From 028c45abfce528dd656aa70fb1263e801fc6b8e5 Mon Sep 17 00:00:00 2001 From: Jacob Cable Date: Tue, 7 Jul 2026 10:08:09 +0100 Subject: [PATCH 1/8] feat(py/plugins/amazon-bedrock): scaffold Amazon Bedrock plugin Package skeleton for the Bedrock port from the Go plugin (genkit-ai/aws-bedrock-go-plugin): plugin class with constructor and per-call config types, workspace wiring, and scaffold tests. Action resolution, Converse generate/stream, embedders, image generation and reranker land in follow-up slices. --- py/packages/genkit-amazon-bedrock/LICENSE | 201 ++++++ py/packages/genkit-amazon-bedrock/README.md | 39 ++ .../genkit-amazon-bedrock/pyproject.toml | 72 ++ .../src/genkit_amazon_bedrock/__init__.py | 27 + .../src/genkit_amazon_bedrock/config.py | 63 ++ .../src/genkit_amazon_bedrock/plugin.py | 121 ++++ .../src/genkit_amazon_bedrock/py.typed | 0 .../tests/plugin_test.py | 70 ++ py/pyproject.toml | 5 + py/uv.lock | 649 ++++++++++++++++++ 10 files changed, 1247 insertions(+) create mode 100644 py/packages/genkit-amazon-bedrock/LICENSE create mode 100644 py/packages/genkit-amazon-bedrock/README.md create mode 100644 py/packages/genkit-amazon-bedrock/pyproject.toml create mode 100644 py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/__init__.py create mode 100644 py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py create mode 100644 py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py create mode 100644 py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/py.typed create mode 100644 py/packages/genkit-amazon-bedrock/tests/plugin_test.py diff --git a/py/packages/genkit-amazon-bedrock/LICENSE b/py/packages/genkit-amazon-bedrock/LICENSE new file mode 100644 index 0000000000..2205396735 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright 2025 Google LLC + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/py/packages/genkit-amazon-bedrock/README.md b/py/packages/genkit-amazon-bedrock/README.md new file mode 100644 index 0000000000..3eb25fc65f --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/README.md @@ -0,0 +1,39 @@ +# Genkit Amazon Bedrock Plugin + +Amazon Bedrock plugin for Genkit Python. Provides access to Bedrock-hosted +models (Anthropic Claude, Amazon Nova, Meta Llama, Mistral, Cohere, and +others), Titan/Cohere/Nova embedders, image generation, and Cohere reranking. + +> Status: scaffold. Feature slices are being ported from the mature Go plugin +> ([genkit-ai/aws-bedrock-go-plugin](https://github.com/genkit-ai/aws-bedrock-go-plugin)). + +## Installation + +```bash +pip install genkit-amazon-bedrock +``` + +## Usage + +```python +from genkit import Genkit +from genkit_amazon_bedrock import Bedrock, ModelDefinition + +ai = Genkit( + plugins=[ + Bedrock( + region='us-east-1', + models=[ModelDefinition(name='anthropic.claude-sonnet-4-5-20250929-v1:0')], + ) + ], + model='bedrock/anthropic.claude-sonnet-4-5-20250929-v1:0', +) +``` + +Credentials resolve through the standard AWS SDK chain (environment, +`~/.aws/credentials`, instance metadata). Pass a pre-configured +`aioboto3.Session` via `session=` for custom wiring. + +## License + +Apache 2.0 diff --git a/py/packages/genkit-amazon-bedrock/pyproject.toml b/py/packages/genkit-amazon-bedrock/pyproject.toml new file mode 100644 index 0000000000..bc4216d9b2 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/pyproject.toml @@ -0,0 +1,72 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +[project] +authors = [{ name = "Google" }] +classifiers = [ + "Development Status :: 3 - Alpha", + "Environment :: Console", + "Environment :: Web Environment", + "Framework :: AsyncIO", + "Framework :: Pydantic", + "Framework :: Pydantic :: 2", + "Intended Audience :: Developers", + "Operating System :: OS Independent", + "Programming Language :: Python", + "Programming Language :: Python :: 3 :: Only", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Programming Language :: Python :: 3.14", + "Topic :: Scientific/Engineering :: Artificial Intelligence", + "Topic :: Software Development :: Libraries", + "Typing :: Typed", + "License :: OSI Approved :: Apache Software License", +] +dependencies = ["genkit", "aioboto3>=13.0"] +description = "Genkit Amazon Bedrock Plugin" +keywords = [ + "genkit", + "ai", + "llm", + "machine-learning", + "artificial-intelligence", + "generative-ai", + "aws", + "bedrock", + "amazon", +] +license = "Apache-2.0" +name = "genkit-amazon-bedrock" +readme = "README.md" +requires-python = ">=3.10" +version = "0.1.0" + +[project.urls] +"Bug Tracker" = "https://github.com/genkit-ai/genkit/issues" +Changelog = "https://github.com/genkit-ai/genkit/blob/main/py/packages/genkit-amazon-bedrock/CHANGELOG.md" +"Documentation" = "https://firebase.google.com/docs/genkit" +"Homepage" = "https://github.com/genkit-ai/genkit" +"Repository" = "https://github.com/genkit-ai/genkit/tree/main/py" + +[build-system] +build-backend = "hatchling.build" +requires = ["hatchling"] + +[tool.hatch.build.targets.wheel] +only-include = ["src/genkit_amazon_bedrock"] +sources = ["src"] diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/__init__.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/__init__.py new file mode 100644 index 0000000000..bec8057544 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/__init__.py @@ -0,0 +1,27 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Amazon Bedrock plugin for Genkit.""" + +from genkit_amazon_bedrock.config import BedrockConfig, ModelDefinition +from genkit_amazon_bedrock.plugin import Bedrock, bedrock_name + +__all__ = [ + 'Bedrock', + 'BedrockConfig', + 'ModelDefinition', + 'bedrock_name', +] diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py new file mode 100644 index 0000000000..44065e93f0 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py @@ -0,0 +1,63 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Configuration types for the Amazon Bedrock plugin.""" + +from typing import Any, Literal + +from pydantic import BaseModel, ConfigDict +from pydantic.alias_generators import to_camel + +from genkit import ModelConfig + +DEFAULT_REGION = 'us-east-1' +DEFAULT_MAX_RETRIES = 3 +DEFAULT_REQUEST_TIMEOUT = 30.0 + + +class BedrockConfig(ModelConfig): + """Per-call configuration for Bedrock models. + + Mirrors the Go plugin's ``Config`` surface. Unknown keys are allowed and + forwarded so callers can use provider-specific options without a plugin + release. + """ + + model_config = ConfigDict( + alias_generator=to_camel, + populate_by_name=True, + extra='allow', + ) + + tool_choice: str | None = None + """Tool choice mode: ``auto``, ``required``/``any``, ``none``, or a tool name.""" + + additional_model_request_fields: dict[str, Any] | None = None + """Forwarded verbatim to the Converse API (e.g. Claude extended thinking).""" + + +class ModelDefinition(BaseModel): + """A Bedrock model to register with Genkit. + + Capabilities are inferred from the built-in registry when not provided; + unknown chat models default to multimodal + tools at the unstable stage. + """ + + name: str + """Bedrock model ID, e.g. ``anthropic.claude-sonnet-4-5-20250929-v1:0``.""" + + type: Literal['chat', 'image', 'embedding'] = 'chat' + """Routes generate calls: chat/text via Converse, image via InvokeModel.""" diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py new file mode 100644 index 0000000000..eaafdfb311 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py @@ -0,0 +1,121 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Amazon Bedrock plugin for Genkit. + +Registers Bedrock-hosted models (Anthropic Claude, Amazon Nova, Meta Llama, +Mistral, Cohere, and others), embedders (Titan, Cohere, Nova), image +generators, and the Cohere reranker as Genkit actions. Text generation uses +the Bedrock Converse and ConverseStream APIs; embeddings, image generation, +and reranking use InvokeModel. + +Ported from the Go plugin (genkit-ai/aws-bedrock-go-plugin). +""" + +from typing import TYPE_CHECKING + +from genkit.plugin_api import ( + Action, + ActionKind, + ActionMetadata, + Plugin, +) +from genkit_amazon_bedrock.config import ( + DEFAULT_MAX_RETRIES, + DEFAULT_REGION, + DEFAULT_REQUEST_TIMEOUT, + ModelDefinition, +) + +if TYPE_CHECKING: + import aioboto3 + +BEDROCK_PLUGIN_NAME = 'bedrock' + + +def bedrock_name(name: str) -> str: + """Fully qualified Genkit action name for a Bedrock model. + + Args: + name: Bedrock model ID. + + Returns: + The namespaced action name, e.g. ``bedrock/anthropic.claude-...``. + """ + return f'{BEDROCK_PLUGIN_NAME}/{name}' + + +class Bedrock(Plugin): + """Amazon Bedrock plugin for Genkit.""" + + name = BEDROCK_PLUGIN_NAME + + def __init__( + self, + region: str | None = None, + max_retries: int = DEFAULT_MAX_RETRIES, + request_timeout: float = DEFAULT_REQUEST_TIMEOUT, + session: 'aioboto3.Session | None' = None, + models: list[ModelDefinition] | None = None, + embedders: list[str] | None = None, + ) -> None: + """Initializes the Bedrock plugin. + + Args: + region: AWS region. Defaults to the SDK resolution chain, falling + back to ``us-east-1`` (Go plugin parity). + max_retries: Retry limit for Bedrock API calls. + request_timeout: Per-call timeout in seconds. + session: Optional pre-configured ``aioboto3.Session`` for custom + credentials or advanced SDK wiring. + models: Bedrock models to register. Models not listed can still be + resolved dynamically by namespaced name. + embedders: Embedding model IDs to register (Titan, Cohere, Nova). + """ + self.region = region or DEFAULT_REGION + self.max_retries = max_retries + self.request_timeout = request_timeout + self._session = session + self.models = models or [] + self.embedders = embedders or [] + + async def init(self) -> list[Action]: + """Initialize plugin. + + Returns: + Empty list (actions are lazily created via ``resolve``). + """ + return [] + + async def resolve(self, action_type: ActionKind, name: str) -> Action | None: + """Resolve an action by namespaced name. + + Args: + action_type: The kind of action to resolve. + name: The namespaced action name. + + Returns: + Action object if resolvable, None otherwise. + """ + return None + + async def list_actions(self) -> list[ActionMetadata]: + """List available Bedrock models and embedders. + + Returns: + ActionMetadata for each configured model and embedder. + """ + return [] diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/py.typed b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/py.typed new file mode 100644 index 0000000000..e69de29bb2 diff --git a/py/packages/genkit-amazon-bedrock/tests/plugin_test.py b/py/packages/genkit-amazon-bedrock/tests/plugin_test.py new file mode 100644 index 0000000000..bb362dd382 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/tests/plugin_test.py @@ -0,0 +1,70 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Tests for the Amazon Bedrock plugin scaffold.""" + +import pytest +from genkit_amazon_bedrock import Bedrock, BedrockConfig, ModelDefinition, bedrock_name + + +def test_plugin_name() -> None: + plugin = Bedrock() + assert plugin.name == 'bedrock' + + +def test_bedrock_name_prefixes_model_id() -> None: + assert bedrock_name('anthropic.claude-sonnet-4-5-20250929-v1:0') == ( + 'bedrock/anthropic.claude-sonnet-4-5-20250929-v1:0' + ) + + +def test_constructor_defaults() -> None: + plugin = Bedrock() + assert plugin.region == 'us-east-1' + assert plugin.max_retries == 3 + assert plugin.request_timeout == 30.0 + assert plugin.models == [] + assert plugin.embedders == [] + + +def test_model_definition_defaults_to_chat() -> None: + model = ModelDefinition(name='amazon.nova-lite-v1:0') + assert model.type == 'chat' + + +def test_config_accepts_camel_case_and_extra_fields() -> None: + config = BedrockConfig.model_validate({ + 'toolChoice': 'auto', + 'additionalModelRequestFields': {'thinking': {'type': 'enabled'}}, + 'someFutureKnob': True, + }) + assert config.tool_choice == 'auto' + assert config.additional_model_request_fields == {'thinking': {'type': 'enabled'}} + + +@pytest.mark.asyncio +async def test_init_returns_no_eager_actions() -> None: + plugin = Bedrock() + assert await plugin.init() == [] + + +@pytest.mark.asyncio +async def test_resolve_returns_none_until_actions_land() -> None: + from genkit.plugin_api import ActionKind + + plugin = Bedrock() + assert await plugin.resolve(ActionKind.MODEL, bedrock_name('amazon.nova-lite-v1:0')) is None + assert await plugin.resolve(ActionKind.FLOW, 'bedrock/whatever') is None diff --git a/py/pyproject.toml b/py/pyproject.toml index 4edb81657f..e796eae48d 100644 --- a/py/pyproject.toml +++ b/py/pyproject.toml @@ -19,6 +19,7 @@ authors = [{ name = "Google" }] dependencies = [ "dotpromptz==0.1.5", "genkit", + "genkit-amazon-bedrock", "genkit-anthropic", "genkit-openai", "genkit-django", @@ -153,6 +154,7 @@ vertexai-imagen = { workspace = true } # Core packages genkit = { workspace = true } +genkit-amazon-bedrock = { workspace = true } genkit-anthropic = { workspace = true } genkit-openai = { workspace = true } genkit-django = { workspace = true } @@ -355,6 +357,7 @@ root = [ # Core package "packages/genkit/src", # Integration packages + "packages/genkit-amazon-bedrock/src", "packages/genkit-anthropic/src", "packages/genkit-openai/src", "packages/genkit-django/src", @@ -384,6 +387,7 @@ exclude = [ ] extraPaths = [ "packages/genkit/src", + "packages/genkit-amazon-bedrock/src", "packages/genkit-anthropic/src", "packages/genkit-openai/src", "packages/genkit-django/src", @@ -426,6 +430,7 @@ project_includes = [ search-path = [ ".", "packages/genkit/src", + "packages/genkit-amazon-bedrock/src", "packages/genkit-anthropic/src", "packages/genkit-openai/src", "packages/genkit-django/src", diff --git a/py/uv.lock b/py/uv.lock index 4a06d0ca48..6beb3c3a08 100644 --- a/py/uv.lock +++ b/py/uv.lock @@ -9,6 +9,10 @@ resolution-markers = [ "python_full_version < '3.11'", ] +[options] +exclude-newer = "2026-07-23T09:18:03.109288Z" +exclude-newer-span = "P7D" + [manifest] members = [ "agents", @@ -22,6 +26,7 @@ members = [ "gemini-code-execution", "gemini-context-caching", "genkit", + "genkit-amazon-bedrock", "genkit-anthropic", "genkit-django", "genkit-evaluators", @@ -73,6 +78,42 @@ requires-dist = [ { name = "uvicorn", extras = ["standard"], specifier = ">=0.24.0" }, ] +[[package]] +name = "aioboto3" +version = "15.5.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "aiobotocore", extra = ["boto3"] }, + { name = "aiofiles" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/a2/01/92e9ab00f36e2899315f49eefcd5b4685fbb19016c7f19a9edf06da80bb0/aioboto3-15.5.0.tar.gz", hash = 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range, which would dictate boto3 versions for every user of the plugin. A thread bridge keeps the event loop unblocked at LLM concurrency levels, matching Strands, pydantic-ai and langchain-aws. Transport goes behind an internal seam so the smithy-based official async SDK can slot in once it matures. --- py/packages/genkit-amazon-bedrock/README.md | 2 +- .../genkit-amazon-bedrock/pyproject.toml | 2 +- .../src/genkit_amazon_bedrock/plugin.py | 6 +- py/uv.lock | 584 +----------------- 4 files changed, 8 insertions(+), 586 deletions(-) diff --git a/py/packages/genkit-amazon-bedrock/README.md b/py/packages/genkit-amazon-bedrock/README.md index 3eb25fc65f..c7325aa449 100644 --- a/py/packages/genkit-amazon-bedrock/README.md +++ b/py/packages/genkit-amazon-bedrock/README.md @@ -32,7 +32,7 @@ ai = Genkit( Credentials resolve through the standard AWS SDK chain (environment, `~/.aws/credentials`, instance metadata). Pass a pre-configured -`aioboto3.Session` via `session=` for custom wiring. +`boto3.session.Session` via `session=` for custom wiring. ## License diff --git a/py/packages/genkit-amazon-bedrock/pyproject.toml b/py/packages/genkit-amazon-bedrock/pyproject.toml index bc4216d9b2..f66d127556 100644 --- a/py/packages/genkit-amazon-bedrock/pyproject.toml +++ b/py/packages/genkit-amazon-bedrock/pyproject.toml @@ -37,7 +37,7 @@ classifiers = [ "Typing :: Typed", "License :: OSI Approved :: Apache Software License", ] -dependencies = ["genkit", "aioboto3>=13.0"] +dependencies = ["genkit", "boto3>=1.36"] description = "Genkit Amazon Bedrock Plugin" keywords = [ "genkit", diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py index eaafdfb311..b327a952e5 100644 --- a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py @@ -41,7 +41,7 @@ ) if TYPE_CHECKING: - import aioboto3 + import boto3.session BEDROCK_PLUGIN_NAME = 'bedrock' @@ -68,7 +68,7 @@ def __init__( region: str | None = None, max_retries: int = DEFAULT_MAX_RETRIES, request_timeout: float = DEFAULT_REQUEST_TIMEOUT, - session: 'aioboto3.Session | None' = None, + session: 'boto3.session.Session | None' = None, models: list[ModelDefinition] | None = None, embedders: list[str] | None = None, ) -> None: @@ -79,7 +79,7 @@ def __init__( back to ``us-east-1`` (Go plugin parity). max_retries: Retry limit for Bedrock API calls. request_timeout: Per-call timeout in seconds. - session: Optional pre-configured ``aioboto3.Session`` for custom + session: Optional pre-configured ``boto3.session.Session`` for custom credentials or advanced SDK wiring. models: Bedrock models to register. 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Capabilities are keyed by base +Bedrock model ID; cross-region inference-profile prefixes are stripped for +lookup only - the full original model ID is always sent to Bedrock untouched. +Unknown chat/text models fall back to modern Converse defaults (multimodal + +tools) at the unstable stage, so newer or inference-profile-only models remain +callable without a plugin release. +""" + +from typing import Literal, NamedTuple + +from genkit import Constrained, ModelInfo, Stage, Supports + +INFERENCE_PROFILE_PREFIXES = ( + 'global.', + 'us-gov.', + 'us.', + 'eu.', + 'jp.', + 'apac.', + 'au.', +) + + +class ModelCapability(NamedTuple): + """Capabilities of a Bedrock chat/text model.""" + + multimodal: bool + tools: bool + + +MODEL_CAPABILITIES: dict[str, ModelCapability] = { + # Anthropic Claude 3 models + 'anthropic.claude-3-haiku-20240307-v1:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-3-sonnet-20240229-v1:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-3-opus-20240229-v1:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-3-5-haiku-20241022-v1:0': ModelCapability(multimodal=False, tools=True), + 'anthropic.claude-3-5-sonnet-20240620-v1:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-3-5-sonnet-20241022-v2:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-3-7-sonnet-20250219-v1:0': ModelCapability(multimodal=True, tools=True), + # Anthropic Claude 4/4.5/4.6 models + 'anthropic.claude-haiku-4-5-20251001-v1:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-opus-4-1-20250805-v1:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-opus-4-20250514-v1:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-sonnet-4-20250514-v1:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-sonnet-4-5-20250929-v1:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-opus-4-5-20251101-v1:0': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-sonnet-4-6': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-opus-4-6-v1': ModelCapability(multimodal=True, tools=True), + # Provisioned-throughput variants (28k/48k/200k context) + 'anthropic.claude-3-haiku-20240307-v1:0:48k': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-3-haiku-20240307-v1:0:200k': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-3-sonnet-20240229-v1:0:28k': ModelCapability(multimodal=True, tools=True), + 'anthropic.claude-3-sonnet-20240229-v1:0:200k': ModelCapability(multimodal=True, tools=True), + # Amazon Nova models + 'amazon.nova-micro-v1:0': ModelCapability(multimodal=False, tools=True), + 'amazon.nova-lite-v1:0': ModelCapability(multimodal=True, tools=True), + 'amazon.nova-pro-v1:0': ModelCapability(multimodal=True, tools=True), + 'amazon.nova-premier-v1:0': ModelCapability(multimodal=True, tools=True), + # Cohere Command models + 'cohere.command-r-v1:0': ModelCapability(multimodal=False, tools=True), + 'cohere.command-r-plus-v1:0': ModelCapability(multimodal=False, tools=True), + # Mistral models + 'mistral.mistral-large-2402-v1:0': ModelCapability(multimodal=False, tools=True), + 'mistral.mistral-large-2407-v1:0': ModelCapability(multimodal=False, tools=True), + 'mistral.mistral-small-2402-v1:0': ModelCapability(multimodal=False, tools=True), + 'mistral.pixtral-large-2502-v1:0': ModelCapability(multimodal=True, tools=True), + # AI21 Labs Jamba models + 'ai21.jamba-1-5-large-v1:0': ModelCapability(multimodal=False, tools=True), + 'ai21.jamba-1-5-mini-v1:0': ModelCapability(multimodal=False, tools=True), + # Meta Llama models + 'meta.llama3-8b-instruct-v1:0': ModelCapability(multimodal=False, tools=True), + 'meta.llama3-70b-instruct-v1:0': ModelCapability(multimodal=False, tools=True), + 'meta.llama3-1-8b-instruct-v1:0': ModelCapability(multimodal=False, tools=True), + 'meta.llama3-1-70b-instruct-v1:0': ModelCapability(multimodal=False, tools=True), + 'meta.llama3-1-405b-instruct-v1:0': ModelCapability(multimodal=False, tools=True), + 'meta.llama3-2-1b-instruct-v1:0': ModelCapability(multimodal=False, tools=True), + 'meta.llama3-2-3b-instruct-v1:0': ModelCapability(multimodal=False, tools=True), + 'meta.llama3-2-11b-instruct-v1:0': ModelCapability(multimodal=True, tools=True), + 'meta.llama3-2-90b-instruct-v1:0': ModelCapability(multimodal=True, tools=True), + 'meta.llama3-3-70b-instruct-v1:0': ModelCapability(multimodal=False, tools=True), + 'meta.llama4-maverick-17b-instruct-v1:0': ModelCapability(multimodal=True, tools=True), + 'meta.llama4-scout-17b-instruct-v1:0': ModelCapability(multimodal=True, tools=True), + # DeepSeek models + 'deepseek.r1-v1:0': ModelCapability(multimodal=False, tools=True), + # Writer models + 'writer.palmyra-x4-v1:0': ModelCapability(multimodal=False, tools=True), + 'writer.palmyra-x5-v1:0': ModelCapability(multimodal=False, tools=True), + # TwelveLabs models + 'twelvelabs.pegasus-1-2-v1:0': ModelCapability(multimodal=False, tools=True), +} + + +def strip_inference_profile_prefix(model_id: str) -> str: + """Strips a cross-region inference-profile prefix from a model ID. + + Used for capability lookup only; requests always carry the original ID. + + Args: + model_id: Bedrock model ID, possibly prefixed (e.g. ``us.anthropic...``). + + Returns: + The base model ID without the inference-profile prefix. + """ + for prefix in INFERENCE_PROFILE_PREFIXES: + if model_id.startswith(prefix): + return model_id.removeprefix(prefix) + return model_id + + +def get_model_info( + model_name: str, + model_type: Literal['chat', 'image', 'embedding'] = 'chat', +) -> ModelInfo: + """Infers Genkit model info for a Bedrock model. + + Args: + model_name: Bedrock model ID or inference-profile ID. + model_type: Routing type for the model. + + Returns: + ModelInfo with capabilities from the registry, or modern Converse + defaults at the unstable stage for unknown chat/text models. + """ + if model_type == 'image': + return ModelInfo( + label=model_name, + stage=Stage.STABLE, + supports=Supports( + multiturn=False, + tools=False, + tool_choice=False, + system_role=False, + media=True, + constrained=Constrained.NONE, + ), + ) + + if model_type == 'embedding': + return ModelInfo( + label=model_name, + stage=Stage.STABLE, + supports=Supports( + multiturn=False, + tools=False, + tool_choice=False, + system_role=False, + media=False, + constrained=Constrained.NONE, + ), + ) + + capability = MODEL_CAPABILITIES.get(strip_inference_profile_prefix(model_name)) + stage = Stage.STABLE if capability is not None else Stage.UNSTABLE + if capability is None: + capability = ModelCapability(multimodal=True, tools=True) + + return ModelInfo( + label=model_name, + stage=stage, + supports=Supports( + multiturn=True, + tools=capability.tools, + tool_choice=capability.tools, + system_role=True, + media=capability.multimodal, + constrained=Constrained.NONE, + ), + ) diff --git a/py/packages/genkit-amazon-bedrock/tests/model_info_test.py b/py/packages/genkit-amazon-bedrock/tests/model_info_test.py new file mode 100644 index 0000000000..2e3f5ba708 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/tests/model_info_test.py @@ -0,0 +1,98 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Tests for the Bedrock model capability registry.""" + +import pytest +from genkit_amazon_bedrock.model_info import ( + INFERENCE_PROFILE_PREFIXES, + MODEL_CAPABILITIES, + get_model_info, + strip_inference_profile_prefix, +) + +from genkit import Stage + + +@pytest.mark.parametrize('prefix', INFERENCE_PROFILE_PREFIXES) +def test_strip_inference_profile_prefix(prefix: str) -> None: + model_id = f'{prefix}anthropic.claude-sonnet-4-5-20250929-v1:0' + assert strip_inference_profile_prefix(model_id) == 'anthropic.claude-sonnet-4-5-20250929-v1:0' + + +def test_strip_leaves_bare_model_id_untouched() -> None: + assert strip_inference_profile_prefix('amazon.nova-lite-v1:0') == 'amazon.nova-lite-v1:0' + + +def test_strip_only_removes_first_matching_prefix() -> None: + assert strip_inference_profile_prefix('us.us.model') == 'us.model' + + +def test_us_gov_wins_over_us() -> None: + assert strip_inference_profile_prefix('us-gov.anthropic.claude-3-opus-20240229-v1:0') == ( + 'anthropic.claude-3-opus-20240229-v1:0' + ) + + +def test_known_model_is_stable_with_registry_capabilities() -> None: + info = get_model_info('anthropic.claude-3-5-haiku-20241022-v1:0') + assert info.stage == Stage.STABLE + assert info.supports.multiturn is True + assert info.supports.system_role is True + assert info.supports.tools is True + assert info.supports.tool_choice is True + assert info.supports.media is False + + +def test_inference_profile_id_resolves_registry_entry() -> None: + info = get_model_info('eu.amazon.nova-micro-v1:0') + assert info.stage == Stage.STABLE + assert info.supports.media is False + assert info.label == 'eu.amazon.nova-micro-v1:0' + + +def test_unknown_model_defaults_to_unstable_converse_capabilities() -> None: + info = get_model_info('vendor.brand-new-model-v1:0') + assert info.stage == Stage.UNSTABLE + assert info.supports.multiturn is True + assert info.supports.tools is True + assert info.supports.media is True + + +def test_image_model_supports_media_output_only() -> None: + info = get_model_info('amazon.titan-image-generator-v1', model_type='image') + assert info.stage == Stage.STABLE + assert info.supports.media is True + assert info.supports.multiturn is False + assert info.supports.tools is False + assert info.supports.system_role is False + + +def test_embedding_model_supports_nothing() -> None: + info = get_model_info('amazon.titan-embed-text-v2:0', model_type='embedding') + assert info.stage == Stage.STABLE + assert info.supports.media is False + assert info.supports.multiturn is False + assert info.supports.tools is False + + +def test_registry_matches_go_plugin_size() -> None: + assert len(MODEL_CAPABILITIES) == 47 + + +def test_all_registry_keys_are_base_ids() -> None: + for model_id in MODEL_CAPABILITIES: + assert strip_inference_profile_prefix(model_id) == model_id From 48f53a6e400b4fad2e0e1914eabb6377f5860c52 Mon Sep 17 00:00:00 2001 From: Jacob Cable Date: Tue, 7 Jul 2026 13:21:27 +0100 Subject: [PATCH 4/8] fix(py/plugins/amazon-bedrock): resolve capabilities from full Bedrock ARNs Reduce foundation-model and inference-profile ARNs to their resource ID before capability lookup, across all AWS partitions (aws, aws-us-gov, aws-cn). Lookup-only, requests still carry the original identifier. Addresses PR review feedback. --- .../src/genkit_amazon_bedrock/model_info.py | 7 +++++- .../tests/model_info_test.py | 25 +++++++++++++++++++ 2 files changed, 31 insertions(+), 1 deletion(-) diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/model_info.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/model_info.py index dc6933d5ac..9909572b2c 100644 --- a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/model_info.py +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/model_info.py @@ -112,13 +112,18 @@ def strip_inference_profile_prefix(model_id: str) -> str: """Strips a cross-region inference-profile prefix from a model ID. Used for capability lookup only; requests always carry the original ID. + Full Bedrock ARNs (foundation-model, inference-profile) are reduced to + their resource ID first, across all partitions (``arn:aws:``, + ``arn:aws-us-gov:``, ``arn:aws-cn:``). Args: - model_id: Bedrock model ID, possibly prefixed (e.g. ``us.anthropic...``). + model_id: Bedrock model ID, inference-profile ID, or full ARN. Returns: The base model ID without the inference-profile prefix. """ + if model_id.startswith('arn:'): + model_id = model_id.rsplit('/', 1)[-1] for prefix in INFERENCE_PROFILE_PREFIXES: if model_id.startswith(prefix): return model_id.removeprefix(prefix) diff --git a/py/packages/genkit-amazon-bedrock/tests/model_info_test.py b/py/packages/genkit-amazon-bedrock/tests/model_info_test.py index 2e3f5ba708..b309c4f9f0 100644 --- a/py/packages/genkit-amazon-bedrock/tests/model_info_test.py +++ b/py/packages/genkit-amazon-bedrock/tests/model_info_test.py @@ -41,6 +41,31 @@ def test_strip_only_removes_first_matching_prefix() -> None: assert strip_inference_profile_prefix('us.us.model') == 'us.model' +def test_strip_handles_inference_profile_arn() -> None: + arn = 'arn:aws:bedrock:us-east-1:123456789012:inference-profile/us.anthropic.claude-3-5-sonnet-20241022-v2:0' + assert strip_inference_profile_prefix(arn) == 'anthropic.claude-3-5-sonnet-20241022-v2:0' + + +def test_strip_handles_foundation_model_arn() -> None: + arn = 'arn:aws:bedrock:us-east-1::foundation-model/anthropic.claude-3-haiku-20240307-v1:0' + assert strip_inference_profile_prefix(arn) == 'anthropic.claude-3-haiku-20240307-v1:0' + + +def test_strip_handles_govcloud_partition_arn() -> None: + arn = ( + 'arn:aws-us-gov:bedrock:us-gov-west-1:123456789012:' + 'inference-profile/us-gov.anthropic.claude-3-5-sonnet-20240620-v1:0' + ) + assert strip_inference_profile_prefix(arn) == 'anthropic.claude-3-5-sonnet-20240620-v1:0' + + +def test_application_inference_profile_arn_falls_back_to_unstable() -> None: + arn = 'arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/abc123opaque' + info = get_model_info(arn) + assert info.stage == Stage.UNSTABLE + assert info.supports.tools is True + + def test_us_gov_wins_over_us() -> None: assert strip_inference_profile_prefix('us-gov.anthropic.claude-3-opus-20240229-v1:0') == ( 'anthropic.claude-3-opus-20240229-v1:0' From 41b32db9c61b3552dd9cd42c2cb1baeedc16cc52 Mon Sep 17 00:00:00 2001 From: Hilary Date: Wed, 29 Jul 2026 11:04:55 +0100 Subject: [PATCH 5/8] feat(py/plugins/amazon-bedrock): add Converse non-streaming generate path Transport seam bridging sync boto3 onto worker threads, pure Converse converters ported from the Go plugin's generate.go, lazy model resolution, and AWS error mapping. Region resolution now fails loudly instead of defaulting to us-east-1, matching Go. boto3 floor moves to 1.37.24 for cache points and reasoningContent. --- py/packages/genkit-amazon-bedrock/README.md | 7 +- .../genkit-amazon-bedrock/pyproject.toml | 2 +- .../src/genkit_amazon_bedrock/__init__.py | 2 + .../src/genkit_amazon_bedrock/config.py | 20 +- .../src/genkit_amazon_bedrock/converters.py | 755 +++++++++++++++ .../src/genkit_amazon_bedrock/model_info.py | 2 +- .../src/genkit_amazon_bedrock/models.py | 131 +++ .../src/genkit_amazon_bedrock/plugin.py | 104 ++- .../src/genkit_amazon_bedrock/transport.py | 143 +++ .../tests/converters_test.py | 863 ++++++++++++++++++ .../genkit-amazon-bedrock/tests/live_test.py | 150 +++ .../tests/models_test.py | 157 ++++ .../tests/plugin_test.py | 81 +- .../tests/request_validation_test.py | 170 ++++ .../tests/transport_test.py | 97 ++ py/uv.lock | 2 +- 16 files changed, 2655 insertions(+), 31 deletions(-) create mode 100644 py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/converters.py create mode 100644 py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/models.py create mode 100644 py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/transport.py create mode 100644 py/packages/genkit-amazon-bedrock/tests/converters_test.py create mode 100644 py/packages/genkit-amazon-bedrock/tests/live_test.py create mode 100644 py/packages/genkit-amazon-bedrock/tests/models_test.py create mode 100644 py/packages/genkit-amazon-bedrock/tests/request_validation_test.py create mode 100644 py/packages/genkit-amazon-bedrock/tests/transport_test.py diff --git a/py/packages/genkit-amazon-bedrock/README.md b/py/packages/genkit-amazon-bedrock/README.md index c7325aa449..ad1c38a72f 100644 --- a/py/packages/genkit-amazon-bedrock/README.md +++ b/py/packages/genkit-amazon-bedrock/README.md @@ -4,7 +4,8 @@ Amazon Bedrock plugin for Genkit Python. Provides access to Bedrock-hosted models (Anthropic Claude, Amazon Nova, Meta Llama, Mistral, Cohere, and others), Titan/Cohere/Nova embedders, image generation, and Cohere reranking. -> Status: scaffold. Feature slices are being ported from the mature Go plugin +> Status: in progress. Non-streaming text generation (Converse) is available; +> remaining feature slices are being ported from the mature Go plugin > ([genkit-ai/aws-bedrock-go-plugin](https://github.com/genkit-ai/aws-bedrock-go-plugin)). ## Installation @@ -32,7 +33,9 @@ ai = Genkit( Credentials resolve through the standard AWS SDK chain (environment, `~/.aws/credentials`, instance metadata). Pass a pre-configured -`boto3.session.Session` via `session=` for custom wiring. +`boto3.session.Session` via `session=` for custom wiring. The region comes +from `region=` or the SDK chain (`AWS_REGION`, `AWS_DEFAULT_REGION`, +`~/.aws/config`); there is deliberately no default region. ## License diff --git a/py/packages/genkit-amazon-bedrock/pyproject.toml b/py/packages/genkit-amazon-bedrock/pyproject.toml index f66d127556..ce62138a6b 100644 --- a/py/packages/genkit-amazon-bedrock/pyproject.toml +++ b/py/packages/genkit-amazon-bedrock/pyproject.toml @@ -37,7 +37,7 @@ classifiers = [ "Typing :: Typed", "License :: OSI Approved :: Apache Software License", ] -dependencies = ["genkit", "boto3>=1.36"] +dependencies = ["genkit", "boto3>=1.37.24"] description = "Genkit Amazon Bedrock Plugin" keywords = [ "genkit", diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/__init__.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/__init__.py index bec8057544..ef79283da7 100644 --- a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/__init__.py +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/__init__.py @@ -17,6 +17,7 @@ """Amazon Bedrock plugin for Genkit.""" from genkit_amazon_bedrock.config import BedrockConfig, ModelDefinition +from genkit_amazon_bedrock.converters import cache_point_part from genkit_amazon_bedrock.plugin import Bedrock, bedrock_name __all__ = [ @@ -24,4 +25,5 @@ 'BedrockConfig', 'ModelDefinition', 'bedrock_name', + 'cache_point_part', ] diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py index 44065e93f0..a6d25a2ce2 100644 --- a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py @@ -23,17 +23,21 @@ from genkit import ModelConfig -DEFAULT_REGION = 'us-east-1' DEFAULT_MAX_RETRIES = 3 -DEFAULT_REQUEST_TIMEOUT = 30.0 +# Socket read timeout, not a whole-call deadline: Bedrock generations can +# legitimately run for many minutes (Nova allows 60-minute inference). +DEFAULT_READ_TIMEOUT = 3600.0 +DEFAULT_CONNECT_TIMEOUT = 60.0 +# The botocore default of 10 pooled connections throttles LLM concurrency. +DEFAULT_MAX_POOL_CONNECTIONS = 50 class BedrockConfig(ModelConfig): """Per-call configuration for Bedrock models. - Mirrors the Go plugin's ``Config`` surface. Unknown keys are allowed and - forwarded so callers can use provider-specific options without a plugin - release. + Mirrors the Go plugin's ``Config`` surface. Unknown keys are tolerated for + forward compatibility but only the declared fields (and + ``additional_model_request_fields``) reach the Converse API. """ model_config = ConfigDict( @@ -42,6 +46,10 @@ class BedrockConfig(ModelConfig): extra='allow', ) + max_tokens: int | None = None + """Maximum tokens to generate. When unset, the plugin leaves the field + unset except for Claude models, where Bedrock requires a value.""" + tool_choice: str | None = None """Tool choice mode: ``auto``, ``required``/``any``, ``none``, or a tool name.""" @@ -59,5 +67,5 @@ class ModelDefinition(BaseModel): name: str """Bedrock model ID, e.g. ``anthropic.claude-sonnet-4-5-20250929-v1:0``.""" - type: Literal['chat', 'image', 'embedding'] = 'chat' + type: Literal['chat', 'text', 'image', 'embedding'] = 'chat' """Routes generate calls: chat/text via Converse, image via InvokeModel.""" diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/converters.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/converters.py new file mode 100644 index 0000000000..67e5058885 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/converters.py @@ -0,0 +1,755 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Pure conversion functions between Genkit types and the Bedrock Converse API. + +Ported from the Go plugin's ``generate.go``. Everything here is side-effect +free and testable without AWS: request builders return the keyword arguments +for ``client.converse(...)``, response parsers take the raw response dict. +""" + +import base64 +import json +from typing import Any + +from genkit import ( + FinishReason, + Message, + ModelRequest, + ModelResponse, + ModelUsage, + Part, + ReasoningPart, + Role, + TextPart, + ToolDefinition, + ToolRequest, + ToolRequestPart, +) +from genkit.plugin_api import GenkitError +from genkit_amazon_bedrock.config import BedrockConfig + +# Metadata keys used to round-trip Bedrock reasoning ("thinking") content back +# into a follow-up request. Bedrock returns signed and sometimes redacted +# reasoning that must be replayed verbatim on the next turn or the model +# rejects it, so both are stashed on the part metadata: the signature verbatim +# (it is a string on the wire), the redacted blob as a base64 string so the +# part stays JSON-serializable. These keys are Bedrock-specific: a generic +# reasoning part (without these) is intentionally NOT round-tripped, so +# foreign reasoning can't corrupt a Bedrock conversation. +REASONING_SIGNATURE_METADATA_KEY = 'bedrockReasoningSignature' +REDACTED_CONTENT_METADATA_KEY = 'bedrockRedactedContent' + +# Custom-part key marking a prompt cache point, mirroring the Go plugin. +CACHE_POINT_CUSTOM_KEY = 'bedrockCachePointType' +DEFAULT_CACHE_POINT_TYPE = 'default' + +# Bedrock requires maxTokens for Claude models; newer families allow more. +DEFAULT_CLAUDE_MAX_TOKENS = 4096 +DEFAULT_EXTENDED_CLAUDE_MAX_TOKENS = 8192 +EXTENDED_CLAUDE_MAX_TOKEN_PATTERNS = ( + 'claude-3-5', + 'claude-3-7', + 'claude-4', + 'claude-haiku-4', + 'claude-sonnet-4', + 'claude-opus-4', +) + +IMAGE_FORMATS = { + 'image/png': 'png', + 'image/jpeg': 'jpeg', + # Common alias; Bedrock's format enum has no "jpg". + 'image/jpg': 'jpeg', + 'image/gif': 'gif', + 'image/webp': 'webp', +} + +DOCUMENT_FORMATS = { + 'application/pdf': 'pdf', + 'text/html': 'html', + 'text/plain': 'txt', + 'text/markdown': 'md', + 'text/csv': 'csv', + 'application/msword': 'doc', + 'application/vnd.openxmlformats-officedocument.wordprocessingml.document': 'docx', + 'application/vnd.ms-excel': 'xls', + 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet': 'xlsx', +} + +# Bedrock stopReason values → Genkit finish reasons. Unknown values map to +# OTHER instead of raising: AWS adds stop reasons without notice. +STOP_REASON_MAP = { + 'end_turn': FinishReason.STOP, + 'stop_sequence': FinishReason.STOP, + # Genkit's core loop drives tool re-entry by inspecting parts, not the + # finish reason, so a tool-use turn is a normal stop. + 'tool_use': FinishReason.STOP, + 'max_tokens': FinishReason.LENGTH, + 'model_context_window_exceeded': FinishReason.LENGTH, + 'content_filtered': FinishReason.BLOCKED, + 'guardrail_intervened': FinishReason.BLOCKED, + 'malformed_model_output': FinishReason.OTHER, + 'malformed_tool_use': FinishReason.OTHER, +} + + +def cache_point_part(cache_type: str = DEFAULT_CACHE_POINT_TYPE) -> Part: + """Builds a prompt cache-point part. + + A cache point should be inserted after a big static prompt that is reused + across multiple requests. + + Args: + cache_type: Bedrock cache-point type; only ``default`` exists today. + + Returns: + A custom Part that converts to a Converse ``cachePoint`` block. + """ + return Part.model_validate({'custom': {CACHE_POINT_CUSTOM_KEY: cache_type}}) + + +def _cache_point_type(root: Any) -> str | None: # noqa: ANN401 + custom = getattr(root, 'custom', None) + if not isinstance(custom, dict): + return None + value = custom.get(CACHE_POINT_CUSTOM_KEY) + # Compare by value: the marker arrives as a plain string after any JSON + # round-trip (resumed/serialized flows). + return value if isinstance(value, str) and value else None + + +def _metadata_bytes(metadata: dict[str, Any] | None, key: str) -> bytes | None: # noqa: ANN401 + """Reads a bytes metadata value stored in its base64-string form. + + Raw bytes are also tolerated for programmatically-built parts; invalid + base64 yields None. + """ + if not metadata: + return None + value = metadata.get(key) + if isinstance(value, bytes): + return value + if isinstance(value, str) and value: + try: + return base64.b64decode(value, validate=True) + except (ValueError, TypeError): + return None + return None + + +def _metadata_str(metadata: dict[str, Any] | None, key: str) -> str | None: # noqa: ANN401 + """Reads a string metadata value, tolerating a UTF-8 bytes form. + + The reasoning signature is a string on the Converse wire and must be + replayed verbatim, never re-encoded. + """ + if not metadata: + return None + value = metadata.get(key) + if isinstance(value, str) and value: + return value + if isinstance(value, bytes): + try: + return value.decode('utf-8') or None + except UnicodeDecodeError: + return None + return None + + +def normalize_config(config: Any) -> BedrockConfig | None: # noqa: ANN401 + """Coerces the request config into a BedrockConfig. + + Accepts a BedrockConfig, any pydantic model (e.g. the core ModelConfig the + framework validates configs into), or a plain dict — the historical shape + on resumed/serialized flows. + + Args: + config: The raw ``request.config`` value. + + Returns: + A BedrockConfig, or None when no config was given. + + Raises: + GenkitError: INVALID_ARGUMENT for unsupported config types. + """ + if config is None: + return None + if isinstance(config, BedrockConfig): + return config + if isinstance(config, dict): + return BedrockConfig.model_validate(config) + dump = getattr(config, 'model_dump', None) + if callable(dump): + return BedrockConfig.model_validate(dump(exclude_none=True)) + raise GenkitError( + message=f'bedrock: unexpected config type {type(config).__name__}, want BedrockConfig, ModelConfig, or dict', + status='INVALID_ARGUMENT', + ) + + +def _effective_max_tokens(config: BedrockConfig | None) -> int | None: + if config is None: + return None + if config.max_tokens is not None and config.max_tokens > 0: + return config.max_tokens + # Legacy/common key from the core ModelConfig surface. + if config.max_output_tokens is not None and config.max_output_tokens > 0: + return int(config.max_output_tokens) + return None + + +def default_max_tokens_for_model(model_id: str) -> int | None: + """Default maxTokens for models that require one (Claude only). + + Substring match on the full lowercased model ID so cross-region + inference-profile IDs (``us.anthropic.claude-...``) match too. + """ + lowered = model_id.lower() + if 'claude' not in lowered: + return None + for pattern in EXTENDED_CLAUDE_MAX_TOKEN_PATTERNS: + if pattern in lowered: + return DEFAULT_EXTENDED_CLAUDE_MAX_TOKENS + return DEFAULT_CLAUDE_MAX_TOKENS + + +def build_inference_config(config: BedrockConfig | None) -> dict[str, Any] | None: # noqa: ANN401 + """Builds the Converse ``inferenceConfig`` member; None when empty.""" + if config is None: + return None + inference_config: dict[str, Any] = {} + max_tokens = _effective_max_tokens(config) + if max_tokens is not None: + inference_config['maxTokens'] = max_tokens + if config.temperature is not None: + inference_config['temperature'] = config.temperature + if config.top_p is not None: + inference_config['topP'] = config.top_p + if config.stop_sequences: + inference_config['stopSequences'] = config.stop_sequences + return inference_config or None + + +def to_bedrock_role(role: Role | str) -> str: + """Maps a Genkit role to a Converse role (only user/assistant exist). + + Genkit's TOOL role becomes ``user``: tool results travel back to Bedrock + inside a user message. + """ + if role in (Role.USER, Role.TOOL): + return 'user' + if role == Role.MODEL: + return 'assistant' + raise GenkitError(message=f'bedrock: unsupported role {role!r}', status='INVALID_ARGUMENT') + + +def _media_mime(media: Any) -> str: # noqa: ANN401 + content_type = (getattr(media, 'content_type', None) or '').strip() + url = getattr(media, 'url', '') or '' + if not content_type and url.startswith('data:'): + header = url.split(',', 1)[0].removeprefix('data:') + content_type = header.split(';', 1)[0].strip() + if not content_type: + raise GenkitError(message='bedrock: media part has no content type', status='INVALID_ARGUMENT') + return content_type.split(';', 1)[0].strip().lower() + + +def _decode_media_payload(url: str) -> bytes: + """Decodes media to raw bytes; boto3 base64-encodes them for the wire. + + Accepts a ``data:;base64,...`` URL or a bare base64 string. + Double-encoding (sending the base64 string as bytes) is the classic bug. + """ + data = (url or '').strip() + if not data: + raise GenkitError(message='bedrock: media part has empty data', status='INVALID_ARGUMENT') + # Substring search tolerates multi-parameter data-URL headers. + marker = data.find(';base64,') + if marker != -1: + payload = data[marker + len(';base64,') :].strip() + elif data.startswith('data:'): + raise GenkitError( + message="bedrock: data URL must be base64-encoded (use ';base64,' prefix)", + status='INVALID_ARGUMENT', + ) + elif data.startswith(('http://', 'https://')): + raise GenkitError( + message='bedrock: remote URLs are not supported; use a data URL or base64-encoded data', + status='INVALID_ARGUMENT', + ) + else: + payload = data + try: + return base64.b64decode(payload, validate=True) + except (ValueError, TypeError) as e: + raise GenkitError(message=f'bedrock: decode base64 media: {e}', status='INVALID_ARGUMENT') from e + + +def media_to_block(root: Any) -> dict[str, Any]: # noqa: ANN401 + """Converts a media part to an image or document content block.""" + media = root.media + mime = _media_mime(media) + payload = _decode_media_payload(media.url) + # Document formats are checked before image formats, matching Go. + document_format = DOCUMENT_FORMATS.get(mime) + if document_format is not None: + return { + 'document': { + 'format': document_format, + 'name': 'document', + 'source': {'bytes': payload}, + } + } + image_format = IMAGE_FORMATS.get(mime) + if image_format is not None: + return {'image': {'format': image_format, 'source': {'bytes': payload}}} + raise GenkitError( + message=( + f'bedrock: unsupported media MIME type {mime!r} ' + '(must be png/jpeg/gif/webp or one of pdf/csv/doc/docx/xls/xlsx/html/txt/md)' + ), + status='INVALID_ARGUMENT', + ) + + +def _tool_response_text(output: Any) -> str: # noqa: ANN401 + if output is None: + return '' + if isinstance(output, str): + return output + try: + return json.dumps(output) + except (TypeError, ValueError) as e: + raise GenkitError(message=f'bedrock: marshal tool response: {e}', status='INVALID_ARGUMENT') from e + + +def _reasoning_part_to_blocks(root: Any) -> list[dict[str, Any]]: # noqa: ANN401 + """Converts a reasoning part back to Converse reasoningContent blocks. + + Only Bedrock-originated reasoning (carrying the signature and/or redacted + metadata) is emitted; a generic reasoning part produces no blocks so it + cannot corrupt the follow-up request. + """ + metadata = getattr(root, 'metadata', None) + blocks: list[dict[str, Any]] = [] + redacted = _metadata_bytes(metadata, REDACTED_CONTENT_METADATA_KEY) + if redacted: + blocks.append({'reasoningContent': {'redactedContent': redacted}}) + signature = _metadata_str(metadata, REASONING_SIGNATURE_METADATA_KEY) + text = getattr(root, 'reasoning', None) or '' + if text and signature: + blocks.append({'reasoningContent': {'reasoningText': {'text': text, 'signature': signature}}}) + return blocks + + +def _tool_use_id(ref: str | None, label: str) -> str: + """Bedrock's toolUseId rejects empty strings, so a missing ref cannot be sent.""" + if not ref: + raise GenkitError( + message=f'bedrock: {label} requires a ref to send as toolUseId', + status='INVALID_ARGUMENT', + ) + return ref + + +def _part_to_blocks(part: Part | Any) -> list[dict[str, Any]]: # noqa: ANN401 + """Converts one Genkit part to Converse content blocks. + + Unknown part kinds are silently dropped, matching Go's request-side + posture (the response side fails loud instead). + """ + root = part.root if isinstance(part, Part) else part + if getattr(root, 'media', None) is not None: + return [media_to_block(root)] + tool_request = getattr(root, 'tool_request', None) + if tool_request is not None: + return [ + { + 'toolUse': { + 'toolUseId': _tool_use_id(tool_request.ref, 'tool request'), + 'name': tool_request.name, + 'input': tool_request.input, + } + } + ] + tool_response = getattr(root, 'tool_response', None) + if tool_response is not None: + return [ + { + 'toolResult': { + 'toolUseId': _tool_use_id(tool_response.ref, 'tool response'), + 'content': [{'text': _tool_response_text(tool_response.output)}], + 'status': 'success', + } + } + ] + cache_type = _cache_point_type(root) + if cache_type is not None: + return [{'cachePoint': {'type': cache_type}}] + # `is not None`: a redacted-only reasoning part has reasoning == ''. + if getattr(root, 'reasoning', None) is not None: + return _reasoning_part_to_blocks(root) + if getattr(root, 'text', None) is not None: + return [{'text': root.text}] + return [] + + +def _system_blocks(message: Message | Any) -> list[dict[str, Any]]: # noqa: ANN401 + """System messages keep only text and cache points; the rest is dropped.""" + blocks: list[dict[str, Any]] = [] + for part in message.content or []: + root = part.root if isinstance(part, Part) else part + cache_type = _cache_point_type(root) + if cache_type is not None: + blocks.append({'cachePoint': {'type': cache_type}}) + # Truthiness, not `is not None`: Bedrock rejects empty system text. + elif getattr(root, 'text', None): + blocks.append({'text': root.text}) + return blocks + + +def convert_messages( + messages: list[Message] | None, +) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]: + """Splits Genkit messages into Converse messages and top-level system blocks. + + Genkit's SYSTEM role becomes the separate top-level ``system`` array, not + a conversation message. Messages that convert to zero blocks are dropped + entirely — Bedrock rejects empty content arrays. + + Returns: + A ``(messages, system)`` tuple of Converse-shaped dicts. + """ + converse_messages: list[dict[str, Any]] = [] + system: list[dict[str, Any]] = [] + for message in messages or []: + if message is None: + continue + if message.role == Role.SYSTEM: + system.extend(_system_blocks(message)) + continue + # Validate the role before converting parts, like Go, so an + # unsupported role errors even when its message converts to nothing. + role = to_bedrock_role(message.role) + blocks: list[dict[str, Any]] = [] + for part in message.content or []: + if part is None: + continue + blocks.extend(_part_to_blocks(part)) + if not blocks: + continue + converse_messages.append({'role': role, 'content': blocks}) + return converse_messages, system + + +def _normalize_tool_schema(schema: Any) -> dict[str, Any]: # noqa: ANN401 + """Normalizes a tool input schema for ``toolSpec.inputSchema.json``. + + Bedrock requires an input schema; a missing one becomes the empty object + schema. Injects ``type``/``properties``/``$schema`` defaults like Go. + """ + if schema is None: + normalized: dict[str, Any] = {'type': 'object', 'properties': {}} + elif isinstance(schema, dict): + normalized = dict(schema) + elif isinstance(schema, (str, bytes)): + try: + parsed = json.loads(schema) + except (ValueError, TypeError): + return {'type': 'object', 'properties': {}} + normalized = parsed if isinstance(parsed, dict) else {'type': 'object', 'properties': {}} + else: + return {'type': 'object', 'properties': {}} + normalized.setdefault('type', 'object') + if normalized.get('type') == 'object': + normalized.setdefault('properties', {}) + normalized.setdefault('$schema', 'http://json-schema.org/draft-07/schema#') + return normalized + + +def to_bedrock_tool(tool: ToolDefinition | None) -> dict[str, Any]: # noqa: ANN401 + """Converts a Genkit tool definition to a Converse toolSpec.""" + if tool is None: + raise GenkitError(message='bedrock: tool definition required', status='INVALID_ARGUMENT') + if not tool.name: + raise GenkitError(message='bedrock: tool name required', status='INVALID_ARGUMENT') + tool_spec: dict[str, Any] = { + 'name': tool.name, + 'inputSchema': {'json': _normalize_tool_schema(tool.input_schema)}, + } + if tool.description: + # Omitted when empty: description is optional, but Bedrock rejects ''. + tool_spec['description'] = tool.description + return {'toolSpec': tool_spec} + + +def _to_bedrock_tool_choice(tool_choice: str, tools: list[ToolDefinition]) -> dict[str, Any]: # noqa: ANN401 + if tool_choice in ('', 'auto'): + return {'auto': {}} + if tool_choice in ('required', 'any'): + return {'any': {}} + for tool in tools: + if tool is not None and tool.name == tool_choice: + return {'tool': {'name': tool_choice}} + raise GenkitError( + message=f'bedrock: tool_choice {tool_choice!r} does not match any declared tool', + status='INVALID_ARGUMENT', + ) + + +def build_converse_request(model_id: str, request: ModelRequest[Any]) -> dict[str, Any]: # noqa: ANN401 + """Builds the keyword arguments for ``client.converse(...)``. + + The model ID is sent verbatim — inference-profile prefixes and ARNs are + preserved; only capability lookup ever strips them. + + Args: + model_id: Bedrock model ID, inference-profile ID, or ARN. + request: The Genkit model request. + + Returns: + Keyword arguments for the Converse call. + """ + if request is None: + raise GenkitError(message='bedrock: model request is nil', status='INVALID_ARGUMENT') + config = normalize_config(request.config) + messages, system = convert_messages(request.messages) + + tools = [tool for tool in (request.tools or []) if tool is not None] if request.tools else [] + # When using tools, AWS Bedrock requires that the conversation doesn't + # end with an assistant message. + if request.tools and messages and messages[-1]['role'] == 'assistant': + messages = messages[:-1] + + kwargs: dict[str, Any] = {'modelId': model_id, 'messages': messages} + if system: + kwargs['system'] = system + + inference_config = build_inference_config(config) + max_tokens_set = bool(inference_config and 'maxTokens' in inference_config) + if not max_tokens_set: + # Bedrock requires maxTokens for Claude models; inject a default only + # when the caller didn't set one. + default_max_tokens = default_max_tokens_for_model(model_id) + if default_max_tokens is not None: + inference_config = dict(inference_config or {}) + inference_config['maxTokens'] = default_max_tokens + if inference_config: + kwargs['inferenceConfig'] = inference_config + + if config is not None and config.additional_model_request_fields: + # Forwarded verbatim (e.g. Claude extended thinking budgets). + kwargs['additionalModelRequestFields'] = config.additional_model_request_fields + + if request.tools: + tool_choice = _requested_tool_choice(request, config) + # "none" means omit toolConfig entirely — Bedrock has no none mode. + if tool_choice == 'none': + return kwargs + tool_config: dict[str, Any] = {'tools': [to_bedrock_tool(tool) for tool in request.tools]} + if tool_choice: + tool_config['toolChoice'] = _to_bedrock_tool_choice(tool_choice, tools) + kwargs['toolConfig'] = tool_config + return kwargs + + +def _requested_tool_choice(request: ModelRequest[Any], config: BedrockConfig | None) -> str: + # The Bedrock-specific config wins over the core request field so callers + # can name a specific tool, which the core enum cannot express. + if config is not None and config.tool_choice: + return config.tool_choice + if request.tool_choice: + return str(request.tool_choice) + return '' + + +def _coerce_value(value: Any, schema: Any) -> Any: # noqa: ANN401 + """Coerces a tool-input value toward its declared schema type. + + Models occasionally return numbers or booleans as strings and floats for + integers; coerce like Go instead of failing tool dispatch. + """ + if not isinstance(schema, dict): + return value + schema_type = schema.get('type') + if schema_type in ('number', 'integer') and isinstance(value, str): + try: + number = float(value) + except ValueError: + return value + return int(number) if schema_type == 'integer' else number + if schema_type == 'integer' and isinstance(value, float): + return int(value) + if schema_type == 'number' and isinstance(value, int) and not isinstance(value, bool): + return float(value) + if schema_type == 'string' and isinstance(value, (int, float)) and not isinstance(value, bool): + # Go coerces wire numbers to their string form; a raw int fails dispatch. + return str(value) + if schema_type == 'boolean' and isinstance(value, str): + # Matches Go's strconv.ParseBool vocabulary. + lowered = value.strip().lower() + if lowered in ('true', 't', '1'): + return True + if lowered in ('false', 'f', '0'): + return False + return value + if schema_type == 'array' and isinstance(value, list): + return [_coerce_value(item, schema.get('items')) for item in value] + if schema_type == 'object' and isinstance(value, dict): + return _coerce_map(value, schema) + return value + + +def _coerce_map(value: dict[str, Any], schema: dict[str, Any]) -> dict[str, Any]: # noqa: ANN401 + # Only object schemas coerce, matching Go; non-object schemas pass through. + if schema.get('type') != 'object': + return value + properties = schema.get('properties') + if not isinstance(properties, dict): + return value + # Keys without a schema are kept as-is. + return {key: _coerce_value(item, properties.get(key)) for key, item in value.items()} + + +def _coerce_tool_input(name: str, value: Any, tools: list[ToolDefinition] | None) -> Any: # noqa: ANN401 + if not isinstance(value, dict): + return value + for tool in tools or []: + if tool is not None and tool.name == name and isinstance(tool.input_schema, dict): + return _coerce_map(value, tool.input_schema) + return value + + +def _reasoning_block_to_part(block: dict[str, Any]) -> Part | None: # noqa: ANN401 + reasoning_text = block.get('reasoningText') + if reasoning_text is not None: + # Both wire shapes occur: {'text': ...} and a bare string. + if isinstance(reasoning_text, str): + text, signature = reasoning_text, None + else: + text = reasoning_text.get('text') or '' + signature = reasoning_text.get('signature') + if not text and not signature: + return None + return _bedrock_reasoning_part(text, signature, None) + redacted = block.get('redactedContent') + if redacted is not None: + if not redacted: + return None + return _bedrock_reasoning_part('', None, redacted) + raise GenkitError( + message=f'bedrock: unhandled reasoning content variant {sorted(block.keys())!r}', + status='INTERNAL', + ) + + +def _bedrock_reasoning_part(text: str, signature: str | None, redacted: bytes | None) -> Part: + metadata: dict[str, Any] = {} + if signature: + # Also stored under the generic key so framework-level consumers see it. + metadata['signature'] = signature + metadata[REASONING_SIGNATURE_METADATA_KEY] = signature + if redacted: + # Base64 string, not raw bytes: part metadata must stay JSON-serializable. + metadata[REDACTED_CONTENT_METADATA_KEY] = base64.b64encode(redacted).decode('ascii') + return Part(root=ReasoningPart(reasoning=text, metadata=metadata or None)) + + +def content_blocks_to_parts( + blocks: list[dict[str, Any]], + tools: list[ToolDefinition] | None = None, +) -> list[Part]: + """Converts Converse response content blocks to Genkit parts. + + Unlike the request side, unknown response blocks fail loud: silently + dropping model output would corrupt conversations. + """ + parts: list[Part] = [] + for block in blocks: + if 'text' in block: + parts.append(Part(root=TextPart(text=block['text']))) + elif 'toolUse' in block: + tool_use = block['toolUse'] + tool_input = tool_use.get('input') + if tool_input is None: + tool_input = {} + parts.append( + Part( + root=ToolRequestPart( + tool_request=ToolRequest( + ref=tool_use.get('toolUseId'), + name=tool_use.get('name') or '', + input=_coerce_tool_input(tool_use.get('name') or '', tool_input, tools), + ) + ) + ) + ) + elif 'reasoningContent' in block: + part = _reasoning_block_to_part(block['reasoningContent']) + if part is not None: + parts.append(part) + else: + raise GenkitError( + message=f'bedrock: unhandled response content variant {sorted(block.keys())!r}', + status='INTERNAL', + ) + return parts + + +def map_finish_reason(stop_reason: str | None) -> FinishReason: + """Maps a Bedrock stopReason to a Genkit finish reason (unknown → OTHER).""" + return STOP_REASON_MAP.get(stop_reason or '', FinishReason.OTHER) + + +def usage_from_response(usage: dict[str, Any] | None) -> ModelUsage | None: # noqa: ANN401 + """Maps Converse token usage; totals are trusted verbatim from AWS. + + Only ``cacheReadInputTokens`` surfaces (as ``cached_content_tokens``), + matching the Go plugin; cache-write tokens are unreported. + """ + if usage is None: + return None + return ModelUsage( + input_tokens=usage.get('inputTokens'), + output_tokens=usage.get('outputTokens'), + total_tokens=usage.get('totalTokens'), + cached_content_tokens=usage.get('cacheReadInputTokens'), + ) + + +def to_model_response(response: dict[str, Any] | None, request: ModelRequest[Any]) -> ModelResponse: # noqa: ANN401 + """Converts a raw Converse response to a Genkit ModelResponse.""" + if response is None: + raise GenkitError(message='bedrock: converse response is nil', status='INTERNAL') + output = response.get('output') or {} + message = output.get('message') + if output and message is None: + raise GenkitError( + message=f'bedrock: unexpected output variant {sorted(output.keys())!r}', + status='INTERNAL', + ) + parts = content_blocks_to_parts((message or {}).get('content') or [], request.tools) + if not parts: + # Guardrail-blocked responses have no content; return a well-formed + # empty message rather than erroring. + parts = [Part(root=TextPart(text=''))] + return ModelResponse( + message=Message(role=Role.MODEL, content=parts), + finish_reason=map_finish_reason(response.get('stopReason')), + usage=usage_from_response(response.get('usage')), + request=request, + ) diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/model_info.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/model_info.py index 9909572b2c..a152168c76 100644 --- a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/model_info.py +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/model_info.py @@ -132,7 +132,7 @@ def strip_inference_profile_prefix(model_id: str) -> str: def get_model_info( model_name: str, - model_type: Literal['chat', 'image', 'embedding'] = 'chat', + model_type: Literal['chat', 'text', 'image', 'embedding'] = 'chat', ) -> ModelInfo: """Infers Genkit model info for a Bedrock model. diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/models.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/models.py new file mode 100644 index 0000000000..cf8061a490 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/models.py @@ -0,0 +1,131 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Bedrock model action implementation (Converse API).""" + +from typing import Any, Protocol + +from botocore.exceptions import ( + BotoCoreError, + ClientError, + ConnectTimeoutError, + EndpointConnectionError, + NoCredentialsError, + NoRegionError, + ParamValidationError, + PartialCredentialsError, + ReadTimeoutError, +) + +from genkit import ModelRequest, ModelResponse, ModelResponseChunk, Role +from genkit.plugin_api import ActionRunContext, GenkitError, StatusName +from genkit_amazon_bedrock.converters import build_converse_request, to_model_response + + +class ConverseTransport(Protocol): + """Structural contract for the transport seam (see ``transport.py``).""" + + async def converse(self, **kwargs: Any) -> dict[str, Any]: # noqa: ANN401 + """Calls the Converse API and returns the raw response dict.""" + ... + + +# AWS error codes → Genkit statuses; anything unlisted maps to UNKNOWN. +_ERROR_CODE_STATUS: dict[str, StatusName] = { + 'ThrottlingException': 'RESOURCE_EXHAUSTED', + 'TooManyRequestsException': 'RESOURCE_EXHAUSTED', + 'ServiceQuotaExceededException': 'RESOURCE_EXHAUSTED', + 'ValidationException': 'INVALID_ARGUMENT', + 'AccessDeniedException': 'PERMISSION_DENIED', + 'UnrecognizedClientException': 'UNAUTHENTICATED', + 'ExpiredTokenException': 'UNAUTHENTICATED', + 'ResourceNotFoundException': 'NOT_FOUND', + 'ModelTimeoutException': 'DEADLINE_EXCEEDED', + 'ModelNotReadyException': 'UNAVAILABLE', + 'ServiceUnavailableException': 'UNAVAILABLE', + 'ModelErrorException': 'INTERNAL', +} + + +# Client-side botocore failures never reach the service, so they carry no error +# code; map the exception type instead. Anything unlisted stays UNKNOWN. +_BOTOCORE_ERROR_STATUS: tuple[tuple[type[BotoCoreError], StatusName], ...] = ( + (ParamValidationError, 'INVALID_ARGUMENT'), + (NoCredentialsError, 'UNAUTHENTICATED'), + (PartialCredentialsError, 'UNAUTHENTICATED'), + (NoRegionError, 'FAILED_PRECONDITION'), + (ReadTimeoutError, 'DEADLINE_EXCEEDED'), + (ConnectTimeoutError, 'DEADLINE_EXCEEDED'), + (EndpointConnectionError, 'UNAVAILABLE'), +) + + +def _from_client_error(error: ClientError) -> GenkitError: + error_info: dict[str, Any] = error.response.get('Error') or {} + code = error_info.get('Code') or '' + message = error_info.get('Message') or str(error) + return GenkitError( + message=f'bedrock converse failed: {code}: {message}' if code else f'bedrock converse failed: {message}', + status=_ERROR_CODE_STATUS.get(code, 'UNKNOWN'), + ) + + +def _from_botocore_error(error: BotoCoreError) -> GenkitError: + status: StatusName = 'UNKNOWN' + for error_type, mapped in _BOTOCORE_ERROR_STATUS: + if isinstance(error, error_type): + status = mapped + break + return GenkitError(message=f'bedrock converse failed: {error}', status=status) + + +class BedrockModel: + """Handles a generate call for one Bedrock chat/text model.""" + + def __init__(self, model_id: str, transport: ConverseTransport) -> None: + """Initializes the model handler. + + Args: + model_id: Bedrock model ID, inference-profile ID, or ARN, sent to + the Converse API verbatim. + transport: The shared transport seam owning the boto3 client. + """ + self._model_id = model_id + self._transport = transport + + async def generate(self, request: ModelRequest[Any], ctx: ActionRunContext | None = None) -> ModelResponse: + """Runs a non-streaming Converse call. + + Args: + request: The Genkit model request. + ctx: Action run context; when a streaming callback is attached the + full response is emitted as a single chunk until + ConverseStream lands in a later slice. + + Returns: + The converted model response. + """ + converse_kwargs = build_converse_request(self._model_id, request) + try: + response = await self._transport.converse(**converse_kwargs) + except ClientError as e: + raise _from_client_error(e) from e + except BotoCoreError as e: + raise _from_botocore_error(e) from e + model_response = to_model_response(response, request) + if ctx is not None and ctx.is_streaming and model_response.message is not None: + ctx.send_chunk(ModelResponseChunk(role=Role.MODEL, index=0, content=model_response.message.content)) + return model_response diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py index b327a952e5..d00e935006 100644 --- a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/plugin.py @@ -27,18 +27,27 @@ from typing import TYPE_CHECKING +from genkit import ModelRequest, ModelResponse +from genkit.model import model_action_metadata from genkit.plugin_api import ( Action, ActionKind, ActionMetadata, + ActionRunContext, Plugin, + to_json_schema, ) from genkit_amazon_bedrock.config import ( + DEFAULT_CONNECT_TIMEOUT, + DEFAULT_MAX_POOL_CONNECTIONS, DEFAULT_MAX_RETRIES, - DEFAULT_REGION, - DEFAULT_REQUEST_TIMEOUT, + DEFAULT_READ_TIMEOUT, + BedrockConfig, ModelDefinition, ) +from genkit_amazon_bedrock.model_info import get_model_info +from genkit_amazon_bedrock.models import BedrockModel +from genkit_amazon_bedrock.transport import BedrockTransport if TYPE_CHECKING: import boto3.session @@ -67,7 +76,9 @@ def __init__( self, region: str | None = None, max_retries: int = DEFAULT_MAX_RETRIES, - request_timeout: float = DEFAULT_REQUEST_TIMEOUT, + read_timeout: float = DEFAULT_READ_TIMEOUT, + connect_timeout: float = DEFAULT_CONNECT_TIMEOUT, + max_pool_connections: int = DEFAULT_MAX_POOL_CONNECTIONS, session: 'boto3.session.Session | None' = None, models: list[ModelDefinition] | None = None, embedders: list[str] | None = None, @@ -75,34 +86,56 @@ def __init__( """Initializes the Bedrock plugin. Args: - region: AWS region. Defaults to the SDK resolution chain, falling - back to ``us-east-1`` (Go plugin parity). + region: AWS region. Defaults to the SDK resolution chain + (``AWS_REGION``, ``AWS_DEFAULT_REGION``, ``~/.aws/config``); + initialization fails loudly when no region resolves rather + than silently picking one. max_retries: Retry limit for Bedrock API calls. - request_timeout: Per-call timeout in seconds. + read_timeout: Socket read timeout in seconds (not a whole-call + deadline; long generations must not be killed mid-flight). + connect_timeout: Socket connect timeout in seconds. + max_pool_connections: HTTP connection pool size. session: Optional pre-configured ``boto3.session.Session`` for custom credentials or advanced SDK wiring. models: Bedrock models to register. Models not listed can still be resolved dynamically by namespaced name. embedders: Embedding model IDs to register (Titan, Cohere, Nova). """ - self.region = region or DEFAULT_REGION + self.region = region self.max_retries = max_retries - self.request_timeout = request_timeout + self.read_timeout = read_timeout + self.connect_timeout = connect_timeout + self.max_pool_connections = max_pool_connections self._session = session self.models = models or [] self.embedders = embedders or [] + self._transport = BedrockTransport( + region=region, + max_retries=max_retries, + read_timeout=read_timeout, + connect_timeout=connect_timeout, + max_pool_connections=max_pool_connections, + session=session, + ) async def init(self) -> list[Action]: """Initialize plugin. + Builds the shared client so misconfiguration (e.g. no resolvable AWS + region) fails at startup instead of on the first model call. + Returns: Empty list (actions are lazily created via ``resolve``). """ + await self._transport.ensure_client() return [] async def resolve(self, action_type: ActionKind, name: str) -> Action | None: """Resolve an action by namespaced name. + Any model ID resolves — the Bedrock catalogue includes arbitrary + inference profiles and ARNs and can never be fully enumerated. + Args: action_type: The kind of action to resolve. name: The namespaced action name. @@ -110,12 +143,59 @@ async def resolve(self, action_type: ActionKind, name: str) -> Action | None: Returns: Action object if resolvable, None otherwise. """ - return None + if action_type != ActionKind.MODEL: + return None + model_id = name.removeprefix(f'{BEDROCK_PLUGIN_NAME}/') + model_type = self._configured_model_type(model_id) + if model_type not in ('chat', 'text'): + # Image generation lands in a later slice. + return None + return self._create_model_action(name, model_id) + + def _configured_model_type(self, model_id: str) -> str: + for definition in self.models: + if definition.name == model_id: + return definition.type + return 'chat' + + def _create_model_action(self, name: str, model_id: str) -> Action: + model_info = get_model_info(model_id) + + async def _generate(request: ModelRequest, ctx: ActionRunContext) -> ModelResponse: + model = BedrockModel(model_id=model_id, transport=self._transport) + return await model.generate(request, ctx) + + return Action( + kind=ActionKind.MODEL, + name=bedrock_name(model_id), + fn=_generate, + metadata={ + 'model': { + 'label': model_info.label, + 'stage': model_info.stage.value if model_info.stage else None, + 'supports': ( + model_info.supports.model_dump(by_alias=True, exclude_none=True) if model_info.supports else {} + ), + 'customOptions': to_json_schema(BedrockConfig), + }, + }, + ) async def list_actions(self) -> list[ActionMetadata]: - """List available Bedrock models and embedders. + """List configured Bedrock models. + + Only explicitly configured models are listed; the catalogue itself is + open-ended, and any model ID still resolves on demand. Returns: - ActionMetadata for each configured model and embedder. + ActionMetadata for each configured chat model. """ - return [] + return [ + model_action_metadata( + name=bedrock_name(definition.name), + info=get_model_info(definition.name, definition.type).model_dump(by_alias=True, exclude_none=True), + config_schema=BedrockConfig, + ) + for definition in self.models + if definition.type in ('chat', 'text') + ] diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/transport.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/transport.py new file mode 100644 index 0000000000..cd36e6434d --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/transport.py @@ -0,0 +1,143 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Transport seam for the Amazon Bedrock plugin. + +Every boto3 call goes through this module. boto3 is synchronous, so calls are +bridged onto worker threads with ``asyncio.to_thread`` to keep the event loop +unblocked for the seconds-to-minutes an LLM call takes. Keeping the whole SDK +surface behind one seam lets us swap in AWS's official async SDK once it +matures without touching converters or models. +""" + +import asyncio +import os +import threading +from typing import TYPE_CHECKING, Any + +from genkit.plugin_api import GenkitError + +if TYPE_CHECKING: + import boto3.session + +NO_REGION_MESSAGE = ( + 'bedrock: no AWS region resolved; set Bedrock(region=...), AWS_REGION, ' + 'AWS_DEFAULT_REGION, or a region in ~/.aws/config' +) + + +class BedrockTransport: + """Owns the shared bedrock-runtime client and the sync-to-async bridge. + + The sync boto3 client is not bound to an event loop (unlike async SDK + clients), so one client instance safely serves both the application loop + and the Dev UI reflection loop; boto3 clients are thread-safe for calls, + only creation needs the lock. + """ + + def __init__( + self, + *, + region: str | None = None, + max_retries: int, + read_timeout: float, + connect_timeout: float, + max_pool_connections: int, + session: 'boto3.session.Session | None' = None, + ) -> None: + """Initializes the transport. + + Args: + region: AWS region; falls back to the SDK resolution chain. + max_retries: Retry limit for Bedrock API calls. + read_timeout: Socket read timeout in seconds. Deliberately not a + whole-call deadline: long generations stream for minutes and + must not be killed mid-flight. + connect_timeout: Socket connect timeout in seconds. + max_pool_connections: HTTP connection pool size, raised off the + botocore default of 10 so the pool is never the bottleneck. + Concurrency is bounded first by the event loop's default + thread-pool executor, which ``asyncio.to_thread`` dispatches to. + session: Optional pre-configured ``boto3.session.Session`` for + custom credentials or advanced SDK wiring. + """ + self._region = region + self._max_retries = max_retries + self._read_timeout = read_timeout + self._connect_timeout = connect_timeout + self._max_pool_connections = max_pool_connections + self._session = session + self._client: Any = None + self._lock = threading.Lock() + + def client(self) -> Any: # noqa: ANN401 + """Returns the shared bedrock-runtime client, building it on first use. + + Raises: + GenkitError: FAILED_PRECONDITION when no region resolves. Matching + the Go plugin, there is deliberately no default region: a + silent ``us-east-1`` fallback sends traffic (and data) to a + region the user never chose. + """ + with self._lock: + if self._client is None: + self._client = self._build_client() + return self._client + + async def ensure_client(self) -> None: + """Builds the client off-loop so init fails fast on config errors.""" + await asyncio.to_thread(self.client) + + async def converse(self, **kwargs: Any) -> dict[str, Any]: # noqa: ANN401 + """Calls the Converse API on a worker thread. + + Args: + kwargs: Keyword arguments passed verbatim to ``converse``. + + Returns: + The raw Converse response dict. + """ + return await asyncio.to_thread(self._converse_sync, kwargs) + + def _converse_sync(self, kwargs: dict[str, Any]) -> dict[str, Any]: # noqa: ANN401 + return self.client().converse(**kwargs) + + def _build_client(self) -> Any: # noqa: ANN401 + import boto3.session + from botocore.config import Config + + session = self._session or boto3.session.Session() + # botocore only began reading AWS_REGION in 1.41, below this package's + # floor, so resolve it here. A caller-supplied session states its own + # region first; otherwise env wins over ~/.aws/config, as in the SDKs. + env_region = os.environ.get('AWS_REGION') + if self._session is not None: + region = self._region or session.region_name or env_region + else: + region = self._region or env_region or session.region_name + if not region: + raise GenkitError(message=NO_REGION_MESSAGE, status='FAILED_PRECONDITION') + + return session.client( + 'bedrock-runtime', + region_name=region, + config=Config( + retries={'max_attempts': self._max_retries, 'mode': 'standard'}, + read_timeout=self._read_timeout, + connect_timeout=self._connect_timeout, + max_pool_connections=self._max_pool_connections, + ), + ) diff --git a/py/packages/genkit-amazon-bedrock/tests/converters_test.py b/py/packages/genkit-amazon-bedrock/tests/converters_test.py new file mode 100644 index 0000000000..30a5bb7790 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/tests/converters_test.py @@ -0,0 +1,863 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Tests for the Converse request/response converters. + +The expectations mirror the Go plugin's ``generate_test.go`` matrix — they +encode Bedrock wire-format truths, not incidental structure. +""" + +import base64 + +import pytest +from genkit_amazon_bedrock.config import BedrockConfig +from genkit_amazon_bedrock.converters import ( + REASONING_SIGNATURE_METADATA_KEY, + REDACTED_CONTENT_METADATA_KEY, + build_converse_request, + build_inference_config, + cache_point_part, + content_blocks_to_parts, + default_max_tokens_for_model, + map_finish_reason, + normalize_config, + to_bedrock_role, + to_bedrock_tool, + to_model_response, + usage_from_response, +) + +from genkit import ( + FinishReason, + Message, + ModelConfig, + ModelRequest, + Part, + ReasoningPart, + Role, + TextPart, + ToolDefinition, +) +from genkit.plugin_api import GenkitError + +PNG_BYTES = b'\x89PNG\r\n\x1a\nfakeimagedata' +PNG_B64 = base64.b64encode(PNG_BYTES).decode() + + +def user_text_request(text: str = 'hello', **kwargs) -> ModelRequest: + return ModelRequest( + messages=[Message(role=Role.USER, content=[Part(root=TextPart(text=text))])], + **kwargs, + ) + + +# --- Stop reasons --------------------------------------------------------- + + +@pytest.mark.parametrize( + 'stop_reason,expected', + [ + ('end_turn', FinishReason.STOP), + ('stop_sequence', FinishReason.STOP), + ('tool_use', FinishReason.STOP), + ('max_tokens', FinishReason.LENGTH), + ('model_context_window_exceeded', FinishReason.LENGTH), + ('content_filtered', FinishReason.BLOCKED), + ('guardrail_intervened', FinishReason.BLOCKED), + ('malformed_model_output', FinishReason.OTHER), + ('malformed_tool_use', FinishReason.OTHER), + ('some_future_reason', FinishReason.OTHER), + ('', FinishReason.OTHER), + (None, FinishReason.OTHER), + ], +) +def test_map_finish_reason(stop_reason, expected) -> None: + assert map_finish_reason(stop_reason) == expected + + +# --- Roles ---------------------------------------------------------------- + + +def test_roles_map_to_converse_vocabulary() -> None: + assert to_bedrock_role(Role.USER) == 'user' + assert to_bedrock_role(Role.TOOL) == 'user' + assert to_bedrock_role(Role.MODEL) == 'assistant' + + +def test_unsupported_role_raises() -> None: + with pytest.raises(GenkitError): + to_bedrock_role('reviewer') + + +def test_unsupported_role_errors_even_for_empty_message() -> None: + # The role is validated before parts are converted, like Go. + request = ModelRequest(messages=[Message(role='reviewer', content=[])]) + with pytest.raises(GenkitError, match='unsupported role'): + build_converse_request('amazon.nova-lite-v1:0', request) + + +# --- Config normalization ------------------------------------------------- + + +def test_normalize_config_none_and_passthrough() -> None: + assert normalize_config(None) is None + config = BedrockConfig(tool_choice='auto') + assert normalize_config(config) is config + + +def test_normalize_config_from_model_config() -> None: + config = normalize_config(ModelConfig(temperature=0.5, max_output_tokens=100, top_p=0.9)) + assert config is not None + assert config.temperature == 0.5 + assert config.max_output_tokens == 100 + assert config.top_p == 0.9 + + +@pytest.mark.parametrize( + 'raw,field,expected', + [ + ({'maxOutputTokens': 50}, 'max_output_tokens', 50), + ({'max_tokens': 60}, 'max_tokens', 60), + ({'maxTokens': 70}, 'max_tokens', 70), + ], +) +def test_normalize_config_from_dict_with_legacy_keys(raw, field, expected) -> None: + config = normalize_config(raw) + assert config is not None + assert getattr(config, field) == expected + + +def test_normalize_config_rejects_unsupported_type() -> None: + with pytest.raises(GenkitError): + normalize_config(42) + + +def test_build_inference_config_empty_is_none() -> None: + assert build_inference_config(None) is None + assert build_inference_config(BedrockConfig()) is None + assert build_inference_config(BedrockConfig(tool_choice='auto')) is None + + +def test_build_inference_config_fields() -> None: + config = BedrockConfig(max_tokens=256, temperature=0.7, top_p=0.9, stop_sequences=['END']) + assert build_inference_config(config) == { + 'maxTokens': 256, + 'temperature': 0.7, + 'topP': 0.9, + 'stopSequences': ['END'], + } + + +def test_bedrock_max_tokens_wins_over_common_field() -> None: + inference_config = build_inference_config(BedrockConfig(max_tokens=100, max_output_tokens=999)) + assert inference_config is not None + assert inference_config['maxTokens'] == 100 + + +def test_explicit_zero_temperature_is_sent() -> None: + # None means unset; an explicit 0.0 is a real setting and must be sent. + inference_config = build_inference_config(BedrockConfig(temperature=0.0)) + assert inference_config == {'temperature': 0.0} + + +def test_top_k_and_version_are_accepted_but_ignored() -> None: + # Converse has no first-class topK or version; Go drops them silently. + request = user_text_request(config=BedrockConfig(top_k=40, version='v9')) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert 'inferenceConfig' not in kwargs + assert 'additionalModelRequestFields' not in kwargs + + +# --- Claude maxTokens injection -------------------------------------------- + + +@pytest.mark.parametrize( + 'model_id,expected', + [ + ('anthropic.claude-3-haiku-20240307-v1:0', 4096), + ('anthropic.claude-3-5-sonnet-20241022-v2:0', 8192), + ('anthropic.claude-3-7-sonnet-20250219-v1:0', 8192), + ('us.anthropic.claude-sonnet-4-5-20250929-v1:0', 8192), + ('anthropic.claude-opus-4-6-v1', 8192), + ('amazon.nova-lite-v1:0', None), + ], +) +def test_default_max_tokens_for_model(model_id, expected) -> None: + assert default_max_tokens_for_model(model_id) == expected + + +def test_claude_gets_default_max_tokens_injected() -> None: + kwargs = build_converse_request('anthropic.claude-3-haiku-20240307-v1:0', user_text_request()) + assert kwargs['inferenceConfig'] == {'maxTokens': 4096} + + +def test_claude_keeps_user_configured_max_tokens() -> None: + request = user_text_request(config=BedrockConfig(max_tokens=32)) + kwargs = build_converse_request('anthropic.claude-3-haiku-20240307-v1:0', request) + assert kwargs['inferenceConfig'] == {'maxTokens': 32} + + +def test_non_claude_without_config_has_no_inference_config() -> None: + kwargs = build_converse_request('amazon.nova-lite-v1:0', user_text_request()) + assert 'inferenceConfig' not in kwargs + + +# --- Request assembly ------------------------------------------------------- + + +def test_model_id_sent_verbatim_with_inference_profile_prefix() -> None: + kwargs = build_converse_request('us.amazon.nova-lite-v1:0', user_text_request()) + assert kwargs['modelId'] == 'us.amazon.nova-lite-v1:0' + + +def test_simple_text_round_trip_shape() -> None: + kwargs = build_converse_request('amazon.nova-lite-v1:0', user_text_request('hi')) + assert kwargs['messages'] == [{'role': 'user', 'content': [{'text': 'hi'}]}] + assert 'system' not in kwargs + assert 'toolConfig' not in kwargs + + +def test_system_message_becomes_top_level_system() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.SYSTEM, content=[Part(root=TextPart(text='be terse'))]), + Message(role=Role.USER, content=[Part(root=TextPart(text='hi'))]), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert kwargs['system'] == [{'text': 'be terse'}] + assert kwargs['messages'] == [{'role': 'user', 'content': [{'text': 'hi'}]}] + + +def test_empty_system_text_is_dropped() -> None: + # Bedrock rejects empty system text, so a blank rendered prompt is dropped + # rather than sent; regular message text has no such floor. + request = ModelRequest( + messages=[ + Message(role=Role.SYSTEM, content=[Part(root=TextPart(text=''))]), + Message(role=Role.USER, content=[Part(root=TextPart(text=''))]), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert 'system' not in kwargs + assert kwargs['messages'] == [{'role': 'user', 'content': [{'text': ''}]}] + + +def test_cache_point_in_system_and_messages() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.SYSTEM, content=[Part(root=TextPart(text='rules')), cache_point_part()]), + Message(role=Role.USER, content=[Part(root=TextPart(text='hi')), cache_point_part()]), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert kwargs['system'] == [{'text': 'rules'}, {'cachePoint': {'type': 'default'}}] + assert kwargs['messages'][0]['content'] == [{'text': 'hi'}, {'cachePoint': {'type': 'default'}}] + + +def test_multi_turn_roles() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.USER, content=[Part(root=TextPart(text='q'))]), + Message(role=Role.MODEL, content=[Part(root=TextPart(text='a'))]), + Message(role=Role.USER, content=[Part(root=TextPart(text='q2'))]), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert [m['role'] for m in kwargs['messages']] == ['user', 'assistant', 'user'] + + +def test_empty_messages_are_dropped() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.USER, content=[Part(root=TextPart(text='hi'))]), + Message(role=Role.MODEL, content=[]), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert len(kwargs['messages']) == 1 + + +def test_tool_role_message_becomes_user_tool_result() -> None: + request = ModelRequest( + messages=[ + Message( + role=Role.TOOL, + content=[ + Part.model_validate({'toolResponse': {'ref': 'call-1', 'name': 'weather', 'output': {'temp': 21}}}) + ], + ), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + message = kwargs['messages'][0] + assert message['role'] == 'user' + tool_result = message['content'][0]['toolResult'] + assert tool_result['toolUseId'] == 'call-1' + assert tool_result['status'] == 'success' + # Non-string outputs ride as a JSON string in a text content block. + assert tool_result['content'] == [{'text': '{"temp": 21}'}] + + +def test_string_tool_output_is_verbatim() -> None: + request = ModelRequest( + messages=[ + Message( + role=Role.TOOL, + content=[ + Part.model_validate({'toolResponse': {'ref': 'call-2', 'name': 'weather', 'output': 'sunny'}}) + ], + ), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + tool_result = kwargs['messages'][0]['content'][0]['toolResult'] + assert tool_result['content'] == [{'text': 'sunny'}] + assert tool_result['toolUseId'] == 'call-2' + + +@pytest.mark.parametrize( + 'part', + [ + {'toolRequest': {'name': 'weather', 'input': {}}}, + {'toolResponse': {'name': 'weather', 'output': 'sunny'}}, + ], + ids=['tool_request', 'tool_response'], +) +def test_tool_part_without_ref_errors(part: dict[str, object]) -> None: + # Bedrock's toolUseId has a one-character floor, so '' cannot be sent. + request = ModelRequest(messages=[Message(role=Role.TOOL, content=[Part.model_validate(part)])]) + with pytest.raises(GenkitError, match='requires a ref to send as toolUseId') as excinfo: + build_converse_request('amazon.nova-lite-v1:0', request) + assert excinfo.value.status == 'INVALID_ARGUMENT' + + +def test_tool_request_part_becomes_tool_use_block() -> None: + request = ModelRequest( + messages=[ + Message( + role=Role.MODEL, + content=[ + Part.model_validate({ + 'toolRequest': {'ref': 'call-9', 'name': 'weather', 'input': {'city': 'Lagos'}} + }) + ], + ), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert kwargs['messages'][0]['content'][0]['toolUse'] == { + 'toolUseId': 'call-9', + 'name': 'weather', + 'input': {'city': 'Lagos'}, + } + + +# --- Media ------------------------------------------------------------------ + + +def test_image_data_url_decodes_to_raw_bytes() -> None: + part = Part.model_validate({'media': {'url': f'data:image/png;base64,{PNG_B64}'}}) + request = ModelRequest(messages=[Message(role=Role.USER, content=[part])]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + image = kwargs['messages'][0]['content'][0]['image'] + assert image['format'] == 'png' + assert image['source']['bytes'] == PNG_BYTES + + +def test_explicit_content_type_beats_data_url_header() -> None: + part = Part.model_validate({'media': {'url': f'data:image/png;base64,{PNG_B64}', 'contentType': 'image/jpeg'}}) + request = ModelRequest(messages=[Message(role=Role.USER, content=[part])]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert kwargs['messages'][0]['content'][0]['image']['format'] == 'jpeg' + + +def test_jpg_alias_normalizes_to_jpeg() -> None: + part = Part.model_validate({'media': {'url': PNG_B64, 'contentType': 'image/jpg'}}) + request = ModelRequest(messages=[Message(role=Role.USER, content=[part])]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert kwargs['messages'][0]['content'][0]['image']['format'] == 'jpeg' + + +def test_document_mime_maps_to_document_block() -> None: + part = Part.model_validate({'media': {'url': PNG_B64, 'contentType': 'application/pdf'}}) + request = ModelRequest(messages=[Message(role=Role.USER, content=[part])]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + document = kwargs['messages'][0]['content'][0]['document'] + assert document['format'] == 'pdf' + assert document['name'] == 'document' + assert document['source']['bytes'] == PNG_BYTES + + +def test_html_is_document_not_image() -> None: + part = Part.model_validate({'media': {'url': PNG_B64, 'contentType': 'text/html'}}) + request = ModelRequest(messages=[Message(role=Role.USER, content=[part])]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert 'document' in kwargs['messages'][0]['content'][0] + + +@pytest.mark.parametrize( + 'mime,block_kind,expected_format', + [ + ('image/gif', 'image', 'gif'), + ('image/webp', 'image', 'webp'), + ('text/csv', 'document', 'csv'), + ('text/markdown', 'document', 'md'), + ('text/plain', 'document', 'txt'), + ('application/vnd.openxmlformats-officedocument.wordprocessingml.document', 'document', 'docx'), + ('application/vnd.openxmlformats-officedocument.spreadsheetml.sheet', 'document', 'xlsx'), + ], +) +def test_media_mime_format_matrix(mime, block_kind, expected_format) -> None: + part = Part.model_validate({'media': {'url': PNG_B64, 'contentType': mime}}) + request = ModelRequest(messages=[Message(role=Role.USER, content=[part])]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + block = kwargs['messages'][0]['content'][0] + assert block[block_kind]['format'] == expected_format + + +@pytest.mark.parametrize( + 'url,match', + [ + ('https://example.com/cat.png', 'remote URLs are not supported'), + ('data:image/png,rawdata', 'must be base64-encoded'), + (' ', 'empty data'), + ('!!!not-base64!!!', 'decode base64 media'), + ], +) +def test_media_payload_validation_errors(url, match) -> None: + part = Part.model_validate({'media': {'url': url, 'contentType': 'image/png'}}) + request = ModelRequest(messages=[Message(role=Role.USER, content=[part])]) + with pytest.raises(GenkitError, match=match): + build_converse_request('amazon.nova-lite-v1:0', request) + + +def test_unsupported_mime_type_errors() -> None: + part = Part.model_validate({'media': {'url': PNG_B64, 'contentType': 'video/mp4'}}) + request = ModelRequest(messages=[Message(role=Role.USER, content=[part])]) + with pytest.raises(GenkitError, match='unsupported media MIME type'): + build_converse_request('amazon.nova-lite-v1:0', request) + + +def test_media_without_content_type_errors() -> None: + part = Part.model_validate({'media': {'url': PNG_B64}}) + request = ModelRequest(messages=[Message(role=Role.USER, content=[part])]) + with pytest.raises(GenkitError, match='no content type'): + build_converse_request('amazon.nova-lite-v1:0', request) + + +# --- Tools and tool choice --------------------------------------------------- + + +WEATHER_TOOL = ToolDefinition( + name='weather', + description='Get the weather', + input_schema={'type': 'object', 'properties': {'city': {'type': 'string'}}}, +) + + +def test_tools_become_tool_specs() -> None: + request = user_text_request(tools=[WEATHER_TOOL]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + tool_spec = kwargs['toolConfig']['tools'][0]['toolSpec'] + assert tool_spec['name'] == 'weather' + assert tool_spec['description'] == 'Get the weather' + assert tool_spec['inputSchema']['json']['properties'] == {'city': {'type': 'string'}} + # No toolChoice unless requested; Bedrock defaults to auto. + assert 'toolChoice' not in kwargs['toolConfig'] + + +def test_tool_schema_defaults_injected() -> None: + tool = ToolDefinition(name='noop', description='') + schema = to_bedrock_tool(tool)['toolSpec']['inputSchema']['json'] + assert schema['type'] == 'object' + assert schema['properties'] == {} + assert schema['$schema'] == 'http://json-schema.org/draft-07/schema#' + + +def test_empty_tool_description_is_omitted() -> None: + # Bedrock rejects an empty description, and a tool declared without a + # docstring reaches the plugin with description ''. + tool_spec = to_bedrock_tool(ToolDefinition(name='noop', description=''))['toolSpec'] + assert 'description' not in tool_spec + assert tool_spec['name'] == 'noop' + + +def test_tool_without_name_errors() -> None: + with pytest.raises(GenkitError, match='tool name required'): + to_bedrock_tool(ToolDefinition(name='', description='')) + + +@pytest.mark.parametrize( + 'tool_choice,expected', + [ + ('auto', {'auto': {}}), + ('required', {'any': {}}), + ('any', {'any': {}}), + ('weather', {'tool': {'name': 'weather'}}), + ], +) +def test_tool_choice_mapping(tool_choice, expected) -> None: + request = user_text_request(tools=[WEATHER_TOOL], config=BedrockConfig(tool_choice=tool_choice)) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert kwargs['toolConfig']['toolChoice'] == expected + + +def test_tool_choice_none_omits_tool_config_entirely() -> None: + request = user_text_request(tools=[WEATHER_TOOL], config=BedrockConfig(tool_choice='none')) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert 'toolConfig' not in kwargs + + +def test_request_tool_choice_used_when_config_silent() -> None: + request = user_text_request(tools=[WEATHER_TOOL], tool_choice='required') + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert kwargs['toolConfig']['toolChoice'] == {'any': {}} + + +def test_unknown_named_tool_choice_errors() -> None: + request = user_text_request(tools=[WEATHER_TOOL], config=BedrockConfig(tool_choice='no-such-tool')) + with pytest.raises(GenkitError, match='does not match any declared tool'): + build_converse_request('amazon.nova-lite-v1:0', request) + + +def test_tool_choice_without_tools_is_ignored() -> None: + request = user_text_request(config=BedrockConfig(tool_choice='weather')) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert 'toolConfig' not in kwargs + + +def test_trailing_assistant_message_dropped_when_tools_present() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.USER, content=[Part(root=TextPart(text='q'))]), + Message(role=Role.MODEL, content=[Part(root=TextPart(text='thinking...'))]), + ], + tools=[WEATHER_TOOL], + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert [m['role'] for m in kwargs['messages']] == ['user'] + + +def test_trailing_assistant_message_kept_without_tools() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.USER, content=[Part(root=TextPart(text='q'))]), + Message(role=Role.MODEL, content=[Part(root=TextPart(text='a'))]), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert [m['role'] for m in kwargs['messages']] == ['user', 'assistant'] + + +def test_trailing_assistant_dropped_even_under_tool_choice_none() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.USER, content=[Part(root=TextPart(text='q'))]), + Message(role=Role.MODEL, content=[Part(root=TextPart(text='a'))]), + ], + tools=[WEATHER_TOOL], + config=BedrockConfig(tool_choice='none'), + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert [m['role'] for m in kwargs['messages']] == ['user'] + + +def test_additional_model_request_fields_forwarded_verbatim() -> None: + thinking = {'thinking': {'type': 'enabled', 'budget_tokens': 2048}} + request = user_text_request(config=BedrockConfig(additional_model_request_fields=thinking)) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert kwargs['additionalModelRequestFields'] == thinking + + +# --- Reasoning round-trip (request side) ------------------------------------- + + +def test_bedrock_reasoning_part_round_trips() -> None: + # The signature is a string on the Converse wire; it must replay verbatim. + part = Part( + root=ReasoningPart( + reasoning='step by step', + metadata={REASONING_SIGNATURE_METADATA_KEY: 'sig-abc123=='}, + ) + ) + request = ModelRequest( + messages=[ + Message(role=Role.MODEL, content=[part]), + Message(role=Role.USER, content=[Part(root=TextPart(text='go on'))]), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert kwargs['messages'][0]['content'] == [ + {'reasoningContent': {'reasoningText': {'text': 'step by step', 'signature': 'sig-abc123=='}}} + ] + + +def test_bytes_signature_form_is_tolerated() -> None: + part = Part( + root=ReasoningPart( + reasoning='step by step', + metadata={REASONING_SIGNATURE_METADATA_KEY: b'sig-abc123=='}, + ) + ) + request = ModelRequest(messages=[Message(role=Role.MODEL, content=[part])]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + block = kwargs['messages'][0]['content'][0]['reasoningContent']['reasoningText'] + assert block['signature'] == 'sig-abc123==' + + +def test_redacted_content_emitted_before_signed_text() -> None: + part = Part( + root=ReasoningPart( + reasoning='visible part', + metadata={ + REASONING_SIGNATURE_METADATA_KEY: 'sig', + REDACTED_CONTENT_METADATA_KEY: base64.b64encode(b'redacted-blob').decode(), + }, + ) + ) + request = ModelRequest(messages=[Message(role=Role.MODEL, content=[part])]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + blocks = kwargs['messages'][0]['content'] + assert blocks[0] == {'reasoningContent': {'redactedContent': b'redacted-blob'}} + assert blocks[1]['reasoningContent']['reasoningText']['text'] == 'visible part' + + +def test_redacted_only_reasoning_part_still_replays() -> None: + # Redacted-only parts have reasoning == '' and must not be dropped. + part = Part( + root=ReasoningPart( + reasoning='', + metadata={REDACTED_CONTENT_METADATA_KEY: base64.b64encode(b'blob').decode()}, + ) + ) + request = ModelRequest(messages=[Message(role=Role.MODEL, content=[part])]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + assert kwargs['messages'][0]['content'] == [{'reasoningContent': {'redactedContent': b'blob'}}] + + +def test_generic_reasoning_part_is_not_replayed() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.USER, content=[Part(root=TextPart(text='q'))]), + Message(role=Role.MODEL, content=[Part(root=ReasoningPart(reasoning='foreign thoughts'))]), + ] + ) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + # The reasoning-only assistant message converts to zero blocks and drops. + assert [m['role'] for m in kwargs['messages']] == ['user'] + + +# --- Response conversion ------------------------------------------------------ + + +def converse_response(**overrides) -> dict: + response = { + 'output': {'message': {'role': 'assistant', 'content': [{'text': 'hello'}]}}, + 'stopReason': 'end_turn', + 'usage': {'inputTokens': 10, 'outputTokens': 5, 'totalTokens': 15}, + } + response.update(overrides) + return response + + +def test_text_response_round_trip() -> None: + request = user_text_request() + response = to_model_response(converse_response(), request) + assert response.message is not None + assert response.message.role == Role.MODEL + assert response.message.content[0].root.text == 'hello' + assert response.finish_reason == FinishReason.STOP + assert response.usage is not None + assert response.usage.input_tokens == 10 + assert response.usage.output_tokens == 5 + assert response.usage.total_tokens == 15 + assert response.request is request + + +def test_tool_use_block_becomes_tool_request_part() -> None: + blocks = [{'toolUse': {'toolUseId': 'call-1', 'name': 'weather', 'input': {'city': 'Lagos'}}}] + parts = content_blocks_to_parts(blocks) + tool_request = parts[0].root.tool_request + assert tool_request is not None + assert tool_request.ref == 'call-1' + assert tool_request.name == 'weather' + assert tool_request.input == {'city': 'Lagos'} + + +def test_tool_use_with_missing_input_gets_empty_object() -> None: + parts = content_blocks_to_parts([{'toolUse': {'toolUseId': 'x', 'name': 'noop'}}]) + tool_request = parts[0].root.tool_request + assert tool_request is not None + assert tool_request.input == {} + + +def test_tool_input_coerced_toward_schema() -> None: + tool = ToolDefinition( + name='calc', + description='', + input_schema={ + 'type': 'object', + 'properties': { + 'count': {'type': 'integer'}, + 'ratio': {'type': 'number'}, + 'enabled': {'type': 'boolean'}, + 'note': {'type': 'string'}, + }, + }, + ) + blocks = [ + { + 'toolUse': { + 'toolUseId': 'c1', + 'name': 'calc', + 'input': {'count': '7', 'ratio': '0.5', 'enabled': 'true', 'note': 'hi', 'extra': '1'}, + } + } + ] + parts = content_blocks_to_parts(blocks, [tool]) + tool_request = parts[0].root.tool_request + assert tool_request is not None + assert tool_request.input == {'count': 7, 'ratio': 0.5, 'enabled': True, 'note': 'hi', 'extra': '1'} + + +@pytest.mark.parametrize('value,expected', [(7, '7'), (7.5, '7.5'), (True, True)], ids=['int', 'float', 'bool']) +def test_number_coerced_to_string_schema(value: object, expected: object) -> None: + # Go coerces a wire number to its string form; without it, tool dispatch + # fails pydantic validation. Booleans are left alone, as in Go. + tool = ToolDefinition( + name='calc', + description='', + input_schema={'type': 'object', 'properties': {'note': {'type': 'string'}}}, + ) + blocks = [{'toolUse': {'toolUseId': 'c1', 'name': 'calc', 'input': {'note': value}}}] + parts = content_blocks_to_parts(blocks, [tool]) + tool_request = parts[0].root.tool_request + assert tool_request is not None + assert tool_request.input == {'note': expected} + + +def test_tool_input_float_truncates_for_integer_schema() -> None: + tool = ToolDefinition( + name='calc', description='', input_schema={'type': 'object', 'properties': {'n': {'type': 'integer'}}} + ) + parts = content_blocks_to_parts([{'toolUse': {'toolUseId': 'c', 'name': 'calc', 'input': {'n': 7.9}}}], [tool]) + tool_request = parts[0].root.tool_request + assert tool_request is not None + assert tool_request.input == {'n': 7} + + +def test_reasoning_text_block_becomes_reasoning_part_with_both_keys() -> None: + blocks = [{'reasoningContent': {'reasoningText': {'text': 'because', 'signature': 'sig'}}}] + parts = content_blocks_to_parts(blocks) + root = parts[0].root + assert root.reasoning == 'because' + assert root.metadata is not None + assert root.metadata['signature'] == 'sig' + assert root.metadata[REASONING_SIGNATURE_METADATA_KEY] == 'sig' + + +def test_reasoning_text_bare_string_shape_is_handled() -> None: + parts = content_blocks_to_parts([{'reasoningContent': {'reasoningText': 'raw thought'}}]) + assert parts[0].root.reasoning == 'raw thought' + + +def test_redacted_content_block_becomes_reasoning_part() -> None: + parts = content_blocks_to_parts([{'reasoningContent': {'redactedContent': b'blob'}}]) + root = parts[0].root + assert root.reasoning == '' + assert root.metadata is not None + # Stored as a base64 string so the part survives JSON serialization. + assert root.metadata[REDACTED_CONTENT_METADATA_KEY] == base64.b64encode(b'blob').decode() + + +def test_reasoning_survives_response_to_request_round_trip() -> None: + # The full circle: wire response blocks -> Genkit parts -> wire request + # blocks, byte-identical, including non-UTF8 redacted content. + redacted_blob = b'\x89\xff\x00binary' + response_blocks = [ + {'reasoningContent': {'reasoningText': {'text': 'because', 'signature': 'sig-abc123=='}}}, + {'reasoningContent': {'redactedContent': redacted_blob}}, + ] + parts = content_blocks_to_parts(response_blocks) + request = ModelRequest(messages=[Message(role=Role.MODEL, content=parts)]) + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + replayed = kwargs['messages'][0]['content'] + assert replayed[0] == {'reasoningContent': {'reasoningText': {'text': 'because', 'signature': 'sig-abc123=='}}} + assert replayed[1] == {'reasoningContent': {'redactedContent': redacted_blob}} + + +def test_reasoning_parts_serialize_to_json() -> None: + # Tracing serializes action output with model_dump_json; raw bytes in + # metadata would crash it for non-UTF8 redacted blobs. + parts = content_blocks_to_parts([ + {'reasoningContent': {'reasoningText': {'text': 'because', 'signature': 'sig'}}}, + {'reasoningContent': {'redactedContent': b'\x89\xff\x00binary'}}, + ]) + message = Message(role=Role.MODEL, content=parts) + assert message.model_dump_json() + + +def test_empty_reasoning_block_is_skipped() -> None: + assert content_blocks_to_parts([{'reasoningContent': {'reasoningText': {}}}]) == [] + + +def test_unknown_reasoning_variant_errors() -> None: + with pytest.raises(GenkitError, match='unhandled reasoning content variant'): + content_blocks_to_parts([{'reasoningContent': {'futureThing': 1}}]) + + +def test_unknown_response_block_errors() -> None: + with pytest.raises(GenkitError, match='unhandled response content variant'): + content_blocks_to_parts([{'video': {'format': 'mp4'}}]) + + +def test_empty_response_content_yields_placeholder_text_part() -> None: + response = converse_response( + output={'message': {'role': 'assistant', 'content': []}}, + stopReason='guardrail_intervened', + ) + model_response = to_model_response(response, user_text_request()) + assert model_response.message is not None + assert model_response.message.content[0].root.text == '' + assert model_response.finish_reason == FinishReason.BLOCKED + + +def test_missing_output_tolerated() -> None: + response = converse_response(output={}) + model_response = to_model_response(response, user_text_request()) + assert model_response.message is not None + assert model_response.message.content[0].root.text == '' + + +def test_usage_maps_cache_read_tokens_only() -> None: + usage = usage_from_response({ + 'inputTokens': 4, + 'outputTokens': 6, + 'totalTokens': 110, + 'cacheReadInputTokens': 100, + 'cacheWriteInputTokens': 50, + }) + assert usage is not None + assert usage.input_tokens == 4 + assert usage.output_tokens == 6 + # Totals are trusted verbatim from AWS, never recomputed. + assert usage.total_tokens == 110 + assert usage.cached_content_tokens == 100 + + +def test_usage_none_when_absent() -> None: + assert usage_from_response(None) is None diff --git a/py/packages/genkit-amazon-bedrock/tests/live_test.py b/py/packages/genkit-amazon-bedrock/tests/live_test.py new file mode 100644 index 0000000000..6608e79046 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/tests/live_test.py @@ -0,0 +1,150 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Live Bedrock tests, mirroring the Go plugin's live matrix. + +Opt-in: set ``BEDROCK_LIVE_TESTS=1`` plus working AWS credentials and a +region (``AWS_REGION`` or ``~/.aws/config``). These call real models and +incur cost. The models used need only default model access. +""" + +import os + +import pytest +from genkit_amazon_bedrock.config import BedrockConfig +from genkit_amazon_bedrock.converters import ( + REASONING_SIGNATURE_METADATA_KEY, +) +from genkit_amazon_bedrock.models import BedrockModel +from genkit_amazon_bedrock.transport import BedrockTransport + +from genkit import FinishReason, Message, ModelRequest, Part, Role, TextPart, ToolDefinition + +pytestmark = [ + pytest.mark.asyncio, + pytest.mark.skipif( + not os.environ.get('BEDROCK_LIVE_TESTS'), + reason='BEDROCK_LIVE_TESTS not set; live Bedrock tests are opt-in', + ), +] + +NOVA = 'us.amazon.nova-lite-v1:0' +DEEPSEEK = 'us.deepseek.r1-v1:0' + + +def make_model(model_id: str) -> BedrockModel: + transport = BedrockTransport( + region=os.environ.get('AWS_REGION'), + max_retries=3, + read_timeout=300.0, + connect_timeout=60.0, + max_pool_connections=10, + ) + return BedrockModel(model_id=model_id, transport=transport) + + +def text_request(text: str, **kwargs) -> ModelRequest: + return ModelRequest( + messages=[Message(role=Role.USER, content=[Part(root=TextPart(text=text))])], + **kwargs, + ) + + +def undocumented_weather_tool() -> ToolDefinition: + # No description on purpose: Bedrock rejects an empty one, and a Genkit + # tool declared without a docstring arrives that way. + return ToolDefinition( + name='get_weather', + description='', + input_schema={ + 'type': 'object', + 'properties': {'city': {'type': 'string'}}, + 'required': ['city'], + }, + ) + + +async def test_nova_sync() -> None: + response = await make_model(NOVA).generate(text_request("Reply with the single word 'pong'.")) + assert response.finish_reason == FinishReason.STOP + assert response.message is not None + assert response.message.content[0].root.text + assert response.usage is not None + assert response.usage.input_tokens is not None and response.usage.input_tokens > 0 + + +async def test_undocumented_tool_round_trip() -> None: + weather = undocumented_weather_tool() + request = ModelRequest( + messages=[Message(role=Role.USER, content=[Part(root=TextPart(text='What is the weather in Lagos?'))])], + tools=[weather], + config=BedrockConfig(tool_choice='get_weather'), + ) + response = await make_model(NOVA).generate(request) + + assert response.message is not None + tool_requests = [part.root.tool_request for part in response.message.content if part.root.tool_request is not None] + assert tool_requests, 'expected the model to call the tool' + assert tool_requests[0].name == 'get_weather' + assert tool_requests[0].ref + + # Feeding the result back must also be accepted. + follow_up = ModelRequest( + messages=[ + *request.messages, + response.message, + Message( + role=Role.TOOL, + content=[ + Part.model_validate({ + 'toolResponse': { + 'ref': tool_requests[0].ref, + 'name': 'get_weather', + 'output': {'celsius': 31}, + } + }) + ], + ), + ], + tools=[weather], + ) + assert (await make_model(NOVA).generate(follow_up)).message is not None + + +async def test_deepseek_reasoning_sync_and_round_trip() -> None: + model = make_model(DEEPSEEK) + config = BedrockConfig(max_tokens=2048) + request = text_request('What is 17 * 23? Think it through.', config=config) + response = await model.generate(request) + + assert response.message is not None + reasoning_parts = [ + part.root for part in response.message.content if getattr(part.root, 'reasoning', None) is not None + ] + assert reasoning_parts, 'expected a reasoning part from a reasoning model' + # Signatures are Anthropic-specific, so replay stays gated off here. + metadata = reasoning_parts[0].metadata + assert metadata is None or not metadata.get(REASONING_SIGNATURE_METADATA_KEY) + + follow_up = ModelRequest( + messages=[ + *request.messages, + response.message, + Message(role=Role.USER, content=[Part(root=TextPart(text='Now add 100 to that.'))]), + ], + config=config, + ) + assert (await model.generate(follow_up)).finish_reason == FinishReason.STOP diff --git a/py/packages/genkit-amazon-bedrock/tests/models_test.py b/py/packages/genkit-amazon-bedrock/tests/models_test.py new file mode 100644 index 0000000000..63610d5b6a --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/tests/models_test.py @@ -0,0 +1,157 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Tests for the BedrockModel generate orchestration (no AWS involved).""" + +from typing import Any + +import pytest +from botocore.exceptions import ( + BotoCoreError, + ClientError, + EndpointConnectionError, + NoCredentialsError, + ParamValidationError, + ReadTimeoutError, +) +from genkit_amazon_bedrock.models import BedrockModel + +from genkit import FinishReason, Message, ModelRequest, Part, Role, TextPart +from genkit.plugin_api import ActionRunContext, GenkitError + + +class FakeTransport: + """Stands in for BedrockTransport; records the Converse kwargs.""" + + def __init__(self, response: dict[str, Any] | None = None, error: Exception | None = None) -> None: + self.response = response + self.error = error + self.kwargs: dict[str, Any] | None = None + + async def converse(self, **kwargs: Any) -> dict[str, Any]: + self.kwargs = kwargs + if self.error is not None: + raise self.error + return self.response or {} + + +def text_request(text: str = 'hello') -> ModelRequest: + return ModelRequest(messages=[Message(role=Role.USER, content=[Part(root=TextPart(text=text))])]) + + +def text_response(text: str = 'world') -> dict[str, Any]: + return { + 'output': {'message': {'role': 'assistant', 'content': [{'text': text}]}}, + 'stopReason': 'end_turn', + 'usage': {'inputTokens': 1, 'outputTokens': 2, 'totalTokens': 3}, + } + + +@pytest.mark.asyncio +async def test_generate_round_trip() -> None: + transport = FakeTransport(response=text_response('hi there')) + model = BedrockModel(model_id='amazon.nova-lite-v1:0', transport=transport) + + response = await model.generate(text_request()) + + assert transport.kwargs is not None + assert transport.kwargs['modelId'] == 'amazon.nova-lite-v1:0' + assert transport.kwargs['messages'] == [{'role': 'user', 'content': [{'text': 'hello'}]}] + assert response.message is not None + assert response.message.content[0].root.text == 'hi there' + assert response.finish_reason == FinishReason.STOP + assert response.usage is not None + assert response.usage.total_tokens == 3 + + +@pytest.mark.asyncio +async def test_streaming_context_receives_single_bridge_chunk() -> None: + transport = FakeTransport(response=text_response('streamed')) + model = BedrockModel(model_id='amazon.nova-lite-v1:0', transport=transport) + chunks = [] + ctx = ActionRunContext(streaming_callback=chunks.append) + + response = await model.generate(text_request(), ctx) + + assert len(chunks) == 1 + assert chunks[0].content[0].root.text == 'streamed' + assert response.message is not None + assert response.message.content[0].root.text == 'streamed' + + +@pytest.mark.asyncio +async def test_non_streaming_context_sends_no_chunks(monkeypatch: pytest.MonkeyPatch) -> None: + transport = FakeTransport(response=text_response()) + model = BedrockModel(model_id='amazon.nova-lite-v1:0', transport=transport) + ctx = ActionRunContext() + # Recorded directly: a context with no callback reports is_streaming False, + # so only spying on send_chunk proves the guard is what suppresses chunks. + sent: list[Any] = [] + monkeypatch.setattr(ctx, 'send_chunk', sent.append) + + await model.generate(text_request(), ctx) + + assert sent == [] + + +@pytest.mark.parametrize( + 'error,expected_status', + [ + (ParamValidationError(report='bad param'), 'INVALID_ARGUMENT'), + (NoCredentialsError(), 'UNAUTHENTICATED'), + (ReadTimeoutError(endpoint_url='https://bedrock-runtime.us-east-1.amazonaws.com'), 'DEADLINE_EXCEEDED'), + (EndpointConnectionError(endpoint_url='https://bedrock-runtime.us-east-1.amazonaws.com'), 'UNAVAILABLE'), + (BotoCoreError(), 'UNKNOWN'), + ], + ids=['param_validation', 'no_credentials', 'read_timeout', 'endpoint_connection', 'unlisted'], +) +@pytest.mark.asyncio +async def test_botocore_errors_map_to_genkit_statuses(error: BotoCoreError, expected_status: str) -> None: + transport = FakeTransport(error=error) + model = BedrockModel(model_id='amazon.nova-lite-v1:0', transport=transport) + + with pytest.raises(GenkitError) as excinfo: + await model.generate(text_request()) + + assert excinfo.value.status == expected_status + assert 'bedrock converse failed' in excinfo.value.original_message + assert excinfo.value.__cause__ is error + + +@pytest.mark.parametrize( + 'code,expected_status', + [ + ('ThrottlingException', 'RESOURCE_EXHAUSTED'), + ('ValidationException', 'INVALID_ARGUMENT'), + ('AccessDeniedException', 'PERMISSION_DENIED'), + ('ResourceNotFoundException', 'NOT_FOUND'), + ('ModelTimeoutException', 'DEADLINE_EXCEEDED'), + ('ServiceUnavailableException', 'UNAVAILABLE'), + ('SomeFutureException', 'UNKNOWN'), + ], +) +@pytest.mark.asyncio +async def test_client_errors_map_to_genkit_statuses(code, expected_status) -> None: + error = ClientError({'Error': {'Code': code, 'Message': 'nope'}}, 'Converse') + transport = FakeTransport(error=error) + model = BedrockModel(model_id='amazon.nova-lite-v1:0', transport=transport) + + with pytest.raises(GenkitError) as excinfo: + await model.generate(text_request()) + + assert excinfo.value.status == expected_status + assert 'bedrock converse failed' in excinfo.value.original_message + assert excinfo.value.__cause__ is error diff --git a/py/packages/genkit-amazon-bedrock/tests/plugin_test.py b/py/packages/genkit-amazon-bedrock/tests/plugin_test.py index bb362dd382..0b57179041 100644 --- a/py/packages/genkit-amazon-bedrock/tests/plugin_test.py +++ b/py/packages/genkit-amazon-bedrock/tests/plugin_test.py @@ -14,11 +14,17 @@ # # SPDX-License-Identifier: Apache-2.0 -"""Tests for the Amazon Bedrock plugin scaffold.""" +"""Tests for the Amazon Bedrock plugin wiring.""" +from types import SimpleNamespace +from typing import Any, cast + +import boto3.session import pytest from genkit_amazon_bedrock import Bedrock, BedrockConfig, ModelDefinition, bedrock_name +from genkit.plugin_api import ActionKind, GenkitError + def test_plugin_name() -> None: plugin = Bedrock() @@ -33,9 +39,12 @@ def test_bedrock_name_prefixes_model_id() -> None: def test_constructor_defaults() -> None: plugin = Bedrock() - assert plugin.region == 'us-east-1' + # No default region: resolution falls to the SDK chain and fails loudly. + assert plugin.region is None assert plugin.max_retries == 3 - assert plugin.request_timeout == 30.0 + assert plugin.read_timeout == 3600.0 + assert plugin.connect_timeout == 60.0 + assert plugin.max_pool_connections == 50 assert plugin.models == [] assert plugin.embedders == [] @@ -48,23 +57,79 @@ def test_model_definition_defaults_to_chat() -> None: def test_config_accepts_camel_case_and_extra_fields() -> None: config = BedrockConfig.model_validate({ 'toolChoice': 'auto', + 'maxTokens': 128, 'additionalModelRequestFields': {'thinking': {'type': 'enabled'}}, 'someFutureKnob': True, }) assert config.tool_choice == 'auto' + assert config.max_tokens == 128 assert config.additional_model_request_fields == {'thinking': {'type': 'enabled'}} @pytest.mark.asyncio async def test_init_returns_no_eager_actions() -> None: - plugin = Bedrock() + plugin = Bedrock(region='us-east-1') assert await plugin.init() == [] @pytest.mark.asyncio -async def test_resolve_returns_none_until_actions_land() -> None: - from genkit.plugin_api import ActionKind +async def test_init_fails_loudly_without_region() -> None: + # A stub session isolates the test from ambient AWS env/config. + stub_session = cast(boto3.session.Session, SimpleNamespace(region_name=None)) + plugin = Bedrock(session=stub_session) + with pytest.raises(GenkitError, match='no AWS region resolved') as excinfo: + await plugin.init() + assert excinfo.value.status == 'FAILED_PRECONDITION' - plugin = Bedrock() - assert await plugin.resolve(ActionKind.MODEL, bedrock_name('amazon.nova-lite-v1:0')) is None + +@pytest.mark.asyncio +async def test_resolve_returns_model_action_for_any_model_id() -> None: + plugin = Bedrock(region='us-east-1') + action = await plugin.resolve(ActionKind.MODEL, bedrock_name('amazon.nova-lite-v1:0')) + assert action is not None + assert action.name == 'bedrock/amazon.nova-lite-v1:0' + assert action.metadata is not None + model_metadata = cast(dict[str, Any], action.metadata['model']) + assert model_metadata['supports']['tools'] is True + assert model_metadata['customOptions']['properties'].get('toolChoice') is not None + + +@pytest.mark.asyncio +async def test_resolve_ignores_non_model_kinds() -> None: + plugin = Bedrock(region='us-east-1') assert await plugin.resolve(ActionKind.FLOW, 'bedrock/whatever') is None + + +@pytest.mark.asyncio +async def test_resolve_skips_non_chat_model_definitions() -> None: + plugin = Bedrock( + region='us-east-1', + models=[ModelDefinition(name='amazon.titan-image-generator-v1', type='image')], + ) + assert await plugin.resolve(ActionKind.MODEL, bedrock_name('amazon.titan-image-generator-v1')) is None + + +@pytest.mark.asyncio +async def test_text_type_routes_like_chat() -> None: + plugin = Bedrock( + region='us-east-1', + models=[ModelDefinition(name='meta.llama3-8b-instruct-v1:0', type='text')], + ) + action = await plugin.resolve(ActionKind.MODEL, bedrock_name('meta.llama3-8b-instruct-v1:0')) + assert action is not None + actions = await plugin.list_actions() + assert [a.name for a in actions] == ['bedrock/meta.llama3-8b-instruct-v1:0'] + + +@pytest.mark.asyncio +async def test_list_actions_lists_configured_chat_models() -> None: + plugin = Bedrock( + region='us-east-1', + models=[ + ModelDefinition(name='amazon.nova-lite-v1:0'), + ModelDefinition(name='amazon.titan-image-generator-v1', type='image'), + ], + ) + actions = await plugin.list_actions() + assert [a.name for a in actions] == ['bedrock/amazon.nova-lite-v1:0'] + assert actions[0].action_type == ActionKind.MODEL diff --git a/py/packages/genkit-amazon-bedrock/tests/request_validation_test.py b/py/packages/genkit-amazon-bedrock/tests/request_validation_test.py new file mode 100644 index 0000000000..84636834e7 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/tests/request_validation_test.py @@ -0,0 +1,170 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Validates built requests against the bedrock-runtime service model. + +Several Converse fields are ``NonEmptyString`` (``min: 1``) and botocore +enforces that client-side, so an empty value fails the call before it reaches +AWS. These tests run the real validator over the request builder's output, which +catches that whole class of defect without credentials or network access. +""" + +import base64 + +import botocore.session +import pytest +from botocore.validate import ParamValidator +from genkit_amazon_bedrock.config import BedrockConfig +from genkit_amazon_bedrock.converters import build_converse_request, cache_point_part + +from genkit import ( + Message, + ModelRequest, + Part, + ReasoningPart, + Role, + TextPart, + ToolDefinition, +) + +CONVERSE_INPUT_SHAPE = ( + botocore.session.get_session().get_service_model('bedrock-runtime').operation_model('Converse').input_shape +) + +PNG_B64 = base64.b64encode(b'\x89PNG\r\n\x1a\nfakeimagedata').decode() + + +def assert_valid_converse_request(request: ModelRequest) -> dict: + """Builds the request and asserts botocore accepts every parameter.""" + kwargs = build_converse_request('amazon.nova-lite-v1:0', request) + report = ParamValidator().validate(kwargs, CONVERSE_INPUT_SHAPE) + assert not report.has_errors(), report.generate_report() + return kwargs + + +def test_undocumented_tool_passes_validation() -> None: + # A tool declared without a docstring reaches the plugin with description + # '', which the NonEmptyString floor on toolSpec.description rejects. + request = ModelRequest( + messages=[Message(role=Role.USER, content=[Part(root=TextPart(text='hi'))])], + tools=[ToolDefinition(name='noop', description='', input_schema={'type': 'object', 'properties': {}})], + ) + kwargs = assert_valid_converse_request(request) + assert 'description' not in kwargs['toolConfig']['tools'][0]['toolSpec'] + + +def test_blank_system_prompt_passes_validation() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.SYSTEM, content=[Part(root=TextPart(text=''))]), + Message(role=Role.USER, content=[Part(root=TextPart(text='hi'))]), + ] + ) + assert_valid_converse_request(request) + + +def test_empty_assistant_text_passes_validation() -> None: + # to_model_response emits a '' text part for guardrail-blocked responses; + # replaying it must stay valid (ContentBlock.text has no floor). + request = ModelRequest( + messages=[ + Message(role=Role.USER, content=[Part(root=TextPart(text='hi'))]), + Message(role=Role.MODEL, content=[Part(root=TextPart(text=''))]), + Message(role=Role.USER, content=[Part(root=TextPart(text='again'))]), + ] + ) + assert_valid_converse_request(request) + + +def test_tool_round_trip_passes_validation() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.USER, content=[Part(root=TextPart(text='weather?'))]), + Message( + role=Role.MODEL, + content=[ + Part.model_validate({ + 'toolRequest': {'ref': 'call-1', 'name': 'weather', 'input': {'city': 'Lagos'}} + }) + ], + ), + Message( + role=Role.TOOL, + content=[ + Part.model_validate({'toolResponse': {'ref': 'call-1', 'name': 'weather', 'output': {'c': 21}}}) + ], + ), + ], + tools=[ + ToolDefinition( + name='weather', + description='Get the weather', + input_schema={'type': 'object', 'properties': {'city': {'type': 'string'}}}, + ) + ], + ) + assert_valid_converse_request(request) + + +def test_media_and_cache_points_pass_validation() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.SYSTEM, content=[Part(root=TextPart(text='rules')), cache_point_part()]), + Message( + role=Role.USER, + content=[ + Part.model_validate({'media': {'url': f'data:image/png;base64,{PNG_B64}'}}), + Part.model_validate({'media': {'url': f'data:application/pdf;base64,{PNG_B64}'}}), + Part(root=TextPart(text='what is this?')), + cache_point_part(), + ], + ), + ] + ) + assert_valid_converse_request(request) + + +def test_reasoning_replay_passes_validation() -> None: + request = ModelRequest( + messages=[ + Message(role=Role.USER, content=[Part(root=TextPart(text='think'))]), + Message( + role=Role.MODEL, + content=[ + Part( + root=ReasoningPart( + reasoning='step one', + metadata={'bedrockReasoningSignature': 'sig-abc', 'signature': 'sig-abc'}, + ) + ), + Part(root=TextPart(text='done')), + ], + ), + Message(role=Role.USER, content=[Part(root=TextPart(text='continue'))]), + ] + ) + assert_valid_converse_request(request) + + +@pytest.mark.parametrize('model_id', ['anthropic.claude-sonnet-4-5-20250929-v1:0', 'amazon.nova-lite-v1:0']) +def test_inference_config_passes_validation(model_id: str) -> None: + request = ModelRequest( + messages=[Message(role=Role.USER, content=[Part(root=TextPart(text='hi'))])], + config=BedrockConfig(temperature=0.0, top_p=0.9, max_tokens=256, stop_sequences=['STOP']), + ) + kwargs = build_converse_request(model_id, request) + report = ParamValidator().validate(kwargs, CONVERSE_INPUT_SHAPE) + assert not report.has_errors(), report.generate_report() diff --git a/py/packages/genkit-amazon-bedrock/tests/transport_test.py b/py/packages/genkit-amazon-bedrock/tests/transport_test.py new file mode 100644 index 0000000000..23d2206638 --- /dev/null +++ b/py/packages/genkit-amazon-bedrock/tests/transport_test.py @@ -0,0 +1,97 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Region resolution tests. Client construction needs no credentials.""" + +import boto3.session +import pytest +from genkit_amazon_bedrock.transport import BedrockTransport + +from genkit.plugin_api import GenkitError + +REGION_ENV_VARS = ('AWS_REGION', 'AWS_DEFAULT_REGION', 'AWS_PROFILE', 'AWS_CONFIG_FILE') + + +@pytest.fixture(autouse=True) +def _isolate_aws_env(monkeypatch: pytest.MonkeyPatch, tmp_path) -> None: + """Drops ambient AWS config so the tests see only what they set.""" + for name in REGION_ENV_VARS: + monkeypatch.delenv(name, raising=False) + # Points botocore at an empty config file rather than the developer's own. + empty_config = tmp_path / 'aws-config' + empty_config.write_text('') + monkeypatch.setenv('AWS_CONFIG_FILE', str(empty_config)) + + +def make_transport(**kwargs) -> BedrockTransport: + defaults = { + 'max_retries': 3, + 'read_timeout': 3600.0, + 'connect_timeout': 60.0, + 'max_pool_connections': 50, + } + return BedrockTransport(**{**defaults, **kwargs}) + + +def test_explicit_region_wins() -> None: + client = make_transport(region='eu-west-1').client() + assert client.meta.region_name == 'eu-west-1' + + +def test_aws_region_env_var_is_honored(monkeypatch: pytest.MonkeyPatch) -> None: + # botocore below 1.41 reads only AWS_DEFAULT_REGION, so the plugin resolves + # AWS_REGION itself; without that this raises FAILED_PRECONDITION. + monkeypatch.setenv('AWS_REGION', 'us-east-2') + assert make_transport().client().meta.region_name == 'us-east-2' + + +def test_aws_default_region_env_var_is_honored(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setenv('AWS_DEFAULT_REGION', 'ap-south-1') + assert make_transport().client().meta.region_name == 'ap-south-1' + + +def test_aws_region_beats_aws_default_region(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setenv('AWS_REGION', 'us-east-2') + monkeypatch.setenv('AWS_DEFAULT_REGION', 'ap-south-1') + assert make_transport().client().meta.region_name == 'us-east-2' + + +def test_supplied_session_region_beats_env(monkeypatch: pytest.MonkeyPatch) -> None: + # A caller who configured a session chose that region deliberately. + monkeypatch.setenv('AWS_REGION', 'us-east-2') + session = boto3.session.Session(region_name='sa-east-1') + assert make_transport(session=session).client().meta.region_name == 'sa-east-1' + + +def test_missing_region_fails_loudly() -> None: + with pytest.raises(GenkitError, match='no AWS region resolved') as excinfo: + make_transport().client() + assert excinfo.value.status == 'FAILED_PRECONDITION' + + +def test_client_is_built_once() -> None: + transport = make_transport(region='eu-west-1') + assert transport.client() is transport.client() + + +def test_botocore_config_carries_the_timeouts() -> None: + config = make_transport(region='eu-west-1', read_timeout=1800.0).client().meta.config + assert config.read_timeout == 1800.0 + assert config.connect_timeout == 60.0 + assert config.max_pool_connections == 50 + # botocore normalizes max_attempts to total attempts: 3 retries plus the first call. + assert config.retries['total_max_attempts'] == 4 + assert config.retries['mode'] == 'standard' diff --git a/py/uv.lock b/py/uv.lock index 32f904ddd0..c891c4b423 100644 --- a/py/uv.lock +++ b/py/uv.lock @@ -1679,7 +1679,7 @@ dependencies = [ [package.metadata] requires-dist = [ - { name = "boto3", specifier = ">=1.36" }, + { name = "boto3", specifier = ">=1.37.24" }, { name = "genkit", editable = "packages/genkit" }, ] From 67a30ad72abdbda7dac33bc9d821fb69acfdf22c Mon Sep 17 00:00:00 2001 From: Hilary Date: Thu, 30 Jul 2026 11:01:10 +0100 Subject: [PATCH 6/8] fix(py/plugins/amazon-bedrock): match core version and narrow test optionals Both land from earlier slices: the scaffold pins 0.1.0 where check_consistency.py wants the core version, and model_info_test.py trips ty and pyright on the optional Supports field. --- py/packages/genkit-amazon-bedrock/pyproject.toml | 2 +- py/packages/genkit-amazon-bedrock/tests/model_info_test.py | 6 ++++++ 2 files changed, 7 insertions(+), 1 deletion(-) diff --git a/py/packages/genkit-amazon-bedrock/pyproject.toml b/py/packages/genkit-amazon-bedrock/pyproject.toml index ce62138a6b..79532c79eb 100644 --- a/py/packages/genkit-amazon-bedrock/pyproject.toml +++ b/py/packages/genkit-amazon-bedrock/pyproject.toml @@ -54,7 +54,7 @@ license = "Apache-2.0" name = "genkit-amazon-bedrock" readme = "README.md" requires-python = ">=3.10" -version = "0.1.0" +version = "0.8.1" [project.urls] "Bug Tracker" = "https://github.com/genkit-ai/genkit/issues" diff --git a/py/packages/genkit-amazon-bedrock/tests/model_info_test.py b/py/packages/genkit-amazon-bedrock/tests/model_info_test.py index b309c4f9f0..c263eb0153 100644 --- a/py/packages/genkit-amazon-bedrock/tests/model_info_test.py +++ b/py/packages/genkit-amazon-bedrock/tests/model_info_test.py @@ -63,6 +63,7 @@ def test_application_inference_profile_arn_falls_back_to_unstable() -> None: arn = 'arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/abc123opaque' info = get_model_info(arn) assert info.stage == Stage.UNSTABLE + assert info.supports is not None assert info.supports.tools is True @@ -75,6 +76,7 @@ def test_us_gov_wins_over_us() -> None: def test_known_model_is_stable_with_registry_capabilities() -> None: info = get_model_info('anthropic.claude-3-5-haiku-20241022-v1:0') assert info.stage == Stage.STABLE + assert info.supports is not None assert info.supports.multiturn is True assert info.supports.system_role is True assert info.supports.tools is True @@ -85,6 +87,7 @@ def test_known_model_is_stable_with_registry_capabilities() -> None: def test_inference_profile_id_resolves_registry_entry() -> None: info = get_model_info('eu.amazon.nova-micro-v1:0') assert info.stage == Stage.STABLE + assert info.supports is not None assert info.supports.media is False assert info.label == 'eu.amazon.nova-micro-v1:0' @@ -92,6 +95,7 @@ def test_inference_profile_id_resolves_registry_entry() -> None: def test_unknown_model_defaults_to_unstable_converse_capabilities() -> None: info = get_model_info('vendor.brand-new-model-v1:0') assert info.stage == Stage.UNSTABLE + assert info.supports is not None assert info.supports.multiturn is True assert info.supports.tools is True assert info.supports.media is True @@ -100,6 +104,7 @@ def test_unknown_model_defaults_to_unstable_converse_capabilities() -> None: def test_image_model_supports_media_output_only() -> None: info = get_model_info('amazon.titan-image-generator-v1', model_type='image') assert info.stage == Stage.STABLE + assert info.supports is not None assert info.supports.media is True assert info.supports.multiturn is False assert info.supports.tools is False @@ -109,6 +114,7 @@ def test_image_model_supports_media_output_only() -> None: def test_embedding_model_supports_nothing() -> None: info = get_model_info('amazon.titan-embed-text-v2:0', model_type='embedding') assert info.stage == Stage.STABLE + assert info.supports is not None assert info.supports.media is False assert info.supports.multiturn is False assert info.supports.tools is False From b33cdc27a4589b7c7b9a1effa086d4737bb39fcc Mon Sep 17 00:00:00 2001 From: Hilary Date: Thu, 30 Jul 2026 15:57:05 +0100 Subject: [PATCH 7/8] feat(py/plugins/amazon-bedrock): add Dev UI sample app lock refreshed with uv 0.12.0; drops exclude-newer options released uv cannot reproduce --- py/pyproject.toml | 1 + py/samples/amazon-bedrock-sample/README.md | 52 ++++++ .../amazon-bedrock-sample/pyproject.toml | 17 ++ py/samples/amazon-bedrock-sample/src/main.py | 167 ++++++++++++++++++ py/uv.lock | 92 ++++++---- 5 files changed, 291 insertions(+), 38 deletions(-) create mode 100644 py/samples/amazon-bedrock-sample/README.md create mode 100644 py/samples/amazon-bedrock-sample/pyproject.toml create mode 100644 py/samples/amazon-bedrock-sample/src/main.py diff --git a/py/pyproject.toml b/py/pyproject.toml index e796eae48d..5292786d00 100644 --- a/py/pyproject.toml +++ b/py/pyproject.toml @@ -132,6 +132,7 @@ override-dependencies = ["werkzeug>=3.1.6"] [tool.uv.sources] # Samples (alphabetical by package name from pyproject.toml) agents = { workspace = true } +amazon-bedrock-sample = { workspace = true } anthropic-sample = { workspace = true } basic-flows = { workspace = true } context = { workspace = true } diff --git a/py/samples/amazon-bedrock-sample/README.md b/py/samples/amazon-bedrock-sample/README.md new file mode 100644 index 0000000000..982435f2a1 --- /dev/null +++ b/py/samples/amazon-bedrock-sample/README.md @@ -0,0 +1,52 @@ +# Amazon Bedrock + +Run text generation, structured output, tool calling, and reasoning through +Genkit with Amazon Bedrock's Converse API. + +You need an AWS account with Amazon Bedrock model access granted for the three +models the sample uses: + +- `us.amazon.nova-lite-v1:0` +- `us.meta.llama3-3-70b-instruct-v1:0` +- `us.deepseek.r1-v1:0` + +Credentials come from the standard AWS chain; environment variables, an +`AWS_PROFILE` (including SSO profiles after `aws sso login`), or instance +credentials. A region is required, from `AWS_REGION`, `AWS_DEFAULT_REGION`, or +the active profile: + +```bash +export AWS_PROFILE=my-profile +export AWS_REGION=us-east-1 +``` + +Run the quick smoke test: + +```bash +uv sync +uv run src/main.py +``` + +To explore all flows in Dev UI instead: + +```bash +genkit start -- uv run src/main.py +``` + +Then open [http://localhost:4000](http://localhost:4000) and try: + +- `haiku` +- `cat_profile` +- `weather_report` +- `reasoning` + +The plugin resolves any Bedrock model ID, inference profile, or ARN on demand, +so the Dev UI model runner also works with models beyond the three declared +ones. Anthropic models are a common addition, but they need a one-time +account-level agreement (Bedrock console → Model access → Anthropic use case +details) before any request succeeds. + +Bedrock has no constrained-decoding mode, so structured output is carried by +prompt instructions: pass `output_instructions=True` alongside `output_format` +and `output_schema`, as `cat_profile` does. Without it the schema never reaches +the model and it answers in prose. diff --git a/py/samples/amazon-bedrock-sample/pyproject.toml b/py/samples/amazon-bedrock-sample/pyproject.toml new file mode 100644 index 0000000000..c4767970e9 --- /dev/null +++ b/py/samples/amazon-bedrock-sample/pyproject.toml @@ -0,0 +1,17 @@ +[project] +name = "amazon-bedrock-sample" +version = "0.1.0" +requires-python = ">=3.10" +dependencies = [ + "genkit", + "genkit-amazon-bedrock", + "pydantic>=2.10.5", + "structlog>=25.2.0", +] + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[tool.hatch.build.targets.wheel] +packages = ["src"] diff --git a/py/samples/amazon-bedrock-sample/src/main.py b/py/samples/amazon-bedrock-sample/src/main.py new file mode 100644 index 0000000000..8944020abb --- /dev/null +++ b/py/samples/amazon-bedrock-sample/src/main.py @@ -0,0 +1,167 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +# SPDX-License-Identifier: Apache-2.0 + +"""Amazon Bedrock samples for the non-streaming Converse path. + +Needs AWS credentials and a region (``AWS_REGION`` or ``~/.aws/config``) with +model access granted for the three models below. Streaming is not wired up yet, +so every flow here is a single Converse call. +""" + +from genkit_amazon_bedrock import Bedrock, ModelDefinition +from pydantic import BaseModel, Field + +from genkit import Genkit, ModelResponse, ReasoningPart + +NOVA = 'bedrock/us.amazon.nova-lite-v1:0' +LLAMA = 'bedrock/us.meta.llama3-3-70b-instruct-v1:0' +DEEPSEEK = 'bedrock/us.deepseek.r1-v1:0' + +# Declaring models is optional — resolve() serves any Bedrock model ID or ARN +# on demand — but declared ones show up in the Dev UI model list. +ai = Genkit( + plugins=[ + Bedrock( + models=[ + ModelDefinition(name='us.amazon.nova-lite-v1:0'), + ModelDefinition(name='us.meta.llama3-3-70b-instruct-v1:0'), + ModelDefinition(name='us.deepseek.r1-v1:0'), + ] + ) + ], + model=NOVA, +) + + +class TopicInput(BaseModel): + """Input for a plain-text generation.""" + + topic: str = Field(default='coding', description='Topic for the haiku') + + +class CatInput(BaseModel): + """Input for a structured generation.""" + + name: str = Field(default='Mittens', description='Name of the cat to invent') + + +class Cat(BaseModel): + """Structured cat profile.""" + + name: str + breed: str + age: int + personality: str + + +class CityInput(BaseModel): + """Input for the weather tool.""" + + city: str = Field(default='Lagos', description='City to look up') + + +@ai.tool() +async def current_weather(city_input: CityInput) -> str: + """Return mocked weather data for tool-calling demos.""" + return f'The weather in {city_input.city} is 31C and humid.' + + +@ai.flow() +async def haiku(data: TopicInput) -> str: + """Plain-text generate through Converse.""" + response = await ai.generate(prompt=f'Write a haiku about {data.topic}.') + return response.text + + +@ai.flow() +async def cat_profile(data: CatInput) -> Cat: + """Structured output, carried by prompt instructions. + + Bedrock has no constrained-decoding mode, and the core's json format only + injects the schema when ``output_instructions`` is set, so it is required + here. Model choice matters too: the Nova models answer in prose often + enough to fail extraction, so this uses Llama 3.3. + """ + response = await ai.generate( + model=LLAMA, + prompt=f'Invent a cat named {data.name}.', + output_format='json', + output_schema=Cat, + output_instructions=True, + config={'maxTokens': 1024}, + ) + return response.output + + +@ai.flow() +async def weather_report(data: CityInput) -> str: + """Tool calling: the model calls the tool, then answers from its output.""" + response = await ai.generate( + prompt=f'What is the weather in {data.city}? Use the tool, then answer in one sentence.', + tools=['current_weather'], + ) + return response.text + + +@ai.flow() +async def reasoning(data: TopicInput) -> dict[str, object]: + """Reasoning parts parsed off a Converse response. + + DeepSeek R1 reasons on every turn, so no thinking config is needed. Its + reasoning carries no signature, which is why ``signatures_present`` is + false here: signatures are Anthropic-specific and gate replay. + """ + response = await ai.generate( + model=DEEPSEEK, + prompt=f'What is 17 * 23? Think it through, then state the answer. Mention {data.topic} once.', + config={'maxTokens': 2048}, + ) + return _reasoning_summary(response) + + +def _reasoning_summary(response: ModelResponse) -> dict[str, object]: + """Summarize the reasoning parts on a response.""" + reasoning_text: list[str] = [] + signed: list[bool] = [] + for message in response.messages: + for part in message.content: + root = part.root + if isinstance(root, ReasoningPart): + reasoning_text.append(root.reasoning) + signed.append(bool(root.metadata and root.metadata.get('bedrockReasoningSignature'))) + return { + 'answer': response.text, + 'reasoning_parts': len(reasoning_text), + 'reasoning_preview': ''.join(reasoning_text)[:500], + 'signatures_present': signed, + } + + +async def main() -> None: + """Run the lightweight flows once from the CLI.""" + try: + print(await haiku(TopicInput())) # noqa: T201 + print(await weather_report(CityInput())) # noqa: T201 + except Exception as error: + # Printed, not raised: in dev mode the Dev UI stays up either way. + print( # noqa: T201 + f'Set AWS credentials and a region, and grant model access for {NOVA}, {LLAMA}, and {DEEPSEEK}, ' + f'before running this sample.\n{error}' + ) + + +if __name__ == '__main__': + ai.run_main(main()) diff --git a/py/uv.lock b/py/uv.lock index c891c4b423..9e66a55918 100644 --- a/py/uv.lock +++ b/py/uv.lock @@ -9,13 +9,10 @@ resolution-markers = [ "python_full_version < '3.11'", ] -[options] -exclude-newer = "2026-07-23T09:19:13.945347Z" -exclude-newer-span = "P7D" - [manifest] members = [ "agents", + "amazon-bedrock-sample", "anthropic-sample", "basic-flows", "context", @@ -103,6 +100,25 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/db/33/ef2f2409450ef6daa61459d5de5c08128e7d3edb773fefd0a324d1310238/altair-6.0.0-py3-none-any.whl", hash = "sha256:09ae95b53d5fe5b16987dccc785a7af8588f2dca50de1e7a156efa8a461515f8", size = 795410, upload-time = "2025-11-12T08:59:09.804Z" }, ] +[[package]] +name = "amazon-bedrock-sample" +version = "0.1.0" +source = { editable = "samples/amazon-bedrock-sample" } +dependencies = [ + { name = "genkit" }, + { name = "genkit-amazon-bedrock" }, + { name = "pydantic" }, + { name = "structlog" }, +] + +[package.metadata] +requires-dist = [ + { name = "genkit", editable = "packages/genkit" }, + { name = "genkit-amazon-bedrock", editable = "packages/genkit-amazon-bedrock" }, + { name = "pydantic", specifier = ">=2.10.5" }, + { name = "structlog", specifier = ">=25.2.0" }, +] + [[package]] name = "annotated-doc" version = "0.0.4" @@ -1224,9 +1240,9 @@ resolution-markers = [ "python_full_version < '3.11'", ] dependencies = [ - { name = "asgiref", marker = "python_full_version < '3.12'" }, - { name = "sqlparse", marker = "python_full_version < '3.12'" }, - { name = "tzdata", marker = "python_full_version < '3.12' and sys_platform == 'win32'" }, + { name = "asgiref" }, + { name = "sqlparse" }, + { name = "tzdata", marker = "sys_platform == 'win32'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/65/95/95f7faa0950867afaa0bef2460c6263afd6a2c78cc9434046ed28160b015/django-5.2.14.tar.gz", hash = "sha256:58a63ba841662e5c686b57ba1fec52ddd68c0b93bd96ac3029d55728f00bf8a2", size = 10895118, upload-time = "2026-05-05T13:57:31.104Z" } wheels = [ @@ -1243,9 +1259,9 @@ resolution-markers = [ "python_full_version == '3.12.*'", ] dependencies = [ - { name = "asgiref", marker = "python_full_version >= '3.12'" }, - { name = "sqlparse", marker = "python_full_version >= '3.12'" }, - { name = "tzdata", marker = "python_full_version >= '3.12' and sys_platform == 'win32'" }, + { name = "asgiref" }, + { name = "sqlparse" }, + { name = "tzdata", marker = "sys_platform == 'win32'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/5e/f1/bf85f0d29ef76abf901f193fe8fef4769d3da7794197832bc30151c071d8/django-6.0.5.tar.gz", hash = "sha256:bc6d6872e98a2864c836e42edd644b362db311147dd5aa8d5b82ba7a032f5269", size = 10924131, upload-time = "2026-05-05T13:54:39.329Z" } wheels = [ @@ -1407,7 +1423,7 @@ name = "exceptiongroup" version = "1.3.1" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "typing-extensions", marker = "python_full_version < '3.11'" }, + { name = "typing-extensions" }, ] sdist = { url = "https://files.pythonhosted.org/packages/50/79/66800aadf48771f6b62f7eb014e352e5d06856655206165d775e675a02c9/exceptiongroup-1.3.1.tar.gz", hash = "sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219", size = 30371, upload-time = "2025-11-21T23:01:54.787Z" } wheels = [ @@ -1670,7 +1686,7 @@ provides-extras = ["flask", "google-cloud", "google-genai", "ollama", "openai", [[package]] name = "genkit-amazon-bedrock" -version = "0.1.0" +version = "0.8.1" source = { editable = "packages/genkit-amazon-bedrock" } dependencies = [ { name = "boto3" }, @@ -2851,17 +2867,17 @@ resolution-markers = [ "python_full_version < '3.11'", ] dependencies = [ - { name = "colorama", marker = "python_full_version < '3.11' and sys_platform == 'win32'" }, - { name = "decorator", marker = "python_full_version < '3.11'" }, - { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, - 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{ name = "pygments", marker = "python_full_version >= '3.11'" }, + { name = "pygments" }, ] sdist = { url = "https://files.pythonhosted.org/packages/ef/4c/5dd1d8af08107f88c7f741ead7a40854b8ac24ddf9ae850afbcf698aa552/ipython_pygments_lexers-1.1.1.tar.gz", hash = "sha256:09c0138009e56b6854f9535736f4171d855c8c08a563a0dcd8022f78355c7e81", size = 8393, upload-time = "2025-01-17T11:24:34.505Z" } wheels = [ @@ -3029,7 +3045,7 @@ name = "jinxed" version = "1.3.0" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "ansicon", marker = "sys_platform == 'win32'" }, + { name = "ansicon" }, ] sdist = { url = "https://files.pythonhosted.org/packages/20/d0/59b2b80e7a52d255f9e0ad040d2e826342d05580c4b1d7d7747cfb8db731/jinxed-1.3.0.tar.gz", hash = "sha256:1593124b18a41b7a3da3b078471442e51dbad3d77b4d4f2b0c26ab6f7d660dbf", size = 80981, upload-time = "2024-07-31T22:39:18.854Z" } wheels = [ @@ -6443,8 +6459,8 @@ name = "taskgroup" version = "0.2.2" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, - { name = "typing-extensions", marker = "python_full_version < '3.11'" }, + { name = "exceptiongroup" }, + { name = "typing-extensions" }, ] sdist = { url = "https://files.pythonhosted.org/packages/f0/8d/e218e0160cc1b692e6e0e5ba34e8865dbb171efeb5fc9a704544b3020605/taskgroup-0.2.2.tar.gz", hash = "sha256:078483ac3e78f2e3f973e2edbf6941374fbea81b9c5d0a96f51d297717f4752d", size = 11504, upload-time = "2025-01-03T09:24:13.761Z" } wheels = [ From f717c8a765b21bd2c71ae5fec556e2b877571eca Mon Sep 17 00:00:00 2001 From: Hilary Date: Mon, 3 Aug 2026 16:56:20 +0100 Subject: [PATCH 8/8] feat(py/plugins/amazon-bedrock): verify Claude paths live and drop maxTokens injection Converse accepts Claude requests without maxTokens and applies a service default, so nothing is injected. Signed reasoning replay confirmed live. --- .../src/genkit_amazon_bedrock/config.py | 4 +- .../src/genkit_amazon_bedrock/converters.py | 35 -------------- .../tests/converters_test.py | 32 +++---------- .../genkit-amazon-bedrock/tests/live_test.py | 46 ++++++++++++++++++- py/samples/amazon-bedrock-sample/README.md | 14 ++++-- py/samples/amazon-bedrock-sample/src/main.py | 21 +++++++++ 6 files changed, 84 insertions(+), 68 deletions(-) diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py index a6d25a2ce2..33a00aa779 100644 --- a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/config.py @@ -47,8 +47,8 @@ class BedrockConfig(ModelConfig): ) max_tokens: int | None = None - """Maximum tokens to generate. When unset, the plugin leaves the field - unset except for Claude models, where Bedrock requires a value.""" + """Maximum tokens to generate. When unset, the field is left unset and + the service applies its own default cap.""" tool_choice: str | None = None """Tool choice mode: ``auto``, ``required``/``any``, ``none``, or a tool name.""" diff --git a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/converters.py b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/converters.py index 67e5058885..d2c76ec466 100644 --- a/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/converters.py +++ b/py/packages/genkit-amazon-bedrock/src/genkit_amazon_bedrock/converters.py @@ -57,18 +57,6 @@ CACHE_POINT_CUSTOM_KEY = 'bedrockCachePointType' DEFAULT_CACHE_POINT_TYPE = 'default' -# Bedrock requires maxTokens for Claude models; newer families allow more. -DEFAULT_CLAUDE_MAX_TOKENS = 4096 -DEFAULT_EXTENDED_CLAUDE_MAX_TOKENS = 8192 -EXTENDED_CLAUDE_MAX_TOKEN_PATTERNS = ( - 'claude-3-5', - 'claude-3-7', - 'claude-4', - 'claude-haiku-4', - 'claude-sonnet-4', - 'claude-opus-4', -) - IMAGE_FORMATS = { 'image/png': 'png', 'image/jpeg': 'jpeg', @@ -212,21 +200,6 @@ def _effective_max_tokens(config: BedrockConfig | None) -> int | None: return None -def default_max_tokens_for_model(model_id: str) -> int | None: - """Default maxTokens for models that require one (Claude only). - - Substring match on the full lowercased model ID so cross-region - inference-profile IDs (``us.anthropic.claude-...``) match too. - """ - lowered = model_id.lower() - if 'claude' not in lowered: - return None - for pattern in EXTENDED_CLAUDE_MAX_TOKEN_PATTERNS: - if pattern in lowered: - return DEFAULT_EXTENDED_CLAUDE_MAX_TOKENS - return DEFAULT_CLAUDE_MAX_TOKENS - - def build_inference_config(config: BedrockConfig | None) -> dict[str, Any] | None: # noqa: ANN401 """Builds the Converse ``inferenceConfig`` member; None when empty.""" if config is None: @@ -540,14 +513,6 @@ def build_converse_request(model_id: str, request: ModelRequest[Any]) -> dict[st kwargs['system'] = system inference_config = build_inference_config(config) - max_tokens_set = bool(inference_config and 'maxTokens' in inference_config) - if not max_tokens_set: - # Bedrock requires maxTokens for Claude models; inject a default only - # when the caller didn't set one. - default_max_tokens = default_max_tokens_for_model(model_id) - if default_max_tokens is not None: - inference_config = dict(inference_config or {}) - inference_config['maxTokens'] = default_max_tokens if inference_config: kwargs['inferenceConfig'] = inference_config diff --git a/py/packages/genkit-amazon-bedrock/tests/converters_test.py b/py/packages/genkit-amazon-bedrock/tests/converters_test.py index 30a5bb7790..55cea95ca6 100644 --- a/py/packages/genkit-amazon-bedrock/tests/converters_test.py +++ b/py/packages/genkit-amazon-bedrock/tests/converters_test.py @@ -31,7 +31,6 @@ build_inference_config, cache_point_part, content_blocks_to_parts, - default_max_tokens_for_model, map_finish_reason, normalize_config, to_bedrock_role, @@ -181,37 +180,20 @@ def test_top_k_and_version_are_accepted_but_ignored() -> None: assert 'additionalModelRequestFields' not in kwargs -# --- Claude maxTokens injection -------------------------------------------- +# --- maxTokens -------------------------------------------------------------- -@pytest.mark.parametrize( - 'model_id,expected', - [ - ('anthropic.claude-3-haiku-20240307-v1:0', 4096), - ('anthropic.claude-3-5-sonnet-20241022-v2:0', 8192), - ('anthropic.claude-3-7-sonnet-20250219-v1:0', 8192), - ('us.anthropic.claude-sonnet-4-5-20250929-v1:0', 8192), - ('anthropic.claude-opus-4-6-v1', 8192), - ('amazon.nova-lite-v1:0', None), - ], -) -def test_default_max_tokens_for_model(model_id, expected) -> None: - assert default_max_tokens_for_model(model_id) == expected - - -def test_claude_gets_default_max_tokens_injected() -> None: - kwargs = build_converse_request('anthropic.claude-3-haiku-20240307-v1:0', user_text_request()) - assert kwargs['inferenceConfig'] == {'maxTokens': 4096} - - -def test_claude_keeps_user_configured_max_tokens() -> None: +def test_configured_max_tokens_is_sent() -> None: request = user_text_request(config=BedrockConfig(max_tokens=32)) kwargs = build_converse_request('anthropic.claude-3-haiku-20240307-v1:0', request) assert kwargs['inferenceConfig'] == {'maxTokens': 32} -def test_non_claude_without_config_has_no_inference_config() -> None: - kwargs = build_converse_request('amazon.nova-lite-v1:0', user_text_request()) +@pytest.mark.parametrize('model_id', ['us.anthropic.claude-sonnet-4-5-20250929-v1:0', 'amazon.nova-lite-v1:0']) +def test_no_max_tokens_is_injected_for_any_model(model_id) -> None: + # Verified live: Converse accepts Claude requests without maxTokens and + # applies a service default, so nothing is guessed on the caller's behalf. + kwargs = build_converse_request(model_id, user_text_request()) assert 'inferenceConfig' not in kwargs diff --git a/py/packages/genkit-amazon-bedrock/tests/live_test.py b/py/packages/genkit-amazon-bedrock/tests/live_test.py index 6608e79046..2b5f6524ef 100644 --- a/py/packages/genkit-amazon-bedrock/tests/live_test.py +++ b/py/packages/genkit-amazon-bedrock/tests/live_test.py @@ -18,7 +18,8 @@ Opt-in: set ``BEDROCK_LIVE_TESTS=1`` plus working AWS credentials and a region (``AWS_REGION`` or ``~/.aws/config``). These call real models and -incur cost. The models used need only default model access. +incur cost. The Anthropic models additionally need the account's one-time +use-case agreement (Bedrock console -> Model access). """ import os @@ -41,6 +42,7 @@ ), ] +CLAUDE = 'us.anthropic.claude-sonnet-4-5-20250929-v1:0' NOVA = 'us.amazon.nova-lite-v1:0' DEEPSEEK = 'us.deepseek.r1-v1:0' @@ -124,6 +126,48 @@ async def test_undocumented_tool_round_trip() -> None: assert (await make_model(NOVA).generate(follow_up)).message is not None +async def test_claude_sync_without_config() -> None: + # No config on purpose: Converse accepts Claude requests without maxTokens + # and applies a service default, so the plugin injects nothing. + response = await make_model(CLAUDE).generate(text_request("Reply with the single word 'pong'.")) + assert response.finish_reason == FinishReason.STOP + assert response.message is not None + text = response.message.content[0].root.text + assert text is not None and 'pong' in text.lower() + + +async def test_claude_reasoning_signature_round_trip() -> None: + model = make_model(CLAUDE) + # Bedrock requires budget_tokens >= 1024 and maxTokens above it; thinking + # requests reject custom temperature, so none is set. + config = BedrockConfig( + max_tokens=4096, + additional_model_request_fields={'thinking': {'type': 'enabled', 'budget_tokens': 1024}}, + ) + request = text_request('What is 17 * 23? Think it through.', config=config) + response = await model.generate(request) + + assert response.message is not None + reasoning_parts = [ + part.root for part in response.message.content if getattr(part.root, 'reasoning', None) is not None + ] + assert reasoning_parts, 'expected a reasoning part on a thinking-enabled sync call' + assert reasoning_parts[0].metadata is not None + assert reasoning_parts[0].metadata.get(REASONING_SIGNATURE_METADATA_KEY) + + # Replaying the signed reasoning verbatim must be accepted by Bedrock. + follow_up = ModelRequest( + messages=[ + *request.messages, + response.message, + Message(role=Role.USER, content=[Part(root=TextPart(text='Now add 100 to that.'))]), + ], + config=config, + ) + follow_up_response = await model.generate(follow_up) + assert follow_up_response.finish_reason == FinishReason.STOP + + async def test_deepseek_reasoning_sync_and_round_trip() -> None: model = make_model(DEEPSEEK) config = BedrockConfig(max_tokens=2048) diff --git a/py/samples/amazon-bedrock-sample/README.md b/py/samples/amazon-bedrock-sample/README.md index 982435f2a1..fe650a743d 100644 --- a/py/samples/amazon-bedrock-sample/README.md +++ b/py/samples/amazon-bedrock-sample/README.md @@ -3,12 +3,17 @@ Run text generation, structured output, tool calling, and reasoning through Genkit with Amazon Bedrock's Converse API. -You need an AWS account with Amazon Bedrock model access granted for the three +You need an AWS account with Amazon Bedrock model access granted for the four models the sample uses: - `us.amazon.nova-lite-v1:0` - `us.meta.llama3-3-70b-instruct-v1:0` - `us.deepseek.r1-v1:0` +- `us.anthropic.claude-sonnet-4-5-20250929-v1:0` + +The Anthropic model additionally needs the account's one-time use-case +agreement (Bedrock console, Model access, Anthropic use case details); the +`thinking` flow fails with `ResourceNotFoundException` until it is granted. Credentials come from the standard AWS chain; environment variables, an `AWS_PROFILE` (including SSO profiles after `aws sso login`), or instance @@ -39,12 +44,11 @@ Then open [http://localhost:4000](http://localhost:4000) and try: - `cat_profile` - `weather_report` - `reasoning` +- `thinking` The plugin resolves any Bedrock model ID, inference profile, or ARN on demand, -so the Dev UI model runner also works with models beyond the three declared -ones. Anthropic models are a common addition, but they need a one-time -account-level agreement (Bedrock console → Model access → Anthropic use case -details) before any request succeeds. +so the Dev UI model runner also works with models beyond the four declared +ones. Bedrock has no constrained-decoding mode, so structured output is carried by prompt instructions: pass `output_instructions=True` alongside `output_format` diff --git a/py/samples/amazon-bedrock-sample/src/main.py b/py/samples/amazon-bedrock-sample/src/main.py index 8944020abb..d4fe85ad6c 100644 --- a/py/samples/amazon-bedrock-sample/src/main.py +++ b/py/samples/amazon-bedrock-sample/src/main.py @@ -29,6 +29,7 @@ NOVA = 'bedrock/us.amazon.nova-lite-v1:0' LLAMA = 'bedrock/us.meta.llama3-3-70b-instruct-v1:0' DEEPSEEK = 'bedrock/us.deepseek.r1-v1:0' +CLAUDE = 'bedrock/us.anthropic.claude-sonnet-4-5-20250929-v1:0' # Declaring models is optional — resolve() serves any Bedrock model ID or ARN # on demand — but declared ones show up in the Dev UI model list. @@ -39,6 +40,7 @@ ModelDefinition(name='us.amazon.nova-lite-v1:0'), ModelDefinition(name='us.meta.llama3-3-70b-instruct-v1:0'), ModelDefinition(name='us.deepseek.r1-v1:0'), + ModelDefinition(name='us.anthropic.claude-sonnet-4-5-20250929-v1:0'), ] ) ], @@ -132,6 +134,25 @@ async def reasoning(data: TopicInput) -> dict[str, object]: return _reasoning_summary(response) +@ai.flow() +async def thinking(data: TopicInput) -> dict[str, object]: + """Claude extended thinking: signed reasoning that survives replay. + + Unlike DeepSeek, Claude signs its reasoning, so ``signatures_present`` is + true here and the parts are replayed verbatim on multi-turn follow-ups. + """ + response = await ai.generate( + model=CLAUDE, + prompt=f'What is 17 * 23? Think it through, then state the answer. Mention {data.topic} once.', + config={ + 'maxTokens': 4096, + # Bedrock requires budget_tokens >= 1024, below maxTokens. + 'additionalModelRequestFields': {'thinking': {'type': 'enabled', 'budget_tokens': 1024}}, + }, + ) + return _reasoning_summary(response) + + def _reasoning_summary(response: ModelResponse) -> dict[str, object]: """Summarize the reasoning parts on a response.""" reasoning_text: list[str] = []