Update main.py

main.py

@@ -1,17 +1,34 @@
-from fastapi import FastAPI, UploadFile, File, Form
+from fastapi import FastAPI, UploadFile, File, Form, Request
 from fastapi.responses import JSONResponse
 import tempfile, shutil, os
 
 from llm import load_and_process_pdf, create_vectorstore, create_rag_chain, get_response
 
-app = FastAPI(title="PDF Q&A Chatbot", description="Ask questions about a PDF file using RAG.", version="1.0")
+app = FastAPI(
+    title="PDF Q&A Chatbot",
+    description="Ask questions about a PDF file using RAG.",
+    version="1.0"
+)
 
-# Global in-memory state for simplicity
+# Global in-memory state
 global_state = {
     "vectorstore": None,
     "rag_chain": None
 }
 
+@app.get("/")
+def home():
+    return {"message": "Welcome to the PDF Q&A Chatbot by Bitfumes"}
+
+@app.get("/ask")
+def ask(prompt: str):
+    """Ask a question using the uploaded and processed PDF."""
+    if not global_state["vectorstore"] or not global_state["rag_chain"]:
+        return JSONResponse(status_code=400, content={"error": "Please upload and process a PDF first."})
+    
+    answer = get_response(global_state["rag_chain"], global_state["vectorstore"], prompt)
+    return {"question": prompt, "answer": answer}
+
 @app.post("/upload/")
 async def upload_pdf(file: UploadFile = File(...)):
     """Endpoint to upload and process a PDF file."""
@@ -31,12 +48,3 @@ async def upload_pdf(file: UploadFile = File(...)):
         return {"message": "PDF processed successfully", "filename": file.filename}
     finally:
         os.unlink(tmp_file_path)
-
-@app.post("/ask/")
-async def ask_question(question: str = Form(...)):
-    """Ask a question about the previously uploaded PDF."""
-    if not global_state["vectorstore"] or not global_state["rag_chain"]:
-        return JSONResponse(status_code=400, content={"error": "Please upload and process a PDF first."})
-
-    answer = get_response(global_state["rag_chain"], global_state["vectorstore"], question)
-    return {"question": question, "answer": answer}