From 6dbd97ce206d396dfa1c7ba9fafe6698292293b1 Mon Sep 17 00:00:00 2001 From: John Richard Date: Thu, 12 Feb 2026 14:19:54 +0800 Subject: [PATCH 1/2] feat: multimodal and types --- docs/guide/getting-started/architecture.md | 116 +++- docs/zh/guide/getting-started/architecture.md | 110 +++- pyproject.toml | 5 +- src/amrita_core/builtins/adapter.py | 12 +- src/amrita_core/builtins/agent.py | 2 +- src/amrita_core/chatmanager.py | 118 ++--- src/amrita_core/libchat.py | 6 +- src/amrita_core/protocol.py | 144 ++++- src/amrita_core/tools/mcp.py | 8 +- src/amrita_core/tools/models.py | 2 +- src/amrita_core/types.py | 15 +- uv.lock | 501 ++++++++++++++++++ 12 files changed, 876 insertions(+), 163 deletions(-) diff --git a/docs/guide/getting-started/architecture.md b/docs/guide/getting-started/architecture.md index 5fa8cce..1eaaccd 100644 --- a/docs/guide/getting-started/architecture.md +++ b/docs/guide/getting-started/architecture.md @@ -2,6 +2,8 @@ ## 2.4.1 Architecture Diagram +### Core Architecture + ```mermaid graph TB subgraph "AmritaCore" @@ -12,7 +14,7 @@ graph TB E[Memory Model] F[Agent Core] end - + UserInput[User Input] --> A A --> B A --> C @@ -22,16 +24,51 @@ graph TB D --> F E --> F F --> ResponseStream[Response Stream] - + ResponseStream --> UserOutput[User Output] F --> E - + LLM[LLM Provider] <---> F - + style AmritaCore fill:#e1f5fe,stroke:#0277bd,stroke-width:2px style F fill:#fff3e0,stroke:#f57c00,stroke-width:2px ``` +### Session and Global Data Container Architecture + +#### Global Container and Session Conversation Context + +```mermaid +graph TB + subgraph "Global Container" + G_Tools[Global Tools] + G_Presets[Global Presets] + G_Config[Global Configuration] + end + + subgraph "SessionsManager" + S1[Session 1
Conversation Context] + S2[Session 2
Conversation Context] + SN[Session N
Conversation Context] + end + + subgraph "Single Session Structure" + Mem[Memory Model
Conversation History] + Tools[Tools Manager
Current Session Tools] + Conf[Configuration
Current Session Config] + end + + G_Tools -.-> Tools + G_Presets -.-> S1 + G_Config -.-> Conf + + style Global_Container fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px + style Session_Container fill:#e3f2fd,stroke:#1565c0,stroke-width:2px + style S1 fill:#bbdefb,stroke:#1565c0,stroke-width:1px + style S2 fill:#bbdefb,stroke:#1565c0,stroke-width:1px + style SN fill:#bbdefb,stroke:#1565c0,stroke-width:1px +``` + ## 2.4.2 Core Component Relationships - **ChatObject**: The main interaction point that manages a single conversation @@ -40,31 +77,60 @@ graph TB - **Tools Manager**: Extends the agent's capabilities with external functions - **Memory Model**: Maintains conversation context and history - **Agent Core**: The central processing unit coordinating all components +- **SessionsManager**: Manages multiple isolated sessions, each as an independent conversation context +- **Session (Conversation Context)**: Stores all relevant information for a specific user or specific conversation, including memory model, tools, configurations, etc. -## 2.4.3 Data Flow Explanation +## 2.4.3 Agent Loop and Session Isolation Mechanism ```mermaid sequenceDiagram - User->>CO: Send input message - CO->>Config: Check configuration - CO->>Events: Trigger input events - CO->>Agent: Initialize processing - Agent->>Memory: Load conversation context - Agent->>Tools: Check for required tools - Agent->>LLM: Format and send request + participant User1 as User1 + participant User2 as User2 + participant SM as SessionsManager + participant S1 as Session 1
(Conversation Context 1) + participant S2 as Session 2
(Conversation Context 2) + participant Agent as Agent Core + participant LLM as LLM Provider + + Note over User1,LLM: Agent Loop Begins + User1->>SM: Request to create Session 1 + User2->>SM: Request to create Session 2 + SM-->>User1: Return Session ID 1 + SM-->>User2: Return Session ID 2 + + Note over User1,User2: Each user interacts in their respective conversation context + + User1->>S1: Send message to Session 1 + S1->>S1: Initialize ChatObject + S1->>Agent: Start Agent Loop to process request + + User2->>S2: Send message to Session 2 + S2->>S2: Initialize ChatObject + S2->>Agent: Start Agent Loop to process request + + par Parallel Processing of Two Conversation Contexts + Agent->>S1: Process in Session 1 Context + Agent->>S2: Process in Session 2 Context + + Agent->>S1: Update Session 1 Memory Model + Agent->>S2: Update Session 2 Memory Model + end + + Agent->>LLM: Send request (from Session 1) LLM-->>Agent: Return response - Agent->>Memory: Update conversation state - Agent->>Events: Trigger output events - CO-->>User: Stream response + Agent-->>S1: Update Session 1 State + S1-->>User1: Stream response + + Agent->>LLM: Send request (from Session 2) + LLM-->>Agent: Return response + Agent-->>S2: Update Session 2 State + S2-->>User2: Stream response + + Note over User1,LLM: Each conversation context maintains independent history and state ``` -1. User input enters through a ChatObject -2. Configuration determines processing behavior -3. The input triggers various events in the Events System -4. Agent Core loads the conversation context from Memory Model -5. Agent Core checks if any tools need to be called based on the input -6. The processed input is sent to the LLM Provider -7. The response from LLM is handled by Agent Core -8. Memory Model is updated with the new conversation state -9. Output events may intercept and modify the final response -10. The response is streamed back to the user via ChatObject \ No newline at end of file +1. **Session as Conversation Context**: Each Session represents an independent conversation context, storing all relevant information for a specific user or specific conversation +2. **Global Data Container**: SessionsManager manages all active conversation contexts, providing global resource sharing +3. **Agent Loop**: Inside each conversation context, the Agent Core executes the complete processing loop +4. **Context Isolation**: Data between different conversation contexts is completely isolated, ensuring conversation histories don't mix +5. **Global Resource Sharing**: Each conversation context can access resources from the Global container, but maintains its own independent state diff --git a/docs/zh/guide/getting-started/architecture.md b/docs/zh/guide/getting-started/architecture.md index 8d49f8c..69369c8 100644 --- a/docs/zh/guide/getting-started/architecture.md +++ b/docs/zh/guide/getting-started/architecture.md @@ -2,6 +2,8 @@ ## 2.4.1 架构图 +### Core Architecture + ```mermaid graph TB subgraph "AmritaCore" @@ -32,6 +34,41 @@ graph TB style F fill:#fff3e0,stroke:#f57c00,stroke-width:2px ``` +### Session 与 Global 数据容器架构 + +#### Global 全局容器与 Session 对话上下文 + +```mermaid +graph TB + subgraph "Global 全局容器" + G_Tools[全局工具] + G_Presets[全局预设] + G_Config[全局配置] + end + + subgraph "SessionsManager" + S1[Session 1
对话上下文] + S2[Session 2
对话上下文] + SN[Session N
对话上下文] + end + + subgraph "单个 Session 结构" + Mem[记忆模型
对话历史] + Tools[工具管理器
当前会话工具] + Conf[配置
当前会话配置] + end + + G_Tools -.-> Tools + G_Presets -.-> S1 + G_Config -.-> Conf + + style Global_Container fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px + style Session_Container fill:#e3f2fd,stroke:#1565c0,stroke-width:2px + style S1 fill:#bbdefb,stroke:#1565c0,stroke-width:1px + style S2 fill:#bbdefb,stroke:#1565c0,stroke-width:1px + style SN fill:#bbdefb,stroke:#1565c0,stroke-width:1px +``` + ## 2.4.2 核心组件关系 - **ChatObject**: 管理单个对话的主要交互点 @@ -40,31 +77,60 @@ graph TB - **工具管理器**: 通过外部函数扩展Agent功能 - **记忆模型**: 维护对话上下文和历史记录 - **Agent核心**: 协调所有组件的中央处理单元 +- **SessionsManager**: 管理多个独立的会话，每个会话都是一个独立的对话上下文 +- **Session（对话上下文）**: 保存特定用户或特定对话的所有相关信息，包括记忆模型、工具、配置等 -## 2.4.3 数据流说明 +## 2.4.3 Agent 循环与 Session 隔离机制 ```mermaid sequenceDiagram - 用户->>ChatObject: 发送输入消息 - ChatObject->>配置: 检查配置 - ChatObject->>事件系统: 触发输入事件 - ChatObject->>Agent核心: 初始化处理 - Agent核心->>记忆模型: 加载对话上下文 - Agent核心->>工具管理器: 检查所需的工具 - Agent核心->>LLM 提供商: 格式化并发送请求 - LLM 提供商-->>Agent核心: 返回响应 - Agent核心->>记忆模型: 更新对话状态 - Agent核心->>事件系统: 触发输出事件 - ChatObject-->>用户: 流式传输响应 + participant User1 as 用户1 + participant User2 as 用户2 + participant SM as SessionsManager + participant S1 as Session 1
(对话上下文1) + participant S2 as Session 2
(对话上下文2) + participant Agent as Agent核心 + participant LLM as LLM 提供商 + + Note over User1,LLM: Agent 循环开始 + User1->>SM: 请求创建 Session 1 + User2->>SM: 请求创建 Session 2 + SM-->>User1: 返回 Session ID 1 + SM-->>User2: 返回 Session ID 2 + + Note over User1,User2: 每个用户在各自的对话上下文中交互 + + User1->>S1: 发送消息到 Session 1 + S1->>S1: 初始化 ChatObject + S1->>Agent: 启动 Agent 循环处理请求 + + User2->>S2: 发送消息到 Session 2 + S2->>S2: 初始化 ChatObject + S2->>Agent: 启动 Agent 循环处理请求 + + par 并行处理两个对话上下文 + Agent->>S1: 在 Session 1 上下文中处理 + Agent->>S2: 在 Session 2 上下文中处理 + + Agent->>S1: 更新 Session 1 记忆模型 + Agent->>S2: 更新 Session 2 记忆模型 + end + + Agent->>LLM: 发送请求 (来自 Session 1) + LLM-->>Agent: 返回响应 + Agent-->>S1: 更新 Session 1 状态 + S1-->>User1: 流式传输响应 + + Agent->>LLM: 发送请求 (来自 Session 2) + LLM-->>Agent: 返回响应 + Agent-->>S2: 更新 Session 2 状态 + S2-->>User2: 流式传输响应 + + Note over User1,LLM: 每个对话上下文保持独立的历史和状态 ``` -1. 用户输入通过 ChatObject 进入 -2. 配置确定处理行为 -3. 输入触发事件系统中的各种事件 -4. Agent核心从记忆模型加载对话上下文 -5. Agent核心根据输入检查是否需要调用任何工具 -6. 处理后的输入发送到 LLM 提供商 -7. LLM 的响应由Agent核心处理 -8. 记忆模型使用新的对话状态进行更新 -9. 输出事件可能会拦截并修改最终响应 -10. 响应通过 ChatObject 流式传输回用户 +1. **Session 作为对话上下文**: 每个 Session 代表一个独立的对话上下文，保存特定用户或特定对话的所有相关信息 +2. **Global 数据容器**: SessionsManager 管理所有活动的对话上下文，提供全局资源共享 +3. **Agent 循环**: 在每个对话上下文内部，Agent 核心执行完整的处理循环 +4. **上下文隔离**: 不同对话上下文之间的数据完全隔离，确保对话历史不混淆 +5. **全局资源共享**: 每个对话上下文可以访问 Global 容器中的公共资源，但拥有各自独立的状态 diff --git a/pyproject.toml b/pyproject.toml index 440349f..017eb1f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,11 +1,14 @@ [project] name = "amrita_core" -version = "0.4.0.post1" +version = "0.4.1" description = "Agent core of Project Amrita" readme = "README.md" requires-python = ">=3.10,<3.14" dependencies = [ + "aiofiles>=25.1.0", + "aiohttp>=3.13.3", "fastmcp>=2.14.4", + "filetype>=1.2.0", "jieba>=0.42.1", "loguru>=0.7.3", "openai>=2.16.0", diff --git a/src/amrita_core/builtins/adapter.py b/src/amrita_core/builtins/adapter.py index a3c1742..23731de 100644 --- a/src/amrita_core/builtins/adapter.py +++ b/src/amrita_core/builtins/adapter.py @@ -17,7 +17,11 @@ from amrita_core.config import AmritaConfig from amrita_core.logging import debug_log -from amrita_core.protocol import ModelAdapter +from amrita_core.protocol import ( + COMPLETION_RETURNING, + ModelAdapter, + StringMessageContent, +) from amrita_core.tools.models import ToolChoice, ToolFunctionSchema from amrita_core.types import ( ModelConfig, @@ -36,7 +40,7 @@ class OpenAIAdapter(ModelAdapter): @override async def call_api( self, messages: Iterable[ChatCompletionMessageParam] - ) -> AsyncGenerator[str | UniResponse[str, None], None]: + ) -> AsyncGenerator[COMPLETION_RETURNING, None]: """Call OpenAI API to get chat responses""" preset: ModelPreset = self.preset preset_config: ModelConfig = preset.config @@ -81,7 +85,7 @@ async def call_api( ) if chunk.choices[0].delta.content is not None: response += chunk.choices[0].delta.content - yield chunk.choices[0].delta.content + yield StringMessageContent(response) debug_log(chunk.choices[0].delta.content) except IndexError: break @@ -93,7 +97,7 @@ async def call_api( if completion.choices[0].message.content is not None else "" ) - yield response + yield StringMessageContent(response) if completion.usage: uni_usage = UniResponseUsage.model_validate( completion.usage, from_attributes=True diff --git a/src/amrita_core/builtins/agent.py b/src/amrita_core/builtins/agent.py index e7ac34c..284489d 100644 --- a/src/amrita_core/builtins/agent.py +++ b/src/amrita_core/builtins/agent.py @@ -5,7 +5,6 @@ from copy import deepcopy from typing import Any -from amrita_core.chatmanager import MessageWithMetadata from amrita_core.config import AmritaConfig, get_config from amrita_core.hook.event import CompletionEvent, PreCompletionEvent from amrita_core.hook.exception import MatcherException as ProcEXC @@ -14,6 +13,7 @@ tools_caller, ) from amrita_core.logging import debug_log, logger +from amrita_core.protocol import MessageWithMetadata from amrita_core.sessions import SessionsManager from amrita_core.tools.manager import ToolsManager, on_tools from amrita_core.tools.models import ToolContext diff --git a/src/amrita_core/chatmanager.py b/src/amrita_core/chatmanager.py index d906d3d..133abde 100644 --- a/src/amrita_core/chatmanager.py +++ b/src/amrita_core/chatmanager.py @@ -2,14 +2,13 @@ import asyncio import copy -from abc import ABC, abstractmethod from asyncio import Lock, Task from collections import defaultdict from collections.abc import AsyncGenerator, Awaitable, Callable from dataclasses import dataclass, field from datetime import datetime -from io import BytesIO, StringIO -from typing import Any, TypeAlias, TypedDict +from io import StringIO +from typing import TYPE_CHECKING, Any, TypeAlias from uuid import uuid4 import pytz @@ -18,12 +17,14 @@ from typing_extensions import Self from amrita_core.preset import PresetManager +from amrita_core.sessions import SessionData from .config import AmritaConfig, get_config from .hook.event import CompletionEvent, PreCompletionEvent from .hook.matcher import MatcherManager from .libchat import call_completion, get_last_response, get_tokens, text_generator from .logging import logger +from .protocol import MessageContent, StringMessageContent from .sessions import SessionsManager from .tokenizer import hybrid_token_count from .types import ( @@ -44,6 +45,9 @@ MemoryModel as Memory, ) +if TYPE_CHECKING: + from .sessions import SessionData + # Global lock for thread-safe operations in the chat manager LOCK = Lock() @@ -66,81 +70,6 @@ def get_current_datetime_timestamp(utc_time: None | datetime = None): return f"[{formatted_date} {formatted_weekday} {formatted_time}]" -class MessageContent(ABC): - """Abstract base class for different types of message content - - This allows for various types of content to be yielded by the chat manager, - not just strings. Subclasses should implement their own representation. - """ - - def __str__(self) -> str: - return self.get_content() - - def __init__(self, content_type: str): - self.type = content_type - - @abstractmethod - def get_content(self): - """Return the actual content of the message""" - raise NotImplementedError("Subclasses must implement get_content method") - - -class StringMessageContent(MessageContent): - """String type message content implementation""" - - def __init__(self, text: str): - super().__init__("string") - self.text = text - - def get_content(self): - return self.text - - -class RawMessageContent(MessageContent): - """Raw message content implementation""" - - def __init__(self, raw_data: Any): - super().__init__("raw") - self.raw_data = raw_data - - def get_content(self): - return self.raw_data - - -class MessageMetadata(TypedDict): - content: str - metadata: dict[str, Any] - - -class MessageWithMetadata(MessageContent): - """Message with additional metadata""" - - def __init__(self, content: Any, metadata: dict): - super().__init__("metadata") - self.content = content - self.metadata = metadata - - def get_content(self) -> Any: - return self.content - - def get_metadata(self) -> dict: - return self.metadata - - def get_full_content(self) -> MessageMetadata: - return MessageMetadata(content=self.content, metadata=self.metadata) - - -class ImageMessage(MessageContent): - """Image message""" - - def __init__(self, image: str | BytesIO): - super().__init__("image") - self.image: str | BytesIO = image - - def get_content(self) -> BytesIO | str: - return self.image - - RESPONSE_TYPE: TypeAlias = str | MessageContent RESPONSE_CALLBACK_TYPE = Callable[[RESPONSE_TYPE], Awaitable[Any]] | None @@ -446,6 +375,7 @@ class ChatObject: response: UniResponse[str, None] # (lateinit) Response preset: ModelPreset # preset used in this call config: AmritaConfig # config used in this call + session: SessionData | None # (lateinit) Session data _response_queue: asyncio.Queue[Any] _overflow_queue: asyncio.Queue[Any] _is_running: bool = False # Whether it is running @@ -454,6 +384,8 @@ class ChatObject: _err: BaseException | None = None _queue_done: bool = False _has_consumer: bool = False + _hook_kwargs: dict[str, Any] + _hook_args: tuple[Any, ...] _callback_fun: RESPONSE_CALLBACK_TYPE = None _callback_lock: Lock __done_marker = object() @@ -468,6 +400,8 @@ def __init__( config: AmritaConfig | None = None, preset: ModelPreset | None = None, auto_create_session: bool = False, + hook_args: tuple[Any, ...] = (), + hook_kwargs: dict[str, Any] = {}, queue_size: int = 25, overflow_queue_size: int = 45, ) -> None: @@ -482,13 +416,16 @@ def __init__( config: Config used for this call preset: Preset used for this call auto_create_session: Whether to automatically create a session if it does not exist + hook_args: Arguments could be passed to the Matcher function + hook_kwargs: Keyword arguments could be passed to the Matcher function queue_size: Maximum number of message chunks to be stored in the queue overflow_queue_size: Maximum number of message chunks to be stored in the overflow queue """ sm = SessionsManager() if auto_create_session and not sm.is_session_registered(session_id): sm.init_session(session_id) - session = sm.get_session_data(session_id, None) + session: SessionData | None = sm.get_session_data(session_id, None) + self.session = session self.train = train self.data = context or sm.get_session_data(session_id).memory self.session_id = session_id @@ -505,6 +442,9 @@ def __init__( if session else PresetManager().get_default_preset() ) + # Hook args + self._hook_args = hook_args + self._hook_kwargs = hook_kwargs # Initialize async queue for streaming responses self._response_queue = asyncio.Queue(queue_size) @@ -822,7 +762,15 @@ async def _process_chat( user_input=self.user_input, original_context=messages, # Use the original context ) - await MatcherManager.trigger_event(chat_event, self.config) + await MatcherManager.trigger_event( + chat_event, + self.config, + self, + self.preset, + *self._hook_args, + session=self.session, + **self._hook_kwargs, + ) self.data.messages = chat_event.get_context_messages().unwrap( exclude_system=True ) @@ -844,7 +792,15 @@ async def _process_chat( self.response = response logger.debug("Triggering chat events..") chat_event = CompletionEvent(self.user_input, messages, self, response.content) - await MatcherManager.trigger_event(chat_event, self.config) + await MatcherManager.trigger_event( + chat_event, + self.config, + self, + self.preset, + session=self.session, + *self._hook_args, + **self._hook_kwargs, + ) response.content = chat_event.model_response data.messages.append( Message[str]( diff --git a/src/amrita_core/libchat.py b/src/amrita_core/libchat.py index c839654..494e9fa 100644 --- a/src/amrita_core/libchat.py +++ b/src/amrita_core/libchat.py @@ -10,7 +10,9 @@ from .config import AmritaConfig, get_config from .logging import debug_log from .protocol import ( + COMPLETION_RETURNING, AdapterManager, + MessageContent, ModelAdapter, ) from .tokenizer import hybrid_token_count @@ -210,7 +212,7 @@ async def call_completion( messages: CONTENT_LIST_TYPE, preset: ModelPreset | None = None, config: AmritaConfig | None = None, -) -> AsyncGenerator[str | UniResponse[str, None], None]: +) -> AsyncGenerator[COMPLETION_RETURNING, None]: """Get chat response from the model. Args: @@ -240,7 +242,7 @@ async def inner(): async def get_last_response( - generator: AsyncGenerator[str | UniResponse[str, None], None], + generator: AsyncGenerator[str | MessageContent | UniResponse[str, None], None], ) -> UniResponse[str, None]: """Extract the last UniResponse from a response generator. diff --git a/src/amrita_core/protocol.py b/src/amrita_core/protocol.py index 0c14313..d27e8be 100644 --- a/src/amrita_core/protocol.py +++ b/src/amrita_core/protocol.py @@ -1,9 +1,17 @@ from __future__ import annotations +import base64 from abc import ABC, abstractmethod from collections.abc import AsyncGenerator, Iterable from dataclasses import dataclass, field -from typing import Any +from io import BytesIO +from pathlib import Path +from typing import Any, TypedDict + +import aiofiles +import aiohttp +import filetype +from filetype.types.base import Type from amrita_core.config import AmritaConfig, get_config @@ -12,22 +20,134 @@ from .types import ModelPreset, ToolCall, UniResponse -class ResponseWrapper( - ABC -): # It will be used in next generation (planned on AmritaCore 1.x) - """Base class for response wrapper""" +def get_image_format(file: Path | bytes): + kind: Type | None = filetype.guess(file) + if kind is None: + return + assert isinstance(kind.mime, str) + if kind and kind.mime.startswith("image/"): + assert isinstance(kind.extension, str) + return kind.extension.lower() # return 'png', 'jpeg' or 'gif' etc. + + +class MessageContent(ABC): + """Abstract base class for different types of message content + + This allows for various types of content to be yielded by the chat manager, + not just strings. Subclasses should implement their own representation. + """ - @abstractmethod def __str__(self) -> str: - """Get response content""" + return self.get_content() - @abstractmethod - def get_type(self) -> str: - """Get the type of the response""" + def __init__(self, content_type: str): + self.type = content_type @abstractmethod + def get_content(self): + """Return the actual content of the message""" + raise NotImplementedError("Subclasses must implement get_content method") + + +class RawMessageContent(MessageContent, ABC): + """Raw message content implementation abstract class""" + + def __init__(self, raw_data: Any): + super().__init__("raw") + self.raw_data = raw_data + + def get_content(self): + return self.raw_data + + +class StringMessageContent(MessageContent): + """String type message content implementation""" + + def __init__(self, text: str): + super().__init__("string") + self.text = text + + def get_content(self) -> str: + return self.text + + +class MessageMetadata(TypedDict): + content: str + metadata: dict[str, Any] + + +class MessageWithMetadata(MessageContent): + """Message with additional metadata""" + + def __init__(self, content: str, metadata: dict[str, Any]): + super().__init__("metadata") + self.content = content + self.metadata = metadata + def get_content(self) -> Any: - """Get the content of the response""" + return self.content + + def get_metadata(self) -> dict: + return self.metadata + + def get_full_content(self) -> MessageMetadata: + return MessageMetadata(content=self.content, metadata=self.metadata) + + +class ImageMessage(MessageContent): + """Image message""" + + def __init__(self, image: str | BytesIO | bytes): + """Construct a new ImageMessage object. + + Args: + image (str | BytesIO | bytes): The image to be responded with, str: URL, BytesIO: file object, bytes: Base64 encoded image + """ + super().__init__("image") + self.image: str | BytesIO | bytes = image + + async def get_image( + self, headers: dict[str, None] | None = None + ) -> BytesIO | bytes: + if isinstance(self.image, str): + self.image = await self.curl_image(headers) + return self.image + + async def curl_image(self, extra_headers: dict | None = None) -> bytes: + if isinstance(self.image, str): + headers = { + "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.90 Safari/537.36" + } + headers.update(extra_headers or {}) + async with aiohttp.ClientSession(headers=headers) as session: + async with session.get(self.image) as response: + if response.status != 200: + raise ValueError(f"Failed to download image from {self.image}") + obj = await response.read() + return obj + raise ValueError("Image must be a URL to use this method") + + def get_content(self) -> str: + if isinstance(self.image, str): + return f"![]({self.image})" + elif isinstance(self.image, BytesIO): + self.image = self.image.getvalue() + image_type = get_image_format(self.image) + if not image_type: + return "[Unsupported image format]" + return f"![](data:image/{image_type};base64,{base64.b64encode(self.image).decode()})" + + async def save_to(self, path: Path, headers: dict | None = None): + async with aiofiles.open(path, "wb") as f: + if isinstance(self.image, BytesIO): + await f.write(self.image.read()) + elif isinstance(self.image, bytes): + await f.write(self.image) + else: + await f.write(await self.curl_image(headers)) + + +COMPLETION_RETURNING = MessageContent | str | UniResponse[str, None] @dataclass @@ -46,7 +166,7 @@ def __init_subclass__(cls) -> None: @abstractmethod async def call_api( self, messages: Iterable - ) -> AsyncGenerator[str | UniResponse[str, None], None]: + ) -> AsyncGenerator[COMPLETION_RETURNING, None]: yield "" async def call_tools( diff --git a/src/amrita_core/tools/mcp.py b/src/amrita_core/tools/mcp.py index 6d7d79d..0b2182e 100644 --- a/src/amrita_core/tools/mcp.py +++ b/src/amrita_core/tools/mcp.py @@ -22,7 +22,7 @@ MCPToolSchema, ToolData, ToolFunctionSchema, - cast_mcp_properties_to_openai, + cast_mcp_properties_to_amrita, ) MCP_SERVER_SCRIPT_TYPE = ClientTransportT @@ -97,7 +97,7 @@ async def _connect(self, update_tools: bool = False): for i in await self.mcp_client.list_tools() ] logger.info(f"Available tools: {[tool.name for tool in self.tools]}") - self._cast_tool_to_openai() + self._cast_tool_to_amrita() def _format_tools_for_openai(self): """Convert MCP tool format to OpenAI tool format""" @@ -111,7 +111,7 @@ def _format_tools_for_openai(self): parameters=FunctionParametersSchema( type="object", required=tool.inputSchema.required, - properties=cast_mcp_properties_to_openai( + properties=cast_mcp_properties_to_amrita( property=tool.inputSchema.properties ), ), @@ -121,7 +121,7 @@ def _format_tools_for_openai(self): ] return openai_tools - def _cast_tool_to_openai(self) -> None: + def _cast_tool_to_amrita(self) -> None: self.openai_tools = self._format_tools_for_openai() def get_tools(self) -> list[ToolFunctionSchema]: diff --git a/src/amrita_core/tools/models.py b/src/amrita_core/tools/models.py index 6ba27c4..236d968 100644 --- a/src/amrita_core/tools/models.py +++ b/src/amrita_core/tools/models.py @@ -44,7 +44,7 @@ def on_none(value: Any | None) -> bool: return value is None -def cast_mcp_properties_to_openai( +def cast_mcp_properties_to_amrita( property: dict[str, MCP_OBJECT_TYPE], ) -> dict[str, FunctionPropertySchema]: """ diff --git a/src/amrita_core/types.py b/src/amrita_core/types.py index 7fbc3e3..dcdaa16 100644 --- a/src/amrita_core/types.py +++ b/src/amrita_core/types.py @@ -3,7 +3,7 @@ import json import time import typing -from collections.abc import Iterable +from collections.abc import Iterable, Sequence from copy import deepcopy from pathlib import Path from typing import Any, Generic, Literal @@ -163,16 +163,11 @@ class TextContent(Content): "text": TextContent, } -USER_INPUT = list[TextContent | ImageContent] | str +USER_INPUT = Sequence[Content] | str | 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From: John Richard Date: Thu, 12 Feb 2026 14:34:14 +0800 Subject: [PATCH 2/2] fix: types --- src/amrita_core/chatmanager.py | 4 ++-- src/amrita_core/protocol.py | 9 ++++----- 2 files changed, 6 insertions(+), 7 deletions(-) diff --git a/src/amrita_core/chatmanager.py b/src/amrita_core/chatmanager.py index 133abde..044072e 100644 --- a/src/amrita_core/chatmanager.py +++ b/src/amrita_core/chatmanager.py @@ -401,7 +401,7 @@ def __init__( preset: ModelPreset | None = None, auto_create_session: bool = False, hook_args: tuple[Any, ...] = (), - hook_kwargs: dict[str, Any] = {}, + hook_kwargs: dict[str, Any] | None = None, queue_size: int = 25, overflow_queue_size: int = 45, ) -> None: @@ -444,7 +444,7 @@ def __init__( ) # Hook args self._hook_args = hook_args - self._hook_kwargs = hook_kwargs + self._hook_kwargs = hook_kwargs or {} # Initialize async queue for streaming responses self._response_queue = asyncio.Queue(queue_size) diff --git a/src/amrita_core/protocol.py b/src/amrita_core/protocol.py index d27e8be..10d6147 100644 --- a/src/amrita_core/protocol.py +++ b/src/amrita_core/protocol.py @@ -106,9 +106,7 @@ def __init__(self, image: str | BytesIO | bytes): super().__init__("image") self.image: str | BytesIO | bytes = image - async def get_image( - self, headers: dict[str, None] | None = None - ) -> BytesIO | bytes: + async def get_image(self, headers: dict[str, Any] | None = None) -> BytesIO | bytes: if isinstance(self.image, str): self.image = await self.curl_image(headers) return self.image @@ -123,7 +121,8 @@ async def curl_image(self, extra_headers: dict | None = None) -> bytes: async with session.get(self.image) as response: if response.status != 200: raise ValueError(f"Failed to download image from {self.image}") - obj = await response.read() + bt = await response.read() + obj = base64.b64encode(bt) return obj raise ValueError("Image must be a URL to use this method") @@ -135,7 +134,7 @@ def get_content(self) -> str: image_type = get_image_format(self.image) if not image_type: return "[Unsupported image format]" - return f"![](data:image/{image_type};base64,{base64.b64encode(self.image).decode()})" + return f"![](data:image/{image_type};base64,{self.image.decode('utf-8')})" async def save_to(self, path: Path, headers: dict | None = None): async with aiofiles.open(path, "wb") as f: