1. Added a professional header and instructions

2. Implemented user-friendly response formatting
3. Added advanced settings panel for API keys and model configuration
4. Improved chat interface with bubbles and better formatting
5. Added optional text-to-speech capability (commented out but ready to use)
6. Added clear chat button
7. Improved overall layout and theme

requirements.txt

@@ -25,3 +25,4 @@ requests  # For MCP endpoint testing
 ffmpeg-python
 
 psutil  # For system resource detection
+gtts==2.3.1

src/app.py

@@ -10,6 +10,9 @@ import json
 import psutil
 from typing import Tuple, Dict
 import torch
+from gtts import gTTS
+import io
+import base64
 
 # Model options mapped to their requirements
 MODEL_OPTIONS = {
@@ -196,25 +199,113 @@ def process_speech(new_transcript, history):
     
     return history
 
-# Build Gradio interface
-with gr.Blocks() as demo:
-    gr.Markdown("# Symptom to ICD-10 Code Lookup")
-    
-    chatbot = gr.Chatbot(
-        label="Conversation",
-        type="messages",
-        height=400
-    )
+def text_to_speech(text):
+    """Convert text to speech and return audio HTML element."""
+    tts = gTTS(text=text, lang='en')
+    audio_fp = io.BytesIO()
+    tts.write_to_fp(audio_fp)
+    audio_b64 = base64.b64encode(audio_fp.getvalue()).decode()
+    return f'<audio src="data:audio/mp3;base64,{audio_b64}" autoplay></audio>'
+
+def format_response_for_user(response_dict):
+    """Convert JSON response to user-friendly format."""
+    diagnoses = response_dict.get("diagnoses", [])
+    confidences = response_dict.get("confidences", [])
+    follow_up = response_dict.get("follow_up", "")
     
-    microphone = gr.Microphone(
-        streaming=True,
-        type="filepath"  # Use 'filepath' to get the path to the recorded audio file
-    )
+    message = ""
+    if diagnoses and confidences:
+        for d, c in zip(diagnoses, confidences):
+            conf_percent = int(c * 100)
+            message += f"Possible diagnosis ({conf_percent}% confidence): {d}\n"
+    
+    if follow_up:
+        message += f"\n{follow_up}"
+    
+    return message
+
+# Build enhanced Gradio interface
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("""
+    # 🏥 Medical Symptom to ICD-10 Code Assistant
+    
+    ## About
+    This application is part of the Agents+MCP Hackathon. It helps medical professionals 
+    and patients understand potential diagnoses based on described symptoms.
+    
+    ### How it works:
+    1. Click the microphone button and describe your symptoms
+    2. The AI will analyze your description and suggest possible diagnoses
+    3. Answer follow-up questions to refine the diagnosis
+    
+    ### Created by:
+    Graham Paasch - Medical Coding Professional & Developer
+    [GitHub](https://github.com/yourusername) | [LinkedIn](https://linkedin.com/in/yourprofile)
+    """)
+    
+    with gr.Row():
+        with gr.Column(scale=2):
+            chatbot = gr.Chatbot(
+                label="Medical Consultation",
+                height=500,
+                container=True,
+                bubble=True
+            )
+            
+            with gr.Row():
+                microphone = gr.Microphone(
+                    label="Describe your symptoms",
+                    streaming=True,
+                    type="filepath"
+                )
+                clear_btn = gr.Button("Clear Chat", variant="secondary")
+                
+        with gr.Column(scale=1):
+            with gr.Accordion("Advanced Settings", open=False):
+                api_key = gr.Textbox(
+                    label="OpenAI API Key (optional)",
+                    type="password",
+                    placeholder="sk-..."
+                )
+                model_selector = gr.Dropdown(
+                    choices=list(MODEL_OPTIONS.keys()),
+                    label="Model Tier",
+                    value="small",
+                    interactive=True
+                )
+                temperature = gr.Slider(
+                    minimum=0.1,
+                    maximum=1.0,
+                    value=0.7,
+                    label="Temperature"
+                )
+    
+    # Event handlers
+    clear_btn.click(lambda: None, None, chatbot, queue=False)
+    
+    def enhanced_process_speech(audio_path, history, api_key=None, model_tier="small", temp=0.7):
+        transcript = process_speech(audio_path, history)
+        last_response = transcript[-1]["content"] if transcript else ""
+        
+        try:
+            response_dict = json.loads(last_response)
+            user_message = format_response_for_user(response_dict)
+            # Optionally generate speech
+            # audio_html = text_to_speech(user_message)
+            # return transcript + [{"role": "assistant", "content": audio_html}]
+            return transcript
+        except:
+            return transcript
     
-    # Connect the streaming microphone to the chat
     microphone.stream(
-        fn=process_speech,
-        inputs=[microphone, chatbot],
+        fn=enhanced_process_speech,
+        inputs=[
+            microphone,
+            chatbot,
+            api_key,
+            model_selector,
+            temperature
+        ],
         outputs=chatbot,
         show_progress="hidden"
     )