Update app.py

app.py

@@ -131,8 +131,9 @@ def process_final_report(agent, file, chatbot_state: List[Dict[str, str]]) -> Tu
         return messages, report_path
 
     try:
-        messages.append({"role": "user", "content": f"Processing Excel file: {os.path.basename(file.name)}"})
-        messages.append({"role": "assistant", "content": "⏳ Extracting and analyzing data..."})
+        messages.append({"role": "user", "content": f"📄 Processing Excel file: {os.path.basename(file.name)}"})
+        messages.append({"role": "assistant", "content": "🔍 Analyzing clinical data... This may take a moment."})
+        
         extracted_text = extract_text_from_excel(file.name)
         chunks = split_text_into_chunks(extracted_text)
         chunk_responses = [None] * len(chunks)
@@ -165,57 +166,32 @@ def process_final_report(agent, file, chatbot_state: List[Dict[str, str]]) -> Tu
                 return index, f"❌ Error analyzing chunk {index+1}: {str(e)}"
             return index, clean_response(response)
 
+        # Process chunks silently without displaying progress
         with ThreadPoolExecutor(max_workers=1) 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."})
+            messages.append({"role": "assistant", "content": "❌ No valid analysis results to summarize."})
             return messages, report_path
 
-        summary = ""
-        current_summary_tokens = 0
-        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."
-                summary_response = ""
-                try:
-                    for result in agent.run_gradio_chat(
-                        message=summary_prompt,
-                        history=[],
-                        temperature=0.2,
-                        max_new_tokens=MAX_NEW_TOKENS,
-                        max_token=MAX_MODEL_TOKENS,
-                        call_agent=False,
-                        conversation=[],
-                    ):
-                        if isinstance(result, str):
-                            summary_response += result
-                        elif hasattr(result, "content"):
-                            summary_response += result.content
-                        elif isinstance(result, list):
-                            for r in result:
-                                if hasattr(r, "content"):
-                                    summary_response += r.content
-                    summary = clean_response(summary_response)
-                    current_summary_tokens = estimate_tokens(summary)
-                except Exception as e:
-                    messages.append({"role": "assistant", "content": f"❌ Error summarizing intermediate results: {str(e)}"})
-                    return messages, report_path
-            summary += f"\n\n### Chunk {i+1} Analysis\n{response}"
-            current_summary_tokens += response_tokens
-
-        final_prompt = f"Summarize the key findings from the following analyses:\n\n{summary}"
-        messages.append({"role": "assistant", "content": "📊 Generating final report..."})
+        summary = "\n\n".join(valid_responses)
+        final_prompt = f"""Please synthesize the following clinical analyses into a concise, well-structured report:
+        
+{summary}
+
+Structure your response with clear sections:
+1. Key Diagnostic Patterns
+2. Medication Concerns
+3. Potential Missed Opportunities
+4. Notable Inconsistencies
+5. Recommended Follow-ups
 
+Use bullet points for clarity and professional medical terminology."""
+        
         final_report_text = ""
         try:
             for result in agent.run_gradio_chat(
@@ -239,16 +215,18 @@ def process_final_report(agent, file, chatbot_state: List[Dict[str, str]]) -> Tu
             messages.append({"role": "assistant", "content": f"❌ Error generating final report: {str(e)}"})
             return messages, report_path
 
-        final_report = f"# 🧠 Final Patient Report\n\n{clean_response(final_report_text)}"
-        messages[-1]["content"] = f"📊 Final Report:\n\n{clean_response(final_report_text)}"
+        final_report = f"# 🧠 Clinical Analysis Report\n\n{clean_response(final_report_text)}"
+        
+        # Update the last message with the final report
+        messages[-1]["content"] = f"## 📋 Clinical Analysis Report\n\n{clean_response(final_report_text)}"
 
         timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
-        report_path = os.path.join(report_dir, f"report_{timestamp}.md")
+        report_path = os.path.join(report_dir, f"clinical_report_{timestamp}.md")
 
         with open(report_path, 'w') as f:
             f.write(final_report)
 
-        messages.append({"role": "assistant", "content": f"✅ Report generated and saved: report_{timestamp}.md"})
+        messages.append({"role": "assistant", "content": f"✅ Report generated successfully. You can download it below."})
 
     except Exception as e:
         messages.append({"role": "assistant", "content": f"❌ Error processing file: {str(e)}"})
@@ -257,63 +235,129 @@ def process_final_report(agent, file, chatbot_state: List[Dict[str, str]]) -> Tu
 
 def create_ui(agent):
     with gr.Blocks(
-        title="Patient History Chat",
+        title="Clinical Analysis Tool",
         css="""
         .gradio-container {
             max-width: 900px !important;
             margin: auto;
-            font-family: 'Segoe UI', sans-serif;
-            background-color: #f8f9fa;
+            font-family: 'Inter', sans-serif;
+            background-color: #f9fafb;
         }
         .gr-button.primary {
-            background: linear-gradient(to right, #4b6cb7, #182848);
+            background: linear-gradient(to right, #4f46e5, #7c3aed);
             color: white;
             border: none;
             border-radius: 8px;
+            padding: 12px 24px;
+            font-weight: 500;
+            transition: all 0.2s;
         }
         .gr-button.primary:hover {
-            background: linear-gradient(to right, #3552a3, #101a3e);
+            background: linear-gradient(to right, #4338ca, #6d28d9);
+            transform: translateY(-1px);
+            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
         }
         .gr-file-upload, .gr-chatbot, .gr-markdown {
             background-color: white;
-            border-radius: 10px;
-            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-            padding: 1rem;
+            border-radius: 12px;
+            box-shadow: 0 1px 3px rgba(0,0,0,0.05);
+            padding: 1.5rem;
+            border: 1px solid #e5e7eb;
         }
         .gr-chatbot {
-            border-left: 4px solid #4b6cb7;
+            min-height: 600px;
+            border-left: none;
         }
-        .gr-file-upload input {
-            font-size: 0.95rem;
+        .chat-message-user {
+            background-color: #f3f4f6;
+            border-radius: 12px;
+            padding: 12px 16px;
+            margin: 8px 0;
+        }
+        .chat-message-assistant {
+            background-color: white;
+            border-radius: 12px;
+            padding: 12px 16px;
+            margin: 8px 0;
+            border: 1px solid #e5e7eb;
         }
-        .chat-message-content p {
+        .chat-message-content ul, .chat-message-content ol {
+            padding-left: 1.5em;
+            margin: 0.5em 0;
+        }
+        .chat-message-content li {
             margin: 0.3em 0;
         }
-        .chat-message-content ul {
-            padding-left: 1.2em;
-            margin: 0.4em 0;
+        h1, h2, h3 {
+            color: #111827;
+        }
+        .gr-markdown h1 {
+            font-size: 1.8rem;
+            margin-bottom: 1rem;
+            font-weight: 600;
+        }
+        .gr-markdown p {
+            color: #4b5563;
+            line-height: 1.6;
+        }
+        .progress-bar {
+            height: 4px;
+            background: #e5e7eb;
+            border-radius: 2px;
+            margin: 12px 0;
+            overflow: hidden;
+        }
+        .progress-bar-fill {
+            height: 100%;
+            background: linear-gradient(to right, #4f46e5, #7c3aed);
+            transition: width 0.3s ease;
         }
         """
     ) as demo:
         gr.Markdown("""
-        <h2 style='color:#182848'>🏥 Patient History Analysis Tool</h2>
-        <p style='color:#444;'>Upload an Excel file containing clinical data. The assistant will analyze it for patterns, inconsistencies, and recommendations.</p>
+        <div style='text-align: center; margin-bottom: 1.5rem;'>
+            <h1 style='margin-bottom: 0.5rem; color: #111827;'>Clinical Documentation Analyzer</h1>
+            <p style='color: #6b7280; margin-top: 0;'>Upload patient records in Excel format for comprehensive clinical analysis</p>
+        </div>
         """)
 
         with gr.Row():
             with gr.Column(scale=3):
                 chatbot = gr.Chatbot(
-                    label="Clinical Assistant",
+                    label="Analysis Results",
                     show_copy_button=True,
                     height=600,
-                    type="messages",
+                    bubble_full_width=False,
                     avatar_images=(None, "https://i.imgur.com/6wX7Zb4.png"),
-                    render_markdown=True
+                    render_markdown=True,
+                    likeable=True,
+                    layout="panel"
                 )
             with gr.Column(scale=1):
-                file_upload = gr.File(label="Upload Excel File", file_types=[".xlsx"], height=100)
-                analyze_btn = gr.Button("🧠 Analyze Patient History", variant="primary", elem_classes="primary")
-                report_output = gr.File(label="Download Report", visible=False, interactive=False)
+                file_upload = gr.File(
+                    label="Upload Patient Records",
+                    file_types=[".xlsx", ".xls"],
+                    height=100,
+                    interactive=True
+                )
+                analyze_btn = gr.Button(
+                    "Analyze Clinical Data",
+                    variant="primary",
+                    elem_classes="primary"
+                )
+                report_output = gr.File(
+                    label="Download Report",
+                    visible=False,
+                    interactive=False
+                )
+                gr.Markdown("""
+                <div style='margin-top: 1rem; padding: 1rem; background-color: #f8fafc; border-radius: 8px;'>
+                    <h3 style='margin-top: 0; margin-bottom: 0.5rem; font-size: 1rem;'>About this tool</h3>
+                    <p style='margin: 0; font-size: 0.9rem; color: #64748b;'>
+                        This tool analyzes clinical documentation to identify patterns, inconsistencies, and opportunities for improved patient care.
+                    </p>
+                </div>
+                """)
 
         chatbot_state = gr.State(value=[])
 
@@ -324,13 +368,23 @@ def create_ui(agent):
                 role = msg.get("role")
                 content = msg.get("content", "")
                 if role == "assistant":
-                    content = content.replace("- ", "\n- ")
-                    content = f"<div class='chat-message-content'>{content}</div>"
+                    # Format lists and sections for better readability
+                    content = content.replace("- ", "• ")
+                    content = re.sub(r"(\d+\.\s)", r"\n\1", content)
+                    content = f"<div class='chat-message-assistant'>{content}</div>"
+                else:
+                    content = f"<div class='chat-message-user'>{content}</div>"
                 formatted_messages.append({"role": role, "content": content})
+            
             report_update = gr.update(visible=report_path is not None, value=report_path)
             return formatted_messages, report_update, formatted_messages
 
-        analyze_btn.click(fn=update_ui, inputs=[file_upload, chatbot_state], outputs=[chatbot, report_output, chatbot_state], api_name="analyze")
+        analyze_btn.click(
+            fn=update_ui,
+            inputs=[file_upload, chatbot_state],
+            outputs=[chatbot, report_output, chatbot_state],
+            api_name="analyze"
+        )
 
     return demo
 
@@ -338,7 +392,13 @@ if __name__ == "__main__":
     try:
         agent = init_agent()
         demo = create_ui(agent)
-        demo.launch(server_name="0.0.0.0", server_port=7860, show_error=True, allowed_paths=["/data/hf_cache/reports"], share=False)
+        demo.launch(
+            server_name="0.0.0.0",
+            server_port=7860,
+            show_error=True,
+            allowed_paths=["/data/hf_cache/reports"],
+            share=False
+        )
     except Exception as e:
         print(f"Error: {str(e)}")
-        sys.exit(1)
+        sys.exit(1)