Update app.py

app.py

@@ -3,7 +3,7 @@ import os
 import pandas as pd
 import json
 import gradio as gr
-from typing import List, Tuple, Dict, Any, Union
+from typing import List, Tuple, Union, Generator
 import hashlib
 import shutil
 import re
@@ -105,46 +105,45 @@ def init_agent():
     agent.init_model()
     return agent
 
-def process_final_report(agent, file, chatbot_state: List[Tuple[str, str]]) -> Tuple[List[Tuple[str, str]], Union[str, None], str]:
-    messages = chatbot_state if chatbot_state else []
+def stream_report(agent, file: gr.File, chatbot_state: List[Tuple[str, str]]) -> Generator:
+    messages = chatbot_state or []
     if file is None or not hasattr(file, "name"):
-        return messages + [("assistant", "❌ Please upload a valid Excel file.")], None, ""
+        yield messages + [("assistant", "❌ Please upload a valid Excel file.")], None, ""
+        return
 
     messages.append(("user", f"📎 Uploaded file: {os.path.basename(file.name)}"))
+    yield messages, None, ""
+
     text = extract_text_from_excel(file.name)
     chunks = split_text_into_chunks(text)
-    chunk_responses = [None] * len(chunks)
+    chunk_responses = []
 
-    def analyze_chunk(i, chunk):
+    for i, chunk in enumerate(chunks):
         prompt = build_prompt_from_text(chunk)
-        response = ""
+        partial = ""
         for res in agent.run_gradio_chat(
             message=prompt, history=[], temperature=0.2,
             max_new_tokens=MAX_NEW_TOKENS, max_token=MAX_MODEL_TOKENS,
             call_agent=False, conversation=[]
         ):
             if isinstance(res, str):
-                response += res
+                partial += res
             elif hasattr(res, "content"):
-                response += res.content
-            elif isinstance(res, list):
-                for r in res:
-                    if hasattr(r, "content"):
-                        response += r.content
-        return i, clean_response(response)
-
-    with ThreadPoolExecutor(max_workers=1) as executor:
-        futures = [executor.submit(analyze_chunk, i, c) for i, c in enumerate(chunks)]
-        for f in as_completed(futures):
-            i, result = f.result()
-            chunk_responses[i] = result
+                partial += res.content
+        cleaned = clean_response(partial)
+        messages.append(("assistant", f"📄 Chunk {i+1}:\n\n{cleaned}"))
+        chunk_responses.append(cleaned)
+        yield messages, None, ""
 
     valid = [r for r in chunk_responses if r and not r.startswith("❌")]
     if not valid:
-        return messages + [("assistant", "❌ No valid results found in the file.")], None, ""
+        messages.append(("assistant", "❌ No valid results found in the file."))
+        yield messages, None, ""
+        return
 
     summary_prompt = f"Summarize this analysis in a final structured report:\n\n" + "\n\n".join(valid)
-    messages.append(("assistant", "⏳ Generating the final report..."))
+    messages.append(("assistant", "📊 Generating final summary..."))
+    yield messages, None, ""
 
     final_report = ""
     for res in agent.run_gradio_chat(
@@ -158,13 +157,12 @@ def process_final_report(agent, file, chatbot_state: List[Tuple[str, str]]) -> T
             final_report += res.content
 
     cleaned = clean_response(final_report)
-    messages.append(("assistant", cleaned))  # ✅ Append answer to chat
-
+    messages.append(("assistant", cleaned))
     report_path = os.path.join(report_dir, f"report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.md")
     with open(report_path, 'w') as f:
         f.write(f"# 🧠 Final Patient Report\n\n{cleaned}")
 
-    return messages, report_path, cleaned
+    yield messages, report_path, cleaned
 
 def create_ui(agent):
     with gr.Blocks(css="""
@@ -213,14 +211,10 @@ Upload clinical Excel records below and click **Analyze** to generate a medical
         report_output = gr.File(label="Download Report", visible=False)
         chatbot_state = gr.State(value=[])
 
-        def update_ui(file, current_state):
-            messages, report_path, final_text = process_final_report(agent, file, current_state)
-            return messages, gr.update(visible=report_path is not None, value=report_path), messages, gr.update(visible=True, value=final_text)
-
         analyze_btn.click(
-            fn=update_ui,
+            fn=stream_report,
             inputs=[file_upload, chatbot_state],
-            outputs=[chatbot, report_output, chatbot_state, report_output_markdown]
+            outputs=[chatbot, report_output, report_output_markdown]
         )
 
     return demo