Update app.py

app.py

@@ -10,7 +10,7 @@ from langchain.chains import ConversationalRetrievalChain, LLMChain
 from langchain.memory import ConversationBufferMemory
 from langchain.prompts import PromptTemplate
 import concurrent.futures
-
+import timeout_decorator
 from PyPDF2 import PdfReader  # New import for PDF metadata extraction
 
 # Configure logging
@@ -92,7 +92,9 @@ If the answer isn't directly available, explain why. """,
             # Extract document context and store it in memory
             document_context = self._extract_document_type()
             logger.info(f"Extracted document context: {document_context}")
-            self.memory.chat_history.append(("System", f"Document context: {document_context}"))
+            
+            # Save document context in memory properly
+            self.memory.save_context({"input": "System"}, {"output": f"Document context: {document_context}"})
         
         except Exception as e:
             logger.error(f"PDF processing error: {e}")
@@ -144,7 +146,6 @@ If the answer isn't directly available, explain why. """,
     def _extract_headings(self, text):
         """Extract headings from the first document's content"""
         try:
-            # Simple heuristic: Extract lines with uppercase or title-case words (like headings)
             headings = [line for line in text.split("\n") if line.strip().istitle()]
             return ', '.join(headings[:5])  # Return the first 5 headings
         except Exception as e:
@@ -186,18 +187,15 @@ def clear_chatbot():
 # Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("# Advanced PDF Chatbot")
-    
     with gr.Row():
         pdf_upload = gr.File(label="Upload PDF", file_types=[".pdf"])
         upload_button = gr.Button("Process PDF")
 
     upload_status = gr.Textbox(label="Upload Status")
     upload_button.click(upload_pdf, inputs=[pdf_upload], outputs=[upload_status])
-    
     chatbot_interface = gr.Chatbot()
     msg = gr.Textbox(placeholder="Enter your query...")
     msg.submit(respond, inputs=[msg, chatbot_interface], outputs=[msg, chatbot_interface])
-    
     clear_button = gr.Button("Clear Conversation")
     clear_button.click(clear_chatbot, outputs=[chatbot_interface])