fix:1.优化mcp插件功能，改用mcp sdk库
This commit is contained in:
xiamuceer
+137
-335
@@ -18,9 +18,9 @@ from app.schemas.mcp_plugin import (
|
||||
import json
|
||||
from app.user_manager import User
|
||||
from app.mcp.registry import mcp_registry
|
||||
from app.services.mcp_test_service import mcp_test_service
|
||||
from app.services.mcp_tool_service import mcp_tool_service
|
||||
from app.logger import get_logger
|
||||
from app.services.ai_service import create_user_ai_service
|
||||
from app.models.settings import Settings as UserSettings
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
@@ -399,13 +399,8 @@ async def test_plugin(
|
||||
"""
|
||||
测试插件连接并调用工具验证功能
|
||||
|
||||
测试流程:
|
||||
1. 测试MCP服务器连接
|
||||
2. 获取工具列表
|
||||
3. 自动选择一个工具进行实际调用测试
|
||||
4. 返回完整测试结果
|
||||
使用新的MCPTestService进行测试
|
||||
"""
|
||||
import time
|
||||
|
||||
result = await db.execute(
|
||||
select(MCPPlugin).where(
|
||||
@@ -426,356 +421,153 @@ async def test_plugin(
|
||||
suggestions=["点击开关按钮启用插件"]
|
||||
)
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
# 使用新的测试服务
|
||||
try:
|
||||
# 1. 确保插件已加载
|
||||
if not mcp_registry.get_client(user.user_id, plugin.plugin_name):
|
||||
success = await mcp_registry.load_plugin(plugin)
|
||||
if not success:
|
||||
return MCPTestResult(
|
||||
success=False,
|
||||
message="插件加载失败",
|
||||
error="无法创建MCP客户端",
|
||||
suggestions=["请检查插件配置", "请确认服务器URL正确"]
|
||||
)
|
||||
test_result = await mcp_test_service.test_plugin_with_ai(plugin, user, db)
|
||||
|
||||
# 2. 测试连接并获取工具列表
|
||||
test_result = await mcp_registry.test_plugin(user.user_id, plugin.plugin_name)
|
||||
|
||||
if not test_result["success"]:
|
||||
plugin.status = "error"
|
||||
plugin.last_error = test_result.get("error", "连接测试失败")
|
||||
plugin.last_test_at = datetime.now()
|
||||
await db.commit()
|
||||
return MCPTestResult(**test_result)
|
||||
|
||||
tools = test_result.get("tools", [])
|
||||
|
||||
if not tools:
|
||||
plugin.status = "error"
|
||||
plugin.last_error = "插件没有提供任何工具"
|
||||
plugin.last_test_at = datetime.now()
|
||||
await db.commit()
|
||||
|
||||
return MCPTestResult(
|
||||
success=False,
|
||||
message="插件没有提供任何工具",
|
||||
error="工具列表为空",
|
||||
response_time_ms=test_result.get("response_time_ms"),
|
||||
suggestions=["请检查插件配置", "请确认MCP服务器正常运行"]
|
||||
)
|
||||
|
||||
# 3. 使用AI智能选择工具并生成测试参数
|
||||
logger.info(f"使用AI分析工具并生成测试计划...")
|
||||
|
||||
# 获取用户的AI设置
|
||||
settings_result = await db.execute(
|
||||
select(UserSettings).where(UserSettings.user_id == user.user_id)
|
||||
)
|
||||
user_settings = settings_result.scalar_one_or_none()
|
||||
|
||||
if not user_settings or not user_settings.api_key:
|
||||
# 如果没有AI配置，回退到简单测试
|
||||
logger.warning("用户未配置AI服务，使用简单连接测试")
|
||||
# 更新插件状态
|
||||
if test_result.success:
|
||||
plugin.status = "active"
|
||||
plugin.last_error = None
|
||||
plugin.last_test_at = datetime.now()
|
||||
plugin.tools = tools
|
||||
await db.commit()
|
||||
|
||||
return MCPTestResult(
|
||||
success=True,
|
||||
message=f"✅ 连接测试成功（未配置AI，跳过工具调用测试）",
|
||||
response_time_ms=test_result.get("response_time_ms"),
|
||||
tools_count=len(tools),
|
||||
suggestions=[
|
||||
f"连接测试: 成功",
|
||||
f"可用工具数: {len(tools)}",
|
||||
"提示: 配置AI服务后可进行智能工具调用测试"
|
||||
]
|
||||
)
|
||||
|
||||
# 使用AI的标准Function Calling机制选择工具
|
||||
ai_service = create_user_ai_service(
|
||||
api_provider=user_settings.api_provider,
|
||||
api_key=user_settings.api_key,
|
||||
api_base_url=user_settings.api_base_url,
|
||||
model_name=user_settings.llm_model,
|
||||
temperature=0.3,
|
||||
max_tokens=1000
|
||||
)
|
||||
|
||||
# 将MCP工具格式转换为OpenAI Function Calling格式
|
||||
openai_tools = []
|
||||
for tool in tools:
|
||||
openai_tool = {
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": tool["name"],
|
||||
"description": tool.get("description", ""),
|
||||
}
|
||||
}
|
||||
# 将 inputSchema 转换为 parameters
|
||||
if "inputSchema" in tool:
|
||||
openai_tool["function"]["parameters"] = tool["inputSchema"]
|
||||
|
||||
openai_tools.append(openai_tool)
|
||||
|
||||
logger.info(f"转换了 {len(openai_tools)} 个MCP工具为OpenAI格式")
|
||||
logger.info(f"工具列表: {[t['function']['name'] for t in openai_tools]}")
|
||||
|
||||
# 使用标准的Function Calling，将转换后的工具传递给AI
|
||||
prompt = f"""你是MCP插件测试助手，需要测试插件 '{plugin.plugin_name}' 的功能。
|
||||
|
||||
请选择一个合适的工具进行测试，优先选择搜索、查询类工具。
|
||||
生成真实有效的测试参数（例如搜索"人工智能最新进展"而不是"test"）。
|
||||
|
||||
现在开始测试这个插件。"""
|
||||
|
||||
system_prompt = "你是专业的API测试工具。当给定工具列表时，选择一个工具并使用合适的参数调用它。"
|
||||
|
||||
# 调用AI的Function Calling
|
||||
logger.info(f"📞 准备调用AI Function Calling")
|
||||
logger.info(f" - Provider: {user_settings.api_provider}")
|
||||
logger.info(f" - Model: {user_settings.llm_model}")
|
||||
logger.info(f" - Tools count: {len(openai_tools)}")
|
||||
logger.debug(f" - Tools: {json.dumps(openai_tools, ensure_ascii=False, indent=2)}")
|
||||
|
||||
ai_response = await ai_service.generate_text(
|
||||
prompt=prompt,
|
||||
system_prompt=system_prompt,
|
||||
tools=openai_tools, # 传递转换后的OpenAI格式工具
|
||||
tool_choice="required" # 要求AI必须选择一个工具
|
||||
)
|
||||
|
||||
logger.info(f"📥 收到AI响应")
|
||||
logger.info(f" - Response keys: {list(ai_response.keys())}")
|
||||
logger.debug(f" - Full response: {json.dumps(ai_response, ensure_ascii=False, indent=2)}")
|
||||
|
||||
# 检查AI是否请求调用工具
|
||||
if not ai_response.get("tool_calls"):
|
||||
# AI未调用工具，记录详细信息
|
||||
logger.error(f"❌ AI未返回工具调用")
|
||||
logger.error(f" - Response: {ai_response}")
|
||||
logger.error(f" - Content: {ai_response.get('content', 'N/A')}")
|
||||
logger.error(f" - Finish reason: {ai_response.get('finish_reason', 'N/A')}")
|
||||
|
||||
else:
|
||||
plugin.status = "error"
|
||||
plugin.last_error = "AI未返回工具调用请求"
|
||||
plugin.last_test_at = datetime.now()
|
||||
await db.commit()
|
||||
|
||||
return MCPTestResult(
|
||||
success=False,
|
||||
message="❌ AI Function Calling失败",
|
||||
error=f"AI未返回工具调用请求。响应: {ai_response.get('content', 'N/A')[:200]}",
|
||||
tools_count=len(tools),
|
||||
suggestions=[
|
||||
"请确认使用的AI模型支持Function Calling",
|
||||
"OpenAI: 需要gpt-4, gpt-3.5-turbo等模型",
|
||||
"Anthropic: 需要claude-3系列模型",
|
||||
f"当前Provider: {user_settings.api_provider}",
|
||||
f"当前模型: {user_settings.llm_model}",
|
||||
f"AI返回内容: {ai_response.get('content', 'N/A')[:100]}"
|
||||
]
|
||||
)
|
||||
plugin.last_error = test_result.error
|
||||
|
||||
# 获取第一个工具调用
|
||||
tool_call = ai_response["tool_calls"][0]
|
||||
function = tool_call["function"]
|
||||
tool_name = function["name"]
|
||||
test_arguments = function["arguments"]
|
||||
plugin.last_test_at = datetime.now()
|
||||
await db.commit()
|
||||
|
||||
# AI返回的arguments可能是JSON字符串，需要解析
|
||||
if isinstance(test_arguments, str):
|
||||
try:
|
||||
test_arguments = json.loads(test_arguments)
|
||||
logger.info(f"✅ 解析AI返回的JSON字符串参数")
|
||||
except json.JSONDecodeError as e:
|
||||
logger.error(f"❌ 解析AI参数失败: {e}")
|
||||
return MCPTestResult(
|
||||
success=False,
|
||||
message="❌ AI返回的参数格式错误",
|
||||
error=f"无法解析参数JSON: {str(e)}",
|
||||
tools_count=len(tools),
|
||||
suggestions=["AI返回的参数不是有效的JSON格式"]
|
||||
)
|
||||
|
||||
logger.info(f"🤖 AI通过Function Calling选择的工具: {tool_name}")
|
||||
logger.info(f"📝 AI生成的参数: {test_arguments}")
|
||||
logger.info(f"📝 参数类型: {type(test_arguments).__name__}")
|
||||
|
||||
# 4. 使用AI选择的工具和参数调用MCP工具
|
||||
call_start = time.time()
|
||||
try:
|
||||
tool_result = await mcp_registry.call_tool(
|
||||
user.user_id,
|
||||
plugin.plugin_name,
|
||||
tool_name,
|
||||
test_arguments
|
||||
)
|
||||
|
||||
call_end = time.time()
|
||||
call_time = round((call_end - call_start) * 1000, 2)
|
||||
total_time = round((call_end - start_time) * 1000, 2)
|
||||
|
||||
# 6. 测试成功，更新插件状态
|
||||
plugin.status = "active"
|
||||
plugin.last_error = None
|
||||
plugin.last_test_at = datetime.now()
|
||||
plugin.tools = tools # 缓存工具列表
|
||||
await db.commit()
|
||||
|
||||
# 格式化工具结果用于显示
|
||||
result_str = str(tool_result)
|
||||
|
||||
# 如果结果太长，截取前800字符
|
||||
if len(result_str) > 800:
|
||||
result_preview = result_str[:800] + "\n...(结果已截断，完整结果请查看日志)"
|
||||
else:
|
||||
result_preview = result_str
|
||||
|
||||
return MCPTestResult(
|
||||
success=True,
|
||||
message=f"✅ Function Calling测试成功！工具 '{tool_name}' 调用正常",
|
||||
response_time_ms=total_time,
|
||||
tools_count=len(tools),
|
||||
suggestions=[
|
||||
f"🤖 AI (Function Calling) 选择: {tool_name}",
|
||||
f"📝 AI生成的参数: {json.dumps(test_arguments, ensure_ascii=False)}",
|
||||
f"⏱️ 调用耗时: {call_time}ms",
|
||||
f"📊 返回结果:\n{result_preview}"
|
||||
]
|
||||
)
|
||||
|
||||
except Exception as call_error:
|
||||
call_end = time.time()
|
||||
total_time = round((call_end - start_time) * 1000, 2)
|
||||
|
||||
logger.warning(f"工具调用失败: {tool_name}, 错误: {call_error}")
|
||||
|
||||
# 工具调用失败,但连接成功
|
||||
plugin.status = "active" # 仍标记为active,因为连接是成功的
|
||||
plugin.last_error = f"工具调用测试失败: {str(call_error)}"
|
||||
plugin.last_test_at = datetime.now()
|
||||
plugin.tools = tools
|
||||
await db.commit()
|
||||
|
||||
return MCPTestResult(
|
||||
success=True, # 连接成功就算测试通过
|
||||
message=f"⚠️ 连接成功，但工具调用失败",
|
||||
response_time_ms=total_time,
|
||||
tools_count=len(tools),
|
||||
error=f"工具 '{tool_name}' 调用失败: {str(call_error)}",
|
||||
suggestions=[
|
||||
f"✅ 连接测试: 成功",
|
||||
f"❌ 工具调用测试: 失败",
|
||||
f"🤖 AI (Function Calling) 选择: {tool_name}",
|
||||
f"📝 AI生成的参数: {json.dumps(test_arguments, ensure_ascii=False)}",
|
||||
f"❌ 错误: {str(call_error)}",
|
||||
"💡 可能原因: API Key无效、参数错误或服务限制"
|
||||
]
|
||||
)
|
||||
return test_result
|
||||
|
||||
except Exception as e:
|
||||
end_time = time.time()
|
||||
total_time = round((end_time - start_time) * 1000, 2)
|
||||
|
||||
logger.error(f"测试插件失败: {plugin.plugin_name}, 错误: {e}")
|
||||
|
||||
plugin.status = "error"
|
||||
plugin.last_error = str(e)
|
||||
plugin.last_test_at = datetime.now()
|
||||
await db.commit()
|
||||
|
||||
return MCPTestResult(
|
||||
success=False,
|
||||
message="❌ 测试失败",
|
||||
response_time_ms=total_time,
|
||||
error=str(e),
|
||||
error_type=type(e).__name__,
|
||||
suggestions=["请检查服务器是否在线", "请确认配置正确", "请检查API Key是否有效"]
|
||||
)
|
||||
raise HTTPException(status_code=500, detail=f"测试失败: {str(e)}")
|
||||
|
||||
|
||||
def _build_test_arguments(tool_name: str, input_schema: dict, plugin_name: str) -> dict:
|
||||
async def _ensure_plugin_loaded(
|
||||
plugin: MCPPlugin,
|
||||
user_id: str
|
||||
) -> bool:
|
||||
"""
|
||||
根据工具schema智能构造测试参数
|
||||
确保插件已加载（共享逻辑）
|
||||
|
||||
Args:
|
||||
tool_name: 工具名称
|
||||
input_schema: 输入schema
|
||||
plugin_name: 插件名称
|
||||
plugin: 插件对象
|
||||
user_id: 用户ID
|
||||
|
||||
Returns:
|
||||
测试参数字典
|
||||
"""
|
||||
# 针对常见MCP工具的默认测试参数
|
||||
test_cases = {
|
||||
# Exa搜索工具
|
||||
"search": {
|
||||
"query": "AI technology",
|
||||
"num_results": 3
|
||||
},
|
||||
"search_and_contents": {
|
||||
"query": "artificial intelligence",
|
||||
"num_results": 2
|
||||
},
|
||||
# Brave搜索
|
||||
"brave_web_search": {
|
||||
"query": "AI news",
|
||||
"count": 3
|
||||
},
|
||||
# Filesystem工具
|
||||
"read_file": {
|
||||
"path": "README.md"
|
||||
},
|
||||
"list_directory": {
|
||||
"path": "."
|
||||
},
|
||||
}
|
||||
|
||||
# 如果有针对特定工具的测试用例，使用它
|
||||
if tool_name in test_cases:
|
||||
logger.info(f"使用预定义测试参数: {test_cases[tool_name]}")
|
||||
return test_cases[tool_name]
|
||||
|
||||
# 否则根据schema自动构造
|
||||
properties = input_schema.get("properties", {})
|
||||
required = input_schema.get("required", [])
|
||||
|
||||
test_args = {}
|
||||
|
||||
for prop_name, prop_schema in properties.items():
|
||||
# 只填充必需的参数
|
||||
if prop_name not in required:
|
||||
continue
|
||||
|
||||
prop_type = prop_schema.get("type", "string")
|
||||
是否加载成功
|
||||
|
||||
# 根据参数名称和类型猜测合适的测试值
|
||||
if "query" in prop_name.lower() or "search" in prop_name.lower():
|
||||
test_args[prop_name] = "test query"
|
||||
elif "url" in prop_name.lower():
|
||||
test_args[prop_name] = "https://example.com"
|
||||
elif "path" in prop_name.lower():
|
||||
test_args[prop_name] = "."
|
||||
elif "count" in prop_name.lower() or "limit" in prop_name.lower() or "num" in prop_name.lower():
|
||||
test_args[prop_name] = 3
|
||||
elif prop_type == "string":
|
||||
test_args[prop_name] = "test"
|
||||
elif prop_type == "number" or prop_type == "integer":
|
||||
test_args[prop_name] = 1
|
||||
elif prop_type == "boolean":
|
||||
test_args[prop_name] = True
|
||||
elif prop_type == "array":
|
||||
test_args[prop_name] = []
|
||||
elif prop_type == "object":
|
||||
test_args[prop_name] = {}
|
||||
Raises:
|
||||
HTTPException: 加载失败
|
||||
"""
|
||||
if not mcp_registry.get_client(user_id, plugin.plugin_name):
|
||||
logger.info(f"插件 {plugin.plugin_name} 未加载，自动加载中...")
|
||||
success = await mcp_registry.load_plugin(plugin)
|
||||
if not success:
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail=f"插件加载失败: {plugin.plugin_name}"
|
||||
)
|
||||
return True
|
||||
|
||||
|
||||
@router.get("/metrics")
|
||||
async def get_metrics(
|
||||
tool_name: Optional[str] = Query(None, description="工具名称（可选，获取特定工具的指标）"),
|
||||
user: User = Depends(require_login)
|
||||
):
|
||||
"""
|
||||
获取MCP工具调用指标
|
||||
|
||||
logger.info(f"自动构造测试参数: {test_args}")
|
||||
return test_args
|
||||
Query参数:
|
||||
- tool_name: 可选，指定工具名称获取特定工具的指标
|
||||
|
||||
Returns:
|
||||
工具调用指标字典，包含：
|
||||
- total_calls: 总调用次数
|
||||
- success_calls: 成功调用次数
|
||||
- failed_calls: 失败调用次数
|
||||
- success_rate: 成功率
|
||||
- avg_duration_ms: 平均耗时（毫秒）
|
||||
- last_call_time: 最后调用时间
|
||||
"""
|
||||
metrics = mcp_tool_service.get_metrics(tool_name)
|
||||
|
||||
return {
|
||||
"metrics": metrics,
|
||||
"tool_name": tool_name,
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
|
||||
|
||||
@router.get("/cache/stats")
|
||||
async def get_cache_stats(
|
||||
user: User = Depends(require_login)
|
||||
):
|
||||
"""
|
||||
获取工具缓存统计信息
|
||||
|
||||
Returns:
|
||||
缓存统计信息，包含：
|
||||
- total_entries: 缓存条目总数
|
||||
- total_hits: 缓存总命中次数
|
||||
- cache_ttl_minutes: 缓存TTL（分钟）
|
||||
- entries: 各缓存条目详情
|
||||
"""
|
||||
stats = mcp_tool_service.get_cache_stats()
|
||||
|
||||
return {
|
||||
"cache_stats": stats,
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
|
||||
|
||||
@router.post("/cache/clear")
|
||||
async def clear_cache(
|
||||
user_id: Optional[str] = Query(None, description="用户ID（可选）"),
|
||||
plugin_name: Optional[str] = Query(None, description="插件名称（可选）"),
|
||||
user: User = Depends(require_login)
|
||||
):
|
||||
"""
|
||||
清理工具缓存
|
||||
|
||||
Query参数:
|
||||
- user_id: 可选，清理特定用户的缓存
|
||||
- plugin_name: 可选，清理特定插件的缓存
|
||||
|
||||
说明:
|
||||
- 不提供任何参数：清理所有缓存
|
||||
- 只提供user_id：清理该用户的所有缓存
|
||||
- 提供user_id和plugin_name：清理特定插件的缓存
|
||||
"""
|
||||
# 非管理员只能清理自己的缓存
|
||||
if user_id and user_id != user.user_id:
|
||||
raise HTTPException(status_code=403, detail="无权清理其他用户的缓存")
|
||||
|
||||
# 如果没有指定user_id，使用当前用户
|
||||
target_user_id = user_id or user.user_id
|
||||
|
||||
mcp_tool_service.clear_cache(target_user_id, plugin_name)
|
||||
|
||||
message = "已清理"
|
||||
if plugin_name:
|
||||
message += f"插件 {plugin_name} 的缓存"
|
||||
elif target_user_id:
|
||||
message += f"用户 {target_user_id} 的所有缓存"
|
||||
else:
|
||||
message += "所有缓存"
|
||||
|
||||
logger.info(f"用户 {user.user_id} {message}")
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"message": message,
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}
|
||||
|
||||
|
||||
@router.get("/{plugin_id}/tools")
|
||||
@@ -802,6 +594,9 @@ async def get_plugin_tools(
|
||||
raise HTTPException(status_code=400, detail="插件未启用")
|
||||
|
||||
try:
|
||||
# 确保插件已加载
|
||||
await _ensure_plugin_loaded(plugin, user.user_id)
|
||||
|
||||
tools = await mcp_registry.get_plugin_tools(user.user_id, plugin.plugin_name)
|
||||
|
||||
# 更新缓存
|
||||
@@ -813,6 +608,8 @@ async def get_plugin_tools(
|
||||
"tools": tools,
|
||||
"count": len(tools)
|
||||
}
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as e:
|
||||
logger.error(f"获取工具列表失败: {plugin.plugin_name}, 错误: {e}")
|
||||
raise HTTPException(status_code=500, detail=f"获取工具列表失败: {str(e)}")
|
||||
@@ -843,6 +640,9 @@ async def call_mcp_tool(
|
||||
raise HTTPException(status_code=400, detail="插件未启用")
|
||||
|
||||
try:
|
||||
# 确保插件已加载
|
||||
await _ensure_plugin_loaded(plugin, user.user_id)
|
||||
|
||||
# 调用工具
|
||||
result = await mcp_registry.call_tool(
|
||||
user.user_id,
|
||||
@@ -857,6 +657,8 @@ async def call_mcp_tool(
|
||||
"tool_name": data.tool_name,
|
||||
"result": result
|
||||
}
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as e:
|
||||
logger.error(f"调用工具失败: {plugin.plugin_name}.{data.tool_name}, 错误: {e}")
|
||||
raise HTTPException(status_code=500, detail=f"工具调用失败: {str(e)}")
|
||||
Reference in New Issue
Block a user