> ## 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.

# BedrockChat 集成

> 使用 LangChain JavaScript 集成 BedrockChat 聊天模型。

[Amazon Bedrock](https://aws.amazon.com/bedrock/) 是一项完全托管的服务，通过单一 API 提供来自领先 AI 公司（如 AI21 Labs、Anthropic、Cohere、Meta、Stability AI 和 Amazon）的高性能基础模型（FMs）选择，以及构建具有安全性、隐私性和负责任 AI 的生成式 AI 应用程序所需的一系列广泛功能。

本文将帮助您开始使用 `BedrockChat` [聊天模型](/oss/javascript/langchain/models)。有关 `BedrockChat` 所有功能和配置的详细文档，请参阅 [API 参考](https://reference.langchain.com/javascript/langchain-community/chat_models/bedrock/BedrockChat)。

<Tip>
  新的 [`ChatBedrockConverse` 聊天模型现已通过专用的 `@langchain/aws`](/oss/javascript/integrations/chat/bedrock_converse) 集成包提供。使用此包可以通过更多模型进行 [工具调用](/oss/javascript/langchain/tools)。
</Tip>

## 概述

### 集成详情

| 类                                                                                                               | 包                                                                | 可序列化 | [Python 支持](https://python.langchain.com/docs/integrations/chat/bedrock/) |                                                  下载量                                                 |                                                 版本                                                |
| :-------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------- | :--: | :-----------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------: |
| [`BedrockChat`](https://reference.langchain.com/javascript/langchain-community/chat_models/bedrock/BedrockChat) | [`@langchain/community`](https://npmjs.com/@langchain/community) |   ✅  |                                     ✅                                     | ![NPM - Downloads](https://img.shields.io/npm/dm/@langchain/community?style=flat-square\&label=%20&) | ![NPM - Version](https://img.shields.io/npm/v/@langchain/community?style=flat-square\&label=%20&) |

### 模型功能

有关如何使用特定功能的指南，请参阅下表标题中的链接。

| [工具调用](/oss/javascript/langchain/tools) | [结构化输出](/oss/javascript/langchain/structured-output) | [图像输入](/oss/javascript/langchain/messages#multimodal) | 音频输入 | 视频输入 | [令牌级流式传输](/oss/javascript/langchain/streaming/) | [令牌使用量](/oss/javascript/langchain/models#token-usage) | [对数概率](/oss/javascript/langchain/models#log-probabilities) |
| :-------------------------------------: | :--------------------------------------------------: | :---------------------------------------------------: | :--: | :--: | :---------------------------------------------: | :---------------------------------------------------: | :--------------------------------------------------------: |
|                    ✅                    |                           ✅                          |                           ✅                           |   ❌  |   ❌  |                        ✅                        |                           ✅                           |                              ❌                             |

## 设置

要访问 Bedrock 模型，您需要创建一个 AWS 账户，设置 Bedrock API 服务，获取访问密钥 ID 和密钥，并安装 `@langchain/community` 集成包。

### 凭证

请前往 [AWS 文档](https://docs.aws.amazon.com/bedrock/latest/userguide/getting-started.html) 注册 AWS 并设置您的凭证。您还需要为您的账户启用模型访问权限，您可以 [按照这些说明](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html) 进行操作。

如果您希望自动追踪模型调用，还可以通过取消注释以下内容来设置您的 [LangSmith](/langsmith/home) API 密钥：

```bash theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
# export LANGSMITH_TRACING="true"
# export LANGSMITH_API_KEY="your-api-key"
```

### 安装

LangChain `BedrockChat` 集成位于 `@langchain/community` 包中。您还需要安装几个官方的 AWS 包作为对等依赖项：

<CodeGroup>
  ```bash npm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  npm install @langchain/community @langchain/core @aws-crypto/sha256-js @aws-sdk/credential-provider-node @smithy/protocol-http @smithy/signature-v4 @smithy/eventstream-codec @smithy/util-utf8 @aws-sdk/types
  ```

  ```bash yarn theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  yarn add @langchain/community @langchain/core @aws-crypto/sha256-js @aws-sdk/credential-provider-node @smithy/protocol-http @smithy/signature-v4 @smithy/eventstream-codec @smithy/util-utf8 @aws-sdk/types
  ```

  ```bash pnpm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  pnpm add @langchain/community @langchain/core @aws-crypto/sha256-js @aws-sdk/credential-provider-node @smithy/protocol-http @smithy/signature-v4 @smithy/eventstream-codec @smithy/util-utf8 @aws-sdk/types
  ```
</CodeGroup>

您还可以在 Web 环境（如 Edge 函数或 Cloudflare Workers）中使用 BedrockChat，方法是省略 @aws-sdk/credential-provider-node 依赖项并使用 Web 入口点：

<CodeGroup>
  ```bash npm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  npm install @langchain/community @langchain/core @aws-crypto/sha256-js @smithy/protocol-http @smithy/signature-v4 @smithy/eventstream-codec @smithy/util-utf8 @aws-sdk/types
  ```

  ```bash yarn theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  yarn add @langchain/community @langchain/core @aws-crypto/sha256-js @smithy/protocol-http @smithy/signature-v4 @smithy/eventstream-codec @smithy/util-utf8 @aws-sdk/types
  ```

  ```bash pnpm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  pnpm add @langchain/community @langchain/core @aws-crypto/sha256-js @smithy/protocol-http @smithy/signature-v4 @smithy/eventstream-codec @smithy/util-utf8 @aws-sdk/types
  ```
</CodeGroup>

## 实例化

目前，聊天模型集成仅支持 Anthropic、Cohere 和 Mistral 模型。对于来自 AI21 或 Amazon 的基础模型，请参阅 [文本生成的 Bedrock 变体](/oss/javascript/integrations/llms/bedrock/)。

有几种不同的方式可以通过 AWS 进行身份验证 - 以下示例依赖于在环境变量中设置的访问密钥、秘密访问密钥和区域：

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
import { BedrockChat } from "@langchain/community/chat_models/bedrock";

const llm = new BedrockChat({
  model: "anthropic.claude-3-5-sonnet-20240620-v1:0",
  region: process.env.BEDROCK_AWS_REGION,
  credentials: {
    accessKeyId: process.env.BEDROCK_AWS_ACCESS_KEY_ID!,
    secretAccessKey: process.env.BEDROCK_AWS_SECRET_ACCESS_KEY!,
  },
  // endpointUrl: "custom.amazonaws.com",
  // modelKwargs: {
  //   anthropic_version: "bedrock-2023-05-31",
  // },
});
```

## 调用

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const aiMsg = await llm.invoke([
  [
    "system",
    "You are a helpful assistant that translates English to French. Translate the user sentence.",
  ],
  ["human", "I love programming."],
])
aiMsg
```

```text theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
AIMessage {
  "content": "J'adore la programmation.",
  "additional_kwargs": {
    "id": "msg_bdrk_01RwhfuWkLLcp7ks1X3u8bwd"
  },
  "response_metadata": {
    "type": "message",
    "role": "assistant",
    "model": "claude-3-5-sonnet-20240620",
    "stop_reason": "end_turn",
    "stop_sequence": null,
    "usage": {
      "input_tokens": 29,
      "output_tokens": 11
    }
  },
  "tool_calls": [],
  "invalid_tool_calls": []
}
```

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
console.log(aiMsg.content)
```

```text theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
J'adore la programmation.
```

## 工具调用

Bedrock 模型的工具调用方式与 [其他模型](/oss/javascript/langchain/tools) 类似，但请注意并非所有 Bedrock 模型都支持工具调用。请参阅 [AWS 模型文档](https://docs.aws.amazon.com/bedrock/latest/APIReference/welcome.html) 了解更多信息。

***

## API 参考

有关 `BedrockChat` 所有功能和配置的详细文档，请参阅 [API 参考](https://reference.langchain.com/javascript/langchain-community/chat_models/bedrock/BedrockChat)。

***

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