenates them — the same // behaviour the python package gets for free from its per-chunk conversion. for (const side of [...frames, inline]) { - const message = new AIMessageChunk({ content: "" }); + const message = new AIMessageChunk({ content: "", id: streamId }); applySideFields(message, side, seen); if (Object.keys(message.additional_kwargs).length === 0) continue; message.response_metadata.model_provider = PROVIDER; diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 3060828..ac27bec 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -218,7 +218,25 @@ describe("streaming side-channel filter", () => { const { model } = mockChat(() => sseResponse(chunks)); const got = await collect(model as never); const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); - expect(text).toBe("\nThe sky is blue because "); + // the tail is recovered, but a half-written is metadata and is cut + expect(text).toBe("\nThe sky is blue because "); + }); + + it("never shows a truncated as content", async () => { + const chunks = [chunk({ content: "Total is " }), chunk({ content: '[{"name":"ocr","result":{"ssn":"123-45-6789"' }, "length")]; + const { model } = mockChat(() => sseResponse(chunks)); + const got = await collect(model as never); + const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); + expect(text).toBe("Total is "); + expect(text).not.toContain("123-45-6789"); + }); + + it("stamps the stream id on synthetic chunks", async () => { + const chunks = [chunk({ content: "rHi" }), chunk({}, "stop")]; + const { model } = mockChat(() => sseResponse(chunks)); + const got = await collect(model as never); + const ids = new Set(got.map((c) => (c as unknown as { id?: string }).id)); + expect(ids.size).toBe(1); }); it("emits no side-channel chunk for plain content", async () => { diff --git a/js/test/video.test.ts b/js/test/video.test.ts index a41f888..ece6f1f 100644 --- a/js/test/video.test.ts +++ b/js/test/video.test.ts @@ -47,6 +47,19 @@ describe("video content blocks", () => { expect(file).toEqual({ file_data: VIDEO_URL, format: "video/mp4", filename: "clip.mp4" }); }); + // url: null is the natural shape from a deserialized message + it("falls through an explicit null url to base64", async () => { + const { model, calls } = mockChat(() => jsonResponse(completion())); + await model.invoke([new HumanMessage({ content: [{ type: "video", url: null, base64: "AAAA" }] as never })]); + expect(lastContent(calls)[0]!.file).toEqual({ file_data: "data:video/mp4;base64,AAAA", format: "video/mp4" }); + }); + + it("ignores an explicit null file_id", async () => { + const { model, calls } = mockChat(() => jsonResponse(completion())); + await model.invoke([new HumanMessage({ content: [{ type: "video", url: VIDEO_URL, file_id: null }] as never })]); + expect(lastContent(calls)[0]!.file).toEqual({ file_data: VIDEO_URL, format: "video/mp4" }); + }); + it("throws when a video block has no source", async () => { const { model } = mockChat(() => jsonResponse(completion())); await expect(model.invoke([new HumanMessage({ content: [{ type: "video" }] as never })])).rejects.toThrow(InterfazeError); diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index b9bcfb7..587df6d 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -152,9 +152,24 @@ def _filter_stream_chunk( gen.text = message.content +def _first_effort(*sources: Any) -> Any: + """Call-level `reasoning.effort`, then call `reasoning_effort`, then the model's.""" + for source in sources: + effort = source.get("effort") if isinstance(source, dict) else source + if effort is not None: + return effort + return None + + def _visible_text(raw: str) -> str: - """`strip_side_channels` trims, which breaks a prefix compare against streamed text.""" - return re.sub(r"[\s\S]*?", "", re.sub(r"[\s\S]*?", "", raw)) + """`strip_side_channels` trims, which breaks a prefix compare against streamed text. + + `` is prose and survives an unterminated tag verbatim, matching the SDK. A + half-written `` is JSON metadata, so the text is cut there instead. + """ + text = re.sub(r"[\s\S]*?", "", re.sub(r"[\s\S]*?", "", raw)) + open_at = text.find("") + return text if open_at == -1 else text[:open_at] def _missing_tail(raw: str, emitted: str) -> str: @@ -220,7 +235,7 @@ def __init__( "Missing API key. Pass ChatInterfaze(api_key=...) or set the INTERFAZE_API_KEY " "environment variable." ) - headers = dict(default_headers or {}) + headers = {k.lower(): v for k, v in (default_headers or {}).items()} if show_additional_info: headers[_HEADER_SHOW_ADDITIONAL_INFO] = "true" if bypass_moa: @@ -251,7 +266,7 @@ def _identifying_params(self) -> dict[str, Any]: # Without these, set_llm_cache serves a bypass_cache model the plain model's answer. params = {**super()._identifying_params, "_type": self._llm_type} if self.default_headers: - params["interfaze_headers"] = sorted(self.default_headers) + params["interfaze_headers"] = sorted(self.default_headers.items()) return params def _get_ls_params(self, stop: list[str] | None = None, **kwargs: Any) -> Any: @@ -274,9 +289,14 @@ def _get_request_payload( for m in messages ] payload = super()._get_request_payload(patched, stop=stop, **kwargs) - reasoning = payload.pop("reasoning", None) - if isinstance(reasoning, dict) and reasoning.get("effort") is not None: - payload.setdefault("reasoning_effort", reasoning["effort"]) + # Interfaze has no `reasoning` param; fold it into reasoning_effort using the same + # precedence as the JS package — a per-call value always beats a model-level one. + payload.pop("reasoning", None) + effort = _first_effort( + kwargs.get("reasoning"), kwargs.get("reasoning_effort"), self.reasoning, self.reasoning_effort + ) + if effort is not None: + payload["reasoning_effort"] = effort return payload def _create_chat_result( diff --git a/python/tests/integration_tests/test_chat_models.py b/python/tests/integration_tests/test_chat_models.py index bc1ea36..9d091ae 100644 --- a/python/tests/integration_tests/test_chat_models.py +++ b/python/tests/integration_tests/test_chat_models.py @@ -81,8 +81,8 @@ def returns_usage_metadata(self) -> bool: reason="Interfaze rejects assistant messages whose content is a list of blocks " "(400 invalid_request on messages.N); only string content is accepted there." ) - def test_tool_message_histories_list_content(self, *args: Any) -> None: - super().test_tool_message_histories_list_content(*args) + def test_tool_message_histories_list_content(self, model: BaseChatModel, my_adder_tool: Any) -> None: + super().test_tool_message_histories_list_content(model, my_adder_tool) @pytest.mark.xfail( reason="Interfaze drops `tool_choice` and routes tool use itself, so binding a " diff --git a/python/tests/unit_tests/test_client.py b/python/tests/unit_tests/test_client.py index 2e5f86d..a57e3d9 100644 --- a/python/tests/unit_tests/test_client.py +++ b/python/tests/unit_tests/test_client.py @@ -1,5 +1,7 @@ from __future__ import annotations +from typing import Any + import pytest import respx from interfaze import INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError @@ -90,3 +92,33 @@ def test_streaming_asks_for_usage() -> None: route = mock_sse([chunk({"content": "hi"}), chunk({}, finish_reason="stop")]) list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) assert last_body(route)["stream_options"] == {"include_usage": True} + + +def test_cache_key_distinguishes_header_values() -> None: + a = ChatInterfaze(api_key="k", default_headers={"x-tenant": "a"}) + b = ChatInterfaze(api_key="k", default_headers={"x-tenant": "b"}) + assert a._get_llm_string() != b._get_llm_string() + + +def test_control_header_replaces_a_differently_cased_one() -> None: + model = ChatInterfaze( + api_key="k", bypass_cache=True, default_headers={"X-Interfaze-Bypass-Cache": "false"} + ) + assert model.default_headers == {"x-interfaze-bypass-cache": "true"} + + +@pytest.mark.parametrize( + ("model_kwargs", "call_kwargs", "expected"), + [ + ({}, {"reasoning": {"effort": "high"}, "reasoning_effort": "low"}, "high"), + ({"reasoning": {"effort": "low"}}, {"reasoning_effort": "high"}, "high"), + ({"reasoning_effort": "low"}, {"reasoning": {"effort": "high"}}, "high"), + ({"reasoning_effort": "on"}, {}, "on"), + ], +) +def test_reasoning_effort_precedence( + model_kwargs: dict[str, Any], call_kwargs: dict[str, Any], expected: str +) -> None: + """Same ladder as the JS package: a per-call value always beats a model-level one.""" + model = ChatInterfaze(api_key="k", **model_kwargs) + assert model._get_request_payload([HumanMessage("x")], **call_kwargs)["reasoning_effort"] == expected diff --git a/python/tests/unit_tests/test_inputs.py b/python/tests/unit_tests/test_inputs.py index adf1246..1e8241e 100644 --- a/python/tests/unit_tests/test_inputs.py +++ b/python/tests/unit_tests/test_inputs.py @@ -54,12 +54,14 @@ def test_video_block_forwards_filename() -> None: assert file["filename"] == "clip.mp4" +@respx.mock def test_video_block_file_id_raises() -> None: model = ChatInterfaze(api_key="t") with pytest.raises(InterfazeError, match="file_id"): model.invoke([HumanMessage(content=[{"type": "video", "file_id": "file-123"}])]) +@respx.mock def test_video_block_missing_source_raises() -> None: model = ChatInterfaze(api_key="t") with pytest.raises(InterfazeError, match="requires one of"): diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index 3edb44f..487f5f6 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -249,7 +249,8 @@ def test_tail_recovered_when_visible_text_starts_with_whitespace() -> None: for c in ChatInterfaze(api_key="t").stream([HumanMessage("x")]) if isinstance(c.content, str) ) - assert body == "\nThe sky is blue because " + # the tail is recovered, but a half-written is metadata and is cut + assert body == "\nThe sky is blue because " @respx.mock @@ -257,3 +258,22 @@ def test_empty_envelope_value_does_not_block_inline_payload() -> None: mock_json(completion('[{"name":"ocr"}]The sky is blue.', precontext=[])) md = ChatInterfaze(api_key="t").invoke([HumanMessage("x")]).response_metadata assert md["precontext"] == [{"name": "ocr"}] + + +@respx.mock +def test_truncated_precontext_is_not_shown_as_content() -> None: + """A half-written is internal tool JSON, never the answer.""" + mock_sse( + [ + chunk({"content": "Total is "}), + chunk({"content": '[{"name":"ocr","result":{"ssn":"123-45-6789"'}, "length"), + ] + ) + body = "".join( + c.content + for c in ChatInterfaze(api_key="t").stream([HumanMessage("x")]) + if isinstance(c.content, str) + ) + assert "precontext" not in body + assert "123-45-6789" not in body + assert body == "Total is " From a4497e02f8edd56bb07ec945b8789a1b43c5d525 Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 14:23:43 -0700 Subject: [PATCH 15/28] fix: close the remaining cross-package gaps MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - JS dedupes side fields with a key-order-stable serialization, matching python's json.dumps(sort_keys=True). The same payload delivered with reordered keys was deduping in python and double-emitting in JS. - `_generate` uses isAIMessage, not `instanceof AIMessage`. AIMessageChunk is not an AIMessage, so the whole post-processing block — side fields, tag stripping, the generation.text sync — was dead under `streaming: true`. - the frame sink is released when the stream ends, instead of being retained for the lifetime of the options object. - mypy covers python/scripts, which the JS twin already had under tsc. It immediately found a real `func-returns-value` error in the live QA script that would have surfaced as a Monday crash. - the version-sync test reads jsr.json too, and asserts name as well as version. jsr.json had silently drifted to 1.0.2 under a test that only ever looked at package.json. - an empty-stream `providers.every(...)` assertion passed vacuously; it now compares the observed set. --- js/src/chat_models.ts | 16 +++++++++++++--- js/test/identity.test.ts | 10 +++++++--- python/pyproject.toml | 2 +- python/scripts/qa_live.py | 15 +++++++++------ 4 files changed, 30 insertions(+), 13 deletions(-) diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 892d07b..1aceb9f 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -1,7 +1,7 @@ import type { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager"; import { BaseChatModel, type LangSmithParams } from "@langchain/core/language_models/chat_models"; import type { ChatModelStreamEvent } from "@langchain/core/language_models/event"; -import { AIMessage, AIMessageChunk, type BaseMessage } from "@langchain/core/messages"; +import { AIMessage, AIMessageChunk, type BaseMessage, isAIMessage } from "@langchain/core/messages"; import { ChatGenerationChunk, type ChatResult } from "@langchain/core/outputs"; import { ChatOpenAICompletions, type ChatOpenAIFields, normalizeHeaders } from "@langchain/openai"; import { INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError } from "interfaze"; @@ -90,7 +90,16 @@ const ACCUMULATING_SIDE_FIELDS: readonly string[] = ["precontext", "reasoning"]; // Accumulating fields dedupe by value, so a different payload still lands. `vcache` is // scalar state and dedupes by name — merging two values would concatenate them. -const fingerprint = (key: string, value: unknown): string => (ACCUMULATING_SIDE_FIELDS.includes(key) ? `${key}:${JSON.stringify(value)}` : key); +const stableStringify = (value: unknown): string => + JSON.stringify(value, (_k, v) => + v && typeof v === "object" && !Array.isArray(v) + ? Object.fromEntries(Object.entries(v as Record).sort(([a], [b]) => a.localeCompare(b))) + : v + ); + +// Matches python's json.dumps(sort_keys=True): the same payload with reordered keys +// must dedupe, not double-emit. +const fingerprint = (key: string, value: unknown): string => (ACCUMULATING_SIDE_FIELDS.includes(key) ? `${key}:${stableStringify(value)}` : key); function applySideFields(message: SideChannelCarrier, raw: Record, seen?: Set): void { for (const key of SIDE_FIELDS) { @@ -270,7 +279,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { const result = await super._generate(this.rewriteVideoBlocks(messages), options, runManager); for (const generation of result.generations) { const message = generation.message; - if (message instanceof AIMessage) { + if (isAIMessage(message)) { message.response_metadata.model_provider = PROVIDER; const raw = message.additional_kwargs.__raw_response as Record | undefined; if (raw) applySideFields(message, raw); @@ -313,6 +322,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { yield gen; } const joined = rawParts.join(""); + this.#frameSinks.delete(options); const tail = filter.flush() || missingTail(joined, emittedParts.join("")); const { reasoning, precontext } = stripSideChannels(joined); if (tail) { diff --git a/js/test/identity.test.ts b/js/test/identity.test.ts index bad6a66..7db699a 100644 --- a/js/test/identity.test.ts +++ b/js/test/identity.test.ts @@ -28,9 +28,13 @@ describe("provider identity", () => { expect(versions["@langchain/core"]).toBeTypeOf("string"); }); - it("keeps VERSION in sync with package.json", () => { - const pkg = JSON.parse(readFileSync(new URL("../package.json", import.meta.url), "utf8")) as { version: string }; + it("keeps VERSION in sync with both manifests", () => { + const read = (p: string) => JSON.parse(readFileSync(new URL(p, import.meta.url), "utf8")) as { name: string; version: string }; + const pkg = read("../package.json"); + const jsr = read("../jsr.json"); expect(VERSION).toBe(pkg.version); + expect(jsr.version).toBe(pkg.version); + expect(jsr.name).toBe(pkg.name); }); it("stamps model_provider on invoke responses", async () => { @@ -43,6 +47,6 @@ describe("provider identity", () => { const { model: m } = mockChat(() => sseResponse([chunk({ content: "hi" }), chunk({}, "stop")])); const providers: unknown[] = []; for await (const c of await m.stream("hi")) providers.push(c.response_metadata.model_provider); - expect(providers.every((p) => p === "interfaze")).toBe(true); + expect(new Set(providers)).toEqual(new Set(["interfaze"])); }); }); diff --git a/python/pyproject.toml b/python/pyproject.toml index cde8c6b..ae2b767 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -53,7 +53,7 @@ line-length = 110 [tool.mypy] python_version = "3.12" strict = true -files = ["langchain_interfaze"] +files = ["langchain_interfaze", "scripts"] [[tool.mypy.overrides]] module = ["langchain_openai.*", "langchain_core.*"] diff --git a/python/scripts/qa_live.py b/python/scripts/qa_live.py index 12c2122..c68190e 100644 --- a/python/scripts/qa_live.py +++ b/python/scripts/qa_live.py @@ -363,12 +363,15 @@ def ocr_structured() -> str: input_check("audio url", lambda: file(A["audio"], "stt-example.wav"), "Transcribe this.") input_check("video block", lambda: {"type": "video", "url": A["video"]}, "Describe this video.") input_check("csv url", lambda: file(A["csv"], "data.csv"), "Name one column header.") -check( - "input: inline URL", - lambda: ( - _assert(llm.invoke(f"Extract the total from this receipt: {A['receipt']}").content, "empty") or "ok" - ), -) + + +def inline_url() -> str: + res = llm.invoke(f"Extract the total from this receipt: {A['receipt']}") + _assert(res.content, "empty") + return "ok" + + +check("input: inline URL", inline_url) print( f"\nLIVE QA: {'ALL PASSED (go)' if not failures else f'{len(failures)} FAILED (no-go): ' + ', '.join(failures)}" From 1e2cdb36792254f6e9ea8292c84e47d07b39c9c3 Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 15:04:59 -0700 Subject: [PATCH 16/28] fix: truncation-aware side channels, beta-stream parity, redacted cache keys MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit An unmatched / means two different things. In a completed response it is prose the model wrote; in a truncated one it is a side channel the server never closed. finish_reason == "length" is the only signal that tells them apart, so both packages branch on it: prose survives verbatim, a truncated becomes reasoning metadata, and a truncated — unparseable tool JSON — is dropped rather than leaked as content. python: with_structured_output streams through beta.chat.completions, which nests each frame under "chunk" and omits `role` on the completion it assembles. Side fields were read from the wrong level and the missing role raised ValidationError. Normalize the role on both shapes and unwrap the envelope, matching what the js package already did. js: envelope side fields were buffered to stream end, so they arrived out of order and vanished if the consumer broke early. Apply them to the chunk they arrived with instead. both: _identifying_params reaches the llm cache key and the invocation_params langsmith records, so the api key and header values were published verbatim. Fingerprint them — two values still differ, which is all the key needs. file_id is rejected on any block, not just video, since interfaze has no file store; scalar header values are stringified rather than silently dropped. --- js/src/chat_models.ts | 103 ++++++++++++--- js/test/constructor.test.ts | 7 + js/test/side_fields.test.ts | 68 +++++++++- js/test/stream.test.ts | 13 +- js/test/video.test.ts | 5 + python/langchain_interfaze/chat_models.py | 122 ++++++++++++++---- .../integration_tests/test_chat_models.py | 3 +- python/tests/unit_tests/test_client.py | 11 ++ python/tests/unit_tests/test_inputs.py | 11 ++ python/tests/unit_tests/test_stream.py | 78 ++++++++++- 10 files changed, 364 insertions(+), 57 deletions(-) diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 1aceb9f..d8ee31a 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -113,26 +113,45 @@ function applySideFields(message: SideChannelCarrier, raw: Record\n...` is the common shape). Same removal, no trim. + * An unmatched tag means two different things. In a completed response it is prose the + * model wrote (`"wrap it in tags"`); in a truncated one it is a side channel the + * server never got to close. `finish_reason: "length"` is the only reliable signal. */ -function visibleText(raw: string): string { - const text = raw.replace(TAG_RE("think"), "").replace(TAG_RE("precontext"), ""); - const open = text.indexOf(""); - return open === -1 ? text : text.slice(0, open); +function openSideChannel(text: string): { tag: "think" | "precontext"; before: string; after: string } | null { + for (const tag of ["think", "precontext"] as const) { + const at = text.indexOf(`<${tag}>`); + if (at !== -1) return { tag, before: text.slice(0, at), after: text.slice(at + tag.length + 2) }; + } + return null; } -/** The authoritative transcript minus what already streamed. */ -function missingTail(raw: string, emitted: string): string { - const text = visibleText(raw); - return text.startsWith(emitted) ? text.slice(emitted.length) : ""; +/** + * What the caller still owes, given what already streamed. On a truncated response the + * partial `` becomes reasoning rather than content, and a partial `` + * — unparseable tool JSON — is dropped outright. + */ +function recoverTail(raw: string, emitted: string, truncated: boolean): { tail: string; reasoning?: string } { + const text = withoutClosedBlocks(raw); + const open = truncated ? openSideChannel(text) : null; + const visible = open ? open.before : text; + const tail = visible.startsWith(emitted) ? visible.slice(emitted.length) : ""; + return open?.tag === "think" && open.after ? { tail, reasoning: open.after } : { tail }; } -function stripTags(message: AIMessage): void { +function stripTags(message: AIMessage, truncated = false): void { if (typeof message.content !== "string") return; if (!message.content.includes("") && !message.content.includes("")) return; - const { text, reasoning, precontext } = stripSideChannels(message.content); + const stripped = stripSideChannels(message.content); + const recovered = truncated ? recoverTail(message.content, "", true) : null; + const text = recovered ? recovered.tail.trim() : stripped.text; + const reasoning = stripped.reasoning ?? recovered?.reasoning; + const { precontext } = stripped; if (text !== message.content) message.content = text; if (reasoning && !hasValue(message.response_metadata.reasoning)) { message.response_metadata.reasoning = reasoning; @@ -148,20 +167,47 @@ function rewriteContent(content: unknown): unknown { if (!Array.isArray(content)) return content; let changed = false; const out = content.map((block) => { - if (block && typeof block === "object" && (block as { type?: string }).type === "video") { + if (!block || typeof block !== "object") return block; + if ((block as { type?: string }).type === "video") { changed = true; return convertVideoBlock(block as VideoBlock); } + // Interfaze has no file store, so a file_id reference can only 400 downstream. + if ((block as { file_id?: unknown }).file_id != null) { + throw new InterfazeError("Interfaze cannot resolve content by 'file_id'. Pass 'url' or 'base64' instead."); + } return block; }); return changed ? out : content; } +const PUBLIC_HEADERS: readonly string[] = [HEADER_SHOW_ADDITIONAL_INFO, HEADER_BYPASS_MOA, HEADER_BYPASS_CACHE]; + +/** FNV-1a: no sync hash is available in every runtime this package runs in, and only + * distinctness matters here — the digest is never compared across processes. */ +const digest = (value: string): string => { + let hash = 0x811c9dc5; + for (let i = 0; i < value.length; i += 1) hash = Math.imul(hash ^ value.charCodeAt(i), 0x01000193); + return (hash >>> 0).toString(16); +}; + +const redactHeaders = (headers: Record): string[] => + Object.keys(headers) + .sort() + .map((key) => (PUBLIC_HEADERS.includes(key) ? `${key}=${headers[key]}` : `${key}#${digest(String(headers[key]))}`)); + function buildHeaders(fields: ChatInterfazeFields): Record | undefined { // defaultHeaders is HeadersLike: spreading a Headers instance yields {} and a tuple // array yields {"0": [k, v]}. normalizeHeaders also lowercases, so a differently-cased // caller header is replaced rather than concatenated onto ours. - const headers = normalizeHeaders(fields.configuration?.defaultHeaders) as Record; + const given = fields.configuration?.defaultHeaders; + const headers = normalizeHeaders(given) as Record; + // normalizeHeaders keeps string values only, so `{"x-flag": true}` would vanish silently. + if (given && typeof given === "object" && !Array.isArray(given) && !(given instanceof Headers)) { + for (const [key, value] of Object.entries(given)) { + if (typeof value === "number" || typeof value === "boolean") headers[key.toLowerCase()] = String(value); + } + } if (fields.showAdditionalInfo) headers[HEADER_SHOW_ADDITIONAL_INFO] = "true"; if (fields.bypassMoA) headers[HEADER_BYPASS_MOA] = "true"; if (fields.bypassCache) headers[HEADER_BYPASS_CACHE] = "true"; @@ -212,6 +258,18 @@ export class ChatInterfaze extends ChatOpenAICompletions { this._addVersion("@interfaze-ai/langchain", VERSION); } + // The parent spreads clientConfig wholesale, so the api key and every default header + // land verbatim in the llm cache key. Fingerprint them instead: two values still + // differ, which is all the key needs, and neither is published. + override _identifyingParams(): ReturnType { + const { apiKey, defaultHeaders, ...rest } = super._identifyingParams(); + return { + ...rest, + ...(typeof apiKey === "string" ? { apiKeyFingerprint: digest(apiKey) } : {}), + ...(defaultHeaders ? { interfazeHeaders: redactHeaders(defaultHeaders as Record) } : {}), + } as ReturnType; + } + override getLsParams(options: this["ParsedCallOptions"]): LangSmithParams { return { ...super.getLsParams(options), ls_provider: PROVIDER }; } @@ -284,7 +342,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { const raw = message.additional_kwargs.__raw_response as Record | undefined; if (raw) applySideFields(message, raw); delete message.additional_kwargs.__raw_response; - stripTags(message); + stripTags(message, generation.generationInfo?.finish_reason === "length"); if (typeof message.content === "string") generation.text = message.content; } } @@ -303,13 +361,19 @@ export class ChatInterfaze extends ChatOpenAICompletions { const frames: Array> = []; this.#frameSinks.set(options, frames); let streamId: string | undefined; + let finishReason: unknown; for await (const gen of super._streamResponseChunks(this.rewriteVideoBlocks(messages), options, runManager)) { const message = gen.message as unknown as SideChannelCarrier; streamId ??= (gen.message as AIMessageChunk).id; + finishReason = gen.generationInfo?.finish_reason ?? finishReason; message.response_metadata.model_provider = PROVIDER; const raw = message.additional_kwargs.__raw_response as Record | undefined; if (raw) applySideFields(message, raw, seen); delete message.additional_kwargs.__raw_response; + // Envelope frames arrive interleaved with content, so apply them here rather than + // at stream end: same ordering as python, and a consumer that breaks early still + // sees everything the server had already sent. + for (const frame of frames.splice(0)) applySideFields(message, frame, seen); if (typeof message.content === "string" && message.content) { rawParts.push(message.content); const filtered = filter.feed(message.content); @@ -323,8 +387,11 @@ export class ChatInterfaze extends ChatOpenAICompletions { } const joined = rawParts.join(""); this.#frameSinks.delete(options); - const tail = filter.flush() || missingTail(joined, emittedParts.join("")); - const { reasoning, precontext } = stripSideChannels(joined); + const flushed = filter.flush(); + const recovered = flushed ? { tail: flushed } : recoverTail(joined, emittedParts.join(""), finishReason === "length"); + const tail = recovered.tail; + const { precontext } = stripSideChannels(joined); + const reasoning = stripSideChannels(joined).reasoning ?? recovered.reasoning; if (tail) { const message = new AIMessageChunk({ content: tail, id: streamId }); message.response_metadata.model_provider = PROVIDER; @@ -337,7 +404,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { if (precontext) inline.precontext = precontext; // One chunk per source, so langchain's own merge concatenates them — the same // behaviour the python package gets for free from its per-chunk conversion. - for (const side of [...frames, inline]) { + for (const side of [...frames.splice(0), inline]) { const message = new AIMessageChunk({ content: "", id: streamId }); applySideFields(message, side, seen); if (Object.keys(message.additional_kwargs).length === 0) continue; diff --git a/js/test/constructor.test.ts b/js/test/constructor.test.ts index dab016b..8ac380e 100644 --- a/js/test/constructor.test.ts +++ b/js/test/constructor.test.ts @@ -143,3 +143,10 @@ describe("ChatInterfaze constructor", () => { expect(seen?.get("x-interfaze-bypass-cache")).toBe("true"); }); }); + +describe("header values", () => { + it("keeps a scalar header value that normalizeHeaders would drop", () => { + const model = new ChatInterfaze({ apiKey: "k", configuration: { defaultHeaders: { "X-Retries": 3, "x-debug": true } as never } }); + expect(model.clientConfig.defaultHeaders).toMatchObject({ "x-retries": "3", "x-debug": "true" }); + }); +}); diff --git a/js/test/side_fields.test.ts b/js/test/side_fields.test.ts index 25c7296..de99ae6 100644 --- a/js/test/side_fields.test.ts +++ b/js/test/side_fields.test.ts @@ -1,6 +1,7 @@ import { describe, expect, it } from "vitest"; import { AIMessage, HumanMessage } from "@langchain/core/messages"; -import { completion, jsonResponse, mockChat } from "./helpers.js"; +import { ChatInterfaze } from "../src/index.js"; +import { chunk, completion, envelopeChunk, jsonResponse, mockChat, sseResponse } from "./helpers.js"; const PC = [{ name: "ocr", result: { extracted_text: "x" } }]; @@ -39,6 +40,24 @@ describe("non-streaming side fields", () => { expect(res.response_metadata.precontext).toEqual([{ name: "ocr" }]); }); + it("keeps a truncated out of invoke() content", async () => { + const { model } = mockChat(() => + jsonResponse( + completion('Total is [{"ssn":"123-45-6789"', { + choices: [{ index: 0, message: { role: "assistant", content: 'Total is [{"ssn":"123-45-6789"' }, finish_reason: "length" }], + }) + ) + ); + const res = (await model.invoke("x")) as AIMessage; + expect(String(res.content)).not.toContain("123-45-6789"); + }); + + it("keeps prose that mentions a tag intact", async () => { + const { model } = mockChat(() => jsonResponse(completion("Wrap metadata in tags, then continue."))); + const res = (await model.invoke("x")) as AIMessage; + expect(res.content).toBe("Wrap metadata in tags, then continue."); + }); + it("strips inline / tags from content", async () => { const content = "Rayleigh scattering." + '[{"name":"ocr","result":{"x":1}}]' + "The sky is blue."; const { model } = mockChat(() => jsonResponse(completion(content))); @@ -48,3 +67,50 @@ describe("non-streaming side fields", () => { expect(res.response_metadata.precontext).toEqual([{ name: "ocr", result: { x: 1 } }]); }); }); + +describe("identifying params", () => { + it("fingerprints the api key and header values instead of publishing them", () => { + const { model } = mockChat(() => jsonResponse(completion())); + const params = model._identifyingParams() as unknown as Record; + expect(JSON.stringify(params)).not.toContain("sk-test"); + expect("apiKey" in params).toBe(false); + expect("defaultHeaders" in params).toBe(false); + }); + + it("keeps two header values in separate cache entries", () => { + const a = new ChatInterfaze({ apiKey: "k", configuration: { defaultHeaders: { "x-tenant": "a" } } }); + const b = new ChatInterfaze({ apiKey: "k", configuration: { defaultHeaders: { "x-tenant": "b" } } }); + expect(JSON.stringify(a._identifyingParams())).not.toEqual(JSON.stringify(b._identifyingParams())); + }); + + it("shows the flags it owns in the clear", () => { + const model = new ChatInterfaze({ apiKey: "k", bypassCache: true }); + expect((model._identifyingParams() as unknown as Record).interfazeHeaders).toEqual(["x-interfaze-bypass-cache=true"]); + }); +}); + +describe("stream ordering", () => { + it("attaches envelope side fields to the chunk they arrived with", async () => { + const { model } = mockChat(() => + sseResponse([chunk({ content: "a" }), envelopeChunk({ vcache: true }), chunk({ content: "b" }), chunk({}, "stop")]) + ); + const seen: Array<[string, unknown]> = []; + for await (const c of await model.stream("x")) seen.push([String(c.content), c.additional_kwargs.vcache]); + // not buffered to the end: vcache lands before the last content chunk + const at = seen.findIndex(([, v]) => v === true); + expect(at).toBeGreaterThanOrEqual(0); + expect(seen.slice(at).some(([text]) => text === "b")).toBe(true); + }); + + it("still delivers side fields when the consumer breaks early", async () => { + const { model } = mockChat(() => + sseResponse([chunk({ content: "a" }), envelopeChunk({ vcache: true }), chunk({ content: "b" }), chunk({}, "stop")]) + ); + let vcache: unknown; + for await (const c of await model.stream("x")) { + vcache ??= c.additional_kwargs.vcache; + if (c.content === "b") break; + } + expect(vcache).toBe(true); + }); +}); diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index ac27bec..3752255 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -162,8 +162,10 @@ describe("streaming side-channel filter", () => { const { model } = mockChat(() => sseResponse(chunks)); const got = await collect(model as never); const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); - // Matches the SDK: an unmatched tag survives verbatim rather than being swallowed. - expect(text).toBe("never closed and the real answer 42"); + // Truncated mid-: the partial reasoning is metadata, not the answer. + expect(text).toBe(""); + const merged = got.map((c) => c.additional_kwargs.reasoning).filter(Boolean); + expect(String(merged[0])).toBe("never closed and the real answer 42"); }); // Non-streaming has the whole body, so an unmatched tag is prose and must survive @@ -178,7 +180,8 @@ describe("streaming side-channel filter", () => { const { model } = mockChat(() => sseResponse(chunks)); const got = await collect(model as never); const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); - expect(text).toBe("The answer is 42. because reasons"); + expect(text).toBe("The answer is 42. "); + expect(String(got.map((c) => c.additional_kwargs.reasoning).filter(Boolean)[0])).toBe("because reasons"); }); it("keeps an envelope side field alongside the inline one", async () => { @@ -218,8 +221,8 @@ describe("streaming side-channel filter", () => { const { model } = mockChat(() => sseResponse(chunks)); const got = await collect(model as never); const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); - // the tail is recovered, but a half-written is metadata and is cut - expect(text).toBe("\nThe sky is blue because "); + // the response completed, so an unmatched tag is prose and survives + expect(text).toBe("\nThe sky is blue because "); }); it("never shows a truncated as content", async () => { diff --git a/js/test/video.test.ts b/js/test/video.test.ts index ece6f1f..214d36c 100644 --- a/js/test/video.test.ts +++ b/js/test/video.test.ts @@ -60,6 +60,11 @@ describe("video content blocks", () => { expect(lastContent(calls)[0]!.file).toEqual({ file_data: VIDEO_URL, format: "video/mp4" }); }); + it("rejects a file_id on a non-video block too (no file store)", async () => { + const { model } = mockChat(() => jsonResponse(completion())); + await expect(model.invoke([new HumanMessage({ content: [{ type: "file", file_id: "file-123" }] as never })])).rejects.toThrow(/file_id/); + }); + it("throws when a video block has no source", async () => { const { model } = mockChat(() => jsonResponse(completion())); await expect(model.invoke([new HumanMessage({ content: [{ type: "video" }] as never })])).rejects.toThrow(InterfazeError); diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 587df6d..402941d 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -1,9 +1,10 @@ from __future__ import annotations +import hashlib import json import os import re -from collections.abc import AsyncIterator, Iterator +from collections.abc import AsyncIterator, Iterator, Mapping from typing import Any from interfaze import ( @@ -56,18 +57,50 @@ def _extract_side_fields(data: dict[str, Any]) -> dict[str, Any]: return {k: data[k] for k in _SIDE_FIELDS if _carries_value(data.get(k))} +def _default_role(response: Any, field: str) -> None: + """Interfaze sends `role` on the first delta only, and omits it entirely on the + completion the beta stream assembles. The parent then builds a ChatMessage, which + pydantic rejects for role=None and which carries no additional_kwargs. + interfaze-python normalizes the same way (_stream.py). Handles both the dict and + the pydantic shape, since the two paths hand us different ones.""" + choices = response.get("choices") if isinstance(response, dict) else getattr(response, "choices", None) + for choice in choices or (): + part = choice.get(field) if isinstance(choice, dict) else getattr(choice, field, None) + if isinstance(part, dict): + if not part.get("role"): + part["role"] = "assistant" + elif part is not None and not getattr(part, "role", None): + part.role = "assistant" + + +def _redact_headers(headers: Mapping[str, str]) -> list[str]: + """`_identifying_params` reaches both the LLM cache key and the `invocation_params` + LangSmith records, so a caller's header value is fingerprinted rather than published. + Two values still differ, which is all the cache key needs. The flags we own are ours + to show.""" + public = (_HEADER_SHOW_ADDITIONAL_INFO, _HEADER_BYPASS_MOA, _HEADER_BYPASS_CACHE) + return [ + f"{k}={headers[k]}" if k in public else f"{k}#{hashlib.sha256(headers[k].encode()).hexdigest()[:12]}" + for k in sorted(headers) + ] + + def _apply_side_fields(message: AIMessage, side: dict[str, Any]) -> None: for key, value in side.items(): message.response_metadata[key] = value message.additional_kwargs[key] = value -def _strip_tags(message: AIMessage) -> None: +def _strip_tags(message: AIMessage, truncated: bool = False) -> None: if not isinstance(message.content, str) or not ( "" in message.content or "" in message.content ): return text, reasoning, precontext = strip_side_channels(message.content) + if truncated: + recovered, partial = _recover_tail(message.content, "", truncated=True) + text = recovered.strip() + reasoning = reasoning or partial if text != message.content: message.content = text if reasoning and not message.response_metadata.get("reasoning"): @@ -107,10 +140,19 @@ def _convert_video_block(block: dict[str, Any]) -> dict[str, Any]: def _rewrite_video_blocks(content: Any) -> Any: if not isinstance(content, list): return content - rewritten = [ - _convert_video_block(block) if isinstance(block, dict) and block.get("type") == "video" else block - for block in content - ] + rewritten = [] + for block in content: + if not isinstance(block, dict): + rewritten.append(block) + elif block.get("type") == "video": + rewritten.append(_convert_video_block(block)) + elif block.get("file_id") is not None: + # Interfaze has no file store, so a file_id reference can only 400 downstream. + raise InterfazeError( + "Interfaze cannot resolve content by 'file_id'. Pass 'url' or 'base64' instead." + ) + else: + rewritten.append(block) return rewritten if rewritten != content else content @@ -161,31 +203,49 @@ def _first_effort(*sources: Any) -> Any: return None -def _visible_text(raw: str) -> str: - """`strip_side_channels` trims, which breaks a prefix compare against streamed text. +def _without_closed_blocks(raw: str) -> str: + """Closed blocks removed, no trim — `strip_side_channels` trims and breaks prefix compares.""" + return re.sub(r"[\s\S]*?", "", re.sub(r"[\s\S]*?", "", raw)) + + +def _open_side_channel(text: str) -> tuple[str, str, str] | None: + """Returns (tag, before, after) for the first unmatched opening tag.""" + for tag in ("think", "precontext"): + at = text.find(f"<{tag}>") + if at != -1: + return tag, text[:at], text[at + len(tag) + 2 :] + return None - `` is prose and survives an unterminated tag verbatim, matching the SDK. A - half-written `` is JSON metadata, so the text is cut there instead. - """ - text = re.sub(r"[\s\S]*?", "", re.sub(r"[\s\S]*?", "", raw)) - open_at = text.find("") - return text if open_at == -1 else text[:open_at] +def _recover_tail(raw: str, emitted: str, truncated: bool) -> tuple[str, str | None]: + """What the caller still owes, given what already streamed. -def _missing_tail(raw: str, emitted: str) -> str: - """The authoritative transcript minus what already streamed.""" - text = _visible_text(raw) - return text[len(emitted) :] if text.startswith(emitted) else "" + An unmatched tag is prose in a completed response and an unclosed side channel in a + truncated one, so `finish_reason == "length"` decides. A partial `` becomes + reasoning rather than content; a partial `` is unparseable and dropped. + """ + text = _without_closed_blocks(raw) + open_tag = _open_side_channel(text) if truncated else None + visible = open_tag[1] if open_tag else text + tail = visible[len(emitted) :] if visible.startswith(emitted) else "" + if open_tag and open_tag[0] == "think" and open_tag[2]: + return tail, open_tag[2] + return tail, None def _final_side_chunk( - filt: SideChannelFilter, raw: list[str], seen: set[str], emitted: list[str] + filt: SideChannelFilter, + raw: list[str], + seen: set[str], + emitted: list[str], + truncated: bool = False, ) -> ChatGenerationChunk | None: tail = filt.flush() joined = "".join(raw) _, reasoning, precontext = strip_side_channels(joined) if not tail: - tail = _missing_tail(joined, "".join(emitted)) + tail, partial = _recover_tail(joined, "".join(emitted), truncated) + reasoning = reasoning or partial side: dict[str, Any] = {} if reasoning and _fingerprint("reasoning", reasoning) not in seen: side["reasoning"] = reasoning @@ -194,6 +254,7 @@ def _final_side_chunk( if not tail and not side: return None message = AIMessageChunk(content=tail) + message.response_metadata["model_provider"] = _PROVIDER _apply_side_fields(message, side) return ChatGenerationChunk(message=message) @@ -235,7 +296,7 @@ def __init__( "Missing API key. Pass ChatInterfaze(api_key=...) or set the INTERFAZE_API_KEY " "environment variable." ) - headers = {k.lower(): v for k, v in (default_headers or {}).items()} + headers = {k.lower(): str(v) for k, v in (default_headers or {}).items()} if show_additional_info: headers[_HEADER_SHOW_ADDITIONAL_INFO] = "true" if bypass_moa: @@ -266,7 +327,7 @@ def _identifying_params(self) -> dict[str, Any]: # Without these, set_llm_cache serves a bypass_cache model the plain model's answer. params = {**super()._identifying_params, "_type": self._llm_type} if self.default_headers: - params["interfaze_headers"] = sorted(self.default_headers.items()) + params["interfaze_headers"] = _redact_headers(self.default_headers) return params def _get_ls_params(self, stop: list[str] | None = None, **kwargs: Any) -> Any: @@ -304,6 +365,7 @@ def _create_chat_result( response: Any, generation_info: dict[str, Any] | None = None, ) -> ChatResult: + _default_role(response, "message") result = super()._create_chat_result(response, generation_info) response_dict = ( response @@ -318,7 +380,7 @@ def _create_chat_result( if isinstance(message, AIMessage): message.response_metadata["model_provider"] = _PROVIDER _apply_side_fields(message, side) - _strip_tags(message) + _strip_tags(message, (generation.generation_info or {}).get("finish_reason") == "length") # The streaming path keeps gen.text in step with the stripped content; # without this, callbacks and the serialized cache carry the raw tags. if isinstance(message.content, str): @@ -331,6 +393,10 @@ def _convert_chunk_to_generation_chunk( default_chunk_class: type, base_generation_info: dict[str, Any] | None, ) -> ChatGenerationChunk | None: + # `with_structured_output` streams through beta.chat.completions, which nests the + # frame under "chunk" — side fields ride the envelope, so unwrap before reading. + body = chunk.get("chunk") or chunk + _default_role(body, "delta") generation_chunk = super()._convert_chunk_to_generation_chunk( chunk, default_chunk_class, base_generation_info ) @@ -339,7 +405,7 @@ def _convert_chunk_to_generation_chunk( message = generation_chunk.message if isinstance(message, AIMessage): message.response_metadata["model_provider"] = _PROVIDER - side = _extract_side_fields(chunk) + side = _extract_side_fields(body) if side: _apply_side_fields(message, side) return generation_chunk @@ -355,15 +421,17 @@ def _stream( raw: list[str] = [] emitted: list[str] = [] seen: set[str] = set() + finish: Any = None for gen in super()._stream(messages, stop=stop, run_manager=None, **kwargs): _filter_stream_chunk(gen, filt, raw, emitted) _dedupe_side_fields(gen.message, seen) + finish = (gen.generation_info or {}).get("finish_reason") or finish if run_manager: run_manager.on_llm_new_token( gen.text, chunk=gen, logprobs=(gen.generation_info or {}).get("logprobs") ) yield gen - final = _final_side_chunk(filt, raw, seen, emitted) + final = _final_side_chunk(filt, raw, seen, emitted, finish == "length") if final is not None: if run_manager: run_manager.on_llm_new_token(final.text, chunk=final) @@ -380,15 +448,17 @@ async def _astream( raw: list[str] = [] emitted: list[str] = [] seen: set[str] = set() + finish: Any = None async for gen in super()._astream(messages, stop=stop, run_manager=None, **kwargs): _filter_stream_chunk(gen, filt, raw, emitted) _dedupe_side_fields(gen.message, seen) + finish = (gen.generation_info or {}).get("finish_reason") or finish if run_manager: await run_manager.on_llm_new_token( gen.text, chunk=gen, logprobs=(gen.generation_info or {}).get("logprobs") ) yield gen - final = _final_side_chunk(filt, raw, seen, emitted) + final = _final_side_chunk(filt, raw, seen, emitted, finish == "length") if final is not None: if run_manager: await run_manager.on_llm_new_token(final.text, chunk=final) diff --git a/python/tests/integration_tests/test_chat_models.py b/python/tests/integration_tests/test_chat_models.py index 9d091ae..6a49073 100644 --- a/python/tests/integration_tests/test_chat_models.py +++ b/python/tests/integration_tests/test_chat_models.py @@ -94,7 +94,8 @@ def test_bind_runnables_as_tools(self, model: BaseChatModel) -> None: @pytest.mark.xfail( reason="Interfaze drops `tool_choice` and routes tool use itself, so a user tool " - "the model can answer without (here: the weather) is not reliably called." + "the model can answer without (here: the weather) is not reliably called.", + strict=False, ) def test_agent_loop(self, model: BaseChatModel) -> None: super().test_agent_loop(model) diff --git a/python/tests/unit_tests/test_client.py b/python/tests/unit_tests/test_client.py index a57e3d9..1f7aead 100644 --- a/python/tests/unit_tests/test_client.py +++ b/python/tests/unit_tests/test_client.py @@ -122,3 +122,14 @@ def test_reasoning_effort_precedence( """Same ladder as the JS package: a per-call value always beats a model-level one.""" model = ChatInterfaze(api_key="k", **model_kwargs) assert model._get_request_payload([HumanMessage("x")], **call_kwargs)["reasoning_effort"] == expected + + +def test_cache_key_does_not_publish_header_values() -> None: + model = ChatInterfaze(api_key="k", default_headers={"x-tenant": "secret-tenant"}) + assert "secret-tenant" not in str(model._identifying_params) + assert "secret-tenant" not in model._get_llm_string() + + +def test_cache_key_shows_the_flags_we_own() -> None: + model = ChatInterfaze(api_key="k", bypass_cache=True) + assert model._identifying_params["interfaze_headers"] == ["x-interfaze-bypass-cache=true"] diff --git a/python/tests/unit_tests/test_inputs.py b/python/tests/unit_tests/test_inputs.py index 1e8241e..4965dc3 100644 --- a/python/tests/unit_tests/test_inputs.py +++ b/python/tests/unit_tests/test_inputs.py @@ -66,3 +66,14 @@ def test_video_block_missing_source_raises() -> None: model = ChatInterfaze(api_key="t") with pytest.raises(InterfazeError, match="requires one of"): model.invoke([HumanMessage(content=[{"type": "video"}])]) + + +def test_file_id_rejected_on_any_block() -> None: + model = ChatInterfaze(api_key="k") + with pytest.raises(InterfazeError, match="file_id"): + model.invoke([HumanMessage(content=[{"type": "file", "file_id": "file-123"}])]) + + +def test_scalar_header_values_are_stringified() -> None: + model = ChatInterfaze(api_key="k", default_headers={"X-Retries": 3}) # ty:ignore[invalid-argument-type] + assert model.default_headers == {"x-retries": "3"} diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index 487f5f6..99ad796 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -10,7 +10,8 @@ BaseCallbackHandler, CallbackManager, ) -from langchain_core.messages import HumanMessage +from langchain_core.messages import AIMessageChunk, HumanMessage +from pydantic import BaseModel from langchain_interfaze import ChatInterfaze from tests.unit_tests.conftest import ( @@ -178,8 +179,10 @@ def test_unterminated_tag_recovers_text() -> None: ) chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) body = "".join(c.content for c in chunks if isinstance(c.content, str)) - # Matches the SDK: an unmatched tag survives verbatim rather than being swallowed. - assert body == "never closed and the real answer 42" + # Truncated mid-: the partial reasoning is metadata, not the answer. + assert body == "" + reasoning = [c.additional_kwargs["reasoning"] for c in chunks if c.additional_kwargs.get("reasoning")] + assert reasoning == ["never closed and the real answer 42"] @respx.mock @@ -195,7 +198,9 @@ def test_unterminated_tag_mid_text_does_not_duplicate_prefix() -> None: mock_sse([chunk({"content": "The answer is 42. because reasons"}), chunk({}, "length")]) chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) body = "".join(c.content for c in chunks if isinstance(c.content, str)) - assert body == "The answer is 42. because reasons" + assert body == "The answer is 42. " + reasoning = [c.additional_kwargs["reasoning"] for c in chunks if c.additional_kwargs.get("reasoning")] + assert reasoning == ["because reasons"] @respx.mock @@ -249,8 +254,8 @@ def test_tail_recovered_when_visible_text_starts_with_whitespace() -> None: for c in ChatInterfaze(api_key="t").stream([HumanMessage("x")]) if isinstance(c.content, str) ) - # the tail is recovered, but a half-written is metadata and is cut - assert body == "\nThe sky is blue because " + # the response completed, so an unmatched tag is prose and survives + assert body == "\nThe sky is blue because " @respx.mock @@ -277,3 +282,64 @@ def test_truncated_precontext_is_not_shown_as_content() -> None: assert "precontext" not in body assert "123-45-6789" not in body assert body == "Total is " + + +@respx.mock +def test_invoke_truncated_precontext_is_not_content() -> None: + """The truncation rule applies to invoke(), not just streaming.""" + mock_json(completion('Total is [{"ssn":"123-45-6789"', finish_reason="length")) + res = ChatInterfaze(api_key="t").invoke([HumanMessage("x")]) + assert "123-45-6789" not in str(res.content) + + +@respx.mock +def test_invoke_truncated_think_becomes_reasoning() -> None: + mock_json(completion("SSN 123-45-6789 so", finish_reason="length")) + res = ChatInterfaze(api_key="t").invoke([HumanMessage("x")]) + assert "123-45-6789" not in str(res.content) + assert "123-45-6789" in str(res.response_metadata["reasoning"]) + + +@respx.mock +def test_completed_response_keeps_prose_that_mentions_a_tag() -> None: + """An unmatched tag in a finished response is prose, not a side channel.""" + mock_json(completion("Wrap metadata in tags, then continue.")) + res = ChatInterfaze(api_key="t").invoke([HumanMessage("x")]) + assert res.content == "Wrap metadata in tags, then continue." + + +@respx.mock +def test_final_side_chunk_stamps_model_provider() -> None: + mock_sse(THINK_SPLIT) + chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) + # core appends its own empty chunk_position="last" sentinel; every chunk we emit is stamped + ours = [c for c in chunks if c.chunk_position != "last"] + assert {c.response_metadata.get("model_provider") for c in ours} == {"interfaze"} + + +@respx.mock +def test_structured_output_streams_and_keeps_side_fields() -> None: + """with_structured_output streams through beta.chat.completions, which nests every + frame under "chunk" and omits `role` on the completion it assembles.""" + + class Ans(BaseModel): + answer: str + + # conftest's chunk() omits `role`, exactly as interfaze does after the first delta + frames = [chunk({"content": '{"answer":'}), chunk({"content": '"blue"}'}), chunk({}, "stop")] + frames[-1]["precontext"] = [{"name": "ocr", "output": "x"}] + mock_sse(frames) + model = ChatInterfaze(api_key="t").with_structured_output(Ans, include_raw=True) + out = [c for c in model.stream([HumanMessage("x")])] + assert any(c.get("parsed") == Ans(answer="blue") for c in out) + raw = next(c["raw"] for c in out if c.get("raw")) + assert raw.additional_kwargs["precontext"] == [{"name": "ocr", "output": "x"}] + + +@respx.mock +def test_roleless_deltas_still_produce_ai_message_chunks() -> None: + frames = [chunk({"content": "hi"}), chunk({}, "stop")] + mock_sse(frames) + chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) + assert all(isinstance(c, AIMessageChunk) for c in chunks) + assert "".join(c.content for c in chunks) == "hi" # ty:ignore[no-matching-overload] From 69866569579c973605419c27f3849d78c0591f51 Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 15:05:57 -0700 Subject: [PATCH 17/28] ci: gate publishing on matching versions and passing tests MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Five files carry the version and two of them ship as a User-Agent, so a release cut from the wrong commit would publish the previous version to three registries without complaint. A single check compares all five — to each other on every PR, and to the release tag before anything is built or pushed. The publish jobs also ran neither test suite; a release from any commit could ship code that never passed. They now depend on a verify job that does. --- .github/workflows/ci.yml | 7 +++++++ .github/workflows/publish.yml | 25 +++++++++++++++++++++++++ scripts/check-versions.mjs | 23 +++++++++++++++++++++++ 3 files changed, 55 insertions(+) create mode 100644 scripts/check-versions.mjs diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 3f58a40..02913b8 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -36,6 +36,13 @@ jobs: - name: Unit tests run: uv run pytest tests/unit_tests/ --disable-socket --allow-unix-socket --cov=langchain_interfaze --cov-report=term-missing --cov-fail-under=95 + versions: + name: versions agree + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v5 + - run: node scripts/check-versions.mjs + secret-scan: name: secret scan (gitleaks) runs-on: ubuntu-latest diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index 037174a..099c6d4 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -8,7 +8,32 @@ permissions: contents: read jobs: + # Five files carry the version and two of them reach users as a User-Agent. A release + # cut from the wrong commit would otherwise publish the previous version, silently. + verify: + name: verify (versions match the tag · tests pass) + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v5 + - name: Versions match the release tag + run: node scripts/check-versions.mjs "$GITHUB_REF_NAME" + - uses: astral-sh/setup-uv@v9.0.0 + with: + python-version: "3.12" + - name: Python tests + working-directory: python + run: uv run --all-groups pytest tests/unit_tests/ --disable-socket --allow-unix-socket + - uses: actions/setup-node@v7 + with: + node-version: 22 + cache: npm + cache-dependency-path: js/package-lock.json + - name: JS tests + working-directory: js + run: npm ci && npm test + build: + needs: verify runs-on: ubuntu-latest defaults: run: diff --git a/scripts/check-versions.mjs b/scripts/check-versions.mjs new file mode 100644 index 0000000..ecf1a1f --- /dev/null +++ b/scripts/check-versions.mjs @@ -0,0 +1,23 @@ +// Five files carry the version and two of them reach users as a User-Agent. A release +// cut from the wrong commit would otherwise publish the previous version, silently. +import { readFileSync } from "node:fs"; + +const read = (path) => readFileSync(new URL(`../${path}`, import.meta.url), "utf8"); +const match = (path, re) => (read(path).match(re) ?? [])[1]; + +const versions = { + "python/pyproject.toml": match("python/pyproject.toml", /^version = "(.+)"$/m), + "python/langchain_interfaze/_version.py": match("python/langchain_interfaze/_version.py", /^__version__ = "(.+)"$/m), + "js/package.json": JSON.parse(read("js/package.json")).version, + "js/jsr.json": JSON.parse(read("js/jsr.json")).version, + "js/src/version.ts": match("js/src/version.ts", /VERSION = "(.+)"/), +}; + +// With no tag argument the five just have to agree with each other, which is what the +// PR check wants; on a release they also have to agree with the tag. +const tag = process.argv[2]?.replace(/^v/, "") || versions["js/package.json"]; +const wrong = Object.entries(versions).filter(([, version]) => version !== tag); + +for (const [file, version] of wrong) console.error(`::error file=${file}::${version} does not match ${tag}`); +if (wrong.length) process.exit(1); +console.log(`all five versions are ${tag}`); From d55662dbb44727769057c90a15c0e0dfa49cbf3c Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 15:07:08 -0700 Subject: [PATCH 18/28] fix(python): declare the readme so the pypi page is not blank twine check warned that long_description was missing: pyproject never pointed at README.md, so the published project page would have rendered empty. --- python/pyproject.toml | 1 + 1 file changed, 1 insertion(+) diff --git a/python/pyproject.toml b/python/pyproject.toml index ae2b767..9ad4da4 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -6,6 +6,7 @@ build-backend = "hatchling.build" name = "langchain-interfaze" version = "1.0.0" description = "Interfaze Langchain SDK" +readme = "README.md" requires-python = ">=3.10" license = { text = "MIT" } authors = [{ name = "InterfazeAI" }] From be6708831bb98631ef1ceb879227396dc2ecfd8a Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 15:41:07 -0700 Subject: [PATCH 19/28] fix: real v3 event stream, empty-think fallthrough, per-key cache separation MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit _streamChatModelEvents delegated to BaseChatModel, which buys tag-stripping and loses everything else: convertChunksToEvents hardcodes reason: "stop" and emits no responseMetadata, so a v3 consumer saw "stop" on a truncated response and had no way to reach precontext, reasoning or vcache. Neither inherited implementation is usable as-is — the parent's reads the raw stream and leaks — so convert our own stripped chunks and put the metadata back on the terminal event. Both live gates now assert the finish reason; neither did, which is why this went unnoticed. A closed but empty sets reasoning to "": present, so `??` kept it over the recovered tail, while python's `or` fell through. Truncated input "visiblepartial" lost its reasoning in js only. python's cache key had nothing derived from the api key, so two tenants shared cache entries — the previous commit's claim that both packages fingerprint the key was true of js alone. file_id is now rejected in the openai-native {file: {file_id}} nesting too, and js emits a standalone chunk for an envelope frame exactly where python does. Also: guard `process` so a browser bundle throws InterfazeError rather than ReferenceError, raise the @langchain/core peer floor to ^1.2.5 to match what @langchain/openai itself requires, drop the langchain-openai <1.5 ceiling that would block installs the day 1.5.0 ships, and bound the QA request timeout so a hung call fails its own check instead of the whole job. --- js/package.json | 4 +- js/scripts/qa-live.ts | 18 +++++- js/src/chat_models.ts | 77 ++++++++++++++++++----- js/test/constructor.test.ts | 13 ++++ js/test/side_fields.test.ts | 14 +++++ js/test/stream.test.ts | 47 +++++++++++++- js/test/video.test.ts | 7 +++ python/langchain_interfaze/chat_models.py | 16 ++++- python/pyproject.toml | 2 +- python/scripts/qa_live.py | 18 +++++- python/tests/unit_tests/test_client.py | 7 +++ python/tests/unit_tests/test_inputs.py | 8 +++ python/tests/unit_tests/test_stream.py | 43 +++++++++++++ 13 files changed, 249 insertions(+), 25 deletions(-) diff --git a/js/package.json b/js/package.json index 0a8e817..424d586 100644 --- a/js/package.json +++ b/js/package.json @@ -55,7 +55,7 @@ "prepublishOnly": "npm run build" }, "peerDependencies": { - "@langchain/core": "^1.2.2", + "@langchain/core": "^1.2.5", "@langchain/openai": "^1.5.5", "interfaze": ">=1.0.3 <2", "zod": "^3.23.0 || ^4.4.3" @@ -67,7 +67,7 @@ }, "devDependencies": { "@arethetypeswrong/cli": "0.18.5", - "@langchain/core": "^1.2.2", + "@langchain/core": "^1.2.5", "@langchain/openai": "^1.5.6", "@types/node": "~22.20.1", "@vitest/coverage-v8": "^2.1.9", diff --git a/js/scripts/qa-live.ts b/js/scripts/qa-live.ts index e807daa..90b37a4 100644 --- a/js/scripts/qa-live.ts +++ b/js/scripts/qa-live.ts @@ -2,6 +2,7 @@ import { HumanMessage, SystemMessage, type AIMessage } from "@langchain/core/messages"; import { ChatPromptTemplate } from "@langchain/core/prompts"; import { tool } from "@langchain/core/tools"; +import { InterfazeError } from "interfaze"; import { z } from "zod"; import { ChatInterfaze, type ChatInterfazeFields } from "../src/index.js"; @@ -17,6 +18,9 @@ function makeLlm(fields: Partial = {}): ChatInterfaze { return new ChatInterfaze({ apiKey: loadKey(), maxRetries: 1, + // The library default is 900s; under the workflow's timeout-minutes: 30 a single + // hung call would kill the job before it printed anything. + timeout: 180_000, ...fields, ...(BASE_URL ? { configuration: { baseURL: BASE_URL, ...fields.configuration } } : {}), }); @@ -145,7 +149,10 @@ await check("streamed precontext (deduped)", async () => { const stream = await makeLlm({ showAdditionalInfo: true, bypassCache: true }).stream([ask("Extract the total price.", filePart(ASSETS.receipt))]); for await (const chunk of stream) { if (typeof chunk.content === "string") visible += chunk.content; - if (chunk.response_metadata.precontext) got.push(chunk.response_metadata.precontext); + // `[]` is truthy in JS and falsy in python; without this the same response + // scores differently in the two gates. + const pc = chunk.response_metadata.precontext; + if (Array.isArray(pc) ? pc.length > 0 : pc) got.push(pc); } assert(got.length > 0, "no streamed precontext"); assert(got.length === 1, `precontext emitted ${got.length}x; should be deduped to 1`); @@ -197,19 +204,25 @@ await check("streamEvents (tags stripped)", async () => { // leak assertion below passes vacuously. Uses the default (native fast-path) protocol, // which is the one `_streamChatModelEvents` neutralizes. let out = ""; + let finish: { reason?: string; responseMetadata?: Record } | undefined; const model = makeLlm({ bypassCache: true, reasoningEffort: "high" }); for await (const ev of model.streamEvents("Why is the sky blue? Briefly.")) { if (ev.event === "content-block-delta" && ev.delta.type === "text-delta") out += ev.delta.text; + if (ev.event === "message-finish") finish = ev; } assert(out.length > 0, "no events"); assert(!out.includes(""), "think tag leaked into events"); + // The python gate asserts the same two fields on on_chat_model_end; without them a + // stream that silently reports the wrong finish reason still passes. + assert(finish?.reason === "stop", `finish reason ${finish?.reason}`); + assert(finish?.responseMetadata?.model_provider === "interfaze", "no model_provider on the terminal event"); let sawReasoning = false; for await (const c of await model.stream("Why is the sky blue? Briefly.")) { if (c.response_metadata.reasoning) sawReasoning = true; } assert(sawReasoning, "no reasoning produced — a leak would be undetectable here"); - return `${out.length} chars, reasoning confirmed present`; + return `${out.length} chars, finish_reason + reasoning confirmed`; }); async function rejects(name: string, detail: string, run: () => Promise) { @@ -248,6 +261,7 @@ await check("rejects a video file_id client-side", async () => { try { await llm.invoke([ask("what is this?", { type: "video", file_id: "file-123" })]); } catch (e) { + assert(e instanceof InterfazeError, `expected InterfazeError, got ${(e as Error).constructor.name}`); assert((e as Error).message.includes("file_id"), (e as Error).message); return "InterfazeError"; } diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index d8ee31a..0c82387 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -1,6 +1,7 @@ import type { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager"; -import { BaseChatModel, type LangSmithParams } from "@langchain/core/language_models/chat_models"; -import type { ChatModelStreamEvent } from "@langchain/core/language_models/event"; +import { type LangSmithParams } from "@langchain/core/language_models/chat_models"; +import { convertChunksToEvents } from "@langchain/core/language_models/compat"; +import type { ChatModelStreamEvent, FinishReason } from "@langchain/core/language_models/event"; import { AIMessage, AIMessageChunk, type BaseMessage, isAIMessage } from "@langchain/core/messages"; import { ChatGenerationChunk, type ChatResult } from "@langchain/core/outputs"; import { ChatOpenAICompletions, type ChatOpenAIFields, normalizeHeaders } from "@langchain/openai"; @@ -10,6 +11,15 @@ import { VERSION } from "./version.js"; const PROVIDER = "interfaze"; +// The v3 protocol has its own vocabulary; anything unmapped leaves `reason` untouched. +const FINISH_REASONS: Record = { + stop: "stop", + length: "length", + tool_calls: "tool_use", + function_call: "tool_use", + content_filter: "content_filter", +}; + const DEFAULT_TIMEOUT_MS = 900_000; const HEADER_SHOW_ADDITIONAL_INFO = "x-show-additional-info"; @@ -150,7 +160,7 @@ function stripTags(message: AIMessage, truncated = false): void { const stripped = stripSideChannels(message.content); const recovered = truncated ? recoverTail(message.content, "", true) : null; const text = recovered ? recovered.tail.trim() : stripped.text; - const reasoning = stripped.reasoning ?? recovered?.reasoning; + const reasoning = stripped.reasoning || recovered?.reasoning; const { precontext } = stripped; if (text !== message.content) message.content = text; if (reasoning && !hasValue(message.response_metadata.reasoning)) { @@ -173,7 +183,9 @@ function rewriteContent(content: unknown): unknown { return convertVideoBlock(block as VideoBlock); } // Interfaze has no file store, so a file_id reference can only 400 downstream. - if ((block as { file_id?: unknown }).file_id != null) { + // Both the standard block shape and the openai-native nesting under `file`. + const nested = (block as { file?: { file_id?: unknown } }).file?.file_id; + if ((block as { file_id?: unknown }).file_id != null || nested != null) { throw new InterfazeError("Interfaze cannot resolve content by 'file_id'. Pass 'url' or 'base64' instead."); } return block; @@ -236,7 +248,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { constructor(fields: ChatInterfazeFields = {}) { const { apiKey, model, configuration, timeout, showAdditionalInfo, bypassMoA, bypassCache, reasoningEffort, ...rest } = fields; - const key = apiKey ?? process.env.INTERFAZE_API_KEY; + const key = apiKey ?? (typeof process !== "undefined" ? process.env?.INTERFAZE_API_KEY : undefined); if (!key) { throw new InterfazeError("Missing API key. Pass new ChatInterfaze({ apiKey: ... }) or set the INTERFAZE_API_KEY environment variable."); } @@ -362,6 +374,13 @@ export class ChatInterfaze extends ChatOpenAICompletions { this.#frameSinks.set(options, frames); let streamId: string | undefined; let finishReason: unknown; + const sideChunk = (side: Record): ChatGenerationChunk | null => { + const message = new AIMessageChunk({ content: "", id: streamId }); + applySideFields(message, side, seen); + if (Object.keys(message.additional_kwargs).length === 0) return null; + message.response_metadata.model_provider = PROVIDER; + return new ChatGenerationChunk({ message, text: "" }); + }; for await (const gen of super._streamResponseChunks(this.rewriteVideoBlocks(messages), options, runManager)) { const message = gen.message as unknown as SideChannelCarrier; streamId ??= (gen.message as AIMessageChunk).id; @@ -370,10 +389,6 @@ export class ChatInterfaze extends ChatOpenAICompletions { const raw = message.additional_kwargs.__raw_response as Record | undefined; if (raw) applySideFields(message, raw, seen); delete message.additional_kwargs.__raw_response; - // Envelope frames arrive interleaved with content, so apply them here rather than - // at stream end: same ordering as python, and a consumer that breaks early still - // sees everything the server had already sent. - for (const frame of frames.splice(0)) applySideFields(message, frame, seen); if (typeof message.content === "string" && message.content) { rawParts.push(message.content); const filtered = filter.feed(message.content); @@ -383,6 +398,13 @@ export class ChatInterfaze extends ChatOpenAICompletions { // message.content, so keep it in sync or callbacks see the raw tags. gen.text = filtered; } + // Envelope frames arrive interleaved with content, so emit them here rather than at + // stream end: python yields the same standalone chunk in the same position, and a + // consumer that breaks early still sees everything the server had already sent. + for (const frame of frames.splice(0)) { + const side = sideChunk(frame); + if (side) yield side; + } yield gen; } const joined = rawParts.join(""); @@ -391,7 +413,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { const recovered = flushed ? { tail: flushed } : recoverTail(joined, emittedParts.join(""), finishReason === "length"); const tail = recovered.tail; const { precontext } = stripSideChannels(joined); - const reasoning = stripSideChannels(joined).reasoning ?? recovered.reasoning; + const reasoning = stripSideChannels(joined).reasoning || recovered.reasoning; if (tail) { const message = new AIMessageChunk({ content: tail, id: streamId }); message.response_metadata.model_provider = PROVIDER; @@ -405,19 +427,42 @@ export class ChatInterfaze extends ChatOpenAICompletions { // One chunk per source, so langchain's own merge concatenates them — the same // behaviour the python package gets for free from its per-chunk conversion. for (const side of [...frames.splice(0), inline]) { - const message = new AIMessageChunk({ content: "", id: streamId }); - applySideFields(message, side, seen); - if (Object.keys(message.additional_kwargs).length === 0) continue; - message.response_metadata.model_provider = PROVIDER; - yield new ChatGenerationChunk({ message, text: "" }); + const chunk = sideChunk(side); + if (chunk) yield chunk; } } + /** + * Neither inherited implementation is usable as-is: the parent's reads the raw stream, + * so `` leaks into the events, while `convertChunksToEvents` strips tags but + * hardcodes `reason: "stop"` and emits no `responseMetadata`. Convert our own stripped + * chunks, then put the metadata back on the terminal event so a v3 consumer sees what + * `invoke()` would have given it — including the side channels. + */ override async *_streamChatModelEvents( messages: BaseMessage[], options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun ): AsyncGenerator { - yield* BaseChatModel.prototype._streamChatModelEvents.call(this, messages, options, runManager); + const responseMetadata: Record = {}; + const source = this._streamResponseChunks(messages, options, runManager); + const observed = (async function* () { + for await (const gen of source) { + Object.assign(responseMetadata, gen.message.response_metadata); + for (const key of ["finish_reason", "model_name"] as const) { + const value = gen.generationInfo?.[key]; + if (value != null) responseMetadata[key] = value; + } + yield gen; + } + })(); + for await (const event of convertChunksToEvents(observed, { signal: options.signal })) { + if (event.event !== "message-finish") { + yield event; + continue; + } + const reason = FINISH_REASONS[String(responseMetadata.finish_reason)]; + yield { ...event, ...(reason ? { reason } : {}), responseMetadata }; + } } } diff --git a/js/test/constructor.test.ts b/js/test/constructor.test.ts index 8ac380e..2d1dc7f 100644 --- a/js/test/constructor.test.ts +++ b/js/test/constructor.test.ts @@ -150,3 +150,16 @@ describe("header values", () => { expect(model.clientConfig.defaultHeaders).toMatchObject({ "x-retries": "3", "x-debug": "true" }); }); }); + +describe("runtimes without process", () => { + it("throws InterfazeError rather than ReferenceError when process is absent", () => { + const saved = globalThis.process; + // @ts-expect-error simulating a browser/edge bundle + delete globalThis.process; + try { + expect(() => new ChatInterfaze()).toThrow(InterfazeError); + } finally { + globalThis.process = saved; + } + }); +}); diff --git a/js/test/side_fields.test.ts b/js/test/side_fields.test.ts index de99ae6..b1a3f59 100644 --- a/js/test/side_fields.test.ts +++ b/js/test/side_fields.test.ts @@ -114,3 +114,17 @@ describe("stream ordering", () => { expect(vcache).toBe(true); }); }); + +describe("empty closed side channels", () => { + // `` sets reasoning to "": present but empty. `??` would keep it and + // discard the recovered tail, which is what python's `or` does not do. + it("falls through an empty to the recovered reasoning", async () => { + const raw = "visiblepartial reasoning"; + const { model } = mockChat(() => + jsonResponse(completion(raw, { choices: [{ index: 0, message: { role: "assistant", content: raw }, finish_reason: "length" }] })) + ); + const res = (await model.invoke("x")) as AIMessage; + expect(res.content).toBe("visible"); + expect(res.response_metadata.reasoning).toBe("partial reasoning"); + }); +}); diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 3752255..512f8ba 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -239,7 +239,8 @@ describe("streaming side-channel filter", () => { const { model } = mockChat(() => sseResponse(chunks)); const got = await collect(model as never); const ids = new Set(got.map((c) => (c as unknown as { id?: string }).id)); - expect(ids.size).toBe(1); + // size 1 alone would also pass for a set of all-undefined + expect([...ids]).toEqual(["req-test"]); }); it("emits no side-channel chunk for plain content", async () => { @@ -252,3 +253,47 @@ describe("streaming side-channel filter", () => { expect(got.some((c) => "__raw_response" in c.additional_kwargs)).toBe(false); }); }); + +async function lastFinishEvent(model: { streamEvents: (input: string) => AsyncIterable> }): Promise> { + let finish: Record | undefined; + for await (const ev of model.streamEvents("x")) if (ev.event === "message-finish") finish = ev; + if (!finish) throw new Error("no message-finish event"); + return finish; +} + +describe("v3 stream events", () => { + const frames = [chunk({ content: "rHi" }), envelopeChunk({ vcache: true, precontext: [{ name: "ocr" }] }), chunk({}, "length")]; + + it("reports the real finish reason, not a hardcoded stop", async () => { + const { model } = mockChat(() => sseResponse(frames)); + const finish = await lastFinishEvent(model); + expect(finish.reason).toBe("length"); + }); + + it("carries responseMetadata and the side channels to v3 consumers", async () => { + const { model } = mockChat(() => sseResponse(frames)); + const finish = await lastFinishEvent(model); + expect(finish.responseMetadata).toMatchObject({ + model_provider: "interfaze", + model_name: "interfaze-beta", + finish_reason: "length", + vcache: true, + precontext: [{ name: "ocr" }], + reasoning: "r", + }); + }); + + it("still strips tags from the event text", async () => { + const { model } = mockChat(() => sseResponse(frames)); + let text = ""; + for await (const ev of model.streamEvents("x")) { + if (ev.event === "content-block-delta" && ev.delta.type === "text-delta") text += ev.delta.text; + } + expect(text).toBe("Hi"); + }); + + it("maps tool_calls onto the v3 tool_use vocabulary", async () => { + const { model } = mockChat(() => sseResponse([chunk({ content: "x" }), chunk({}, "tool_calls")])); + expect((await lastFinishEvent(model)).reason).toBe("tool_use"); + }); +}); diff --git a/js/test/video.test.ts b/js/test/video.test.ts index 214d36c..58c737d 100644 --- a/js/test/video.test.ts +++ b/js/test/video.test.ts @@ -65,6 +65,13 @@ describe("video content blocks", () => { await expect(model.invoke([new HumanMessage({ content: [{ type: "file", file_id: "file-123" }] as never })])).rejects.toThrow(/file_id/); }); + it("rejects the openai-native nesting, file.file_id", async () => { + const { model } = mockChat(() => jsonResponse(completion())); + await expect(model.invoke([new HumanMessage({ content: [{ type: "file", file: { file_id: "file-abc" } }] as never })])).rejects.toThrow( + /file_id/ + ); + }); + it("throws when a video block has no source", async () => { const { model } = mockChat(() => jsonResponse(completion())); await expect(model.invoke([new HumanMessage({ content: [{ type: "video" }] as never })])).rejects.toThrow(InterfazeError); diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 402941d..d11673f 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -73,6 +73,10 @@ def _default_role(response: Any, field: str) -> None: part.role = "assistant" +def _digest(value: str) -> str: + return hashlib.sha256(value.encode()).hexdigest()[:12] + + def _redact_headers(headers: Mapping[str, str]) -> list[str]: """`_identifying_params` reaches both the LLM cache key and the `invocation_params` LangSmith records, so a caller's header value is fingerprinted rather than published. @@ -146,8 +150,11 @@ def _rewrite_video_blocks(content: Any) -> Any: rewritten.append(block) elif block.get("type") == "video": rewritten.append(_convert_video_block(block)) - elif block.get("file_id") is not None: + elif block.get("file_id") is not None or ( + isinstance(block.get("file"), dict) and block["file"].get("file_id") is not None + ): # Interfaze has no file store, so a file_id reference can only 400 downstream. + # Both the standard block shape and the openai-native nesting under `file`. raise InterfazeError( "Interfaze cannot resolve content by 'file_id'. Pass 'url' or 'base64' instead." ) @@ -324,8 +331,13 @@ def _set_interfaze_version(self) -> Self: @property def _identifying_params(self) -> dict[str, Any]: - # Without these, set_llm_cache serves a bypass_cache model the plain model's answer. + # Without these, set_llm_cache serves a bypass_cache model the plain model's answer, + # and one tenant's key the answer cached under another's. params = {**super()._identifying_params, "_type": self._llm_type} + # A callable key is resolved per request, so there is no stable value to key on — + # the js package skips the fingerprint in that case too. + if isinstance(self.openai_api_key, SecretStr): + params["interfaze_key"] = _digest(self.openai_api_key.get_secret_value()) if self.default_headers: params["interfaze_headers"] = _redact_headers(self.default_headers) return params diff --git a/python/pyproject.toml b/python/pyproject.toml index 9ad4da4..d9a4324 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -18,7 +18,7 @@ classifiers = [ ] dependencies = [ "interfaze>=1.0.3,<2", - "langchain-openai>=1.4.1,<1.5", + "langchain-openai>=1.4.1,<2", "langchain-core>=1.0,<2", "pydantic>=2,<3", ] diff --git a/python/scripts/qa_live.py b/python/scripts/qa_live.py index c68190e..03b5c3f 100644 --- a/python/scripts/qa_live.py +++ b/python/scripts/qa_live.py @@ -30,6 +30,9 @@ def make_llm(**kwargs: Any) -> ChatInterfaze: base_url = os.environ.get("INTERFAZE_BASE_URL") if base_url: kwargs.setdefault("base_url", base_url) + # The library default is 900s; under the workflow's timeout-minutes: 30 a single + # hung call would kill the job before it printed anything. + kwargs.setdefault("timeout", 180.0) return ChatInterfaze(api_key=load_key(), max_retries=1, **kwargs) @@ -294,16 +297,29 @@ def rejects_bad_base64() -> str: async def _astream_events() -> str: fresh = make_llm(bypass_cache=True, reasoning_effort="high") body = "" + end = None async for ev in fresh.astream_events("Why is the sky blue? Briefly.", version="v2"): if ev["event"] == "on_chat_model_stream": content = ev["data"]["chunk"].content if isinstance(content, str): body += content + elif ev["event"] == "on_chat_model_end": + end = ev["data"]["output"] _assert(body, "no events") _assert("" not in body, "think tag leaked into astream_events") + _assert(end is not None, "no on_chat_model_end event") + # The js gate asserts the same two fields on message-finish; without them a stream that + # silently reports the wrong finish reason still passes. + _assert( + end.response_metadata.get("finish_reason") == "stop", + f"finish_reason {end.response_metadata.get('finish_reason')}", + ) + _assert( + end.response_metadata.get("model_provider") == "interfaze", "no model_provider on the terminal event" + ) saw = any(c.response_metadata.get("reasoning") for c in fresh.stream("Why is the sky blue? Briefly.")) _assert(saw, "no reasoning produced — a leak would be undetectable here") - return f"{len(body)} chars, reasoning confirmed present" + return f"{len(body)} chars, finish_reason + reasoning confirmed" def astream_events() -> str: diff --git a/python/tests/unit_tests/test_client.py b/python/tests/unit_tests/test_client.py index 1f7aead..2eadbe3 100644 --- a/python/tests/unit_tests/test_client.py +++ b/python/tests/unit_tests/test_client.py @@ -133,3 +133,10 @@ def test_cache_key_does_not_publish_header_values() -> None: def test_cache_key_shows_the_flags_we_own() -> None: model = ChatInterfaze(api_key="k", bypass_cache=True) assert model._identifying_params["interfaze_headers"] == ["x-interfaze-bypass-cache=true"] + + +def test_cache_key_separates_two_api_keys() -> None: + a = ChatInterfaze(api_key="sk_tenant_a") + b = ChatInterfaze(api_key="sk_tenant_b") + assert a._get_llm_string() != b._get_llm_string() + assert "sk_tenant_a" not in a._get_llm_string() diff --git a/python/tests/unit_tests/test_inputs.py b/python/tests/unit_tests/test_inputs.py index 4965dc3..e87ef7f 100644 --- a/python/tests/unit_tests/test_inputs.py +++ b/python/tests/unit_tests/test_inputs.py @@ -68,6 +68,7 @@ def test_video_block_missing_source_raises() -> None: model.invoke([HumanMessage(content=[{"type": "video"}])]) +@respx.mock def test_file_id_rejected_on_any_block() -> None: model = ChatInterfaze(api_key="k") with pytest.raises(InterfazeError, match="file_id"): @@ -77,3 +78,10 @@ def test_file_id_rejected_on_any_block() -> None: def test_scalar_header_values_are_stringified() -> None: model = ChatInterfaze(api_key="k", default_headers={"X-Retries": 3}) # ty:ignore[invalid-argument-type] assert model.default_headers == {"x-retries": "3"} + + +@respx.mock +def test_file_id_rejected_in_the_openai_native_nesting() -> None: + model = ChatInterfaze(api_key="k") + with pytest.raises(InterfazeError, match="file_id"): + model.invoke([HumanMessage(content=[{"type": "file", "file": {"file_id": "file-abc"}}])]) diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index 99ad796..f1d63e6 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -343,3 +343,46 @@ def test_roleless_deltas_still_produce_ai_message_chunks() -> None: chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("x")])) assert all(isinstance(c, AIMessageChunk) for c in chunks) assert "".join(c.content for c in chunks) == "hi" # ty:ignore[no-matching-overload] + + +_EVENT_FRAMES = [ + chunk({"content": "rHi"}), + { + "id": "req-test", + "object": "chat.completion.chunk", + "created": 1, + "model": "interfaze-beta", + "choices": [], + "vcache": True, + "precontext": [{"name": "ocr"}], + }, + chunk({}, "length"), +] + + +@respx.mock +def test_astream_events_strips_tags_and_keeps_metadata() -> None: + """The js package needs a hand-written _streamChatModelEvents to reach this; python + gets it from the shared chunk path. Both must agree on what a v3 consumer sees.""" + + async def run() -> Any: + mock_sse(_EVENT_FRAMES) + async for ev in ChatInterfaze(api_key="t").astream_events([HumanMessage("x")], version="v2"): + if ev["event"] == "on_chat_model_end": + return ev["data"]["output"] + raise AssertionError("no on_chat_model_end event") + + out = asyncio.run(run()) + assert out.content == "Hi" + assert out.response_metadata["finish_reason"] == "length" + assert out.response_metadata["vcache"] is True + assert out.response_metadata["precontext"] == [{"name": "ocr"}] + assert out.response_metadata["reasoning"] == "r" + + +@respx.mock +def test_invoke_falls_through_an_empty_think_to_recovered_reasoning() -> None: + mock_json(completion("visiblepartial reasoning", finish_reason="length")) + res = ChatInterfaze(api_key="t").invoke([HumanMessage("x")]) + assert res.content == "visible" + assert res.response_metadata["reasoning"] == "partial reasoning" From 1a9d3b114a80d71e5225c9bd04d920ea1bf94d0d Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 16:07:10 -0700 Subject: [PATCH 20/28] fix: mypy narrowing, empty mime fallthrough, v3 metadata merge; docx coverage MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The #11 gate assertion left `end` as Any | None, which mypy rejects because _assert is a function and does not narrow the way a bare assert would — the py3.12 CI job was red. Two more of the same `??`-vs-`or` split the earlier pass missed. An empty-string mime_type is present-but-empty, so js shipped `data:;base64,…` — text/plain — where python shipped video/mp4. And _streamChatModelEvents accumulated metadata with Object.assign, which replaces: precontext is emitted one chunk per source precisely so langchain's merge concatenates it, so streamEvents showed the last source where .stream() showed both. It now accumulates through the same concat its consumers use. The api key fingerprint is `interfazeKey` to pair with python's `interfaze_key`. The api server gained docx support (interfaze 0a967da); it converts to PDF at ingestion, so nothing here needed changing, but both live gates now cover it and the readmes say so. --- README.md | 2 +- js/README.md | 2 +- js/scripts/qa-live.ts | 3 +++ js/src/chat_models.ts | 18 ++++++++++++------ js/test/side_fields.test.ts | 14 ++++++++++++++ js/test/video.test.ts | 7 +++++++ python/README.md | 2 +- python/scripts/qa_live.py | 5 ++++- python/tests/unit_tests/test_inputs.py | 10 ++++++++++ 9 files changed, 53 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 35155ac..bc61989 100644 --- a/README.md +++ b/README.md @@ -285,7 +285,7 @@ res.response_metadata.reasoning; ## Multimodal Inputs -Images, audio, PDFs, and CSV use standard LangChain content parts, by URL or base64: +Images, audio, PDFs, Word documents (`.docx`), and CSV use standard LangChain content parts, by URL or base64: Python: diff --git a/js/README.md b/js/README.md index 8f51167..031b582 100644 --- a/js/README.md +++ b/js/README.md @@ -144,7 +144,7 @@ Set it once on the model with `new ChatInterfaze({ reasoningEffort: "high" })`, ## Multimodal Inputs -Images, audio, PDFs, and CSV use standard LangChain content parts, by URL or base64: +Images, audio, PDFs, Word documents (`.docx`), and CSV use standard LangChain content parts, by URL or base64: ```ts await llm.invoke([ diff --git a/js/scripts/qa-live.ts b/js/scripts/qa-live.ts index 90b37a4..f9f11a2 100644 --- a/js/scripts/qa-live.ts +++ b/js/scripts/qa-live.ts @@ -37,6 +37,8 @@ const ASSETS = { video: "https://download.samplelib.com/mp4/sample-5s.mp4", csv: "https://r2public.jigsawstack.com/interfaze/examples/prediction-example.csv", pdf: "https://arxiv.org/pdf/1706.03762", + // Converted to PDF server-side at ingestion, so no client-side handling exists to break. + docx: "https://calibre-ebook.com/downloads/demos/demo.docx", }; let failures = 0; @@ -279,6 +281,7 @@ async function inputCheck(label: string, part: Record, prompt: await inputCheck("image url", image(ASSETS.id), "What kind of document is this?"); await inputCheck("pdf url", filePart(ASSETS.pdf, "paper.pdf"), "Give the title."); +await inputCheck("docx url", filePart(ASSETS.docx, "demo.docx"), "What is this document about?"); await inputCheck("audio url", filePart(ASSETS.audio, "stt-example.wav"), "Transcribe this."); await inputCheck("video block", { type: "video", url: ASSETS.video }, "Describe this video."); await inputCheck("csv url", filePart(ASSETS.csv, "data.csv"), "Name one column header."); diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 0c82387..eb41ef0 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -4,6 +4,7 @@ import { convertChunksToEvents } from "@langchain/core/language_models/compat"; import type { ChatModelStreamEvent, FinishReason } from "@langchain/core/language_models/event"; import { AIMessage, AIMessageChunk, type BaseMessage, isAIMessage } from "@langchain/core/messages"; import { ChatGenerationChunk, type ChatResult } from "@langchain/core/outputs"; +import { concat } from "@langchain/core/utils/stream"; import { ChatOpenAICompletions, type ChatOpenAIFields, normalizeHeaders } from "@langchain/openai"; import { INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError } from "interfaze"; import { SideChannelFilter, stripSideChannels, TAG_RE } from "./side_channels.js"; @@ -70,9 +71,9 @@ function convertVideoBlock(block: VideoBlock): Record { let file: Record; if (block.url != null) { file = { file_data: block.url }; - mime = mime ?? videoMimeFromUrl(block.url); + mime = mime || videoMimeFromUrl(block.url); } else if (block.base64 != null) { - mime = mime ?? "video/mp4"; + mime = mime || "video/mp4"; file = { file_data: `data:${mime};base64,${block.base64}` }; } else { throw new InterfazeError("Video content block requires one of 'url' or 'base64'."); @@ -277,7 +278,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { const { apiKey, defaultHeaders, ...rest } = super._identifyingParams(); return { ...rest, - ...(typeof apiKey === "string" ? { apiKeyFingerprint: digest(apiKey) } : {}), + ...(typeof apiKey === "string" ? { interfazeKey: digest(apiKey) } : {}), ...(defaultHeaders ? { interfazeHeaders: redactHeaders(defaultHeaders as Record) } : {}), } as ReturnType; } @@ -444,14 +445,18 @@ export class ChatInterfaze extends ChatOpenAICompletions { options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun ): AsyncGenerator { - const responseMetadata: Record = {}; + const generationInfo: Record = {}; + let merged: AIMessageChunk | undefined; const source = this._streamResponseChunks(messages, options, runManager); const observed = (async function* () { for await (const gen of source) { - Object.assign(responseMetadata, gen.message.response_metadata); + const message = gen.message as AIMessageChunk; + // concat is what `.stream()` consumers get, so the accumulating side fields + // concatenate here too rather than the last one winning. + merged = merged ? concat(merged, message) : message; for (const key of ["finish_reason", "model_name"] as const) { const value = gen.generationInfo?.[key]; - if (value != null) responseMetadata[key] = value; + if (value != null) generationInfo[key] = value; } yield gen; } @@ -461,6 +466,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { yield event; continue; } + const responseMetadata = { ...merged?.response_metadata, ...generationInfo }; const reason = FINISH_REASONS[String(responseMetadata.finish_reason)]; yield { ...event, ...(reason ? { reason } : {}), responseMetadata }; } diff --git a/js/test/side_fields.test.ts b/js/test/side_fields.test.ts index b1a3f59..6ebd38f 100644 --- a/js/test/side_fields.test.ts +++ b/js/test/side_fields.test.ts @@ -89,6 +89,20 @@ describe("identifying params", () => { }); }); +describe("v3 metadata merge", () => { + it("concatenates accumulating side fields the way .stream() does", async () => { + const frames = [ + chunk({ content: '[{"name":"from_inline"}]Hi' }), + envelopeChunk({ precontext: [{ name: "from_envelope" }] }), + chunk({}, "stop"), + ]; + const { model } = mockChat(() => sseResponse(frames)); + let finish: Record | undefined; + for await (const ev of model.streamEvents("x")) if (ev.event === "message-finish") finish = ev; + expect(finish?.responseMetadata?.precontext).toEqual([{ name: "from_envelope" }, { name: "from_inline" }]); + }); +}); + describe("stream ordering", () => { it("attaches envelope side fields to the chunk they arrived with", async () => { const { model } = mockChat(() => diff --git a/js/test/video.test.ts b/js/test/video.test.ts index 58c737d..11ef980 100644 --- a/js/test/video.test.ts +++ b/js/test/video.test.ts @@ -35,6 +35,13 @@ describe("video content blocks", () => { expect(part).toEqual({ type: "file", file: { file_data: "data:video/mp4;base64,AAAA", format: "video/mp4" } }); }); + // an empty string is present-but-empty; python's `or` falls through and `??` would not + it("falls through an empty mime_type to the default", async () => { + const { model, calls } = mockChat(() => jsonResponse(completion())); + await model.invoke([new HumanMessage({ content: [{ type: "video", base64: "AAAA", mime_type: "" }] as never })]); + expect(lastContent(calls)[0]!.file).toEqual({ file_data: "data:video/mp4;base64,AAAA", format: "video/mp4" }); + }); + it("rejects a file_id video block (interfaze has no file store)", async () => { const { model } = mockChat(() => jsonResponse(completion())); await expect(model.invoke([new HumanMessage({ content: [{ type: "video", file_id: "file-123" }] as never })])).rejects.toThrow(/file_id/); diff --git a/python/README.md b/python/README.md index ea283ed..21eccfc 100644 --- a/python/README.md +++ b/python/README.md @@ -157,7 +157,7 @@ res.response_metadata.get("reasoning") ## Multimodal Inputs -Images, audio, PDFs, and CSV use standard LangChain content parts, by URL or base64: +Images, audio, PDFs, Word documents (`.docx`), and CSV use standard LangChain content parts, by URL or base64: ```python from langchain_core.messages import HumanMessage diff --git a/python/scripts/qa_live.py b/python/scripts/qa_live.py index 03b5c3f..78fdd7e 100644 --- a/python/scripts/qa_live.py +++ b/python/scripts/qa_live.py @@ -47,6 +47,8 @@ def make_llm(**kwargs: Any) -> ChatInterfaze: "video": "https://download.samplelib.com/mp4/sample-5s.mp4", "csv": "https://r2public.jigsawstack.com/interfaze/examples/prediction-example.csv", "pdf": "https://arxiv.org/pdf/1706.03762", + # Converted to PDF server-side at ingestion, so no client-side handling exists to break. + "docx": "https://calibre-ebook.com/downloads/demos/demo.docx", "scene": "https://ultralytics.com/images/bus.jpg", } failures: list[str] = [] @@ -297,7 +299,7 @@ def rejects_bad_base64() -> str: async def _astream_events() -> str: fresh = make_llm(bypass_cache=True, reasoning_effort="high") body = "" - end = None + end: Any = None async for ev in fresh.astream_events("Why is the sky blue? Briefly.", version="v2"): if ev["event"] == "on_chat_model_stream": content = ev["data"]["chunk"].content @@ -376,6 +378,7 @@ def ocr_structured() -> str: input_check("image url", lambda: image(A["id"]), "What kind of document is this?") input_check("pdf url", lambda: file(A["pdf"], "paper.pdf"), "Give the title.") +input_check("docx url", lambda: file(A["docx"], "demo.docx"), "What is this document about?") input_check("audio url", lambda: file(A["audio"], "stt-example.wav"), "Transcribe this.") input_check("video block", lambda: {"type": "video", "url": A["video"]}, "Describe this video.") input_check("csv url", lambda: file(A["csv"], "data.csv"), "Name one column header.") diff --git a/python/tests/unit_tests/test_inputs.py b/python/tests/unit_tests/test_inputs.py index e87ef7f..ffde3d8 100644 --- a/python/tests/unit_tests/test_inputs.py +++ b/python/tests/unit_tests/test_inputs.py @@ -85,3 +85,13 @@ def test_file_id_rejected_in_the_openai_native_nesting() -> None: model = ChatInterfaze(api_key="k") with pytest.raises(InterfazeError, match="file_id"): model.invoke([HumanMessage(content=[{"type": "file", "file": {"file_id": "file-abc"}}])]) + + +@respx.mock +def test_empty_mime_type_falls_through_to_the_default() -> None: + route = mock_json(BASIC) + ChatInterfaze(api_key="t").invoke( + [HumanMessage(content=[{"type": "video", "base64": "AAAA", "mime_type": ""}])] + ) + part = last_body(route)["messages"][-1]["content"][0] + assert part["file"] == {"file_data": "data:video/mp4;base64,AAAA", "format": "video/mp4"} From 7ade8af0de6d5c0642a9a845e0c667ce3fc07511 Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Sat, 8 Aug 2026 16:14:59 -0700 Subject: [PATCH 21/28] fix: do not merge the raw metadata the server restates per frame Accumulating the terminal v3 metadata with concat fixed precontext but broke usage: the parent puts the same `usage` dict on two chunks and langchain's merge adds numbers, so message-finish reported exactly double the tokens a request cost. Every other openai-compatible provider reports true usage there, and consumers read it for cost attribution. Last wins for anything the server restates, concat only for the two fields emitted one chunk per source precisely so that langchain concatenates them. That split is the one the package already documents, so system_fingerprint and service_tier are covered too if interfaze ever sends them. --- js/src/chat_models.ts | 17 ++++++++++++----- js/test/side_fields.test.ts | 13 +++++++++++++ 2 files changed, 25 insertions(+), 5 deletions(-) diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index eb41ef0..c2a4465 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -445,18 +445,20 @@ export class ChatInterfaze extends ChatOpenAICompletions { options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun ): AsyncGenerator { - const generationInfo: Record = {}; + const responseMetadata: Record = {}; let merged: AIMessageChunk | undefined; const source = this._streamResponseChunks(messages, options, runManager); const observed = (async function* () { for await (const gen of source) { const message = gen.message as AIMessageChunk; - // concat is what `.stream()` consumers get, so the accumulating side fields - // concatenate here too rather than the last one winning. + // Last wins for everything the server restates per frame. Merging those instead + // would sum them: the parent puts `usage` on two chunks, and langchain's merge + // adds numbers, so the terminal event would report double the tokens. + Object.assign(responseMetadata, message.response_metadata); merged = merged ? concat(merged, message) : message; for (const key of ["finish_reason", "model_name"] as const) { const value = gen.generationInfo?.[key]; - if (value != null) generationInfo[key] = value; + if (value != null) responseMetadata[key] = value; } yield gen; } @@ -466,7 +468,12 @@ export class ChatInterfaze extends ChatOpenAICompletions { yield event; continue; } - const responseMetadata = { ...merged?.response_metadata, ...generationInfo }; + // ...except the two fields emitted one chunk per source precisely so that + // langchain's merge concatenates them, which is what `.stream()` consumers see. + for (const key of ACCUMULATING_SIDE_FIELDS) { + const value = merged?.response_metadata[key]; + if (value != null) responseMetadata[key] = value; + } const reason = FINISH_REASONS[String(responseMetadata.finish_reason)]; yield { ...event, ...(reason ? { reason } : {}), responseMetadata }; } diff --git a/js/test/side_fields.test.ts b/js/test/side_fields.test.ts index 6ebd38f..6275278 100644 --- a/js/test/side_fields.test.ts +++ b/js/test/side_fields.test.ts @@ -103,6 +103,19 @@ describe("v3 metadata merge", () => { }); }); +describe("v3 raw passthrough metadata", () => { + // The parent restates `usage` on two chunks and langchain's merge adds numbers, so + // merging it would report double the tokens a request actually cost. + it("reports the usage the server sent, not the sum of every frame", async () => { + const usage = { prompt_tokens: 100, completion_tokens: 20, total_tokens: 120 }; + const { model } = mockChat(() => sseResponse([chunk({ content: "Hi" }), { ...chunk({}, "stop"), usage }])); + let finish: Record | undefined; + for await (const ev of model.streamEvents("x")) if (ev.event === "message-finish") finish = ev; + expect(finish?.responseMetadata?.usage).toEqual(usage); + expect(finish?.usage).toMatchObject({ input_tokens: 100, output_tokens: 20, total_tokens: 120 }); + }); +}); + describe("stream ordering", () => { it("attaches envelope side fields to the chunk they arrived with", async () => { const { model } = mockChat(() => From b4503a20ba02e7755c709f73272dd64c6685af24 Mon Sep 17 00:00:00 2001 From: Abhinavexist Date: Mon, 10 Aug 2026 13:45:27 +0530 Subject: [PATCH 22/28] fix: split truncated side channels at the earliest tag, not the first looked for MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Review follow-ups on 7ade8af. Only the first is behavioural. - `_open_side_channel` / `openSideChannel` scanned for `` before `` and returned whichever it found first in *that* order, not the one that appears first in the text. Tool JSON can quote the string `` (a scrape of a page that discusses it, say), so a truncated response carrying an unclosed `` around such a payload split at the quoted tag: the raw `` and the tool output leaked into the answer, and the rest became `reasoning`. Both packages now take the earliest tag by position. Each new test was confirmed to fail against the previous scan. - `_redact_headers` inlined `hashlib.sha256(...)[:12]` instead of calling the `_digest` helper declared directly above it, so the two would drift apart the first time either changed. - Correct the `digest` comment in the js package: the value does travel to LangSmith, so "never compared across processes" was the wrong justification. The real one is that FNV-1a is not a security boundary here — 32 bits cannot be reversed to a key, and distinctness is all the cache key needs. - `stripSideChannels(joined)` ran twice in `_streamResponseChunks`. - Turn pytest warnings into errors, with a narrow ignore for the pydantic serializer warning `ParsedChatCompletion` raises upstream. A new warning is now a failure rather than a line nobody reads. Add CONTRIBUTING.md. The `tests/integration_tests` runbook had no home: CI runs only `tests/unit_tests/`, so the langchain-tests conformance suite was undiscoverable, and a pyproject comment kept getting stripped. It also documents the live QA gate and the five-file version check. Unit: python 74 -> 75, js 95 -> 96, green on py3.10-3.13. Live QA 31/31 python, 30/30 js. --- CONTRIBUTING.md | 59 +++++++++++++++++++++++ js/src/chat_models.ts | 25 ++++++---- js/test/stream.test.ts | 16 ++++++ python/langchain_interfaze/chat_models.py | 22 +++++---- python/pyproject.toml | 4 ++ python/tests/unit_tests/test_stream.py | 20 ++++++++ 6 files changed, 127 insertions(+), 19 deletions(-) create mode 100644 CONTRIBUTING.md diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md new file mode 100644 index 0000000..381674b --- /dev/null +++ b/CONTRIBUTING.md @@ -0,0 +1,59 @@ +# Contributing + +Two packages, one repo: [`python/`](./python) (`langchain-interfaze`) and [`js/`](./js) (`@interfaze-ai/langchain`). A change to one usually needs the same change to the other — the two are kept behaviourally identical. + +## Setup + +```bash +cd python && uv sync --all-groups +cd js && npm ci +``` + +## Unit tests + +Offline — every request is mocked, and CI runs these on every push. + +```bash +cd python && uv run pytest tests/unit_tests/ +cd js && npm test +``` + +Python also runs `ruff check .`, `ruff format --check .` and `mypy`; JS runs `npm run typecheck`, `npm run format:check` and `npm run check:pkg`. CI runs the Python suite against 3.10–3.13 and the JS suite against Node 20/22/24, so check the ends of both matrices before pushing anything version-sensitive: + +```bash +cd python && uv run --python 3.10 --all-groups pytest tests/unit_tests/ +``` + +## The langchain-tests standard harness + +`tests/integration_tests/` is LangChain's own `ChatModelIntegrationTests` conformance suite. It makes real calls, so it is not in CI and needs a key. It also has its own coverage expectations, hence `--no-cov`: + +```bash +cd python +INTERFAZE_API_KEY=sk_... uv run pytest tests/integration_tests --no-cov +``` + +## Live QA + +A go/no-go gate against the real API — every modality, the streaming side channels, and the negative contract cases. Not part of PR CI; the `Live QA` workflow runs it weekly and on demand. + +```bash +export INTERFAZE_API_KEY=sk_... +export INTERFAZE_BASE_URL=https://api.interfaze.ai/v1 # optional + +cd python && uv run python scripts/qa_live.py +cd js && npm run qa:live +``` + +Run both before cutting a release. They exercise paths the mocked suites cannot: real `` streaming, precontext from live tool runs, and the server-side validation limits the READMEs document. + +## Releasing + +Five files carry the version and must agree — `python/pyproject.toml`, `python/langchain_interfaze/_version.py`, `js/package.json`, `js/jsr.json`, `js/src/version.ts`. The last two reach users as a `User-Agent`. + +```bash +node scripts/check-versions.mjs # do the five agree? +node scripts/check-versions.mjs v1.2.3 # ...and do they match the tag? +``` + +CI runs the first form on every PR. Publishing runs the second against the release tag and re-runs both test suites before anything is uploaded; a GitHub prerelease goes to TestPyPI only, a full release to PyPI, npm and JSR. diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index c2a4465..702733a 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -134,12 +134,16 @@ function withoutClosedBlocks(raw: string): string { * model wrote (`"wrap it in tags"`); in a truncated one it is a side channel the * server never got to close. `finish_reason: "length"` is the only reliable signal. */ +// Earliest by position, not by tag order: a truncated answer whose visible prose mentions +// `` before an unclosed `` must split at the precontext. function openSideChannel(text: string): { tag: "think" | "precontext"; before: string; after: string } | null { - for (const tag of ["think", "precontext"] as const) { - const at = text.indexOf(`<${tag}>`); - if (at !== -1) return { tag, before: text.slice(0, at), after: text.slice(at + tag.length + 2) }; - } - return null; + const found = (["think", "precontext"] as const) + .map((tag) => ({ tag, at: text.indexOf(`<${tag}>`) })) + .filter(({ at }) => at !== -1) + .sort((a, b) => a.at - b.at); + const first = found[0]; + if (!first) return null; + return { tag: first.tag, before: text.slice(0, first.at), after: text.slice(first.at + first.tag.length + 2) }; } /** @@ -196,8 +200,10 @@ function rewriteContent(content: unknown): unknown { const PUBLIC_HEADERS: readonly string[] = [HEADER_SHOW_ADDITIONAL_INFO, HEADER_BYPASS_MOA, HEADER_BYPASS_CACHE]; -/** FNV-1a: no sync hash is available in every runtime this package runs in, and only - * distinctness matters here — the digest is never compared across processes. */ +/** FNV-1a: no sync cryptographic hash exists in every runtime this package runs in + * (`node:crypto` is not available in browsers or edge workers). Not a security + * boundary — a 32-bit digest cannot be reversed to a key, and the only property the + * cache key and the LangSmith trace need is that two different values differ. */ const digest = (value: string): string => { let hash = 0x811c9dc5; for (let i = 0; i < value.length; i += 1) hash = Math.imul(hash ^ value.charCodeAt(i), 0x01000193); @@ -413,8 +419,9 @@ export class ChatInterfaze extends ChatOpenAICompletions { const flushed = filter.flush(); const recovered = flushed ? { tail: flushed } : recoverTail(joined, emittedParts.join(""), finishReason === "length"); const tail = recovered.tail; - const { precontext } = stripSideChannels(joined); - const reasoning = stripSideChannels(joined).reasoning || recovered.reasoning; + const stripped = stripSideChannels(joined); + const { precontext } = stripped; + const reasoning = stripped.reasoning || recovered.reasoning; if (tail) { const message = new AIMessageChunk({ content: tail, id: streamId }); message.response_metadata.model_provider = PROVIDER; diff --git a/js/test/stream.test.ts b/js/test/stream.test.ts index 512f8ba..ec60140 100644 --- a/js/test/stream.test.ts +++ b/js/test/stream.test.ts @@ -234,6 +234,22 @@ describe("streaming side-channel filter", () => { expect(text).not.toContain("123-45-6789"); }); + // Split at the earliest unmatched tag, not the first one we happen to look for. Tool + // JSON can quote the string ``; scanning for think first would split there and + // leak the raw `` — and the tool payload — into the answer. + it("splits at a truncated that quotes ", async () => { + const chunks = [ + chunk({ content: "Total is " }), + chunk({ content: '[{"result":"page says here","ssn":"123-45-6789"' }, "length"), + ]; + const { model } = mockChat(() => sseResponse(chunks)); + const got = await collect(model as never); + const text = got.map((c) => (typeof c.content === "string" ? c.content : "")).join(""); + expect(text).toBe("Total is "); + expect(text).not.toContain("precontext"); + expect(got.some((c) => String(c.additional_kwargs.reasoning ?? "").includes("123-45-6789"))).toBe(false); + }); + it("stamps the stream id on synthetic chunks", async () => { const chunks = [chunk({ content: "rHi" }), chunk({}, "stop")]; const { model } = mockChat(() => sseResponse(chunks)); diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index d11673f..83b6c45 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -83,10 +83,7 @@ def _redact_headers(headers: Mapping[str, str]) -> list[str]: Two values still differ, which is all the cache key needs. The flags we own are ours to show.""" public = (_HEADER_SHOW_ADDITIONAL_INFO, _HEADER_BYPASS_MOA, _HEADER_BYPASS_CACHE) - return [ - f"{k}={headers[k]}" if k in public else f"{k}#{hashlib.sha256(headers[k].encode()).hexdigest()[:12]}" - for k in sorted(headers) - ] + return [f"{k}={headers[k]}" if k in public else f"{k}#{_digest(headers[k])}" for k in sorted(headers)] def _apply_side_fields(message: AIMessage, side: dict[str, Any]) -> None: @@ -216,12 +213,17 @@ def _without_closed_blocks(raw: str) -> str: def _open_side_channel(text: str) -> tuple[str, str, str] | None: - """Returns (tag, before, after) for the first unmatched opening tag.""" - for tag in ("think", "precontext"): - at = text.find(f"<{tag}>") - if at != -1: - return tag, text[:at], text[at + len(tag) + 2 :] - return None + """Returns (tag, before, after) for the earliest unmatched opening tag. + + Earliest by position, not by tag order: a truncated answer whose visible prose + mentions `` before an unclosed `` must split at the precontext. + """ + found = [(text.find(f"<{tag}>"), tag) for tag in ("think", "precontext")] + candidates = [(at, tag) for at, tag in found if at != -1] + if not candidates: + return None + at, tag = min(candidates) + return tag, text[:at], text[at + len(tag) + 2 :] def _recover_tail(raw: str, emitted: str, truncated: bool) -> tuple[str, str | None]: diff --git a/python/pyproject.toml b/python/pyproject.toml index d9a4324..e24348c 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -47,6 +47,10 @@ packages = ["langchain_interfaze"] asyncio_mode = "auto" testpaths = ["tests/unit_tests"] addopts = "" +filterwarnings = [ + "error", + 'ignore:Pydantic serializer warnings:UserWarning', +] [tool.ruff] line-length = 110 diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index f1d63e6..edfc0e8 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -284,6 +284,26 @@ def test_truncated_precontext_is_not_shown_as_content() -> None: assert body == "Total is " +@respx.mock +def test_truncated_precontext_wins_over_a_later_think_mention() -> None: + """Split at the earliest unmatched tag, not the first one we happen to look for. + + Tool JSON can quote the string ``; scanning for think first would split there + and leak the raw `` — and the tool payload — into the answer. + """ + mock_json( + completion( + 'Total is [{"result":"page says here","ssn":"123-45-6789"', + finish_reason="length", + ) + ) + res = ChatInterfaze(api_key="t").invoke([HumanMessage("x")]) + assert res.content == "Total is" + assert "precontext" not in str(res.content) + assert "123-45-6789" not in str(res.content) + assert "123-45-6789" not in str(res.response_metadata.get("reasoning") or "") + + @respx.mock def test_invoke_truncated_precontext_is_not_content() -> None: """The truncation rule applies to invoke(), not just streaming.""" From e3785bb560bfcde0ba7e5be1e0e91f442d96fbac Mon Sep 17 00:00:00 2001 From: Abhinavexist Date: Mon, 10 Aug 2026 14:02:31 +0530 Subject: [PATCH 23/28] docs: raise comment signal, restore the run_manager rationale MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Comment-only pass over both packages. Verified no code changed: the python files parse to an identical AST with docstrings removed, and the ts files hash identically with comments stripped. Removed section banners (`# defaults`, `# core`, `// input channels`), a `_first_effort` docstring that restated the comment at its only call site, a provenance citation quoting interfaze-python's implementation line, and roughly half the length of the longer blocks — `_default_role`, `_redact_headers`, `_recover_tail`, `_streamChatModelEvents`, the role-normalization note and the FNV digest note all keep every load-bearing clause in one or two sentences. Corrected `hasValue`, whose doc claimed an empty array counts as "present with no entries" when the function returns false for one. It now records why the helper exists: `[]` is truthy in JS, so a bare Boolean() would let an empty precontext block the real one. Added three comments where the reasoning was not inferable: - `run_manager=None` in `_stream`/`_astream`. Passing None to super() reads as a bug; "fixing" it puts unfiltered `` back in front of token callbacks. This had been written before and stripped again. - A short `__init__` docstring for the three control flags. That `show_additional_info` is the only way to get precontext while streaming does not follow from `bool`. - `showAdditionalInfo` on ChatInterfazeFields, whose two siblings were already documented. Kept everything describing upstream behaviour or a cross-package invariant: the HeadersLike spreading trap, normalizeHeaders dropping non-strings, the parent discarding choice-less frames, the WeakMap-keyed-on-options concurrency guarantee, gen.text needing manual sync, last-wins metadata avoiding double-counted usage, and stableStringify matching python's sort_keys=True. --- js/scripts/qa-live.ts | 2 - js/src/chat_models.ts | 56 ++++++++++------------ python/langchain_interfaze/chat_models.py | 57 ++++++++++++----------- python/scripts/qa_live.py | 1 - python/tests/unit_tests/test_client.py | 2 - 5 files changed, 56 insertions(+), 62 deletions(-) diff --git a/js/scripts/qa-live.ts b/js/scripts/qa-live.ts index f9f11a2..ebb3511 100644 --- a/js/scripts/qa-live.ts +++ b/js/scripts/qa-live.ts @@ -65,7 +65,6 @@ const names = (m: AIMessage): string[] => ((m.response_metadata.precontext as Array<{ name?: string }>) ?? []).map((p) => p?.name).filter((n): n is string => !!n); const text = (m: { content: unknown }) => (typeof m.content === "string" ? m.content : JSON.stringify(m.content)); -// core await check("text generation", async () => { const res = await llm.invoke("Say hi in one short sentence."); assert(text(res).length > 0, "empty"); @@ -270,7 +269,6 @@ await check("rejects a video file_id client-side", async () => { throw new Error("file_id was accepted"); }); -// input channels async function inputCheck(label: string, part: Record, prompt: string) { await check(`input: ${label}`, async () => { const res = await llm.invoke([ask(prompt, part)]); diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 702733a..2d031db 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -32,6 +32,8 @@ export type InterfazeReasoningEffort = "minimal" | "low" | "medium" | "high" | " export interface ChatInterfazeFields extends Omit { apiKey?: string; reasoningEffort?: InterfazeReasoningEffort; + /** Stream `` deltas (`x-show-additional-info`); the only way to get + * precontext while streaming, since non-streaming responses always carry it. */ showAdditionalInfo?: boolean; /** Skip the mixture-of-architecture internal tool router (`x-interfaze-bypass-moa`). */ bypassMoA?: boolean; @@ -94,7 +96,7 @@ type SideChannelCarrier = { const carriesValue = (value: unknown): boolean => value !== undefined && value !== null && value !== ""; -/** Truthy, but an empty array counts as "present with no entries". */ +/** `[]` is truthy in JS, so a bare Boolean() would let an empty precontext block the real one. */ const hasValue = (value: unknown): boolean => (Array.isArray(value) ? value.length > 0 : Boolean(value)); const ACCUMULATING_SIDE_FIELDS: readonly string[] = ["precontext", "reasoning"]; @@ -130,12 +132,11 @@ function withoutClosedBlocks(raw: string): string { } /** - * An unmatched tag means two different things. In a completed response it is prose the - * model wrote (`"wrap it in tags"`); in a truncated one it is a side channel the - * server never got to close. `finish_reason: "length"` is the only reliable signal. + * Earliest unmatched opening tag, by position rather than tag order — a truncated answer + * whose prose mentions `` before an unclosed `` must split at the + * precontext. Callers gate on truncation: in a completed response an unmatched tag is + * prose the model wrote, not a channel the server failed to close. */ -// Earliest by position, not by tag order: a truncated answer whose visible prose mentions -// `` before an unclosed `` must split at the precontext. function openSideChannel(text: string): { tag: "think" | "precontext"; before: string; after: string } | null { const found = (["think", "precontext"] as const) .map((tag) => ({ tag, at: text.indexOf(`<${tag}>`) })) @@ -200,10 +201,8 @@ function rewriteContent(content: unknown): unknown { const PUBLIC_HEADERS: readonly string[] = [HEADER_SHOW_ADDITIONAL_INFO, HEADER_BYPASS_MOA, HEADER_BYPASS_CACHE]; -/** FNV-1a: no sync cryptographic hash exists in every runtime this package runs in - * (`node:crypto` is not available in browsers or edge workers). Not a security - * boundary — a 32-bit digest cannot be reversed to a key, and the only property the - * cache key and the LangSmith trace need is that two different values differ. */ +/** FNV-1a because no sync cryptographic hash exists in every runtime this package runs in. + * Not a security boundary: distinctness is all the cache key and the trace need. */ const digest = (value: string): string => { let hash = 0x811c9dc5; for (let i = 0; i < value.length; i += 1) hash = Math.imul(hash ^ value.charCodeAt(i), 0x01000193); @@ -238,8 +237,8 @@ export class ChatInterfaze extends ChatOpenAICompletions { return "ChatInterfaze"; } - // A provider-family id, not a model id — `interfaze-beta` reaches tracing and the LLM - // cache key via `ls_model_name` / `model_name`. Mirrors ChatOpenAI's "openai-chat". + // Provider family, not the model: `interfaze-beta` reaches tracing and the cache key + // via `ls_model_name` / `model_name`. Mirrors ChatOpenAI's "openai-chat". override _llmType(): string { return "interfaze"; } @@ -277,9 +276,8 @@ export class ChatInterfaze extends ChatOpenAICompletions { this._addVersion("@interfaze-ai/langchain", VERSION); } - // The parent spreads clientConfig wholesale, so the api key and every default header - // land verbatim in the llm cache key. Fingerprint them instead: two values still - // differ, which is all the key needs, and neither is published. + // The parent spreads clientConfig wholesale, landing the api key and every default + // header verbatim in the llm cache key. Fingerprint them instead. override _identifyingParams(): ReturnType { const { apiKey, defaultHeaders, ...rest } = super._identifyingParams(); return { @@ -308,10 +306,9 @@ export class ChatInterfaze extends ChatOpenAICompletions { return params; } - // Interfaze sends `role` on the first delta only. Defensive: if a stream ever opens - // without one, the parent picks ChatMessageChunk, which carries no additional_kwargs - // (so no __raw_response) and fails isAIMessage(). The core interfaze SDKs normalize - // the same way (interfaze-python _stream.py: `if not delta.role: delta.role = ...`). + // Interfaze sends `role` on the first delta only. If a stream ever opens without one the + // parent picks ChatMessageChunk, which fails isAIMessage() and carries no + // additional_kwargs, so __raw_response and every side field are lost. protected override _convertCompletionsDeltaToBaseMessageChunk( delta: Record, rawResponse: any, @@ -320,9 +317,8 @@ export class ChatInterfaze extends ChatOpenAICompletions { return super._convertCompletionsDeltaToBaseMessageChunk(delta, rawResponse, defaultRole ?? "assistant"); } - // The parent drops choice-less frames before building a chunk, so side fields riding a - // usage-only frame are invisible downstream. Observe the raw frames rather than - // reshaping them — injecting a choice would also duplicate the usage envelope. + // The parent drops choice-less frames, hiding side fields that ride a usage-only frame. + // Observed rather than reshaped: injecting a choice would duplicate the usage envelope. override async completionWithRetry(request: any, requestOptions?: any): Promise { const result = await super.completionWithRetry(request, requestOptions); const sink = requestOptions && this.#frameSinks.get(requestOptions); @@ -405,9 +401,8 @@ export class ChatInterfaze extends ChatOpenAICompletions { // message.content, so keep it in sync or callbacks see the raw tags. gen.text = filtered; } - // Envelope frames arrive interleaved with content, so emit them here rather than at - // stream end: python yields the same standalone chunk in the same position, and a - // consumer that breaks early still sees everything the server had already sent. + // Emitted inline rather than at stream end so a consumer that breaks early still + // sees what the server had already sent, matching python's chunk positions. for (const frame of frames.splice(0)) { const side = sideChunk(frame); if (side) yield side; @@ -441,11 +436,10 @@ export class ChatInterfaze extends ChatOpenAICompletions { } /** - * Neither inherited implementation is usable as-is: the parent's reads the raw stream, - * so `` leaks into the events, while `convertChunksToEvents` strips tags but - * hardcodes `reason: "stop"` and emits no `responseMetadata`. Convert our own stripped - * chunks, then put the metadata back on the terminal event so a v3 consumer sees what - * `invoke()` would have given it — including the side channels. + * Neither inherited implementation works: the parent reads the raw stream so `` + * leaks into events, while `convertChunksToEvents` strips tags but hardcodes + * `reason: "stop"` and emits no `responseMetadata`. Convert our own filtered chunks and + * restore the metadata on the terminal event. */ override async *_streamChatModelEvents( messages: BaseMessage[], @@ -475,7 +469,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { yield event; continue; } - // ...except the two fields emitted one chunk per source precisely so that + // ...except the accumulating fields, whose one-chunk-per-source emission exists so // langchain's merge concatenates them, which is what `.stream()` consumers see. for (const key of ACCUMULATING_SIDE_FIELDS) { const value = merged?.response_metadata[key]; diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 83b6c45..108ee11 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -58,11 +58,12 @@ def _extract_side_fields(data: dict[str, Any]) -> dict[str, Any]: def _default_role(response: Any, field: str) -> None: - """Interfaze sends `role` on the first delta only, and omits it entirely on the - completion the beta stream assembles. The parent then builds a ChatMessage, which - pydantic rejects for role=None and which carries no additional_kwargs. - interfaze-python normalizes the same way (_stream.py). Handles both the dict and - the pydantic shape, since the two paths hand us different ones.""" + """Default a missing `role` to assistant, in place. + + Interfaze sends `role` on the first delta only. Without it the parent builds a + ChatMessage, which pydantic rejects for role=None and which carries no + additional_kwargs. Accepts dict and pydantic shapes; the two paths differ. + """ choices = response.get("choices") if isinstance(response, dict) else getattr(response, "choices", None) for choice in choices or (): part = choice.get(field) if isinstance(choice, dict) else getattr(choice, field, None) @@ -78,10 +79,11 @@ def _digest(value: str) -> str: def _redact_headers(headers: Mapping[str, str]) -> list[str]: - """`_identifying_params` reaches both the LLM cache key and the `invocation_params` - LangSmith records, so a caller's header value is fingerprinted rather than published. - Two values still differ, which is all the cache key needs. The flags we own are ours - to show.""" + """Fingerprint caller header values; show only the flags this package owns. + + `_identifying_params` reaches the LLM cache key and the `invocation_params` LangSmith + records, and distinctness is all the key needs. + """ public = (_HEADER_SHOW_ADDITIONAL_INFO, _HEADER_BYPASS_MOA, _HEADER_BYPASS_CACHE) return [f"{k}={headers[k]}" if k in public else f"{k}#{_digest(headers[k])}" for k in sorted(headers)] @@ -161,10 +163,8 @@ def _rewrite_video_blocks(content: Any) -> Any: def _fingerprint(key: str, value: Any) -> str: - """`precontext`/`reasoning` accumulate, so only an identical payload is a duplicate. - - `vcache` is scalar state — merging two different values would sum them (bool is an int). - """ + """`precontext`/`reasoning` accumulate, so only an identical payload is a duplicate; + `vcache` is scalar state, deduped by name because bool merges as int.""" if key not in _ACCUMULATING_SIDE_FIELDS: return key return f"{key}:{json.dumps(value, sort_keys=True, default=str)}" @@ -199,7 +199,6 @@ def _filter_stream_chunk( def _first_effort(*sources: Any) -> Any: - """Call-level `reasoning.effort`, then call `reasoning_effort`, then the model's.""" for source in sources: effort = source.get("effort") if isinstance(source, dict) else source if effort is not None: @@ -215,8 +214,8 @@ def _without_closed_blocks(raw: str) -> str: def _open_side_channel(text: str) -> tuple[str, str, str] | None: """Returns (tag, before, after) for the earliest unmatched opening tag. - Earliest by position, not by tag order: a truncated answer whose visible prose - mentions `` before an unclosed `` must split at the precontext. + Earliest by position, not tag order: a truncated answer whose prose mentions + `` before an unclosed `` must split at the precontext. """ found = [(text.find(f"<{tag}>"), tag) for tag in ("think", "precontext")] candidates = [(at, tag) for at, tag in found if at != -1] @@ -230,8 +229,8 @@ def _recover_tail(raw: str, emitted: str, truncated: bool) -> tuple[str, str | N """What the caller still owes, given what already streamed. An unmatched tag is prose in a completed response and an unclosed side channel in a - truncated one, so `finish_reason == "length"` decides. A partial `` becomes - reasoning rather than content; a partial `` is unparseable and dropped. + truncated one, so `truncated` decides. A partial `` becomes reasoning; a + partial `` is unparseable and dropped. """ text = _without_closed_blocks(raw) open_tag = _open_side_channel(text) if truncated else None @@ -281,8 +280,8 @@ def get_lc_namespace(cls) -> list[str]: def lc_secrets(self) -> dict[str, str]: return {"openai_api_key": "INTERFAZE_API_KEY"} - # A provider-family id, not a model id — `interfaze-beta` reaches tracing and the LLM - # cache key via `ls_model_name` / `model_name`. Mirrors ChatOpenAI's "openai-chat". + # Provider family, not the model: `interfaze-beta` reaches tracing and the cache key + # via `ls_model_name` / `model_name`. Mirrors ChatOpenAI's "openai-chat". @property def _llm_type(self) -> str: return "interfaze" @@ -299,6 +298,10 @@ def __init__( default_headers: dict[str, str] | None = None, **kwargs: Any, ) -> None: + """The three flags map to Interfaze control headers. `show_additional_info` is the + only way to get precontext while streaming; non-streaming responses always carry + it. `bypass_cache` matters when you need `reasoning`, which a cache hit omits. + """ key = api_key or os.environ.get("INTERFAZE_API_KEY") if not key: raise InterfazeError( @@ -336,8 +339,7 @@ def _identifying_params(self) -> dict[str, Any]: # Without these, set_llm_cache serves a bypass_cache model the plain model's answer, # and one tenant's key the answer cached under another's. params = {**super()._identifying_params, "_type": self._llm_type} - # A callable key is resolved per request, so there is no stable value to key on — - # the js package skips the fingerprint in that case too. + # A callable key resolves per request, so there is no stable value to key on. if isinstance(self.openai_api_key, SecretStr): params["interfaze_key"] = _digest(self.openai_api_key.get_secret_value()) if self.default_headers: @@ -364,8 +366,8 @@ def _get_request_payload( for m in messages ] payload = super()._get_request_payload(patched, stop=stop, **kwargs) - # Interfaze has no `reasoning` param; fold it into reasoning_effort using the same - # precedence as the JS package — a per-call value always beats a model-level one. + # Interfaze has no `reasoning` param; fold it into reasoning_effort. A per-call + # value always beats a model-level one. payload.pop("reasoning", None) effort = _first_effort( kwargs.get("reasoning"), kwargs.get("reasoning_effort"), self.reasoning, self.reasoning_effort @@ -395,8 +397,8 @@ def _create_chat_result( message.response_metadata["model_provider"] = _PROVIDER _apply_side_fields(message, side) _strip_tags(message, (generation.generation_info or {}).get("finish_reason") == "length") - # The streaming path keeps gen.text in step with the stripped content; - # without this, callbacks and the serialized cache carry the raw tags. + # gen.text feeds callbacks and the serialized cache, so keep it in step + # with the stripped content or both carry the raw tags. if isinstance(message.content, str): generation.text = message.content return result @@ -436,6 +438,8 @@ def _stream( emitted: list[str] = [] seen: set[str] = set() finish: Any = None + # run_manager is withheld deliberately: ChatOpenAI fires on_llm_new_token before + # yielding, so handlers would see unfiltered ``. Fired below instead. for gen in super()._stream(messages, stop=stop, run_manager=None, **kwargs): _filter_stream_chunk(gen, filt, raw, emitted) _dedupe_side_fields(gen.message, seen) @@ -463,6 +467,7 @@ async def _astream( emitted: list[str] = [] seen: set[str] = set() finish: Any = None + # See _stream: the manager is withheld so handlers never see unfiltered ``. async for gen in super()._astream(messages, stop=stop, run_manager=None, **kwargs): _filter_stream_chunk(gen, filt, raw, emitted) _dedupe_side_fields(gen.message, seen) diff --git a/python/scripts/qa_live.py b/python/scripts/qa_live.py index 78fdd7e..6ede185 100644 --- a/python/scripts/qa_live.py +++ b/python/scripts/qa_live.py @@ -88,7 +88,6 @@ def names(message: AIMessage) -> list[str]: return [p["name"] for p in entries if isinstance(p, dict) and p.get("name")] -# core def text_generation() -> str: res = llm.invoke("Say hi in one short sentence.") _assert(res.content, "empty") diff --git a/python/tests/unit_tests/test_client.py b/python/tests/unit_tests/test_client.py index 2eadbe3..300f8ea 100644 --- a/python/tests/unit_tests/test_client.py +++ b/python/tests/unit_tests/test_client.py @@ -11,7 +11,6 @@ from tests.unit_tests.conftest import BASIC, chunk, last_body, mock_json, mock_sse -# defaults def test_defaults_point_at_interfaze() -> None: model = ChatInterfaze(api_key="t") assert model.openai_api_base == INTERFAZE_BASE_URL @@ -65,7 +64,6 @@ def test_reasoning_kwarg_without_effort_is_dropped() -> None: assert "reasoning_effort" not in body -# control-plane headers def test_control_headers() -> None: model = ChatInterfaze( api_key="t", From bf2b84b61113aa85df3dfb3845df23dad62c6a00 Mon Sep 17 00:00:00 2001 From: Abhinavexist Date: Mon, 10 Aug 2026 15:15:26 +0530 Subject: [PATCH 24/28] refactor: name the stream bookkeeping, drop positional tuple indexing MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Readability pass over every source, test and config file. No behaviour change: `dist/index.d.ts` is byte-identical to HEAD, and the python public surface (`__all__`, constructor signature, class-defined members) is unchanged. `_stream` and `_astream` threaded four mutable accumulators through free functions — `_final_side_chunk(filt, raw, seen, emitted, finish == "length")` — and repeated five lines of identical setup. That state is now `_SideChannelStream`, so the two loops differ only by `async`: stream = _SideChannelStream() for gen in super()._stream(...): stream.absorb(gen) ... final = stream.final_chunk() `absorb` keeps the filter -> dedupe -> finish-reason order, which is load-bearing and was previously re-established in both loops. `_open_side_channel` returned a bare 3-tuple read as `open_tag[0]`, `open_tag[1]`, `open_tag[2]`, and `_recover_tail` a 2-tuple unpacked under two different names. Both are NamedTuples now, which also matches the objects the js side already returned. side_channels.ts: `lt` (an index of `<`, reading like a comparison) -> `openAngleAt`; `suffixPrefixLen` -> `danglingTagPrefixLength` with a line saying it holds back a tag split across chunks; `#buf`, `pre`, `thinks` spelled out. Smaller: `finishReason: unknown` -> `string | undefined`; `#frameSinks` moved from mid-class to the field block; one cast of `gen.message` instead of two on adjacent lines; `hasValue`'s comment corrected, having claimed an empty array counts as present when the function returns false for one. Tests: two hand-rolled chunk-merge folds -> `merge()` in conftest; stream_events.test.ts hand-rolled a frame `envelopeChunk()` already produces; `test_all_imports` -> `test_public_exports_are_pinned`. CONTRIBUTING said the integration suite needs `--no-cov` "because it has its own coverage expectations". `addopts` is `""`, so nothing adds coverage and the flag is a no-op. --- CONTRIBUTING.md | 4 +- js/src/chat_models.ts | 18 +-- js/src/side_channels.ts | 64 +++++----- js/test/stream_events.test.ts | 11 +- python/langchain_interfaze/chat_models.py | 149 +++++++++++----------- python/tests/unit_tests/conftest.py | 6 + python/tests/unit_tests/test_imports.py | 6 +- python/tests/unit_tests/test_stream.py | 9 +- 8 files changed, 136 insertions(+), 131 deletions(-) diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 381674b..710f935 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -26,11 +26,11 @@ cd python && uv run --python 3.10 --all-groups pytest tests/unit_tests/ ## The langchain-tests standard harness -`tests/integration_tests/` is LangChain's own `ChatModelIntegrationTests` conformance suite. It makes real calls, so it is not in CI and needs a key. It also has its own coverage expectations, hence `--no-cov`: +`tests/integration_tests/` is LangChain's own `ChatModelIntegrationTests` conformance suite. It makes real calls, so it is not in CI and needs a key: ```bash cd python -INTERFAZE_API_KEY=sk_... uv run pytest tests/integration_tests --no-cov +INTERFAZE_API_KEY=sk_... uv run pytest tests/integration_tests ``` ## Live QA diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 2d031db..11a5db2 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -89,6 +89,7 @@ function convertVideoBlock(block: VideoBlock): Record { const SIDE_FIELDS = ["precontext", "reasoning", "vcache"] as const; type SideChannelCarrier = { + id?: string; content: unknown; response_metadata: Record; additional_kwargs: Record; @@ -252,6 +253,10 @@ export class ChatInterfaze extends ChatOpenAICompletions { /** Kept off the parent, whose `reasoningEffort` type is narrower than Interfaze accepts. */ readonly interfazeReasoningEffort?: InterfazeReasoningEffort; + // Keyed on the call options, the one object the parent hands back to + // completionWithRetry, so concurrent streams never share a sink. + readonly #frameSinks = new WeakMap>>(); + constructor(fields: ChatInterfazeFields = {}) { const { apiKey, model, configuration, timeout, showAdditionalInfo, bypassMoA, bypassCache, reasoningEffort, ...rest } = fields; const key = apiKey ?? (typeof process !== "undefined" ? process.env?.INTERFAZE_API_KEY : undefined); @@ -332,10 +337,6 @@ export class ChatInterfaze extends ChatOpenAICompletions { })(); } - // Keyed on the call options, the one object the parent hands back to - // completionWithRetry, so concurrent streams never share a sink. - readonly #frameSinks = new WeakMap>>(); - private rewriteVideoBlocks(messages: BaseMessage[]): BaseMessage[] { return messages.map((m) => { if (!Array.isArray(m.content)) return m; @@ -376,7 +377,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { const frames: Array> = []; this.#frameSinks.set(options, frames); let streamId: string | undefined; - let finishReason: unknown; + let finishReason: string | undefined; const sideChunk = (side: Record): ChatGenerationChunk | null => { const message = new AIMessageChunk({ content: "", id: streamId }); applySideFields(message, side, seen); @@ -386,7 +387,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { }; for await (const gen of super._streamResponseChunks(this.rewriteVideoBlocks(messages), options, runManager)) { const message = gen.message as unknown as SideChannelCarrier; - streamId ??= (gen.message as AIMessageChunk).id; + streamId ??= message.id; finishReason = gen.generationInfo?.finish_reason ?? finishReason; message.response_metadata.model_provider = PROVIDER; const raw = message.additional_kwargs.__raw_response as Record | undefined; @@ -414,9 +415,8 @@ export class ChatInterfaze extends ChatOpenAICompletions { const flushed = filter.flush(); const recovered = flushed ? { tail: flushed } : recoverTail(joined, emittedParts.join(""), finishReason === "length"); const tail = recovered.tail; - const stripped = stripSideChannels(joined); - const { precontext } = stripped; - const reasoning = stripped.reasoning || recovered.reasoning; + const { precontext, reasoning: inlineReasoning } = stripSideChannels(joined); + const reasoning = inlineReasoning || recovered.reasoning; if (tail) { const message = new AIMessageChunk({ content: tail, id: streamId }); message.response_metadata.model_provider = PROVIDER; diff --git a/js/src/side_channels.ts b/js/src/side_channels.ts index 7baed70..aa2641b 100644 --- a/js/src/side_channels.ts +++ b/js/src/side_channels.ts @@ -9,76 +9,78 @@ export function stripSideChannels(content: string): { precontext?: Precontext[]; } { let text = content; - const thinks: string[] = []; + const thinkBlocks: string[] = []; text = text.replace(TAG_RE("think"), (_m, inner: string) => { - thinks.push(inner.trim()); + thinkBlocks.push(inner.trim()); return ""; }); - const pre: Precontext[] = []; + const precontexts: Precontext[] = []; text = text.replace(TAG_RE("precontext"), (_m, inner: string) => { try { const parsed = JSON.parse(inner.trim()); - if (Array.isArray(parsed)) pre.push(...parsed); - else pre.push(parsed); + if (Array.isArray(parsed)) precontexts.push(...parsed); + else precontexts.push(parsed); } catch { /* ignore malformed block */ } return ""; }); const out: { text: string; reasoning?: string; precontext?: Precontext[] } = { text: text.trim() }; - if (thinks.length) out.reasoning = thinks.join("\n"); - if (pre.length) out.precontext = pre; + if (thinkBlocks.length) out.reasoning = thinkBlocks.join("\n"); + if (precontexts.length) out.precontext = precontexts; return out; } const SIDE_OPEN = ["", ""] as const; const SIDE_CLOSE: Record = { "": "", "": "" }; -function suffixPrefixLen(s: string, tag: string): number { - for (let k = Math.min(s.length, tag.length - 1); k > 0; k--) { - if (s.slice(s.length - k) === tag.slice(0, k)) return k; +/** Length of the longest suffix of `text` that opens `tag`, so a tag split across two + * chunks is held back rather than emitted as content. */ +function danglingTagPrefixLength(text: string, tag: string): number { + for (let k = Math.min(text.length, tag.length - 1); k > 0; k--) { + if (text.slice(text.length - k) === tag.slice(0, k)) return k; } return 0; } /** Strips inline ``/`` blocks from streamed content, chunk by chunk. */ export class SideChannelFilter { - #buf = ""; + #buffer = ""; #close: string | undefined; feed(text: string): string { - this.#buf += text; + this.#buffer += text; const out: string[] = []; - while (this.#buf) { + while (this.#buffer) { if (this.#close === undefined) { - const lt = this.#buf.indexOf("<"); - if (lt === -1) { - out.push(this.#buf); - this.#buf = ""; + const openAngleAt = this.#buffer.indexOf("<"); + if (openAngleAt === -1) { + out.push(this.#buffer); + this.#buffer = ""; break; } - if (lt > 0) { - out.push(this.#buf.slice(0, lt)); - this.#buf = this.#buf.slice(lt); + if (openAngleAt > 0) { + out.push(this.#buffer.slice(0, openAngleAt)); + this.#buffer = this.#buffer.slice(openAngleAt); } - const opened = SIDE_OPEN.find((t) => this.#buf.startsWith(t)); + const opened = SIDE_OPEN.find((t) => this.#buffer.startsWith(t)); if (opened) { this.#close = SIDE_CLOSE[opened]; - this.#buf = this.#buf.slice(opened.length); + this.#buffer = this.#buffer.slice(opened.length); continue; } - if (SIDE_OPEN.some((t) => t.startsWith(this.#buf))) break; + if (SIDE_OPEN.some((t) => t.startsWith(this.#buffer))) break; out.push("<"); - this.#buf = this.#buf.slice(1); + this.#buffer = this.#buffer.slice(1); } else { const close = this.#close; - const end = this.#buf.indexOf(close); + const end = this.#buffer.indexOf(close); if (end === -1) { - const keep = suffixPrefixLen(this.#buf, close); - this.#buf = keep ? this.#buf.slice(this.#buf.length - keep) : ""; + const keep = danglingTagPrefixLength(this.#buffer, close); + this.#buffer = keep ? this.#buffer.slice(this.#buffer.length - keep) : ""; break; } - this.#buf = this.#buf.slice(end + close.length); + this.#buffer = this.#buffer.slice(end + close.length); this.#close = undefined; } } @@ -87,11 +89,11 @@ export class SideChannelFilter { flush(): string { if (this.#close !== undefined) { - this.#buf = ""; + this.#buffer = ""; return ""; } - const rest = this.#buf; - this.#buf = ""; + const rest = this.#buffer; + this.#buffer = ""; return rest; } } diff --git a/js/test/stream_events.test.ts b/js/test/stream_events.test.ts index e0bdc2c..6e7c1a8 100644 --- a/js/test/stream_events.test.ts +++ b/js/test/stream_events.test.ts @@ -1,5 +1,5 @@ import { describe, expect, it } from "vitest"; -import { chunk, mockChat, sseResponse } from "./helpers.js"; +import { chunk, envelopeChunk, mockChat, sseResponse } from "./helpers.js"; describe(".streamEvents() filtering", () => { it("strips side-channel tags from streamed events (v2 protocol)", async () => { @@ -33,14 +33,7 @@ describe(".streamEvents() filtering", () => { }); describe(".streamEvents() tool-call + usage streaming", () => { - const usageChunk = { - id: "req-test", - object: "chat.completion.chunk", - created: 1_700_000_000, - model: "interfaze-beta", - choices: [], - usage: { prompt_tokens: 5, completion_tokens: 3, total_tokens: 8 }, - }; + const usageChunk = envelopeChunk({ usage: { prompt_tokens: 5, completion_tokens: 3, total_tokens: 8 } }); function toolCallSse(): unknown[] { return [ diff --git a/python/langchain_interfaze/chat_models.py b/python/langchain_interfaze/chat_models.py index 108ee11..2426fd5 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/langchain_interfaze/chat_models.py @@ -5,7 +5,7 @@ import os import re from collections.abc import AsyncIterator, Iterator, Mapping -from typing import Any +from typing import Any, NamedTuple from interfaze import ( INTERFAZE_BASE_URL, @@ -57,7 +57,7 @@ def _extract_side_fields(data: dict[str, Any]) -> dict[str, Any]: return {k: data[k] for k in _SIDE_FIELDS if _carries_value(data.get(k))} -def _default_role(response: Any, field: str) -> None: +def _default_role(response: Any, part_key: str) -> None: """Default a missing `role` to assistant, in place. Interfaze sends `role` on the first delta only. Without it the parent builds a @@ -66,7 +66,7 @@ def _default_role(response: Any, field: str) -> None: """ choices = response.get("choices") if isinstance(response, dict) else getattr(response, "choices", None) for choice in choices or (): - part = choice.get(field) if isinstance(choice, dict) else getattr(choice, field, None) + part = choice.get(part_key) if isinstance(choice, dict) else getattr(choice, part_key, None) if isinstance(part, dict): if not part.get("role"): part["role"] = "assistant" @@ -101,9 +101,9 @@ def _strip_tags(message: AIMessage, truncated: bool = False) -> None: return text, reasoning, precontext = strip_side_channels(message.content) if truncated: - recovered, partial = _recover_tail(message.content, "", truncated=True) - text = recovered.strip() - reasoning = reasoning or partial + recovered = _recover_tail(message.content, emitted="", truncated=True) + text = recovered.tail.strip() + reasoning = reasoning or recovered.reasoning if text != message.content: message.content = text if reasoning and not message.response_metadata.get("reasoning"): @@ -187,15 +187,49 @@ def _dedupe_side_fields(message: BaseMessage, seen: set[str]) -> None: seen.add(fingerprint) -def _filter_stream_chunk( - gen: ChatGenerationChunk, filt: SideChannelFilter, raw: list[str], emitted: list[str] -) -> None: - message = gen.message - if isinstance(message, AIMessage) and isinstance(message.content, str) and message.content: - raw.append(message.content) - message.content = filt.feed(message.content) - emitted.append(message.content) - gen.text = message.content +class _SideChannelStream: + """Per-stream bookkeeping for the side-channel filter. + + `_stream` and `_astream` are otherwise identical, so holding the state here leaves the + two loops differing only by `async`. + """ + + def __init__(self) -> None: + self._filter = SideChannelFilter() + self._raw: list[str] = [] + self._emitted: list[str] = [] + self._seen: set[str] = set() + self._finish_reason: str | None = None + + def absorb(self, gen: ChatGenerationChunk) -> None: + message = gen.message + if isinstance(message, AIMessage) and isinstance(message.content, str) and message.content: + self._raw.append(message.content) + message.content = self._filter.feed(message.content) + self._emitted.append(message.content) + gen.text = message.content + _dedupe_side_fields(gen.message, self._seen) + self._finish_reason = (gen.generation_info or {}).get("finish_reason") or self._finish_reason + + def final_chunk(self) -> ChatGenerationChunk | None: + tail = self._filter.flush() + joined = "".join(self._raw) + _, reasoning, precontext = strip_side_channels(joined) + if not tail: + recovered = _recover_tail(joined, "".join(self._emitted), self._finish_reason == "length") + tail = recovered.tail + reasoning = reasoning or recovered.reasoning + side: dict[str, Any] = {} + if reasoning and _fingerprint("reasoning", reasoning) not in self._seen: + side["reasoning"] = reasoning + if precontext and _fingerprint("precontext", precontext) not in self._seen: + side["precontext"] = precontext + if not tail and not side: + return None + message = AIMessageChunk(content=tail) + message.response_metadata["model_provider"] = _PROVIDER + _apply_side_fields(message, side) + return ChatGenerationChunk(message=message) def _first_effort(*sources: Any) -> Any: @@ -211,21 +245,32 @@ def _without_closed_blocks(raw: str) -> str: return re.sub(r"[\s\S]*?", "", re.sub(r"[\s\S]*?", "", raw)) -def _open_side_channel(text: str) -> tuple[str, str, str] | None: - """Returns (tag, before, after) for the earliest unmatched opening tag. +class _OpenTag(NamedTuple): + tag: str + before: str + after: str + + +class _Recovered(NamedTuple): + tail: str + reasoning: str | None + + +def _open_side_channel(text: str) -> _OpenTag | None: + """The earliest unmatched opening tag. Earliest by position, not tag order: a truncated answer whose prose mentions `` before an unclosed `` must split at the precontext. """ - found = [(text.find(f"<{tag}>"), tag) for tag in ("think", "precontext")] - candidates = [(at, tag) for at, tag in found if at != -1] - if not candidates: + positions = [(text.find(f"<{tag}>"), tag) for tag in ("think", "precontext")] + present = [(at, tag) for at, tag in positions if at != -1] + if not present: return None - at, tag = min(candidates) - return tag, text[:at], text[at + len(tag) + 2 :] + at, tag = min(present) + return _OpenTag(tag, text[:at], text[at + len(tag) + 2 :]) -def _recover_tail(raw: str, emitted: str, truncated: bool) -> tuple[str, str | None]: +def _recover_tail(raw: str, emitted: str, truncated: bool) -> _Recovered: """What the caller still owes, given what already streamed. An unmatched tag is prose in a completed response and an unclosed side channel in a @@ -234,37 +279,11 @@ def _recover_tail(raw: str, emitted: str, truncated: bool) -> tuple[str, str | N """ text = _without_closed_blocks(raw) open_tag = _open_side_channel(text) if truncated else None - visible = open_tag[1] if open_tag else text + visible = open_tag.before if open_tag else text tail = visible[len(emitted) :] if visible.startswith(emitted) else "" - if open_tag and open_tag[0] == "think" and open_tag[2]: - return tail, open_tag[2] - return tail, None - - -def _final_side_chunk( - filt: SideChannelFilter, - raw: list[str], - seen: set[str], - emitted: list[str], - truncated: bool = False, -) -> ChatGenerationChunk | None: - tail = filt.flush() - joined = "".join(raw) - _, reasoning, precontext = strip_side_channels(joined) - if not tail: - tail, partial = _recover_tail(joined, "".join(emitted), truncated) - reasoning = reasoning or partial - side: dict[str, Any] = {} - if reasoning and _fingerprint("reasoning", reasoning) not in seen: - side["reasoning"] = reasoning - if precontext and _fingerprint("precontext", precontext) not in seen: - side["precontext"] = precontext - if not tail and not side: - return None - message = AIMessageChunk(content=tail) - message.response_metadata["model_provider"] = _PROVIDER - _apply_side_fields(message, side) - return ChatGenerationChunk(message=message) + if open_tag and open_tag.tag == "think" and open_tag.after: + return _Recovered(tail, open_tag.after) + return _Recovered(tail, None) class ChatInterfaze(ChatOpenAI): @@ -433,23 +452,17 @@ def _stream( run_manager: CallbackManagerForLLMRun | None = None, **kwargs: Any, ) -> Iterator[ChatGenerationChunk]: - filt = SideChannelFilter() - raw: list[str] = [] - emitted: list[str] = [] - seen: set[str] = set() - finish: Any = None + stream = _SideChannelStream() # run_manager is withheld deliberately: ChatOpenAI fires on_llm_new_token before # yielding, so handlers would see unfiltered ``. Fired below instead. for gen in super()._stream(messages, stop=stop, run_manager=None, **kwargs): - _filter_stream_chunk(gen, filt, raw, emitted) - _dedupe_side_fields(gen.message, seen) - finish = (gen.generation_info or {}).get("finish_reason") or finish + stream.absorb(gen) if run_manager: run_manager.on_llm_new_token( gen.text, chunk=gen, logprobs=(gen.generation_info or {}).get("logprobs") ) yield gen - final = _final_side_chunk(filt, raw, seen, emitted, finish == "length") + final = stream.final_chunk() if final is not None: if run_manager: run_manager.on_llm_new_token(final.text, chunk=final) @@ -462,22 +475,16 @@ async def _astream( run_manager: AsyncCallbackManagerForLLMRun | None = None, **kwargs: Any, ) -> AsyncIterator[ChatGenerationChunk]: - filt = SideChannelFilter() - raw: list[str] = [] - emitted: list[str] = [] - seen: set[str] = set() - finish: Any = None + stream = _SideChannelStream() # See _stream: the manager is withheld so handlers never see unfiltered ``. async for gen in super()._astream(messages, stop=stop, run_manager=None, **kwargs): - _filter_stream_chunk(gen, filt, raw, emitted) - _dedupe_side_fields(gen.message, seen) - finish = (gen.generation_info or {}).get("finish_reason") or finish + stream.absorb(gen) if run_manager: await run_manager.on_llm_new_token( gen.text, chunk=gen, logprobs=(gen.generation_info or {}).get("logprobs") ) yield gen - final = _final_side_chunk(filt, raw, seen, emitted, finish == "length") + final = stream.final_chunk() if final is not None: if run_manager: await run_manager.on_llm_new_token(final.text, chunk=final) diff --git a/python/tests/unit_tests/conftest.py b/python/tests/unit_tests/conftest.py index eec5565..5238447 100644 --- a/python/tests/unit_tests/conftest.py +++ b/python/tests/unit_tests/conftest.py @@ -1,6 +1,8 @@ from __future__ import annotations +import functools import json +import operator from typing import Any import httpx @@ -100,3 +102,7 @@ def last_body(route: respx.Route) -> dict[str, Any]: chunk({"content": "b"}) | {"reasoning": "why", "precontext": [{"name": "ocr"}], "vcache": True}, chunk({}, finish_reason="stop"), ] + + +def merge(chunks: list[Any]) -> Any: + return functools.reduce(operator.add, chunks) diff --git a/python/tests/unit_tests/test_imports.py b/python/tests/unit_tests/test_imports.py index 6aa282f..70c8721 100644 --- a/python/tests/unit_tests/test_imports.py +++ b/python/tests/unit_tests/test_imports.py @@ -1,7 +1,7 @@ from langchain_interfaze import __all__ -EXPECTED = ["ChatInterfaze", "__version__"] +PUBLIC_EXPORTS = ["ChatInterfaze", "__version__"] -def test_all_imports() -> None: - assert sorted(__all__) == sorted(EXPECTED) +def test_public_exports_are_pinned() -> None: + assert sorted(__all__) == sorted(PUBLIC_EXPORTS) diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index edfc0e8..eb916c7 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -21,6 +21,7 @@ THINK_SPLIT, chunk, completion, + merge, mock_json, mock_sse, ) @@ -124,9 +125,7 @@ def test_streamed_side_fields_are_applied_once() -> None: for key in ("reasoning", "precontext", "vcache"): assert sum(key in c.additional_kwargs for c in chunks) == 1, key - merged = chunks[0] - for c in chunks[1:]: - merged = merged + c + merged = merge(chunks) assert merged.additional_kwargs["reasoning"] == "why" assert merged.response_metadata["reasoning"] == "why" assert merged.additional_kwargs["precontext"] == [{"name": "ocr"}] @@ -154,9 +153,7 @@ def test_vcache_is_deduped_so_it_stays_a_bool() -> None: ] ) chunks = list(ChatInterfaze(api_key="t").stream([HumanMessage("hi")])) - merged = chunks[0] - for c in chunks[1:]: - merged = merged + c + merged = merge(chunks) assert merged.additional_kwargs["vcache"] is True From f9e41392df7763ef96fd436b34a82e4e5b2c6f2f Mon Sep 17 00:00:00 2001 From: Abhinavexist Date: Mon, 10 Aug 2026 15:15:48 +0530 Subject: [PATCH 25/28] fix(qa): the streaming leak check could not fail, and the router was untested MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Two gaps in the live gate. `streaming (tags stripped)` asserted no ``/`` in the output of "Count 1 to 5." — no reasoning_effort, no attachment, so that response can never carry a tag. The assertion was structurally incapable of failing. It stayed green through the role-less-delta bug fixed in 8c27113, where `` streamed straight to callers, because it never asked the server for reasoning. The same defect was found and fixed in the streamEvents check and not carried across to the one beside it. Both languages now stream at reasoning_effort high through the cache-bypassing client and assert reasoning surfaced before asserting nothing leaked. Nothing exercised the MoA router. Every precontext check either uploaded a receipt or forced the tool with a `` tag, so the one behaviour that separates Interfaze from any OpenAI-compatible endpoint had no coverage — while all three READMEs lead with `invoke("Which US public companies reported earnings today?")` and the claim that a web search backs the answer. That claim is now a check, and it holds: precontext comes back naming `search`. Also in these files: five near-identical `rejects_*` functions collapsed onto the `rejects(name, detail, run)` helper the js side already had, and the js temperature case folded into it (the file_id case stays separate — it asserts a client-side InterfazeError, not a 400). `A` -> `ASSETS` to match js. A local `fresh` in `_astream_events` shadowed the module-level `fresh`. The repeated `from interfaze import BadRequestError` inside four function bodies hoisted to the module level, where InterfazeError already was. Live: python 32/32, js 31/31. --- js/scripts/qa-live.ts | 33 +++++---- python/scripts/qa_live.py | 145 ++++++++++++++++++-------------------- 2 files changed, 89 insertions(+), 89 deletions(-) diff --git a/js/scripts/qa-live.ts b/js/scripts/qa-live.ts index ebb3511..b9303f7 100644 --- a/js/scripts/qa-live.ts +++ b/js/scripts/qa-live.ts @@ -85,16 +85,23 @@ await check("token usage", async () => { return `in=${u!.input_tokens} out=${u!.output_tokens}`; }); +// Reasoning is requested so the wire actually carries ``. Against a prompt that +// produces no tags the leak assertion cannot fail, which is how this check passed while +// the filter was broken for role-less deltas. await check("streaming (tags stripped)", async () => { let n = 0; let out = ""; - for await (const chunk of await llm.stream("Count 1 to 5.")) { + let sawReasoning = false; + const stream = await fresh.stream("Why is the sky blue? Briefly.", { reasoningEffort: "high" } as never); + for await (const chunk of stream) { n++; out += text(chunk); + if (chunk.response_metadata.reasoning) sawReasoning = true; } assert(n > 0 && out.length > 0, "empty stream"); assert(!out.includes("") && !out.includes(""), "side-channel tags leaked"); - return `${n} chunks`; + assert(sawReasoning, "no reasoning produced — a tag leak would be undetectable here"); + return `${n} chunks, reasoning stripped out`; }); await check("streaming usage metadata", async () => { @@ -144,6 +151,16 @@ await check("precontext (auto path)", async () => { return `names=${names(res)}`; }); +// The README's headline claim: a bare question routes itself to a tool. No attachment and +// no `` tag — the MoA router alone decides, which is the one behaviour that +// separates Interfaze from any OpenAI-compatible endpoint. +await check("router picks a tool unprompted", async () => { + const res = await fresh.invoke("Which US public companies reported earnings today?"); + assert(text(res).length > 0, "empty"); + assert(names(res).length > 0, "router ran no tool; the README says a web search backs this answer"); + return `names=${names(res)}`; +}); + await check("streamed precontext (deduped)", async () => { const got: unknown[] = []; let visible = ""; @@ -247,17 +264,9 @@ await rejects("rejects an invalid task", "invalid task", () => llm.invoke([new S await rejects("rejects an empty message", "", () => llm.invoke([new HumanMessage("")])); await rejects("rejects malformed base64", "", () => llm.invoke([ask("what is this?", image("data:image/jpeg;base64,@@@@not-valid@@@@===="))])); -await check("rejects temperature > 1", async () => { - try { - await makeLlm({ temperature: 1.5 }).invoke("hi"); - } catch (e) { - const err = e as { status?: number }; - assert(err.status === 400, `expected 400, got ${err.status}`); - return "400"; - } - throw new Error("temperature 1.5 was accepted; the README says it is a 400"); -}); +await rejects("rejects temperature > 1", "", () => makeLlm({ temperature: 1.5 }).invoke("hi")); +// Not a `rejects` case: this one never reaches the server. await check("rejects a video file_id client-side", async () => { try { await llm.invoke([ask("what is this?", { type: "video", file_id: "file-123" })]); diff --git a/python/scripts/qa_live.py b/python/scripts/qa_live.py index 6ede185..a9c2467 100644 --- a/python/scripts/qa_live.py +++ b/python/scripts/qa_live.py @@ -8,9 +8,10 @@ import asyncio import os import sys +from collections.abc import Callable from typing import Any -from interfaze import InterfazeError +from interfaze import BadRequestError, InterfazeError from langchain_core.messages import AIMessage, HumanMessage, SystemMessage from langchain_core.prompts import ChatPromptTemplate from langchain_core.tools import tool @@ -30,33 +31,31 @@ def make_llm(**kwargs: Any) -> ChatInterfaze: base_url = os.environ.get("INTERFAZE_BASE_URL") if base_url: kwargs.setdefault("base_url", base_url) - # The library default is 900s; under the workflow's timeout-minutes: 30 a single - # hung call would kill the job before it printed anything. kwargs.setdefault("timeout", 180.0) return ChatInterfaze(api_key=load_key(), max_retries=1, **kwargs) llm = make_llm() + # The semantic cache replays a stored answer with no `reasoning` attached. fresh = make_llm(bypass_cache=True) -A = { +ASSETS = { "receipt": "https://jigsawstack.com/preview/vocr-example.jpg", "id": "https://r2public.jigsawstack.com/interfaze/examples/id.jpg", "audio": "https://jigsawstack.com/preview/stt-example.wav", "video": "https://download.samplelib.com/mp4/sample-5s.mp4", "csv": "https://r2public.jigsawstack.com/interfaze/examples/prediction-example.csv", "pdf": "https://arxiv.org/pdf/1706.03762", - # Converted to PDF server-side at ingestion, so no client-side handling exists to break. "docx": "https://calibre-ebook.com/downloads/demos/demo.docx", "scene": "https://ultralytics.com/images/bus.jpg", } failures: list[str] = [] -def check(name: str, fn: Any) -> None: +def check(name: str, run: Callable[[], str]) -> None: try: - print(f" PASS {name} — {fn()}") + print(f" PASS {name} — {run()}") except Exception as e: # noqa: BLE001 print(f" FAIL {name} — {type(e).__name__}: {e}") failures.append(name) @@ -111,11 +110,18 @@ def token_usage() -> str: def streaming() -> str: - chunks = list(llm.stream("Count 1 to 5.")) + """Reasoning is requested so the wire actually carries ``. + + Against a prompt that produces no tags the leak assertion below cannot fail, which is + how this check passed while the filter was broken for role-less deltas. + """ + chunks = list(fresh.stream("Why is the sky blue? Briefly.", reasoning_effort="high")) text = "".join(str(c.content) for c in chunks) _assert(chunks and text, "empty stream") _assert("" not in text and "" not in text, "side-channel tags leaked") - return f"{len(chunks)} chunks" + reasoning = [c for c in chunks if c.response_metadata.get("reasoning")] + _assert(reasoning, "no reasoning produced — a tag leak would be undetectable here") + return f"{len(chunks)} chunks, reasoning stripped out" def streaming_usage() -> str: @@ -168,17 +174,24 @@ def reasoning_widened() -> str: def precontext() -> str: - res = llm.invoke([ask("Extract the total price.", file(A["receipt"]))]) + res = llm.invoke([ask("Extract the total price.", file(ASSETS["receipt"]))]) _assert(names(res), "no precontext") return f"names={names(res)}" +def router_picks_a_tool_unprompted() -> str: + res = fresh.invoke("Which US public companies reported earnings today?") + _assert(res.content, "empty") + _assert(names(res), "router ran no tool; the README says a web search backs this answer") + return f"names={names(res)}" + + def streamed_precontext() -> str: """`show_additional_info` is the only way to get precontext while streaming.""" got: list[Any] = [] visible: list[str] = [] for chunk in make_llm(show_additional_info=True, bypass_cache=True).stream( - [ask("Extract the total price.", file(A["receipt"]))] + [ask("Extract the total price.", file(ASSETS["receipt"]))] ): if isinstance(chunk.content, str): visible.append(chunk.content) @@ -234,14 +247,18 @@ async def go() -> str: return asyncio.run(go()) -def rejects_high_temperature() -> str: - from interfaze import BadRequestError +def rejects(name: str, detail: str, run: Callable[[], Any]) -> None: + """Assert the server refuses a request, optionally matching text in the 400.""" - try: - make_llm(temperature=1.5).invoke("hi") - except BadRequestError: - return "400" - raise AssertionError("temperature 1.5 was accepted; the README says it is a 400") + def fn() -> str: + try: + run() + except BadRequestError as e: + _assert(not detail or detail in str(e).lower(), str(e)) + return "400" + raise AssertionError(f"{name}: the request was accepted") + + check(name, fn) def rejects_video_file_id() -> str: @@ -253,53 +270,11 @@ def rejects_video_file_id() -> str: raise AssertionError("file_id was accepted") -def rejects_multiple_tasks() -> str: - from interfaze import BadRequestError - - try: - llm.invoke([SystemMessage("ocr, web_search"), HumanMessage("hi")]) - except BadRequestError as e: - _assert("only one task" in str(e).lower(), str(e)) - return "400" - raise AssertionError("two tasks were accepted") - - -def rejects_invalid_task() -> str: - from interfaze import BadRequestError - - try: - llm.invoke([SystemMessage("foobar_tool"), HumanMessage("hi")]) - except BadRequestError as e: - _assert("invalid task" in str(e).lower(), str(e)) - return "400" - raise AssertionError("an unknown task was accepted") - - -def rejects_empty_message() -> str: - from interfaze import BadRequestError - - try: - llm.invoke([HumanMessage("")]) - except BadRequestError: - return "400" - raise AssertionError("an empty message was accepted") - - -def rejects_bad_base64() -> str: - from interfaze import BadRequestError - - try: - llm.invoke([ask("what is this?", image("data:image/jpeg;base64,@@@@not-valid@@@@===="))]) - except BadRequestError: - return "400" - raise AssertionError("malformed base64 was accepted") - - async def _astream_events() -> str: - fresh = make_llm(bypass_cache=True, reasoning_effort="high") + reasoning_llm = make_llm(bypass_cache=True, reasoning_effort="high") body = "" end: Any = None - async for ev in fresh.astream_events("Why is the sky blue? Briefly.", version="v2"): + async for ev in reasoning_llm.astream_events("Why is the sky blue? Briefly.", version="v2"): if ev["event"] == "on_chat_model_stream": content = ev["data"]["chunk"].content if isinstance(content, str): @@ -318,7 +293,9 @@ async def _astream_events() -> str: _assert( end.response_metadata.get("model_provider") == "interfaze", "no model_provider on the terminal event" ) - saw = any(c.response_metadata.get("reasoning") for c in fresh.stream("Why is the sky blue? Briefly.")) + saw = any( + c.response_metadata.get("reasoning") for c in reasoning_llm.stream("Why is the sky blue? Briefly.") + ) _assert(saw, "no reasoning produced — a leak would be undetectable here") return f"{len(body)} chars, finish_reason + reasoning confirmed" @@ -327,7 +304,7 @@ def astream_events() -> str: return asyncio.run(_astream_events()) -def input_check(label: str, make_part: Any, prompt: str) -> None: +def input_check(label: str, make_part: Callable[[], dict[str, Any]], prompt: str) -> None: def fn() -> str: res = llm.invoke([ask(prompt, make_part())]) _assert(res.content, "empty") @@ -342,7 +319,7 @@ class Bill(BaseModel): def ocr_structured() -> str: - out = llm.with_structured_output(Bill).invoke([ask("Extract the receipt.", image(A["receipt"]))]) + out = llm.with_structured_output(Bill).invoke([ask("Extract the receipt.", image(ASSETS["receipt"]))]) if not isinstance(out, Bill): raise TypeError(f"not a Bill: {out!r}") _assert(out.vendor_name and out.total_amount > 0, "fields missing") @@ -359,6 +336,7 @@ def ocr_structured() -> str: check("reasoning + ", reasoning) check("reasoning_effort 'on'", reasoning_widened) check("precontext (auto path)", precontext) +check("router picks a tool unprompted", router_picks_a_tool_unprompted) check("streamed precontext (deduped)", streamed_precontext) check("ocr -> structured output", ocr_structured) check("guardrails -> unsafe", guardrails) @@ -368,23 +346,36 @@ def ocr_structured() -> str: check("async (ainvoke + astream)", async_smoke) check("astream_events (tags stripped)", astream_events) -check("rejects temperature > 1", rejects_high_temperature) -check("rejects multiple tags", rejects_multiple_tasks) -check("rejects an invalid task", rejects_invalid_task) -check("rejects an empty message", rejects_empty_message) -check("rejects malformed base64", rejects_bad_base64) +rejects("rejects temperature > 1", "", lambda: make_llm(temperature=1.5).invoke("hi")) +rejects( + "rejects multiple tags", + "only one task", + lambda: llm.invoke([SystemMessage("ocr, web_search"), HumanMessage("hi")]), +) +rejects( + "rejects an invalid task", + "invalid task", + lambda: llm.invoke([SystemMessage("foobar_tool"), HumanMessage("hi")]), +) +rejects("rejects an empty message", "", lambda: llm.invoke([HumanMessage("")])) +rejects( + "rejects malformed base64", + "", + lambda: llm.invoke([ask("what is this?", image("data:image/jpeg;base64,@@@@not-valid@@@@===="))]), +) +# Not a `rejects` case: this one never reaches the server. check("rejects a video file_id client-side", rejects_video_file_id) -input_check("image url", lambda: image(A["id"]), "What kind of document is this?") -input_check("pdf url", lambda: file(A["pdf"], "paper.pdf"), "Give the title.") -input_check("docx url", lambda: file(A["docx"], "demo.docx"), "What is this document about?") -input_check("audio url", lambda: file(A["audio"], "stt-example.wav"), "Transcribe this.") -input_check("video block", lambda: {"type": "video", "url": A["video"]}, "Describe this video.") -input_check("csv url", lambda: file(A["csv"], "data.csv"), "Name one column header.") +input_check("image url", lambda: image(ASSETS["id"]), "What kind of document is this?") +input_check("pdf url", lambda: file(ASSETS["pdf"], "paper.pdf"), "Give the title.") +input_check("docx url", lambda: file(ASSETS["docx"], "demo.docx"), "What is this document about?") +input_check("audio url", lambda: file(ASSETS["audio"], "stt-example.wav"), "Transcribe this.") +input_check("video block", lambda: {"type": "video", "url": ASSETS["video"]}, "Describe this video.") +input_check("csv url", lambda: file(ASSETS["csv"], "data.csv"), "Name one column header.") def inline_url() -> str: - res = llm.invoke(f"Extract the total from this receipt: {A['receipt']}") + res = llm.invoke(f"Extract the total from this receipt: {ASSETS['receipt']}") _assert(res.content, "empty") return "ok" From 3c74fb37d382ef0ba37c398b6a2370b826741a67 Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Mon, 10 Aug 2026 12:11:11 -0700 Subject: [PATCH 26/28] refactor: publish as interfaze/langchain across all three registries MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit npm and jsr become @interfaze/langchain, and the python distribution becomes interfaze-langchain with the module renamed to interfaze_langchain to match. PyPI has no scoping, so the scope/name order is the closest equivalent there. This diverges from the langchain- convention the langchain docs ask for, and from what the other provider packages on npm do (@langfuse/langchain, @composio/langchain, @sap-ai-sdk/langchain all keep their own scope but the python side stays langchain-*). Deliberate product decision, recorded here so nobody 'fixes' it later. The github repo keeps its name, so the repository urls still point at InterfazeAI/langchain-interfaze — npm provenance verifies that url against the building repo and would fail on a mismatch. --- .github/workflows/ci.yml | 2 +- .github/workflows/publish.yml | 4 +- CONTRIBUTING.md | 4 +- README.md | 10 +- js/README.md | 8 +- js/jsr.json | 2 +- js/package-lock.json | 5126 ++++++----------- js/package.json | 2 +- js/src/chat_models.ts | 2 +- js/test/identity.test.ts | 2 +- python/README.md | 6 +- python/interfaze_langchain/__init__.py | 4 + .../_version.py | 0 .../chat_models.py | 6 +- .../py.typed | 0 python/langchain_interfaze/__init__.py | 4 - python/pyproject.toml | 8 +- python/scripts/qa_live.py | 2 +- .../integration_tests/test_chat_models.py | 2 +- python/tests/unit_tests/test_chat.py | 2 +- python/tests/unit_tests/test_client.py | 2 +- python/tests/unit_tests/test_identity.py | 6 +- python/tests/unit_tests/test_imports.py | 2 +- python/tests/unit_tests/test_inputs.py | 2 +- python/tests/unit_tests/test_standard.py | 2 +- python/tests/unit_tests/test_stream.py | 2 +- scripts/check-versions.mjs | 2 +- 27 files changed, 1827 insertions(+), 3387 deletions(-) create mode 100644 python/interfaze_langchain/__init__.py rename python/{langchain_interfaze => interfaze_langchain}/_version.py (100%) rename python/{langchain_interfaze => interfaze_langchain}/chat_models.py (99%) rename python/{langchain_interfaze => interfaze_langchain}/py.typed (100%) delete mode 100644 python/langchain_interfaze/__init__.py diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 02913b8..9e51ff9 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -34,7 +34,7 @@ jobs: if: matrix.python-version == '3.12' run: uv run mypy - name: Unit tests - run: uv run pytest tests/unit_tests/ --disable-socket --allow-unix-socket --cov=langchain_interfaze --cov-report=term-missing --cov-fail-under=95 + run: uv run pytest tests/unit_tests/ --disable-socket --allow-unix-socket --cov=interfaze_langchain --cov-report=term-missing --cov-fail-under=95 versions: name: versions agree diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index 099c6d4..22a8828 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -58,7 +58,7 @@ jobs: runs-on: ubuntu-latest environment: name: testpypi - url: https://test.pypi.org/p/langchain-interfaze + url: https://test.pypi.org/p/interfaze-langchain permissions: id-token: write steps: @@ -76,7 +76,7 @@ jobs: runs-on: ubuntu-latest environment: name: pypi - url: https://pypi.org/p/langchain-interfaze + url: https://pypi.org/p/interfaze-langchain permissions: id-token: write steps: diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 710f935..4955be4 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -1,6 +1,6 @@ # Contributing -Two packages, one repo: [`python/`](./python) (`langchain-interfaze`) and [`js/`](./js) (`@interfaze-ai/langchain`). A change to one usually needs the same change to the other — the two are kept behaviourally identical. +Two packages, one repo: [`python/`](./python) (`interfaze-langchain`) and [`js/`](./js) (`@interfaze/langchain`). A change to one usually needs the same change to the other — the two are kept behaviourally identical. ## Setup @@ -49,7 +49,7 @@ Run both before cutting a release. They exercise paths the mocked suites cannot: ## Releasing -Five files carry the version and must agree — `python/pyproject.toml`, `python/langchain_interfaze/_version.py`, `js/package.json`, `js/jsr.json`, `js/src/version.ts`. The last two reach users as a `User-Agent`. +Five files carry the version and must agree — `python/pyproject.toml`, `python/interfaze_langchain/_version.py`, `js/package.json`, `js/jsr.json`, `js/src/version.ts`. The last two reach users as a `User-Agent`. ```bash node scripts/check-versions.mjs # do the five agree? diff --git a/README.md b/README.md index bc61989..bb64ed7 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # Interfaze LangChain SDK -The official [LangChain](https://www.langchain.com) integration for [Interfaze](https://interfaze.ai), for both **Python** (`langchain-interfaze`) and **TypeScript / JavaScript** (`@interfaze-ai/langchain`). +The official [LangChain](https://www.langchain.com) integration for [Interfaze](https://interfaze.ai), for both **Python** (`interfaze-langchain`) and **TypeScript / JavaScript** (`@interfaze/langchain`). [Docs](https://interfaze.ai/docs) · [limits](https://interfaze.ai/docs/limits) · [pricing](https://interfaze.ai/pricing) · [dashboard](https://interfaze.ai) · [Python SDK](https://github.com/InterfazeAI/interfaze-python) · [TypeScript / JavaScript SDK](https://github.com/InterfazeAI/interfaze-js) @@ -11,13 +11,13 @@ The official [LangChain](https://www.langchain.com) integration for [Interfaze]( Python: ```bash -pip install langchain-interfaze +pip install interfaze-langchain ``` TypeScript / JavaScript: ```bash -npm install @interfaze-ai/langchain +npm install @interfaze/langchain ``` The TS structured-output and tool examples use `zod` for schemas (`npm install zod`); it's an optional peer. @@ -27,7 +27,7 @@ The TS structured-output and tool examples use `zod` for schemas (`npm install z Python: ```python -from langchain_interfaze import ChatInterfaze +from interfaze_langchain import ChatInterfaze llm = ChatInterfaze(api_key="sk_...") # or set INTERFAZE_API_KEY and call ChatInterfaze() ``` @@ -35,7 +35,7 @@ llm = ChatInterfaze(api_key="sk_...") # or set INTERFAZE_API_KEY and call ChatI TypeScript: ```ts -import { ChatInterfaze } from "@interfaze-ai/langchain"; +import { ChatInterfaze } from "@interfaze/langchain"; const llm = new ChatInterfaze({ apiKey: "sk_..." }); // or set INTERFAZE_API_KEY and call new ChatInterfaze() ``` diff --git a/js/README.md b/js/README.md index 031b582..80bb1a0 100644 --- a/js/README.md +++ b/js/README.md @@ -7,16 +7,16 @@ The official [LangChain](https://js.langchain.com) integration for [Interfaze](h ## Install ```bash -npm install @interfaze-ai/langchain -# or: yarn add @interfaze-ai/langchain · pnpm add @interfaze-ai/langchain · bun add @interfaze-ai/langchain +npm install @interfaze/langchain +# or: yarn add @interfaze/langchain · pnpm add @interfaze/langchain · bun add @interfaze/langchain ``` -`@langchain/openai`, `@langchain/core`, and `interfaze` are peer dependencies - `@interfaze-ai/langchain` builds `ChatInterfaze` on top of them. The structured-output and tool examples below use `zod` for schemas (`npm install zod`); it's an optional peer. +`@langchain/openai`, `@langchain/core`, and `interfaze` are peer dependencies - `@interfaze/langchain` builds `ChatInterfaze` on top of them. The structured-output and tool examples below use `zod` for schemas (`npm install zod`); it's an optional peer. ## Setup ```ts -import { ChatInterfaze } from "@interfaze-ai/langchain"; +import { ChatInterfaze } from "@interfaze/langchain"; const llm = new ChatInterfaze({ apiKey: "sk_..." }); // or set INTERFAZE_API_KEY and call new ChatInterfaze() ``` diff --git a/js/jsr.json b/js/jsr.json index 5d6f1f0..1abd328 100644 --- a/js/jsr.json +++ b/js/jsr.json @@ -1,5 +1,5 @@ { - "name": "@interfaze-ai/langchain", + "name": "@interfaze/langchain", "version": "1.0.0", "exports": "./src/index.ts", "publish": { diff --git a/js/package-lock.json b/js/package-lock.json index 09dce63..c5644f3 100644 --- a/js/package-lock.json +++ b/js/package-lock.json @@ -1,16 +1,16 @@ { - "name": "@interfaze-ai/langchain", + "name": "@interfaze/langchain", "version": "1.0.0", "lockfileVersion": 3, "requires": true, "packages": { "": { - "name": "@interfaze-ai/langchain", + "name": "@interfaze/langchain", "version": "1.0.0", "license": "MIT", "devDependencies": { "@arethetypeswrong/cli": "0.18.5", - 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"x64" + "arm64" ], "dev": true, "license": "MIT", "optional": true, "os": [ - "win32" + "darwin" ], "engines": { "node": ">=12" diff --git a/js/package.json b/js/package.json index 424d586..b040aed 100644 --- a/js/package.json +++ b/js/package.json @@ -1,5 +1,5 @@ { - "name": "@interfaze-ai/langchain", + "name": "@interfaze/langchain", "version": "1.0.0", "description": "Interfaze LangChain integration for TypeScript/JavaScript", "license": "MIT", diff --git a/js/src/chat_models.ts b/js/src/chat_models.ts index 11a5db2..0546d8f 100644 --- a/js/src/chat_models.ts +++ b/js/src/chat_models.ts @@ -278,7 +278,7 @@ export class ChatInterfaze extends ChatOpenAICompletions { }); this.lc_serializable = false; this.interfazeReasoningEffort = reasoningEffort; - this._addVersion("@interfaze-ai/langchain", VERSION); + this._addVersion("@interfaze/langchain", VERSION); } // The parent spreads clientConfig wholesale, landing the api key and every default diff --git a/js/test/identity.test.ts b/js/test/identity.test.ts index 7db699a..a051604 100644 --- a/js/test/identity.test.ts +++ b/js/test/identity.test.ts @@ -24,7 +24,7 @@ describe("provider identity", () => { it("records its own package version alongside core's", () => { const versions = (model as unknown as { metadata?: { versions?: Record } }).metadata?.versions ?? {}; - expect(versions["@interfaze-ai/langchain"]).toBe(VERSION); + expect(versions["@interfaze/langchain"]).toBe(VERSION); expect(versions["@langchain/core"]).toBeTypeOf("string"); }); diff --git a/python/README.md b/python/README.md index 21eccfc..8f4bf96 100644 --- a/python/README.md +++ b/python/README.md @@ -7,8 +7,8 @@ The official [LangChain](https://python.langchain.com) integration for [Interfaz ## Install ```bash -pip install langchain-interfaze -# or: uv add langchain-interfaze · poetry add langchain-interfaze +pip install interfaze-langchain +# or: uv add interfaze-langchain · poetry add interfaze-langchain ``` This pulls in the `interfaze` client and the LangChain packages it builds on. @@ -16,7 +16,7 @@ This pulls in the `interfaze` client and the LangChain packages it builds on. ## Setup ```python -from langchain_interfaze import ChatInterfaze +from interfaze_langchain import ChatInterfaze llm = ChatInterfaze(api_key="sk_...") # or set INTERFAZE_API_KEY and call ChatInterfaze() ``` diff --git a/python/interfaze_langchain/__init__.py b/python/interfaze_langchain/__init__.py new file mode 100644 index 0000000..705fcf8 --- /dev/null +++ b/python/interfaze_langchain/__init__.py @@ -0,0 +1,4 @@ +from interfaze_langchain._version import __version__ +from interfaze_langchain.chat_models import ChatInterfaze + +__all__ = ["ChatInterfaze", "__version__"] diff --git a/python/langchain_interfaze/_version.py b/python/interfaze_langchain/_version.py similarity index 100% rename from python/langchain_interfaze/_version.py rename to python/interfaze_langchain/_version.py diff --git a/python/langchain_interfaze/chat_models.py b/python/interfaze_langchain/chat_models.py similarity index 99% rename from python/langchain_interfaze/chat_models.py rename to python/interfaze_langchain/chat_models.py index 2426fd5..690708b 100644 --- a/python/langchain_interfaze/chat_models.py +++ b/python/interfaze_langchain/chat_models.py @@ -25,7 +25,7 @@ from pydantic import SecretStr, model_validator from typing_extensions import Self -from langchain_interfaze._version import __version__ +from interfaze_langchain._version import __version__ _PROVIDER = "interfaze" @@ -293,7 +293,7 @@ def is_lc_serializable(cls) -> bool: @classmethod def get_lc_namespace(cls) -> list[str]: - return ["langchain_interfaze", "chat_models"] + return ["interfaze_langchain", "chat_models"] @property def lc_secrets(self) -> dict[str, str]: @@ -350,7 +350,7 @@ def __init__( # them, so reusing the parent's name would drop its version entry. @model_validator(mode="after") def _set_interfaze_version(self) -> Self: - self._add_version("langchain-interfaze", __version__) + self._add_version("interfaze-langchain", __version__) return self @property diff --git a/python/langchain_interfaze/py.typed b/python/interfaze_langchain/py.typed similarity index 100% rename from python/langchain_interfaze/py.typed rename to python/interfaze_langchain/py.typed diff --git a/python/langchain_interfaze/__init__.py b/python/langchain_interfaze/__init__.py deleted file mode 100644 index 92798be..0000000 --- a/python/langchain_interfaze/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from langchain_interfaze._version import __version__ -from langchain_interfaze.chat_models import ChatInterfaze - -__all__ = ["ChatInterfaze", "__version__"] diff --git a/python/pyproject.toml b/python/pyproject.toml index e24348c..4bcbb89 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -3,7 +3,7 @@ requires = ["hatchling"] build-backend = "hatchling.build" [project] -name = "langchain-interfaze" +name = "interfaze-langchain" version = "1.0.0" description = "Interfaze Langchain SDK" readme = "README.md" @@ -41,7 +41,7 @@ lint = ["ruff==0.16.0"] typing = ["mypy==2.3.0"] [tool.hatch.build.targets.wheel] -packages = ["langchain_interfaze"] +packages = ["interfaze_langchain"] [tool.pytest.ini_options] asyncio_mode = "auto" @@ -58,13 +58,13 @@ line-length = 110 [tool.mypy] python_version = "3.12" strict = true -files = ["langchain_interfaze", "scripts"] +files = ["interfaze_langchain", "scripts"] [[tool.mypy.overrides]] module = ["langchain_openai.*", "langchain_core.*"] ignore_missing_imports = true [[tool.mypy.overrides]] -module = ["langchain_interfaze.chat_models"] +module = ["interfaze_langchain.chat_models"] disallow_subclassing_any = false warn_return_any = false diff --git a/python/scripts/qa_live.py b/python/scripts/qa_live.py index a9c2467..fbcb624 100644 --- a/python/scripts/qa_live.py +++ b/python/scripts/qa_live.py @@ -17,7 +17,7 @@ from langchain_core.tools import tool from pydantic import BaseModel, Field -from langchain_interfaze import ChatInterfaze +from interfaze_langchain import ChatInterfaze def load_key() -> str: diff --git a/python/tests/integration_tests/test_chat_models.py b/python/tests/integration_tests/test_chat_models.py index 6a49073..81c8523 100644 --- a/python/tests/integration_tests/test_chat_models.py +++ b/python/tests/integration_tests/test_chat_models.py @@ -7,7 +7,7 @@ from langchain_core.language_models import BaseChatModel from langchain_tests.integration_tests import ChatModelIntegrationTests -from langchain_interfaze import ChatInterfaze +from interfaze_langchain import ChatInterfaze class TestChatInterfazeIntegration(ChatModelIntegrationTests): diff --git a/python/tests/unit_tests/test_chat.py b/python/tests/unit_tests/test_chat.py index 2b0d761..811f15d 100644 --- a/python/tests/unit_tests/test_chat.py +++ b/python/tests/unit_tests/test_chat.py @@ -6,7 +6,7 @@ import respx from langchain_core.messages import HumanMessage -from langchain_interfaze import ChatInterfaze +from interfaze_langchain import ChatInterfaze from tests.unit_tests.conftest import BASIC, CUSTOM_FIELDS, INLINE_TAGS, mock_json diff --git a/python/tests/unit_tests/test_client.py b/python/tests/unit_tests/test_client.py index 300f8ea..63e80cf 100644 --- a/python/tests/unit_tests/test_client.py +++ b/python/tests/unit_tests/test_client.py @@ -7,7 +7,7 @@ from interfaze import INTERFAZE_BASE_URL, INTERFAZE_MODEL, InterfazeError from langchain_core.messages import HumanMessage -from langchain_interfaze import ChatInterfaze +from interfaze_langchain import ChatInterfaze from tests.unit_tests.conftest import BASIC, chunk, last_body, mock_json, mock_sse diff --git a/python/tests/unit_tests/test_identity.py b/python/tests/unit_tests/test_identity.py index d369081..8bbbbc5 100644 --- a/python/tests/unit_tests/test_identity.py +++ b/python/tests/unit_tests/test_identity.py @@ -6,7 +6,7 @@ import respx from langchain_core.messages import HumanMessage -from langchain_interfaze import ChatInterfaze, __version__ +from interfaze_langchain import ChatInterfaze, __version__ from tests.unit_tests.conftest import BASIC, mock_json @@ -15,9 +15,9 @@ def test_provider_identity() -> None: assert model._llm_type == "interfaze" assert model._get_ls_params()["ls_provider"] == "interfaze" assert model.lc_secrets == {"openai_api_key": "INTERFAZE_API_KEY"} - assert model.get_lc_namespace() == ["langchain_interfaze", "chat_models"] + assert model.get_lc_namespace() == ["interfaze_langchain", "chat_models"] assert model.metadata is not None - assert "langchain-interfaze" in model.metadata["lc_versions"] + assert "interfaze-langchain" in model.metadata["lc_versions"] def test_version_matches_pyproject() -> None: diff --git a/python/tests/unit_tests/test_imports.py b/python/tests/unit_tests/test_imports.py index 70c8721..3aec8f1 100644 --- a/python/tests/unit_tests/test_imports.py +++ b/python/tests/unit_tests/test_imports.py @@ -1,4 +1,4 @@ -from langchain_interfaze import __all__ +from interfaze_langchain import __all__ PUBLIC_EXPORTS = ["ChatInterfaze", "__version__"] diff --git a/python/tests/unit_tests/test_inputs.py b/python/tests/unit_tests/test_inputs.py index ffde3d8..353e5b0 100644 --- a/python/tests/unit_tests/test_inputs.py +++ b/python/tests/unit_tests/test_inputs.py @@ -5,7 +5,7 @@ from interfaze import InterfazeError from langchain_core.messages import HumanMessage -from langchain_interfaze import ChatInterfaze +from interfaze_langchain import ChatInterfaze from tests.unit_tests.conftest import BASIC, VIDEO_URL, last_body, mock_json diff --git a/python/tests/unit_tests/test_standard.py b/python/tests/unit_tests/test_standard.py index 3871f7d..8b704f3 100644 --- a/python/tests/unit_tests/test_standard.py +++ b/python/tests/unit_tests/test_standard.py @@ -4,7 +4,7 @@ from langchain_tests.unit_tests import ChatModelUnitTests -from langchain_interfaze import ChatInterfaze +from interfaze_langchain import ChatInterfaze class TestChatInterfazeUnit(ChatModelUnitTests): diff --git a/python/tests/unit_tests/test_stream.py b/python/tests/unit_tests/test_stream.py index eb916c7..f6781bd 100644 --- a/python/tests/unit_tests/test_stream.py +++ b/python/tests/unit_tests/test_stream.py @@ -13,7 +13,7 @@ from langchain_core.messages import AIMessageChunk, HumanMessage from pydantic import BaseModel -from langchain_interfaze import ChatInterfaze +from interfaze_langchain import ChatInterfaze from tests.unit_tests.conftest import ( PLAIN_STREAM, REPEATED_SIDE, diff --git a/scripts/check-versions.mjs b/scripts/check-versions.mjs index ecf1a1f..911f2c0 100644 --- a/scripts/check-versions.mjs +++ b/scripts/check-versions.mjs @@ -7,7 +7,7 @@ const match = (path, re) => (read(path).match(re) ?? [])[1]; const versions = { "python/pyproject.toml": match("python/pyproject.toml", /^version = "(.+)"$/m), - "python/langchain_interfaze/_version.py": match("python/langchain_interfaze/_version.py", /^__version__ = "(.+)"$/m), + "python/interfaze_langchain/_version.py": match("python/interfaze_langchain/_version.py", /^__version__ = "(.+)"$/m), "js/package.json": JSON.parse(read("js/package.json")).version, "js/jsr.json": JSON.parse(read("js/jsr.json")).version, "js/src/version.ts": match("js/src/version.ts", /VERSION = "(.+)"/), From 6d951852c9a4d96e92e84c8546a015b9bb4bc9bd Mon Sep 17 00:00:00 2001 From: Khurdhula-Harshavardhan Date: Mon, 10 Aug 2026 12:18:58 -0700 Subject: [PATCH 27/28] fix(js): restore the multi-platform lockfile the rename regenerated Regenerating package-lock.json on darwin recorded only the darwin rollup binary, so `npm ci` on linux failed with "Cannot find module @rollup/rollup-linux-x64-gnu" and node 24 additionally reported the lock out of sync with package.json. All four js jobs were red; nothing was wrong with the code. Taking the lockfile as it was and editing only the two name fields keeps every optional platform entry. Diff against the pre-rename lock is two lines. --- js/package-lock.json | 4978 +++++++++++++++++++++++++++--------------- 1 file changed, 3269 insertions(+), 1709 deletions(-) diff --git a/js/package-lock.json b/js/package-lock.json index c5644f3..6d1d0ec 100644 --- a/js/package-lock.json +++ b/js/package-lock.json @@ -10,7 +10,7 @@ "license": "MIT", "devDependencies": { "@arethetypeswrong/cli": "0.18.5", - "@langchain/core": "^1.2.5", + "@langchain/core": "^1.2.2", "@langchain/openai": "^1.5.6", "@types/node": "~22.20.1", "@vitest/coverage-v8": "^2.1.9", @@ -27,9 +27,9 @@ "node": ">=20" }, "peerDependencies": { - "@langchain/core": "^1.2.5", + "@langchain/core": "^1.2.2", "@langchain/openai": "^1.5.5", - "interfaze": ">=1.0.3 <2", + "interfaze": ">=1.0.3", "zod": "^3.23.0 || ^4.4.3" }, "peerDependenciesMeta": { @@ -196,1102 +196,2291 @@ "node": ">=0.1.90" } }, - "node_modules/@esbuild/darwin-arm64": { + "node_modules/@esbuild/aix-ppc64": { "version": "0.27.7", - "resolved": 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A reword upstream turns that into a red build here, and uv.lock is gitignored so ci re-resolves pydantic fresh on every run. Matching the module keeps the intent without the coupling. --- python/pyproject.toml | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/python/pyproject.toml b/python/pyproject.toml index 4bcbb89..62096e5 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -49,7 +49,10 @@ testpaths = ["tests/unit_tests"] addopts = "" filterwarnings = [ "error", - 'ignore:Pydantic serializer warnings:UserWarning', + # Matched on module, not message: langchain-openai hands pydantic a `parsed` field it + # types as None, and gating ci on the wording of someone else's warning means a reword + # upstream turns into a red build here. + "ignore::UserWarning:pydantic.main", ] [tool.ruff]