Add debugging logs to predict endpoint

app.py

@@ -1,5 +1,10 @@
-from fastapi import FastAPI, HTTPException
+from fastapi import FastAPI, HTTPException, Request
 from pydantic import BaseModel
+import logging
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger("LLM-API")
 
 app = FastAPI()
 
@@ -9,11 +14,18 @@ class InputText(BaseModel):
 
 @app.get("/")
 def root():
+    logger.info("Root endpoint called.")
     return {"message": "Welcome to the LLM API"}
 
 @app.post("/predict")
-def predict(data: InputText):
-    # Access the input_text from the request body
-    input_text = data.input_text
-    # For now, return the input text as a response
-    return {"response": f"The input was: {input_text}"}
+async def predict(data: InputText, request: Request):
+    logger.info("Received request: %s", await request.body())
+    try:
+        # Log the received input
+        input_text = data.input_text
+        logger.info(f"Processing input: {input_text}")
+        # Return a mock response for now
+        return {"response": f"The input was: {input_text}"}
+    except Exception as e:
+        logger.error(f"Error occurred: {e}")
+        raise HTTPException(status_code=500, detail=str(e))