feat: 集成 AWS Bedrock 支持

- 新增 BedrockClient 客户端实现,支持 Converse API
- 支持两种认证方式:IAM 凭证和 IAM 角色
- 支持对话生成、流式输出、工具调用、多模态、文本嵌入
- 添加配置模板和完整文档
- 更新依赖:aioboto3, botocore
This commit is contained in:
Eric-Terminal
2025-12-06 17:26:40 +08:00
parent c059c7a2f1
commit 2348dc1082
9 changed files with 1115 additions and 2 deletions

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#!/usr/bin/env python3
"""
AWS Bedrock 客户端测试脚本
测试 BedrockClient 的基本功能
"""
import asyncio
import sys
from pathlib import Path
# 添加项目根目录到 Python 路径
project_root = Path(__file__).parent
sys.path.insert(0, str(project_root))
from src.config.api_ada_configs import APIProvider, ModelInfo
from src.llm_models.model_client.bedrock_client import BedrockClient
from src.llm_models.payload_content.message import MessageBuilder
async def test_basic_conversation():
"""测试基本对话功能"""
print("=" * 60)
print("测试 1: 基本对话功能")
print("=" * 60)
# 配置 API Provider请替换为你的真实凭证
provider = APIProvider(
name="bedrock_test",
base_url="", # Bedrock 不需要
api_key="YOUR_AWS_ACCESS_KEY_ID", # 替换为你的 AWS Access Key
client_type="bedrock",
max_retry=2,
timeout=60,
retry_interval=10,
extra_params={
"aws_secret_key": "YOUR_AWS_SECRET_ACCESS_KEY", # 替换为你的 AWS Secret Key
"region": "us-east-1",
},
)
# 配置模型信息
model = ModelInfo(
model_identifier="us.anthropic.claude-3-5-sonnet-20240620-v1:0",
name="claude-3.5-sonnet-bedrock",
api_provider="bedrock_test",
price_in=3.0,
price_out=15.0,
force_stream_mode=False,
)
# 创建客户端
client = BedrockClient(provider)
# 构建消息
builder = MessageBuilder()
builder.add_user_message("你好!请用一句话介绍 AWS Bedrock。")
try:
# 发送请求
response = await client.get_response(
model_info=model, message_list=[builder.build()], max_tokens=200, temperature=0.7
)
print(f"✅ 响应内容: {response.content}")
if response.usage:
print(
f"📊 Token 使用: 输入={response.usage.prompt_tokens}, "
f"输出={response.usage.completion_tokens}, "
f"总计={response.usage.total_tokens}"
)
print("\n测试通过!✅\n")
except Exception as e:
print(f"❌ 测试失败: {e!s}")
import traceback
traceback.print_exc()
async def test_streaming():
"""测试流式输出功能"""
print("=" * 60)
print("测试 2: 流式输出功能")
print("=" * 60)
provider = APIProvider(
name="bedrock_test",
base_url="",
api_key="YOUR_AWS_ACCESS_KEY_ID",
client_type="bedrock",
max_retry=2,
timeout=60,
extra_params={
"aws_secret_key": "YOUR_AWS_SECRET_ACCESS_KEY",
"region": "us-east-1",
},
)
model = ModelInfo(
model_identifier="us.anthropic.claude-3-5-sonnet-20240620-v1:0",
name="claude-3.5-sonnet-bedrock",
api_provider="bedrock_test",
price_in=3.0,
price_out=15.0,
force_stream_mode=True, # 启用流式模式
)
client = BedrockClient(provider)
builder = MessageBuilder()
builder.add_user_message("写一个关于人工智能的三行诗。")
try:
print("🔄 流式响应中...")
response = await client.get_response(
model_info=model, message_list=[builder.build()], max_tokens=100, temperature=0.7
)
print(f"✅ 完整响应: {response.content}")
print("\n测试通过!✅\n")
except Exception as e:
print(f"❌ 测试失败: {e!s}")
async def test_multimodal():
"""测试多模态(图片输入)功能"""
print("=" * 60)
print("测试 3: 多模态功能(需要准备图片)")
print("=" * 60)
print("⏭️ 跳过(需要实际图片文件)\n")
async def test_tool_calling():
"""测试工具调用功能"""
print("=" * 60)
print("测试 4: 工具调用功能")
print("=" * 60)
from src.llm_models.payload_content.tool_option import ToolOption, ToolOptionBuilder, ToolParamType
provider = APIProvider(
name="bedrock_test",
base_url="",
api_key="YOUR_AWS_ACCESS_KEY_ID",
client_type="bedrock",
extra_params={
"aws_secret_key": "YOUR_AWS_SECRET_ACCESS_KEY",
"region": "us-east-1",
},
)
model = ModelInfo(
model_identifier="us.anthropic.claude-3-5-sonnet-20240620-v1:0",
name="claude-3.5-sonnet-bedrock",
api_provider="bedrock_test",
)
# 定义工具
tool_builder = ToolOptionBuilder()
tool_builder.set_name("get_weather").set_description("获取指定城市的天气信息").add_param(
name="city", param_type=ToolParamType.STRING, description="城市名称", required=True
)
tool = tool_builder.build()
client = BedrockClient(provider)
builder = MessageBuilder()
builder.add_user_message("北京今天天气怎么样?")
try:
response = await client.get_response(
model_info=model, message_list=[builder.build()], tool_options=[tool], max_tokens=200
)
if response.tool_calls:
print(f"✅ 模型调用了工具:")
for call in response.tool_calls:
print(f" - 工具名: {call.func_name}")
print(f" - 参数: {call.args}")
else:
print(f"⚠️ 模型没有调用工具,而是直接回复: {response.content}")
print("\n测试通过!✅\n")
except Exception as e:
print(f"❌ 测试失败: {e!s}")
async def main():
"""主测试函数"""
print("\n🚀 AWS Bedrock 客户端测试开始\n")
print("⚠️ 请确保已配置 AWS 凭证!")
print("⚠️ 修改脚本中的 'YOUR_AWS_ACCESS_KEY_ID''YOUR_AWS_SECRET_ACCESS_KEY'\n")
# 运行测试
await test_basic_conversation()
# await test_streaming()
# await test_multimodal()
# await test_tool_calling()
print("=" * 60)
print("🎉 所有测试完成!")
print("=" * 60)
if __name__ == "__main__":
asyncio.run(main())