Delete api_service.py

api_service.py

@@ -1,92 +0,0 @@
-# filename: api_service.py
-
-from fastapi import FastAPI, HTTPException
-from fastapi.middleware.cors import CORSMiddleware
-from pydantic import BaseModel
-from typing import Dict, Any, Optional
-
-# Import the core logic and model loading functions
-from backend_pam import load_agent as load_backend_agent, PAM
-from frontend_pam import load_frontend_agent, FrontendPAM
-
-# --- Global Agent Variables ---
-backend_agent: Optional[PAM] = None
-frontend_agent: Optional[FrontendPAM] = None
-
-# --- Data Model for API Request ---
-class UserInput(BaseModel):
-    user_input: str
-
-# --- FastAPI Initialization ---
-app = FastAPI(
-    title="PAM Unified Inference Service (Technical & Chat)",
-    version="2.0.0",
-    docs_url=None,
-    redoc_url=None
-)
-
-# --- CORS Setup ---
-origins = [
-    "https://www.uminur.app",
-    "https://api.uminur.app",
-]
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=origins,
-    allow_credentials=True,
-    allow_methods=["POST", "GET"],
-    allow_headers=["*"],
-)
-
-# --- Startup Event ---
-@app.on_event("startup")
-async def startup_event():
-    global backend_agent, frontend_agent
-    print("FastAPI: Starting up PAM agents...")
-
-    backend_agent = load_backend_agent()
-    frontend_agent = load_frontend_agent()
-
-    if not backend_agent or not frontend_agent:
-        print("FastAPI: ERROR — One or both agents failed to initialize.")
-
-# --- Health Check ---
-@app.get("/health", status_code=200, tags=["Status"])
-def health_check():
-    backend_ok = backend_agent is not None
-    frontend_ok = frontend_agent is not None
-
-    if backend_ok and frontend_ok:
-        return {"status": "ok", "backend_ready": True, "frontend_ready": True}
-
-    raise HTTPException(
-        status_code=503,
-        detail=f"Service Unavailable: Backend Ready: {backend_ok}, Frontend Ready: {frontend_ok}"
-    )
-
-# --- Technical Endpoint ---
-@app.post("/ai/technical/", tags=["Technical"])
-async def technical_endpoint(input_data: UserInput) -> Dict[str, Any]:
-    if backend_agent is None:
-        raise HTTPException(status_code=503, detail="Backend PAM is not initialized.")
-
-    try:
-        pam_reply = backend_agent.process_input(input_data.user_input)
-        return pam_reply
-    except Exception as e:
-        print(f"Error during technical inference: {e}")
-        raise HTTPException(status_code=500, detail="Internal Server Error (technical)")
-
-# --- Chat Endpoint ---
-@app.post("/ai/chat/", tags=["Chat"])
-async def chat_endpoint(input_data: UserInput) -> Dict[str, Any]:
-    if frontend_agent is None:
-        raise HTTPException(status_code=503, detail="Frontend PAM is not initialized.")
-
-    try:
-        pam_reply = frontend_agent.respond(input_data.user_input)
-        return pam_reply
-    except Exception as e:
-        print(f"Error during chat inference: {e}")
-        raise HTTPException(status_code=500, detail="Internal Server Error (chat)")