追踪 Amazon Bedrock 应用

pip install boto3 langsmith

npm install @aws-sdk/client-bedrock-runtime langsmith

import boto3
from langsmith import traceable

# 初始化 Bedrock 运行时客户端（确保已设置 AWS 凭证和区域）
bedrock = boto3.client("bedrock-runtime", region_name="us-east-1")
model_id = "anthropic.claude-haiku-4-5-20251001-v1:0"  # 示例 Bedrock 模型 ID

# 装饰模型调用函数以自动捕获带有标签/元数据的追踪信息
@traceable(tags=["aws-bedrock", "langsmith", "integration-test"],
           metadata={"env": "dev", "model_provider": "bedrock", "model_id": "claude-3-haiku"})
def generate_text(prompt: str) -> str:
    # 为对话 API 准备单轮对话输入
    messages = [
        {"role": "user", "content": [{"text": prompt}]}
    ]
    # 使用统一的对话 API 调用 Bedrock 模型
    response = bedrock.converse(
        modelId=model_id,
        messages=messages,
        inferenceConfig={"maxTokens": 512, "temperature": 0.5, "topP": 0.9}
    )
    # 从响应中提取模型的回复文本
    output_text = response["output"]["message"]["content"][0]["text"]
    return output_text

# 使用提示词调用被追踪的函数
result = generate_text("如何将 AWS Bedrock 模型输出追踪到 LangSmith 以进行调试？")
print(result)

import { BedrockRuntimeClient, ConverseCommand } from "@aws-sdk/client-bedrock-runtime";
import { traceable } from "langsmith";

const client = new BedrockRuntimeClient({ region: "us-east-1" });
const modelId = "anthropic.claude-haiku-4-5-20251001-v1:0";

// 将 Bedrock 调用包装在带有标签和元数据的可追踪函数中
const invokeBedrock = traceable(
  async (userInput: string) => {
    // 为 Bedrock 对话 API 准备对话消息
    const conversation = [
      { role: "user", content: [{ text: userInput }] }
    ];
    // 创建并发送 Bedrock 对话命令（单轮聊天）
    const command = new ConverseCommand({
      modelId,
      messages: conversation,
      inferenceConfig: { maxTokens: 512, temperature: 0.5, topP: 0.9 }
    });
    const response = await client.send(command);
    // 从响应中提取助手的回复文本
    const outputText = response.output?.message?.content[0]?.text;
    return outputText;
  },
  {
    tags: ["aws-bedrock", "langsmith", "integration-test"],
    metadata: { env: "dev", model_provider: "bedrock", model_id: "claude-3-haiku" }
  }
);

// 使用提示词调用被追踪的函数
const answer = await invokeBedrock("如何将 AWS Bedrock 模型输出追踪到 LangSmith 以进行调试？");
console.log(answer);