> ## Documentation Index > Fetch the complete documentation index at: https://langchain-zh.cn/llms.txt > Use this file to discover all available pages before exploring further. # ChatAnthropic 集成 > 使用 LangChain Python 与 ChatAnthropic 聊天模型集成。 你可以在 [Claude](https://platform.claude.com/docs/en/about-claude/models/overview) 文档中找到关于 Anthropic 最新模型、其成本、上下文窗口和支持的输入类型的信息。 **API 参考** 有关所有功能和配置选项的详细文档，请前往 [`ChatAnthropic`](https://reference.langchain.com/python/langchain-anthropic/chat_models/ChatAnthropic) API 参考。 **AWS Bedrock 和 Google VertexAI** 请注意，某些 Anthropic 模型也可以通过 AWS Bedrock 和 Google VertexAI 访问。请参阅 [`ChatBedrock`](/oss/python/integrations/chat/bedrock/) 和 [`ChatVertexAI`](/oss/python/integrations/chat/google_vertex_ai#anthropic-on-vertex-ai) 集成，以通过这些服务使用 Anthropic 模型。 对于 AWS Bedrock 上具有与 `ChatAnthropic` 相同 API 的 Anthropic 模型，请使用 `langchain-aws` 中的 [`ChatAnthropicBedrock`](/oss/python/integrations/chat/bedrock#chatanthropicbedrock)。 ## 概述 ### 集成详情 | 类 | 包 | 可序列化 | JS/TS 支持 | 下载量 | 最新版本 | | :------------------------------------------------------------------------------------------------------ | :----------------------------------------------------------------------------------- | :--: | :------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | [`ChatAnthropic`](https://reference.langchain.com/python/langchain-anthropic/chat_models/ChatAnthropic) | [`langchain-anthropic`](https://reference.langchain.com/python/langchain-anthropic/) | beta | ✅ [(npm)](https://js.langchain.com/docs/integrations/chat/anthropic) | Downloads per month | PyPI - Latest version | ### 模型功能 | [工具调用](/oss/python/langchain/tools) | [结构化输出](/oss/python/langchain/structured-output) | [图像输入](/oss/python/langchain/messages#multimodal) | 音频输入 | 视频输入 | [令牌级流式传输](/oss/python/langchain/streaming/) | 原生异步 | [令牌使用量](/oss/python/langchain/models#token-usage) | [对数概率](/oss/python/langchain/models#log-probabilities) | | :---------------------------------: | :----------------------------------------------: | :-----------------------------------------------: | :--: | :--: | :-----------------------------------------: | :--: | :-----------------------------------------------: | :----------------------------------------------------: | | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ## 设置 要访问 Anthropic (Claude) 模型，你需要安装 `langchain-anthropic` 集成包并获取一个 [Claude](https://platform.claude.com/docs/en/get-started#prerequisites) API 密钥。 ### 安装 ```bash pip theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} pip install -U langchain-anthropic ``` ```bash uv theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} uv add langchain-anthropic ``` ### 凭据 前往 [Claude 控制台](https://console.anthropic.com) 注册并生成 Claude API 密钥。完成后，设置 `ANTHROPIC_API_KEY` 环境变量： ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} import getpass import os if "ANTHROPIC_API_KEY" not in os.environ: os.environ["ANTHROPIC_API_KEY"] = getpass.getpass("输入你的 Anthropic API 密钥：") ``` 要启用模型调用的自动跟踪，请设置你的 [LangSmith](/langsmith/home) API 密钥： ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} os.environ["LANGSMITH_API_KEY"] = getpass.getpass("输入你的 LangSmith API 密钥：") os.environ["LANGSMITH_TRACING"] = "true" ``` ## 实例化 现在我们可以实例化模型对象并生成聊天补全： ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} from langchain_anthropic import ChatAnthropic model = ChatAnthropic( model="claude-haiku-4-5-20251001", # temperature=, # max_tokens=, # timeout=, # max_retries=, # ... ) ``` 有关所有可用实例化参数的详细信息，请参阅 [`ChatAnthropic`](https://reference.langchain.com/python/langchain-anthropic/chat_models/ChatAnthropic) API 参考。 ## 调用 ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} messages = [ ( "system", "你是一位乐于助人的翻译。将用户句子翻译成法语。", ), ( "human", "I love programming.", ), ] model.invoke(messages) ``` ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} print(ai_msg.text) ``` ```text theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} J'adore la programmation. ``` ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} for chunk in model.stream(messages): print(chunk.text, end="") ``` ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} AIMessageChunk(content="J", id="run-272ff5f9-8485-402c-b90d-eac8babc5b25") AIMessageChunk(content="'", id="run-272ff5f9-8485-402c-b90d-eac8babc5b25") AIMessageChunk(content="a", id="run-272ff5f9-8485-402c-b90d-eac8babc5b25") AIMessageChunk(content="ime", id="run-272ff5f9-8485-402c-b90d-eac8babc5b25") AIMessageChunk(content=" la", id="run-272ff5f9-8485-402c-b90d-eac8babc5b25") AIMessageChunk(content=" programm", id="run-272ff5f9-8485-402c-b90d-eac8babc5b25") AIMessageChunk(content="ation", id="run-272ff5f9-8485-402c-b90d-eac8babc5b25") AIMessageChunk(content=".", id="run-272ff5f9-8485-402c-b90d-eac8babc5b25") ``` 要从流中聚合完整消息： ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} stream = model.stream(messages) full = next(stream) for chunk in stream: full += chunk full ``` ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} AIMessageChunk(content="J'aime la programmation.", id="run-b34faef0-882f-4869-a19c-ed2b856e6361") ``` ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} await model.ainvoke(messages) # stream async for chunk in (await model.astream(messages)) # batch await model.abatch([messages]) ``` ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} AIMessage( content="J'aime la programmation.", response_metadata={ "id": "msg_01Trik66aiQ9Z1higrD5XFx3", "model": "claude-sonnet-4-6", "stop_reason": "end_turn", "stop_sequence": None, "usage": {"input_tokens": 25, "output_tokens": 11}, }, id="run-5886ac5f-3c2e-49f5-8a44-b1e92808c929-0", usage_metadata={ "input_tokens": 25, "output_tokens": 11, "total_tokens": 36, }, ) ``` 在我们的 [模型](/oss/python/langchain/models#invocation) 指南中了解更多支持的调用方法。 ## 内容块 当使用工具、[扩展思考](#extended-thinking) 和其他功能时，来自单个 Anthropic [`AIMessage`](https://reference.langchain.com/python/langchain-core/messages/ai/AIMessage) 的内容可以是一个字符串，也可以是 Anthropic 内容块的列表。 例如，当 Anthropic 模型调用一个工具时，工具调用是消息内容的一部分（同时也在标准化的 [`AIMessage.tool_calls`](https://reference.langchain.com/python/langchain/messages/#langchain.messages.AIMessage.tool_calls) 中公开）： ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} from langchain_anthropic import ChatAnthropic from typing_extensions import Annotated model = ChatAnthropic(model="claude-haiku-4-5-20251001") def get_weather( location: Annotated[str, ..., "Location as city and state."] ) -> str: """Get the weather at a location.""" return "It's sunny." model_with_tools = model.bind_tools([get_weather]) response = model_with_tools.invoke("Which city is hotter today: LA or NY?") response.content ``` ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} [{'text': "I'll help you compare the temperatures of Los Angeles and New York by checking their current weather. I'll retrieve the weather for both cities.", 'type': 'text'}, {'id': 'toolu_01CkMaXrgmsNjTso7so94RJq', 'input': {'location': 'Los Angeles, CA'}, 'name': 'get_weather', 'type': 'tool_use'}, {'id': 'toolu_01SKaTBk9wHjsBTw5mrPVSQf', 'input': {'location': 'New York, NY'}, 'name': 'get_weather', 'type': 'tool_use'}] ``` 使用 `content_blocks` 将以 LangChain 的标准格式呈现内容，该格式与其他模型提供商保持一致。阅读更多关于 [内容块](/oss/python/langchain/messages#standard-content-blocks) 的信息。 ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} response.content_blocks ``` 你也可以使用 `tool_calls` 属性以标准格式专门访问工具调用： ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} response.tool_calls ``` ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} [{'name': 'GetWeather', 'args': {'location': 'Los Angeles, CA'}, 'id': 'toolu_01Ddzj5PkuZkrjF4tafzu54A'}, {'name': 'GetWeather', 'args': {'location': 'New York, NY'}, 'id': 'toolu_012kz4qHZQqD4qg8sFPeKqpP'}] ``` ## 工具 Anthropic 的工具使用功能允许你定义 Claude 在对话期间可以调用的外部函数。这实现了动态信息检索、计算以及与外部系统的交互。 有关如何将工具绑定到模型实例的详细信息，请参阅 [`ChatAnthropic.bind_tools`](https://reference.langchain.com/python/langchain-anthropic/chat_models/ChatAnthropic/bind_tools)。 关于 Claude 内置工具（代码执行、网页浏览、文件 API 等）的信息，请参阅 [内置工具](#built-in-tools)。 ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} from pydantic import BaseModel, Field class GetWeather(BaseModel): '''Get the current weather in a given location''' location: str = Field(description="The city and state, e.g. San Francisco, CA") class GetPopulation(BaseModel): '''Get the current population in a given location''' location: str = Field(description="The city and state, e.g. San Francisco, CA") model_with_tools = model.bind_tools([GetWeather, GetPopulation]) # [!code highlight] ai_msg = model_with_tools.invoke("Which city is hotter today and which is bigger: LA or NY?") ai_msg.tool_calls ``` ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} [ { "name": "GetWeather", "args": {"location": "Los Angeles, CA"}, "id": "toolu_01KzpPEAgzura7hpBqwHbWdo", }, { "name": "GetWeather", "args": {"location": "New York, NY"}, "id": "toolu_01JtgbVGVJbiSwtZk3Uycezx", }, { "name": "GetPopulation", "args": {"location": "Los Angeles, CA"}, "id": "toolu_01429aygngesudV9nTbCKGuw", }, { "name": "GetPopulation", "args": {"location": "New York, NY"}, "id": "toolu_01JPktyd44tVMeBcPPnFSEJG", }, ] ``` ### 严格工具使用 严格工具使用需要： * Claude Sonnet 4.5 或 Opus 4.1。 * `langchain-anthropic>=1.1.0` Anthropic 支持选择性的 [严格模式工具调用](https://platform.claude.com/docs/en/build-with-claude/structured-outputs)。这通过约束解码保证了工具名称和参数经过验证且类型正确。 没有严格模式时，Claude 偶尔会生成破坏应用程序的无效工具输入： * **类型不匹配**：`passengers: "2"` 而不是 `passengers: 2` * **缺少必填字段**：省略了你的函数期望的字段 * **无效的枚举值**：超出允许集合的值 * **模式违规**：嵌套对象不符合预期结构 严格工具使用保证模式合规的工具调用： * 工具输入严格遵循你的 `input_schema` * 保证字段类型和必填字段 * 消除对格式错误输入的异常处理 * 使用的工具 `name` 始终来自提供的工具 | 使用严格工具调用 | 使用标准工具调用 | | ---------------------------- | ---------- | | 构建可靠性至关重要的智能体工作流时 | 简单、单轮的工具调用 | | 具有许多参数或嵌套对象的工具时 | 原型设计和实验 | | 需要特定类型（例如 `int` 与 `str`）的函数时 | | 要启用严格工具使用，请在调用 [`bind_tools`](https://reference.langchain.com/python/langchain-anthropic/chat_models/ChatAnthropic/bind_tools) 时指定 `strict=True`。 ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} from langchain_anthropic import ChatAnthropic model = ChatAnthropic(model="claude-sonnet-4-6") def get_weather(location: str) -> str: """Get the weather at a location.""" return "It's sunny." model_with_tools = model.bind_tools([get_weather], strict=True) # [!code highlight] ``` 考虑一个 `passengers` 必须是整数的预订系统： ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} from langchain_anthropic import ChatAnthropic from typing import Literal model = ChatAnthropic(model="claude-sonnet-4-6") def book_flight( destination: str, departure_date: str, passengers: int, # [!code highlight] cabin_class: Literal["economy", "business", "first"] ) -> str: """Book a flight to a destination. Args: destination: The destination city departure_date: Date in YYYY-MM-DD format passengers: Number of passengers (must be an integer) cabin_class: The cabin class for the flight """ return f"Booked {passengers} passengers to {destination}" model_with_tools = model.bind_tools( [book_flight], strict=True, # [!code highlight] tool_choice="any", ) response = model_with_tools.invoke("Book 2 passengers to Tokyo, business class, 2025-01-15") # 使用 strict=True 时，passengers 保证是 int，而不是 "2" 或 "two" print(response.tool_calls[0]["args"]["passengers"]) ``` ```text theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} 2 ``` 严格工具使用有一些需要注意的 JSON 模式限制。有关详细信息，请参阅 [Claude 文档](https://platform.claude.com/docs/en/build-with-claude/structured-outputs#json-schema-limitations)。 如果你的工具模式使用了不支持的功能，你将收到 400 错误。在这些情况下，请简化模式或使用标准（非严格）工具调用。 ### 输入示例 对于复杂的工具，你可以提供使用示例来帮助 Claude 正确理解如何使用它们。这是通过设置工具的 `extras` 参数中的 `input_examples` 来实现的。 ```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} from langchain_anthropic import ChatAnthropic from langchain.tools import tool @tool( extras={ # [!code highlight] "input_examples": [ # [!code highlight] { # [!code highlight] "query": "weather report", # [!code highlight] "location": "San Francisco", # [!code highlight] "format": "detailed" # [!code highlight] }, # [!code highlight] { # [!code highlight] "query": "temperature", # [!code highlight] "location": "New York", # [!code highlight] "format": "brief" # [!code highlight] } # [!code highlight] ] # [!code highlight] } # [!code highlight] ) def search_weather_data(query: str, location: str, format: str = "brief") -> str: """Search weather database with specific query and format preferences. Args: query: The type of weather information to retrieve location: City or region to search format: Output format, either 'brief' or 'detailed' """ return f"{format.title()} {query} for {location}: Data found" model = ChatAnthropic(model="claude-sonnet-4-6") model_with_tools = model.bind_tools([search_weather_data]) response = model_with_tools.invoke( "Get me a detailed weather report for Seattle" ) ``` `extras` 参数还支持： * `defer_loading` (bool)：按需加载工具以用于 [工具搜索](#tool-search) * `cache_control` (dict)：为工具启用 [提示缓存](#caching-tools) ### 细粒度工具流式传输 Anthropic 支持 \[细粒度工具 ***
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