Update app.py

app.py

@@ -17,7 +17,7 @@ class AdvancedPdfChatbot:
         os.environ["OPENAI_API_KEY"] = openai_api_key
         self.embeddings = OpenAIEmbeddings()
         self.text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
-        self.llm = ChatOpenAI(temperature=0, model_name='gpt-4')  # Corrected model name
+        self.llm = ChatOpenAI(temperature=0, model_name='gpt-4')
         self.refinement_llm = ChatOpenAI(temperature=0, model_name='gpt-3.5-turbo')
         
         self.memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
@@ -52,6 +52,9 @@ class AdvancedPdfChatbot:
         self.setup_conversation_chain()
 
     def setup_conversation_chain(self):
+        if not self.db:
+            raise ValueError("Database not initialized. Please upload a PDF first.")
+            
         refinement_chain = LLMChain(
             llm=self.refinement_llm,
             prompt=self.refinement_prompt,
@@ -82,9 +85,9 @@ class AdvancedPdfChatbot:
         def _call(self, inputs):
             query = inputs['query']
             chat_history = inputs.get('chat_history', [])
-            refined_query = self.refinement_chain.run(query=query, chat_history=chat_history)
-            response = self.qa_chain({"question": refined_query, "chat_history": chat_history})
-            return {"answer": response['answer']}
+            refined_query = self.refinement_chain.run({'query': query, 'chat_history': chat_history})
+            response = self.qa_chain.run({"question": refined_query, "chat_history": chat_history})
+            return {"answer": response}
 
     def chat(self, query):
         if not self.overall_chain:
@@ -105,14 +108,22 @@ pdf_chatbot = AdvancedPdfChatbot(openai_api_key)
 def upload_pdf(pdf_file):
     if pdf_file is None:
         return "Please upload a PDF file."
-    file_path = pdf_file.name
-    pdf_chatbot.load_and_process_pdf(file_path)
-    return file_path
+    file_path = pdf_file.name if hasattr(pdf_file, 'name') else pdf_file
+    try:
+        pdf_chatbot.load_and_process_pdf(file_path)
+        return f"PDF processed successfully: {file_path}"
+    except Exception as e:
+        return f"Error processing PDF: {str(e)}"
 
 def respond(message, history):
-    bot_message = pdf_chatbot.chat(message)
-    history.append((message, bot_message))
-    return "", history
+    if not message:
+        return "", history
+    try:
+        bot_message = pdf_chatbot.chat(message)
+        history.append((message, bot_message))
+        return "", history
+    except Exception as e:
+        return f"Error: {str(e)}", history
 
 def clear_chatbot():
     pdf_chatbot.memory.clear()
@@ -131,15 +142,17 @@ with gr.Blocks() as demo:
 
     upload_status = gr.Textbox(label="Upload Status")
     upload_button.click(upload_pdf, inputs=[pdf_upload], outputs=[upload_status])
+    
     path_button = gr.Button("Get PDF Path")
     pdf_path_display = gr.Textbox(label="Current PDF Path")
+    
     chatbot_interface = gr.Chatbot()
-    msg = gr.Textbox()
-    clear = gr.Button("Clear")
+    msg = gr.Textbox(placeholder="Type your question here...")
+    clear = gr.Button("Clear Chat")
 
     msg.submit(respond, inputs=[msg, chatbot_interface], outputs=[msg, chatbot_interface])
     clear.click(clear_chatbot, outputs=[chatbot_interface])
     path_button.click(get_pdf_path, outputs=[pdf_path_display])
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()