Update app.py

app.py

@@ -315,23 +315,38 @@ def qa_llm():
     return RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents=True)
 
 def process_answer(user_question):
+    """Generate an answer to the user’s question using a general RAG-based prompt."""
     try:
-        qa = qa_llm()
-        prompt = f"""
-        You are a helpful and accurate RAG-based chatbot. Your role is to analyze the content from uploaded PDF documents and 
-        provide informative and detailed answers to any questions asked by the user. Use the uploaded knowledge to answer precisely.
-
-        Question: {user_question}
-        """
-        output = qa({"query": prompt})
-        return output['result']
+        logging.info("Processing user question")
+        qa = qa_llm()  # Set up the retrieval-based QA chain
+
+        # Generalized, flexible prompt for any kind of PDF (resume, legal doc, etc.)
+        tailored_prompt = f"""
+You are an intelligent and helpful AI assistant that provides answers strictly based on the provided document contents.
+If the question cannot be answered using the documents, say: 'The document does not contain this information.'
+Otherwise, respond clearly and concisely with relevant and factual details from the PDF.
+
+Question: {user_question}
+"""
+
+        generated_text = qa({"query": tailored_prompt})
+        answer = generated_text['result']
+
+        # Add a safeguard for uncertain or hallucinated answers
+        if "not provide" in answer.lower() or "no information" in answer.lower() or len(answer.strip()) < 10:
+            return "The document does not contain this information."
+
+        logging.info("Answer generated successfully")
+        return answer
+
     except Exception as e:
-        logging.error(f"QA failed: {e}")
-        return "❌ Could not generate a valid answer."
+        logging.error(f"Error during answer generation: {str(e)}")
+        return "Sorry, something went wrong while processing your question."
+
 
 # ---------------- STREAMLIT UI ---------------- #
 
-# Sidebar Upload
+# Sidebar Upload 
 st.sidebar.header("📤 Upload PDF Files")
 uploaded_files = st.sidebar.file_uploader("Select one or more PDF files", type="pdf", accept_multiple_files=True)