后端新增《蚕茧识别V2》模块

bbit_ai/app/app.py

@@ -4,6 +4,7 @@ from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from uvicorn import Config, Server
 
+from config.yolo import YOLOSingleton
 from mcp_local.mcp_pipe import init_mcp_server
 from routers.Bot import botRouter
 from routers.Chat import chatRouter
@@ -21,7 +22,7 @@ async def ai_lab():
     app = FastAPI(title="BBIT_AI")
 
     origins = [
-        "http://localhost:8090",  # Vite dev 默认端口
+        "http://localhost:8091",  # Vite dev 默认端口
         "https://ai.ronsunny.cn:8090",
         "*",  # ⚠️ 生产环境不要用
     ]
@@ -40,11 +41,11 @@ async def ai_lab():
         reportDataRouter,
         serviceRouter,
         botRouter,
-        visionRouter,
         rqRouter,
     ]
     for r in routers:
         app.include_router(r, prefix="/llm", tags=["llm"])
+    app.include_router(visionRouter, prefix="/cv", tags=["cv"])
     app.include_router(publicRouter, prefix="/api/public", tags=["api"])
     config = Config(app=app, host="0.0.0.0", port=13011, log_level="info")
     server = Server(config)
@@ -52,12 +53,14 @@ async def ai_lab():
 
 
 async def main():
+    # 初始化模型
+    YOLOSingleton.init_model()
     # 主干AI实验室FastAPI服务
     task_api = asyncio.create_task(ai_lab())
 
     # MCP服务-ailab
-    # endpoint_url = "wss://ai.ronsunny.cn:8090/aimcp/mcp_endpoint/mcp/?token=TsSP9lBq6Oa1WMkachHoS2TtNt4GKV/Gli24pk5Rjpk%3D"
-    endpoint_url_ai_lab = "ws://ce_bot_mcp:8004/mcp_endpoint/mcp/?token=TsSP9lBq6Oa1WMkachHoS2TtNt4GKV/Gli24pk5Rjpk%3D"
+    endpoint_url_ai_lab = "wss://ai.ronsunny.cn:8090/aimcp/mcp_endpoint/mcp/?token=TsSP9lBq6Oa1WMkachHoS2TtNt4GKV/Gli24pk5Rjpk%3D"
+    # endpoint_url_ai_lab = "ws://ce_bot_mcp:8004/mcp_endpoint/mcp/?token=TsSP9lBq6Oa1WMkachHoS2TtNt4GKV/Gli24pk5Rjpk%3D"
     task_mcp1 = asyncio.create_task(init_mcp_server(endpoint_url_ai_lab))
 
     # MCP服务-ql