Update app.py

app.py

@@ -1,40 +1,46 @@
 from fastapi import FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
+from contextlib import asynccontextmanager
 import base64
 import os
 
-app = FastAPI()
-
-# Middleware to handle CORS (optional, but useful if Testing4 calls this API)
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],  # Adjust as needed for security
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# Load LoRA weights globally
-lora_weights = None
-
-@app.on_event("startup")
-async def startup_event():
-    global lora_weights
+# Create the FastAPI app
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    # Load LoRA weights during app startup
     lora_path = "./lora_file.pth"
     if os.path.exists(lora_path):
         with open(lora_path, "rb") as f:
             # Base64 encode the LoRA weights for easy JSON transmission
-            lora_weights = base64.b64encode(f.read()).decode("utf-8")
+            app.state.lora_weights = base64.b64encode(f.read()).decode("utf-8")
             print("LoRA weights loaded and preprocessed successfully.")
     else:
         print("LoRA file not found during startup.")
-        raise HTTPException(status_code=500, detail="LoRA file not found.")
+        raise RuntimeError("LoRA file not found.")
+
+    # Yield control to the application
+    yield
+
+    # Perform any cleanup (if needed) here
+    print("Application shutting down.")
+
+app = FastAPI(lifespan=lifespan)
+
+# Middleware to handle CORS (optional, but useful for cross-origin requests)
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Adjust for security
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
 
 @app.post("/modify-prompt")
 async def modify_prompt(prompt: str):
-    global lora_weights
+    lora_weights = getattr(app.state, "lora_weights", None)
     if lora_weights is None:
         raise HTTPException(status_code=500, detail="LoRA weights not loaded.")
+    
     # Combine prompt with preprocessed LoRA data
     extended_prompt = {
         "prompt": prompt,