Update app.py

app.py

@@ -131,7 +131,8 @@ def init_agent():
     return agent
 
 def process_final_report(agent, file, chatbot_state: List[Dict[str, str]]) -> Tuple[List[Dict[str, str]], Union[str, None]]:
-    """Process the Excel file and generate a final report."""
+    from concurrent.futures import ThreadPoolExecutor, as_completed
+
     messages = chatbot_state if chatbot_state else []
     report_path = None
 
@@ -145,16 +146,13 @@ def process_final_report(agent, file, chatbot_state: List[Dict[str, str]]) -> Tu
 
         extracted_text = extract_text_from_excel(file.name)
         chunks = split_text_into_chunks(extracted_text, max_tokens=MAX_CHUNK_TOKENS)
-        chunk_responses = []
+        chunk_responses = [None] * len(chunks)
 
-        for i, chunk in enumerate(chunks):
-            messages.append({"role": "assistant", "content": f"🔍 Analyzing chunk {i+1}/{len(chunks)}..."})
+        def analyze_chunk(index: int, chunk: str) -> Tuple[int, str]:
             prompt = build_prompt_from_text(chunk)
             prompt_tokens = estimate_tokens(prompt)
-
             if prompt_tokens > MAX_MODEL_TOKENS:
-                messages.append({"role": "assistant", "content": f"❌ Chunk {i+1} prompt too long ({prompt_tokens} tokens). Skipping..."})
-                continue
+                return index, f"❌ Chunk {index+1} prompt too long ({prompt_tokens} tokens). Skipping..."
 
             response = ""
             try:
@@ -176,19 +174,28 @@ def process_final_report(agent, file, chatbot_state: List[Dict[str, str]]) -> Tu
                             if hasattr(r, "content"):
                                 response += r.content
             except Exception as e:
-                messages.append({"role": "assistant", "content": f"❌ Error analyzing chunk {i+1}: {str(e)}"})
-                continue
-
-            chunk_responses.append(clean_response(response))
-            messages.append({"role": "assistant", "content": f"✅ Chunk {i+1} analysis complete"})
-
-        if not chunk_responses:
+                return index, f"❌ Error analyzing chunk {index+1}: {str(e)}"
+
+            return index, clean_response(response)
+
+        with ThreadPoolExecutor(max_workers=4) as executor:
+            futures = [executor.submit(analyze_chunk, i, chunk) for i, chunk in enumerate(chunks)]
+            for future in as_completed(futures):
+                i, result = future.result()
+                chunk_responses[i] = result
+                if not result.startswith("❌"):
+                    messages.append({"role": "assistant", "content": f"✅ Chunk {i+1} analysis complete"})
+                else:
+                    messages.append({"role": "assistant", "content": result})
+
+        valid_responses = [res for res in chunk_responses if not res.startswith("❌")]
+        if not valid_responses:
             messages.append({"role": "assistant", "content": "❌ No valid chunk responses to summarize."})
             return messages, report_path
 
         summary = ""
         current_summary_tokens = 0
-        for i, response in enumerate(chunk_responses):
+        for i, response in enumerate(valid_responses):
             response_tokens = estimate_tokens(response)
             if current_summary_tokens + response_tokens > MAX_MODEL_TOKENS - PROMPT_OVERHEAD - MAX_NEW_TOKENS:
                 summary_prompt = f"Summarize the following analysis:\n\n{summary}\n\nProvide a concise summary."
@@ -261,8 +268,6 @@ def process_final_report(agent, file, chatbot_state: List[Dict[str, str]]) -> Tu
         messages.append({"role": "assistant", "content": f"❌ Error processing file: {str(e)}"})
 
     return messages, report_path
-
-
 def create_ui(agent):
     """Create the Gradio UI for the patient history analysis tool."""
     with gr.Blocks(