Update app.py

app.py

@@ -245,7 +245,7 @@ Analyze this patient record excerpt for missed diagnoses (limit response to 500
         
         with gr.Row():
             with gr.Column(scale=3):
-                chatbot = gr.Chatbot(label="Analysis", height=500)
+                chatbot = gr.Chatbot(label="Analysis", height=500, type="messages")
                 msg_input = gr.Textbox(placeholder="Ask about potential oversights...")
                 send_btn = gr.Button("Analyze", variant="primary")
                 file_upload = gr.File(file_types=[".pdf", ".csv", ".xls", ".xlsx"], file_count="single")
@@ -254,54 +254,58 @@ Analyze this patient record excerpt for missed diagnoses (limit response to 500
                 final_summary = gr.Markdown("## Summary")
                 status = gr.Textbox(label="Status", interactive=False)
 
-        def analyze(message: str, history: List[List[str]], files: List):
+        def analyze(message: str, history: List[Dict], file_obj) -> tuple:
             try:
-                if not files:
+                if not file_obj:
                     return history, "Please upload a file first", "No file uploaded"
-                
-                file = files[0]
-                file_type = file.name.split(".")[-1].lower()
-                history.append([message, None])
-                
+
+                file_path = file_obj.name
+                file_type = os.path.splitext(file_path)[-1].lower().replace(".", "")
+                history.append({"role": "user", "content": message})
+
                 # Process file
-                processed = process_file_cached(file.name, file_type)
+                processed = process_file_cached(file_path, file_type)
                 if "error" in processed[0]:
+                    history.append({"role": "assistant", "content": processed[0]["error"]})
                     return history, processed[0]["error"], "File processing failed"
-                
+
                 # Prepare chunks
                 chunks = []
                 for item in processed:
                     if "content" in item:
                         chunks.append(item["content"])
                     elif "rows" in item:
-                        rows_text = "\n".join([", ".join(map(str, row)) for row in item["rows"][:100]])  # Limit rows
+                        rows_text = "\n".join([", ".join(map(str, row)) for row in item["rows"][:100]])
                         chunks.append(f"=== {item.get('sheet', 'Data')} ===\n{rows_text}")
-                
+
                 if not chunks:
+                    history.append({"role": "assistant", "content": "No processable content found."})
                     return history, "No processable content found", "Content extraction failed"
-                
-                # Process chunks
+
+                # Analyze each chunk
                 responses = []
-                for i, chunk in enumerate(chunks[:5]):  # Limit to 5 chunks
+                for i, chunk in enumerate(chunks[:5]):
                     try:
-                        prompt = PROMPT_TEMPLATE.format(chunk=chunk[:5000])  # Limit chunk size
-                        response = agent.run_quick_summary(prompt, 0.2, 256, 500)  # Limit tokens
+                        prompt = PROMPT_TEMPLATE.format(chunk=chunk[:5000])
+                        response = agent.run_quick_summary(prompt, 0.2, 256, 500)
                         cleaned = clean_response(response)
                         if cleaned:
                             responses.append(f"Analysis {i+1}:\n{cleaned}")
                     except Exception as e:
-                        logger.warning(f"Error processing chunk {i+1}: {str(e)}")
+                        logger.warning(f"Error analyzing chunk {i+1}: {str(e)}")
                         continue
-                
+
                 if not responses:
+                    history.append({"role": "assistant", "content": "No valid analysis generated."})
                     return history, "No valid analysis generated", "Analysis failed"
-                
+
                 summary = "\n\n".join(responses)
-                history[-1][1] = summary
+                history.append({"role": "assistant", "content": summary})
                 return history, "Analysis completed", "Success"
-                
+
             except Exception as e:
                 logger.error(f"Analysis error: {e}")
+                history.append({"role": "assistant", "content": f"Error: {str(e)}"})
                 return history, f"Error: {str(e)}", "Failed"
             finally:
                 torch.cuda.empty_cache()
@@ -312,14 +316,16 @@ Analyze this patient record excerpt for missed diagnoses (limit response to 500
             inputs=[msg_input, chatbot, file_upload],
             outputs=[chatbot, final_summary, status]
         )
+
         msg_input.submit(
             analyze,
             inputs=[msg_input, chatbot, file_upload],
             outputs=[chatbot, final_summary, status]
         )
-    
+
     return demo
 
+
 if __name__ == "__main__":
     try:
         agent = init_agent()
@@ -331,4 +337,4 @@ if __name__ == "__main__":
         )
     except Exception as e:
         logger.error(f"Fatal error: {e}")
-        raise
+        raise