Update app.py

app.py

@@ -25,53 +25,51 @@ class PDFChatbot:
         relevant_chunks = [chunk.page_content for chunk in relevant_chunks]
         return "\n\n".join(relevant_chunks)
     def chat_with_pdf(self, user_question: str, pdf_content: str) -> str:
-       """Generate response using Azure OpenAI based on PDF content and user question."""
-        try:
-            # Split PDF content into chunks
-            # Get relevant context for the question
-            relevant_context = self.get_relevant_context(user_question)
-            # Prepare messages for the chat
-            messages = [
-               {
-                   "role": "system",
-                   "content": """You are an experienced insurance agent assistant who helps customers understand their insurance policies and coverage details. Follow these guidelines:
-                   1. Only provide information based on the PDF content provided
-                   2. If the answer is not in the PDF, clearly state that the information is not available in the document
-                   3. Provide clear, concise, and helpful responses in a professional manner
-                   4. Always respond in Vietnamese using proper grammar and formatting
-                   5. When possible, reference specific sections or clauses from the policy
-                   6. Use insurance terminology appropriately but explain complex terms when necessary
-                   7. Be empathetic and patient, as insurance can be confusing for customers
-                   8. If asked about claims, coverage limits, deductibles, or policy terms, provide accurate information from the document
-                   9. Always prioritize customer understanding and satisfaction
-                   10. If multiple interpretations are possible, explain the different scenarios clearly
-                   Remember: You are here to help customers understand their insurance coverage better."""
-               },
-               {
-                   "role": "user",
-                   "content": f"""Insurance Document Content:
+        """Generate response using Azure OpenAI based on PDF content and user question."""
+        # Split PDF content into chunks
+        # Get relevant context for the question
+        relevant_context = self.get_relevant_context(user_question)
+        # Prepare messages for the chat
+        messages = [
+           {
+               "role": "system",
+               "content": """You are an experienced insurance agent assistant who helps customers understand their insurance policies and coverage details. Follow these guidelines:
+               1. Only provide information based on the PDF content provided
+               2. If the answer is not in the PDF, clearly state that the information is not available in the document
+               3. Provide clear, concise, and helpful responses in a professional manner
+               4. Always respond in Vietnamese using proper grammar and formatting
+               5. When possible, reference specific sections or clauses from the policy
+               6. Use insurance terminology appropriately but explain complex terms when necessary
+               7. Be empathetic and patient, as insurance can be confusing for customers
+               8. If asked about claims, coverage limits, deductibles, or policy terms, provide accurate information from the document
+               9. Always prioritize customer understanding and satisfaction
+               10. If multiple interpretations are possible, explain the different scenarios clearly
+               Remember: You are here to help customers understand their insurance coverage better."""
+           },
+           {
+               "role": "user",
+               "content": f"""Insurance Document Content:
 {relevant_context}
 Customer Question: {user_question}
 Please provide a helpful response based on the insurance document content above."""
-                }
-            ]
-           # Add conversation history
-            for msg in self.conversation_history[-2:]:  # Keep last 6 messages for context
-               messages.append(msg)
-            # Get response from Azure OpenAI
-            response = self.azure_client.chat.completions.create(
-               model="gpt-4o-mini",
-               messages=messages,
-               max_tokens=300, #TODO
-               temperature=0.7
-            )
-            bot_response = response.choices[0].message.content
-            # Update conversation history
-            self.conversation_history.append({"role": "user", "content": user_question})
-            self.conversation_history.append({"role": "assistant", "content": bot_response})
-            return bot_response
-        except Exception as e:
-            return f"Error generating response: {str(e)}"
+            }
+        ]
+        # Add conversation history
+        for msg in self.conversation_history[-2:]:  # Keep last 6 messages for context
+           messages.append(msg)
+        # Get response from Azure OpenAI
+        response = self.azure_client.chat.completions.create(
+           model="gpt-4o-mini",
+           messages=messages,
+           max_tokens=300, #TODO
+           temperature=0.7
+        )
+        bot_response = response.choices[0].message.content
+        # Update conversation history
+        self.conversation_history.append({"role": "user", "content": user_question})
+        self.conversation_history.append({"role": "assistant", "content": bot_response})
+        return bot_response
+
 def main():
     # st.set_page_config(page_title="Insurance PDF Chatbot", page_icon="🛡️", layout="wide")
     st.title("🛡️ Insurance Policy Assistant")
@@ -88,7 +86,7 @@ def main():
             st.session_state.chatbot.conversation_history = []
             st.session_state.chat_history = []
             st.rerun()
-   # Main chat interface
+    # Main chat interface
     if st.session_state.pdf_processed:
         st.header("💬 Ask About Your Insurance Policy")
         # Display chat history
@@ -97,7 +95,7 @@ def main():
                 st.markdown(f"**You:** {question}")
                 st.markdown(f"**Insurance Assistant:** {answer}")
                 st.divider()
-       # Chat input
+        # Chat input
         user_question = st.chat_input("Hãy đặt những câu hỏi về hợp đồng bảo hiểm cơ bản...")
         if user_question:
             with st.spinner("Analyzing your policy..."):