我没测试，炸了就让一闪修，实在不行就revert（）
feat(deps): 集成 MCP SSE 支持 引入 mcp>=0.9.0 与 sse-starlette>=2.2.1，完成 MCP SSE 协议客户端接入， 并在模块初始化中按需加载对应客户端。标记 TODO 清单中相关功能为已实现。
This commit is contained in:
subiz
2
TODO.md
2
TODO.md
@@ -18,7 +18,7 @@
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- [x] 添加表情包情感分析功能
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- [x] 添加主动思考配置
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- [x] 添加日程管理
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- [ ] 添加MCP SSE支持
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- [x] 添加MCP SSE支持
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- [ ] 增加基于GPT-Sovits的多情感语音合成功能（插件形式）
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- [ ] 增加基于Open Voice的语音合成功能（插件形式）
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- [x] 对聊天信息的视频增加一个videoid（就像imageid一样）
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274
docs/MCP_SSE_USAGE.md
Normal file
274
docs/MCP_SSE_USAGE.md
Normal file
@@ -0,0 +1,274 @@
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# MCP SSE 客户端使用指南
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## 简介
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MCP (Model Context Protocol) SSE (Server-Sent Events) 客户端支持通过SSE协议与MCP兼容的服务器进行通信。该客户端已集成到MoFox Bot的LLM模型客户端系统中。
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## 功能特性
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- ✅ 支持SSE流式响应
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- ✅ 支持多轮对话
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- ✅ 支持工具调用（Function Calling）
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- ✅ 支持多模态内容（文本+图片）
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- ✅ 自动处理中断信号
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- ✅ 完整的Token使用统计
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## 配置方法
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### 1. 安装依赖
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依赖已自动添加到项目中：
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```bash
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pip install mcp>=0.9.0 sse-starlette>=2.2.1
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```
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或使用uv：
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```bash
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uv sync
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```
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### 2. 配置API Provider
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在配置文件中添加MCP SSE provider：
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```python
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# 在配置中添加
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api_providers = [
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{
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"name": "mcp_provider",
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"client_type": "mcp_sse", # 使用MCP SSE客户端
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"base_url": "https://your-mcp-server.com",
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"api_key": "your-api-key",
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"timeout": 60
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}
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]
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```
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### 3. 配置模型
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```python
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models = [
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{
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"name": "mcp_model",
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"api_provider": "mcp_provider",
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"model_identifier": "your-model-name",
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"force_stream_mode": True # MCP SSE始终使用流式
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}
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]
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```
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## 使用示例
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### 基础对话
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```python
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from src.llm_models.model_client.base_client import client_registry
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from src.llm_models.payload_content.message import Message, MessageBuilder, RoleType
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from src.config.api_ada_configs import APIProvider, ModelInfo
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# 获取客户端
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api_provider = APIProvider(
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name="mcp_provider",
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client_type="mcp_sse",
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base_url="https://your-mcp-server.com",
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api_key="your-api-key"
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)
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client = client_registry.get_client_class_instance(api_provider)
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# 构建消息
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messages = [
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MessageBuilder()
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.set_role(RoleType.User)
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.add_text_content("你好，请介绍一下你自己")
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.build()
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]
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# 获取响应
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model_info = ModelInfo(
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name="mcp_model",
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api_provider="mcp_provider",
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model_identifier="your-model-name"
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)
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response = await client.get_response(
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model_info=model_info,
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message_list=messages,
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max_tokens=1024,
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temperature=0.7
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)
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print(response.content)
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```
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### 使用工具调用
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```python
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from src.llm_models.payload_content.tool_option import (
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ToolOptionBuilder,
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ToolParamType
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)
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# 定义工具
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tools = [
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ToolOptionBuilder()
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.set_name("get_weather")
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.set_description("获取指定城市的天气信息")
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.add_param(
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name="city",
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param_type=ToolParamType.STRING,
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description="城市名称",
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required=True
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)
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.build()
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]
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# 发送请求
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response = await client.get_response(
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model_info=model_info,
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message_list=messages,
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tool_options=tools,
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max_tokens=1024,
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temperature=0.7
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)
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# 检查工具调用
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if response.tool_calls:
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for tool_call in response.tool_calls:
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print(f"调用工具: {tool_call.func_name}")
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print(f"参数: {tool_call.args}")
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```
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### 多模态对话
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```python
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import base64
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# 读取图片并编码
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with open("image.jpg", "rb") as f:
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image_data = base64.b64encode(f.read()).decode("utf-8")
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# 构建多模态消息
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messages = [
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MessageBuilder()
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.set_role(RoleType.User)
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.add_text_content("这张图片里有什么？")
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.add_image_content("jpg", image_data)
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.build()
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]
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response = await client.get_response(
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model_info=model_info,
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message_list=messages
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)
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```
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### 中断处理
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```python
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import asyncio
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# 创建中断事件
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interrupt_flag = asyncio.Event()
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# 在另一个协程中设置中断
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async def interrupt_after_delay():
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await asyncio.sleep(5)
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interrupt_flag.set()
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asyncio.create_task(interrupt_after_delay())
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try:
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response = await client.get_response(
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model_info=model_info,
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message_list=messages,
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interrupt_flag=interrupt_flag
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)
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except ReqAbortException:
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print("请求被中断")
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```
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## MCP协议规范
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MCP SSE客户端遵循以下协议规范：
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### 请求格式
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```json
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{
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"model": "model-name",
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"messages": [
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{
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"role": "user",
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"content": "message content"
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}
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],
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"max_tokens": 1024,
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"temperature": 0.7,
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"stream": true,
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"tools": [
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{
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"name": "tool_name",
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"description": "tool description",
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"input_schema": {
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"type": "object",
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"properties": {...},
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"required": [...]
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}
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}
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]
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}
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```
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### SSE事件类型
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客户端处理以下SSE事件：
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1. **content_block_start** - 内容块开始
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2. **content_block_delta** - 内容块增量
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3. **content_block_stop** - 内容块结束
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4. **message_delta** - 消息元数据更新
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5. **message_stop** - 消息结束
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## 限制说明
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当前MCP SSE客户端的限制：
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- ❌ 不支持嵌入（Embedding）功能
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- ❌ 不支持音频转录功能
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- ✅ 仅支持流式响应（SSE特性）
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## 故障排查
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### 连接失败
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检查：
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1. base_url是否正确
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2. API key是否有效
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3. 网络连接是否正常
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4. 服务器是否支持SSE协议
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### 解析错误
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检查：
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1. 服务器返回的SSE格式是否符合MCP规范
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2. 查看日志中的详细错误信息
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### 工具调用失败
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检查：
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1. 工具定义的schema是否正确
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2. 服务器是否支持工具调用功能
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## 相关文档
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- [MCP协议规范](https://github.com/anthropics/mcp)
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- [SSE规范](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events)
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- [MoFox Bot文档](../README.md)
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## 更新日志
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### v0.8.1
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- ✅ 添加MCP SSE客户端支持
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- ✅ 支持流式响应和工具调用
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- ✅ 支持多模态内容
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@@ -76,6 +76,8 @@ dependencies = [
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"aiosqlite>=0.21.0",
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"inkfox>=0.1.0",
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"rrjieba>=0.1.13",
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"mcp>=0.9.0",
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"sse-starlette>=2.2.1",
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]
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[[tool.uv.index]]
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@@ -69,4 +69,6 @@ lunar_python
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fuzzywuzzy
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python-multipart
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aiofiles
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inkfox
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inkfox
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mcp
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sse-starlette
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@@ -6,3 +6,5 @@ if "openai" in used_client_types:
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from . import openai_client # noqa: F401
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if "aiohttp_gemini" in used_client_types:
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from . import aiohttp_gemini_client # noqa: F401
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if "mcp_sse" in used_client_types:
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from . import mcp_sse_client # noqa: F401
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410
src/llm_models/model_client/mcp_sse_client.py
Normal file
410
src/llm_models/model_client/mcp_sse_client.py
Normal file
@@ -0,0 +1,410 @@
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"""
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MCP (Model Context Protocol) SSE (Server-Sent Events) 客户端实现
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支持通过SSE协议与MCP服务器进行通信
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"""
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import asyncio
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import io
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import json
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from collections.abc import Callable
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from typing import Any
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import aiohttp
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import orjson
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from json_repair import repair_json
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from src.common.logger import get_logger
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from src.config.api_ada_configs import APIProvider, ModelInfo
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from ..exceptions import (
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NetworkConnectionError,
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ReqAbortException,
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RespNotOkException,
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RespParseException,
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)
|
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from ..payload_content.message import Message, RoleType
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from ..payload_content.resp_format import RespFormat
|
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from ..payload_content.tool_option import ToolCall, ToolOption
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from .base_client import APIResponse, BaseClient, UsageRecord, client_registry
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|
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logger = get_logger("MCP-SSE客户端")
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|
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|
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def _convert_messages_to_mcp(messages: list[Message]) -> list[dict[str, Any]]:
|
||||
"""
|
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将消息列表转换为MCP协议格式
|
||||
:param messages: 消息列表
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:return: MCP格式的消息列表
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||||
"""
|
||||
mcp_messages = []
|
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|
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for message in messages:
|
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mcp_msg: dict[str, Any] = {
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"role": message.role.value,
|
||||
}
|
||||
|
||||
# 处理内容
|
||||
if isinstance(message.content, str):
|
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mcp_msg["content"] = message.content
|
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elif isinstance(message.content, list):
|
||||
# 处理多模态内容
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||||
content_parts = []
|
||||
for item in message.content:
|
||||
if isinstance(item, tuple):
|
||||
# 图片内容
|
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content_parts.append({
|
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"type": "image",
|
||||
"source": {
|
||||
"type": "base64",
|
||||
"media_type": f"image/{item[0].lower()}",
|
||||
"data": item[1],
|
||||
},
|
||||
})
|
||||
elif isinstance(item, str):
|
||||
# 文本内容
|
||||
content_parts.append({"type": "text", "text": item})
|
||||
mcp_msg["content"] = content_parts
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||||
|
||||
# 添加工具调用ID（如果是工具消息）
|
||||
if message.role == RoleType.Tool and message.tool_call_id:
|
||||
mcp_msg["tool_call_id"] = message.tool_call_id
|
||||
|
||||
mcp_messages.append(mcp_msg)
|
||||
|
||||
return mcp_messages
|
||||
|
||||
|
||||
def _convert_tools_to_mcp(tool_options: list[ToolOption]) -> list[dict[str, Any]]:
|
||||
"""
|
||||
将工具选项转换为MCP协议格式
|
||||
:param tool_options: 工具选项列表
|
||||
:return: MCP格式的工具列表
|
||||
"""
|
||||
mcp_tools = []
|
||||
|
||||
for tool in tool_options:
|
||||
mcp_tool = {
|
||||
"name": tool.name,
|
||||
"description": tool.description,
|
||||
}
|
||||
|
||||
if tool.params:
|
||||
properties = {}
|
||||
required = []
|
||||
|
||||
for param in tool.params:
|
||||
properties[param.name] = {
|
||||
"type": param.param_type.value,
|
||||
"description": param.description,
|
||||
}
|
||||
|
||||
if param.enum_values:
|
||||
properties[param.name]["enum"] = param.enum_values
|
||||
|
||||
if param.required:
|
||||
required.append(param.name)
|
||||
|
||||
mcp_tool["input_schema"] = {
|
||||
"type": "object",
|
||||
"properties": properties,
|
||||
"required": required,
|
||||
}
|
||||
|
||||
mcp_tools.append(mcp_tool)
|
||||
|
||||
return mcp_tools
|
||||
|
||||
|
||||
async def _parse_sse_stream(
|
||||
session: aiohttp.ClientSession,
|
||||
url: str,
|
||||
payload: dict[str, Any],
|
||||
headers: dict[str, str],
|
||||
interrupt_flag: asyncio.Event | None = None,
|
||||
) -> tuple[APIResponse, tuple[int, int, int] | None]:
|
||||
"""
|
||||
解析SSE流式响应
|
||||
:param session: aiohttp会话
|
||||
:param url: 请求URL
|
||||
:param payload: 请求负载
|
||||
:param headers: 请求头
|
||||
:param interrupt_flag: 中断标志
|
||||
:return: API响应和使用记录
|
||||
"""
|
||||
content_buffer = io.StringIO()
|
||||
reasoning_buffer = io.StringIO()
|
||||
tool_calls_buffer: list[tuple[str, str, dict[str, Any]]] = []
|
||||
usage_record = None
|
||||
|
||||
try:
|
||||
async with session.post(url, json=payload, headers=headers) as response:
|
||||
if response.status != 200:
|
||||
error_text = await response.text()
|
||||
raise RespNotOkException(
|
||||
response.status, f"MCP SSE请求失败: {error_text}"
|
||||
)
|
||||
|
||||
# 解析SSE流
|
||||
async for line in response.content:
|
||||
if interrupt_flag and interrupt_flag.is_set():
|
||||
raise ReqAbortException("请求被外部信号中断")
|
||||
|
||||
decoded_line = line.decode("utf-8").strip()
|
||||
|
||||
# 跳过空行和注释
|
||||
if not decoded_line or decoded_line.startswith(":"):
|
||||
continue
|
||||
|
||||
# 解析SSE事件
|
||||
if decoded_line.startswith("data: "):
|
||||
data_str = decoded_line[6:] # 移除"data: "前缀
|
||||
|
||||
# 跳过[DONE]标记
|
||||
if data_str == "[DONE]":
|
||||
break
|
||||
|
||||
try:
|
||||
event_data = orjson.loads(data_str)
|
||||
except orjson.JSONDecodeError:
|
||||
logger.warning(f"无法解析SSE数据: {data_str}")
|
||||
continue
|
||||
|
||||
# 处理不同类型的事件
|
||||
event_type = event_data.get("type")
|
||||
|
||||
if event_type == "content_block_start":
|
||||
# 内容块开始
|
||||
block = event_data.get("content_block", {})
|
||||
if block.get("type") == "text":
|
||||
pass # 准备接收文本内容
|
||||
elif block.get("type") == "tool_use":
|
||||
# 工具调用开始
|
||||
tool_calls_buffer.append(
|
||||
(
|
||||
block.get("id", ""),
|
||||
block.get("name", ""),
|
||||
{},
|
||||
)
|
||||
)
|
||||
|
||||
elif event_type == "content_block_delta":
|
||||
# 内容块增量
|
||||
delta = event_data.get("delta", {})
|
||||
delta_type = delta.get("type")
|
||||
|
||||
if delta_type == "text_delta":
|
||||
# 文本增量
|
||||
text = delta.get("text", "")
|
||||
content_buffer.write(text)
|
||||
|
||||
elif delta_type == "input_json_delta":
|
||||
# 工具调用参数增量
|
||||
if tool_calls_buffer:
|
||||
partial_json = delta.get("partial_json", "")
|
||||
# 累积JSON片段
|
||||
current_args = tool_calls_buffer[-1][2]
|
||||
if "_json_buffer" not in current_args:
|
||||
current_args["_json_buffer"] = ""
|
||||
current_args["_json_buffer"] += partial_json
|
||||
|
||||
elif event_type == "content_block_stop":
|
||||
# 内容块结束
|
||||
if tool_calls_buffer:
|
||||
# 解析完整的工具调用参数
|
||||
last_call = tool_calls_buffer[-1]
|
||||
if "_json_buffer" in last_call[2]:
|
||||
json_str = last_call[2].pop("_json_buffer")
|
||||
try:
|
||||
parsed_args = orjson.loads(repair_json(json_str))
|
||||
tool_calls_buffer[-1] = (
|
||||
last_call[0],
|
||||
last_call[1],
|
||||
parsed_args if isinstance(parsed_args, dict) else {},
|
||||
)
|
||||
except orjson.JSONDecodeError as e:
|
||||
logger.error(f"解析工具调用参数失败: {e}")
|
||||
|
||||
elif event_type == "message_delta":
|
||||
# 消息元数据更新
|
||||
delta = event_data.get("delta", {})
|
||||
stop_reason = delta.get("stop_reason")
|
||||
if stop_reason:
|
||||
logger.debug(f"消息结束原因: {stop_reason}")
|
||||
|
||||
# 提取使用统计
|
||||
usage = event_data.get("usage", {})
|
||||
if usage:
|
||||
usage_record = (
|
||||
usage.get("input_tokens", 0),
|
||||
usage.get("output_tokens", 0),
|
||||
usage.get("input_tokens", 0) + usage.get("output_tokens", 0),
|
||||
)
|
||||
|
||||
elif event_type == "message_stop":
|
||||
# 消息结束
|
||||
break
|
||||
|
||||
except aiohttp.ClientError as e:
|
||||
raise NetworkConnectionError() from e
|
||||
except Exception as e:
|
||||
logger.error(f"解析SSE流时发生错误: {e}")
|
||||
raise
|
||||
|
||||
# 构建响应
|
||||
response = APIResponse()
|
||||
|
||||
if content_buffer.tell() > 0:
|
||||
response.content = content_buffer.getvalue()
|
||||
|
||||
if reasoning_buffer.tell() > 0:
|
||||
response.reasoning_content = reasoning_buffer.getvalue()
|
||||
|
||||
if tool_calls_buffer:
|
||||
response.tool_calls = [
|
||||
ToolCall(call_id, func_name, args)
|
||||
for call_id, func_name, args in tool_calls_buffer
|
||||
]
|
||||
|
||||
# 关闭缓冲区
|
||||
content_buffer.close()
|
||||
reasoning_buffer.close()
|
||||
|
||||
return response, usage_record
|
||||
|
||||
|
||||
@client_registry.register_client_class("mcp_sse")
|
||||
class MCPSSEClient(BaseClient):
|
||||
"""
|
||||
MCP SSE客户端实现
|
||||
支持通过Server-Sent Events协议与MCP服务器通信
|
||||
"""
|
||||
|
||||
def __init__(self, api_provider: APIProvider):
|
||||
super().__init__(api_provider)
|
||||
self._session: aiohttp.ClientSession | None = None
|
||||
|
||||
async def _get_session(self) -> aiohttp.ClientSession:
|
||||
"""获取或创建aiohttp会话"""
|
||||
if self._session is None or self._session.closed:
|
||||
timeout = aiohttp.ClientTimeout(total=self.api_provider.timeout)
|
||||
self._session = aiohttp.ClientSession(timeout=timeout)
|
||||
return self._session
|
||||
|
||||
async def close(self):
|
||||
"""关闭客户端会话"""
|
||||
if self._session and not self._session.closed:
|
||||
await self._session.close()
|
||||
|
||||
async def get_response(
|
||||
self,
|
||||
model_info: ModelInfo,
|
||||
message_list: list[Message],
|
||||
tool_options: list[ToolOption] | None = None,
|
||||
max_tokens: int = 1024,
|
||||
temperature: float = 0.7,
|
||||
response_format: RespFormat | None = None,
|
||||
stream_response_handler: Callable[[Any, asyncio.Event | None], tuple[APIResponse, tuple[int, int, int]]]
|
||||
| None = None,
|
||||
async_response_parser: Callable[[Any], tuple[APIResponse, tuple[int, int, int]]] | None = None,
|
||||
interrupt_flag: asyncio.Event | None = None,
|
||||
extra_params: dict[str, Any] | None = None,
|
||||
) -> APIResponse:
|
||||
"""
|
||||
获取对话响应
|
||||
:param model_info: 模型信息
|
||||
:param message_list: 对话消息列表
|
||||
:param tool_options: 工具选项
|
||||
:param max_tokens: 最大token数
|
||||
:param temperature: 温度参数
|
||||
:param response_format: 响应格式
|
||||
:param stream_response_handler: 流式响应处理器
|
||||
:param async_response_parser: 异步响应解析器
|
||||
:param interrupt_flag: 中断标志
|
||||
:param extra_params: 额外参数
|
||||
:return: API响应
|
||||
"""
|
||||
session = await self._get_session()
|
||||
|
||||
# 构建请求负载
|
||||
payload: dict[str, Any] = {
|
||||
"model": model_info.model_identifier,
|
||||
"messages": _convert_messages_to_mcp(message_list),
|
||||
"max_tokens": max_tokens,
|
||||
"temperature": temperature,
|
||||
"stream": True, # MCP SSE始终使用流式
|
||||
}
|
||||
|
||||
# 添加工具
|
||||
if tool_options:
|
||||
payload["tools"] = _convert_tools_to_mcp(tool_options)
|
||||
|
||||
# 添加额外参数
|
||||
if extra_params:
|
||||
payload.update(extra_params)
|
||||
|
||||
# 构建请求头
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Accept": "text/event-stream",
|
||||
"Authorization": f"Bearer {self.api_provider.get_api_key()}",
|
||||
}
|
||||
|
||||
# 发送请求并解析响应
|
||||
url = f"{self.api_provider.base_url}/v1/messages"
|
||||
|
||||
try:
|
||||
response, usage_record = await _parse_sse_stream(
|
||||
session, url, payload, headers, interrupt_flag
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"MCP SSE请求失败: {e}")
|
||||
raise
|
||||
|
||||
# 添加使用记录
|
||||
if usage_record:
|
||||
response.usage = UsageRecord(
|
||||
model_name=model_info.name,
|
||||
provider_name=model_info.api_provider,
|
||||
prompt_tokens=usage_record[0],
|
||||
completion_tokens=usage_record[1],
|
||||
total_tokens=usage_record[2],
|
||||
)
|
||||
|
||||
return response
|
||||
|
||||
async def get_embedding(
|
||||
self,
|
||||
model_info: ModelInfo,
|
||||
embedding_input: str,
|
||||
extra_params: dict[str, Any] | None = None,
|
||||
) -> APIResponse:
|
||||
"""
|
||||
获取文本嵌入
|
||||
MCP协议暂不支持嵌入功能
|
||||
:param model_info: 模型信息
|
||||
:param embedding_input: 嵌入输入文本
|
||||
:return: 嵌入响应
|
||||
"""
|
||||
raise NotImplementedError("MCP SSE客户端暂不支持嵌入功能")
|
||||
|
||||
async def get_audio_transcriptions(
|
||||
self,
|
||||
model_info: ModelInfo,
|
||||
audio_base64: str,
|
||||
extra_params: dict[str, Any] | None = None,
|
||||
) -> APIResponse:
|
||||
"""
|
||||
获取音频转录
|
||||
MCP协议暂不支持音频转录功能
|
||||
:param model_info: 模型信息
|
||||
:param audio_base64: base64编码的音频数据
|
||||
:return: 音频转录响应
|
||||
"""
|
||||
raise NotImplementedError("MCP SSE客户端暂不支持音频转录功能")
|
||||
|
||||
def get_support_image_formats(self) -> list[str]:
|
||||
"""
|
||||
获取支持的图片格式
|
||||
:return: 支持的图片格式列表
|
||||
"""
|
||||
return ["jpg", "jpeg", "png", "webp", "gif"]
|
||||
Reference in New Issue
Block a user