> ## 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.
# ChatBedrockConverse 集成
> 使用 LangChain JavaScript 集成 ChatBedrockConverse 聊天模型。
[Amazon Bedrock Converse](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_Converse.html) 是一项全托管服务，通过 API 提供来自领先 AI 初创公司和亚马逊的基础模型（FMs）。您可以从广泛的 FMs 中选择最适合您用例的模型。它为 Bedrock 模型提供了统一的对话接口，但尚未完全支持旧版 [Bedrock 模型服务](/oss/javascript/integrations/chat/bedrock) 中的所有功能。
本文将帮助您开始使用 `ChatBedrockConverse` [聊天模型](/oss/javascript/langchain/models)。有关 `ChatBedrockConverse` 所有功能和配置的详细文档，请参阅 [API 参考](https://reference.langchain.com/javascript/langchain-aws/ChatBedrockConverse)。
## 概述
### 集成详情
| 类 | 包 | 可序列化 | [Python 支持](https://python.langchain.com/docs/integrations/chat/bedrock/#beta-bedrock-converse-api) | 下载量 | 版本 |
| :---------------------------------------------------------------------------------------------------- | :--------------------------------------------------- | :--: | :-------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------: |
| [`ChatBedrockConverse`](https://reference.langchain.com/javascript/langchain-aws/ChatBedrockConverse) | [`@langchain/aws`](https://npmjs.com/@langchain/aws) | ✅ | ✅ |  |  |
### 模型功能
下表标题中的链接提供了如何使用特定功能的指南。
| [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 和秘密密钥，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，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 的 `ChatBedrockConverse` 集成位于 `@langchain/aws` 包中：
```bash npm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
npm install @langchain/aws @langchain/core
```
```bash yarn theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
yarn add @langchain/aws @langchain/core
```
```bash pnpm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
pnpm add @langchain/aws @langchain/core
```
## 实例化
现在我们可以实例化模型对象并生成聊天补全。
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 { ChatBedrockConverse } from "@langchain/aws";
const llm = new ChatBedrockConverse({
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!,
},
});
```
## 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 {
"id": "f5dc5791-224e-4fe5-ba2e-4cc51d9e7795",
"content": "J'adore la programmation.",
"additional_kwargs": {},
"response_metadata": {
"$metadata": {
"httpStatusCode": 200,
"requestId": "f5dc5791-224e-4fe5-ba2e-4cc51d9e7795",
"attempts": 1,
"totalRetryDelay": 0
},
"metrics": {
"latencyMs": 584
},
"stopReason": "end_turn",
"usage": {
"inputTokens": 29,
"outputTokens": 11,
"totalTokens": 40
}
},
"tool_calls": [],
"invalid_tool_calls": [],
"usage_metadata": {
"input_tokens": 29,
"output_tokens": 11,
"total_tokens": 40
}
}
```
```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 `ChatBedrockConverse` 所有功能和配置的详细文档，请参阅 [API 参考](https://reference.langchain.com/javascript/langchain-aws/ChatBedrockConverse)。
***
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