updated code ✅✅

mediSync/app.py

@@ -449,7 +449,8 @@ class MediSyncApp:
         )
 
 def create_interface():
-    """Create and launch the Gradio interface for Hugging Face Spaces."""
+    """Create and launch the Gradio interface with all fixes implemented."""
+
     app = MediSyncApp()
 
     # Example medical report for demo
@@ -471,24 +472,53 @@ def create_interface():
     RECOMMENDATIONS: Follow-up chest CT to further characterize the nodular opacity in the right lower lobe.
     """
 
-    # Get sample image - simplified for Hugging Face Spaces
+    # Get sample image path with robust error handling
     sample_image_path = None
     try:
-        # Try to use a sample image from the web
-        sample_url = "https://raw.githubusercontent.com/ieee8023/covid-chestxray-dataset/master/images/1-s2.0-S0929664620300449-gr2_lrg-a.jpg"
-        response = requests.get(sample_url, timeout=10)
-        if response.status_code == 200:
-            sample_image = Image.open(io.BytesIO(response.content))
-            sample_image_path = sample_image
+        sample_images_dir = Path(__file__).parent.parent / "data" / "sample"
+        os.makedirs(sample_images_dir, exist_ok=True)
+        
+        # Check for existing images first
+        sample_images = list(sample_images_dir.glob("*.png")) + list(sample_images_dir.glob("*.jpg"))
+        
+        if not sample_images:
+            # Download fallback sample image if none exist
+            fallback_url = "https://raw.githubusercontent.com/ieee8023/covid-chestxray-dataset/master/images/1-s2.0-S0929664620300449-gr2_lrg-a.jpg"
+            sample_path = sample_images_dir / "sample_xray.jpg"
+            
+            try:
+                response = requests.get(fallback_url, timeout=10)
+                if response.status_code == 200:
+                    with open(sample_path, 'wb') as f:
+                        f.write(response.content)
+                    sample_image_path = str(sample_path)
+                    logging.info("Successfully downloaded fallback sample image")
+                else:
+                    logging.warning(f"Failed to download sample image. Status code: {response.status_code}")
+            except Exception as download_error:
+                logging.warning(f"Could not download sample image: {str(download_error)}")
+        else:
+            sample_image_path = str(sample_images[0])
     except Exception as e:
-        logging.warning(f"Could not load sample image: {str(e)}")
+        logging.error(f"Error setting up sample images: {str(e)}")
 
-    # Define interface
+    # Define interface with robust parameter handling
     with gr.Blocks(
         title="MediSync: Multi-Modal Medical Analysis System", 
-        theme=gr.themes.Soft(),
-        css=".alert {padding: 10px; border-radius: 5px;} .alert-error {background-color: #ffebee;} .alert-success {background-color: #e8f5e9;}"
+        theme=gr.themes.Soft()
     ) as interface:
+        # Get appointment ID from URL parameters using JavaScript
+        appointment_id = gr.Textbox(
+            visible=False,
+            value="",
+            _js="""
+            function() {
+                const params = new URLSearchParams(window.location.search);
+                return params.get('appointment_id') || '';
+            }
+            """
+        )
+
         gr.Markdown("""
         # MediSync: Multi-Modal Medical Analysis System
         
@@ -499,20 +529,22 @@ def create_interface():
         1. Upload a chest X-ray image
         2. Enter the corresponding medical report text
         3. Choose the analysis type: image-only, text-only, or multimodal (combined)
-        4. View the analysis results
+        4. Click "End Consultation" when finished to complete your appointment
         """)
 
         with gr.Tab("Multimodal Analysis"):
             with gr.Row():
                 with gr.Column():
                     multi_img_input = gr.Image(label="Upload X-ray Image", type="pil")
-                    multi_img_enhance = gr.Button("Enhance Image", variant="secondary")
+                    multi_img_enhance = gr.Button("Enhance Image")
+
                     multi_text_input = gr.Textbox(
                         label="Enter Medical Report Text",
                         placeholder="Enter the radiologist's report text here...",
                         lines=10,
-                        value=example_report,
+                        value=example_report if not sample_image_path else None,
                     )
+
                     multi_analyze_btn = gr.Button(
                         "Analyze Image & Text", variant="primary"
                     )
@@ -532,7 +564,7 @@ def create_interface():
             with gr.Row():
                 with gr.Column():
                     img_input = gr.Image(label="Upload X-ray Image", type="pil")
-                    img_enhance = gr.Button("Enhance Image", variant="secondary")
+                    img_enhance = gr.Button("Enhance Image")
                     img_analyze_btn = gr.Button("Analyze Image", variant="primary")
 
                 with gr.Column():
@@ -559,7 +591,7 @@ def create_interface():
                     text_analyze_btn = gr.Button("Analyze Text", variant="primary")
 
                 with gr.Column():
-                    text_output = gr.Textbox(label="Processed Text", interactive=False)
+                    text_output = gr.Textbox(label="Processed Text")
                     text_results = gr.HTML(label="Analysis Results")
                     text_plot = gr.HTML(label="Entity Visualization")
 
@@ -577,20 +609,33 @@ def create_interface():
             
             ### Key Features
             
-            - **X-ray Image Analysis**: Detects abnormalities in chest X-rays
-            - **Medical Report Processing**: Extracts key information from patient reports
-            - **Multi-modal Integration**: Combines insights from both image and text data
+            - **X-ray Image Analysis**: Detects abnormalities in chest X-rays using pre-trained vision models
+            - **Medical Report Processing**: Extracts key information from patient reports using NLP models
+            - **Multi-modal Integration**: Combines insights from both image and text data for more accurate analysis
+            
+            ### Models Used
+            
+            - **X-ray Analysis**: facebook/deit-base-patch16-224-medical-cxr
+            - **Medical Text Analysis**: medicalai/ClinicalBERT
             
             ### Important Disclaimer
             
             This tool is for educational and research purposes only. It is not intended to provide medical advice or replace professional healthcare. Always consult with qualified healthcare providers for medical decisions.
             """)
 
+        # Consultation completion section
+        with gr.Row():
+            with gr.Column():
+                end_consultation_btn = gr.Button(
+                    "End Consultation", 
+                    variant="stop",
+                    size="lg"
+                )
+                completion_status = gr.HTML()
+
         # Set up event handlers
         multi_img_enhance.click(
-            app.enhance_image, 
-            inputs=multi_img_input, 
-            outputs=multi_img_input
+            app.enhance_image, inputs=multi_img_input, outputs=multi_img_input
         )
         multi_analyze_btn.click(
             app.analyze_multimodal,
@@ -598,11 +643,7 @@ def create_interface():
             outputs=[multi_results, multi_plot],
         )
 
-        img_enhance.click(
-            app.enhance_image, 
-            inputs=img_input, 
-            outputs=img_output
-        )
+        img_enhance.click(app.enhance_image, inputs=img_input, outputs=img_output)
         img_analyze_btn.click(
             app.analyze_image,
             inputs=img_input,
@@ -615,12 +656,59 @@ def create_interface():
             outputs=[text_output, text_results, text_plot],
         )
 
-    # Launch configuration for Hugging Face Spaces
-    interface.launch(
-        server_name="0.0.0.0",
-        server_port=int(os.getenv("PORT", "7860")),
-        share=False
-    )
+        def complete_consultation(appointment_id):
+            """Handle consultation completion."""
+            if not appointment_id:
+                return "<div class='alert alert-error'>No appointment ID found. Please contact support.</div>"
+            
+            try:
+                # Replace with your actual Flask app URL
+                flask_app_url = "http://127.0.0.1:600/complete_consultation"
+                
+                response = requests.post(
+                    flask_app_url,
+                    json={"appointment_id": appointment_id},
+                    timeout=10
+                )
+                
+                if response.status_code == 200:
+                    return """
+                    <div class='alert alert-success'>
+                        Consultation completed successfully. Redirecting...
+                        <script>
+                            setTimeout(function() {
+                                window.location.href = "http://127.0.0.1:600/doctors";
+                            }, 2000);
+                        </script>
+                    </div>
+                    """
+                else:
+                    return f"""
+                    <div class='alert alert-error'>
+                        Error completing appointment (Status: {response.status_code}). 
+                        Please contact support.
+                    </div>
+                    """
+                    
+            except Exception as e:
+                return f"""
+                <div class='alert alert-error'>
+                    Error: {str(e)}
+                </div>
+                """
+
+        end_consultation_btn.click(
+            fn=complete_consultation,
+            inputs=[appointment_id],
+            outputs=completion_status
+        )
+
+    try:
+        interface.launch()
+    except Exception as e:
+        logging.error(f"Failed to launch interface: {str(e)}")
+        raise RuntimeError("Failed to launch MediSync interface") from e
+
 
 if __name__ == "__main__":
     logging.basicConfig(