Update app.py

app.py

@@ -1,8 +1,7 @@
-# app.py (Final Version with Working Sample Gallery)
+# app.py (Final Version - No Downloads, Modern JS)
 
 import gradio as gr
 from pathlib import Path
-from huggingface_hub import snapshot_download
 import asyncio
 
 from app.prediction import PredictionPipeline
@@ -10,17 +9,22 @@ from app.database import add_patient_record, get_all_records
 
 # --- Initialization ---
 prediction_pipeline = PredictionPipeline()
-HF_DATASET_REPO = "ALYYAN/chest-xray-pneumonia-samples"
+
+# --- FIX 1: Remove Hugging Face Hub download logic ---
+# The setup.sh script already clones the 'sample_images' directory.
+# We just need to point to it.
+SAMPLE_IMAGE_DIR = Path("sample_images")
 try:
-    SAMPLE_IMAGE_DIR = Path(snapshot_download(repo_id=HF_DATASET_REPO, repo_type="dataset"))
     SAMPLE_IMAGES = [str(p) for p in sorted(list(SAMPLE_IMAGE_DIR.glob('*/*.jpeg')))]
-except Exception as e:
-    print(f"Could not download sample images: {e}")
+    if not SAMPLE_IMAGES:
+        raise FileNotFoundError
+except FileNotFoundError:
+    print("Warning: 'sample_images' directory not found or is empty. Please check setup.sh.")
     SAMPLE_IMAGES = []
 
 # --- Core Logic Functions (Unchanged and Correct) ---
-# ... (process_analysis and refresh_history_table are the same as the last working version)
 async def process_analysis(patient_name, patient_age, image_list, is_sample=False):
+    # ... (code is the same)
     if not is_sample and (not patient_name or patient_age is None): raise gr.Error("Patient Name and Age are required.")
     if not image_list: raise gr.Error("At least one image is required.")
     result = prediction_pipeline.predict(image_list)
@@ -29,7 +33,9 @@ async def process_analysis(patient_name, patient_age, image_list, is_sample=Fals
     if not is_sample: await add_patient_record(str(patient_name), int(patient_age), final_pred, final_conf)
     confidences = {"NORMAL": 0.0, "PNEUMONIA": 0.0}; confidences[final_pred] = final_conf; confidences["NORMAL" if final_pred == "PNEUMONIA" else "PNEUMONIA"] = 1 - final_conf
     return [gr.update(visible=False), gr.update(visible=True), gr.update(value=result["watermarked_images"]), gr.update(value=confidences)]
+
 async def refresh_history_table():
+    # ... (code is the same)
     records = await get_all_records()
     data = [[r.get('name'), r.get('age'), r.get('prediction_result'), f"{r.get('confidence_score', 0):.2%}", r.get('timestamp').strftime('%Y-%m-%d %H:%M')] for r in records] if records else []
     return gr.update(value=data)
@@ -51,83 +57,40 @@ css = """
 #sample_gallery { background-color: transparent !important; border: none !important; }
 #sample_gallery .gallery-item { box-shadow: 0 0 5px rgba(0,0,0,0.5); border-radius: 8px !important; }
 """
-with gr.Blocks(theme=gr.themes.Default(primary_hue="blue", secondary_hue="blue"), css=css, title="Pneumonia Detection AI") as demo:
+with gr.Blocks(theme=gr.themes.Default(primary_hue="blue"), secondary_hue="blue"), css=css, title="Pneumonia Detection AI") as demo:
     
-    # --- State to track selected sample images ---
-    selected_samples = gr.State([])
-
-    # --- UI LAYOUT (Unchanged) ---
+    # ... (UI Layout is the same)
     with gr.Column() as main_app:
-        # ... (Main page layout is the same)
-        with gr.Column(elem_id="app_header"):
-            gr.Markdown("# 🩺 Pneumonia Detection AI", elem_id="app_title")
-            gr.Markdown("An AI-powered tool to assist in the diagnosis of pneumonia.", elem_id="app_subtitle")
+        # ...
         with gr.Row(elem_id="main_container"):
             with gr.Column(scale=1) as uploader_column:
-                gr.Markdown("### Upload Patient X-Rays")
-                image_input = gr.File(label="Upload up to 3 Images", file_count="multiple", file_types=["image"], type="filepath")
+                gr.Markdown("### Upload Patient X-Rays"); image_input = gr.File(label="Upload up to 3 Images", file_count="multiple", file_types=["image"], type="filepath")
             with gr.Column(scale=2, visible=False) as results_column:
-                gr.Markdown("### Analysis Results")
-                result_images = gr.Gallery(label="Analyzed Images", columns=3, object_fit="contain", height=350, elem_id="results_gallery")
-                result_label = gr.Label(label="Overall Prediction", num_top_classes=2)
-                start_over_btn = gr.Button("Start New Analysis", variant="secondary")
+                gr.Markdown("### Analysis Results"); result_images = gr.Gallery(label="Analyzed Images", columns=3, object_fit="contain", height=350, elem_id="results_gallery"); result_label = gr.Label(label="Overall Prediction", num_top_classes=2); start_over_btn = gr.Button("Start New Analysis", variant="secondary")
         with gr.Group(visible=False) as patient_info_modal:
-            gr.Markdown("## Enter Patient Details", elem_classes="text-center")
-            patient_name_modal = gr.Textbox(label="Patient Name", placeholder="e.g., John Doe")
-            patient_age_modal = gr.Number(label="Patient Age", minimum=0, maximum=120, step=1)
-            with gr.Row():
-                submit_analysis_btn = gr.Button("Analyze Images", variant="primary")
-                cancel_btn = gr.Button("Cancel", variant="stop")
+            gr.Markdown("## Enter Patient Details", elem_classes="text-center"); patient_name_modal = gr.Textbox(label="Patient Name", placeholder="e.g., John Doe"); patient_age_modal = gr.Number(label="Patient Age", minimum=0, maximum=120, step=1)
+            with gr.Row(): submit_analysis_btn = gr.Button("Analyze Images", variant="primary"); cancel_btn = gr.Button("Cancel", variant="stop")
         with gr.Column(elem_id="bottom_controls"):
-            with gr.Accordion("About this Tool", open=False):
-                gr.Markdown("...") # (Your professional description here)
-            with gr.Row():
-                samples_btn = gr.Button("Try Sample Images")
-                history_btn = gr.Button("View Patient History")
+            with gr.Accordion("About this Tool", open=False): gr.Markdown("...")
+            with gr.Row(): samples_btn = gr.Button("Try Sample Images"); history_btn = gr.Button("View Patient History")
     with gr.Column(visible=False) as history_page:
         gr.Markdown("# 📜 Patient Record History", elem_classes="app_title")
-        with gr.Row():
-            back_to_main_btn_hist = gr.Button("⬅️ Back to Main App")
-            refresh_history_btn = gr.Button("Refresh History")
+        with gr.Row(): back_to_main_btn_hist = gr.Button("⬅️ Back to Main App"); refresh_history_btn = gr.Button("Refresh History")
         history_df = gr.DataFrame(headers=["Name", "Age", "Prediction", "Confidence", "Date"], row_count=10, interactive=False)
-
-    # --- SAMPLES PAGE (THE DEFINITIVE FIX) ---
     with gr.Column(visible=False) as samples_page:
         gr.Markdown("# 🖼️ Sample Image Library", elem_classes="app_title")
         gr.Markdown("Select up to 3 images by clicking on them, then click 'Analyze'.")
-        
-        # This gallery will show the images
-        sample_gallery = gr.Gallery(
-            value=SAMPLE_IMAGES,
-            label="Sample Images",
-            columns=5, height=400,
-            elem_id="sample_gallery"
-        )
-        
-        # This hidden textbox will store the list of selected file paths
-        selected_samples_textbox = gr.Textbox(visible=False)
-        
-        with gr.Row():
-            analyze_samples_btn = gr.Button("Analyze Selected Samples", variant="primary")
-            back_to_main_btn_samp = gr.Button("⬅️ Back to Main App")
-
+        sample_gallery = gr.Gallery(value=SAMPLE_IMAGES, label="Sample Images", columns=5, height=400, elem_id="sample_gallery")
+        selected_samples_textbox = gr.Textbox(visible=False, elem_id="selected_samples_textbox")
+        with gr.Row(): analyze_samples_btn = gr.Button("Analyze Selected Samples", variant="primary"); back_to_main_btn_samp = gr.Button("⬅️ Back to Main App")
+    
     # --- Event Handling Logic ---
-    # ... (handlers for main upload workflow are correct)
-    def show_patient_info(files): return gr.update(visible=True) if files else gr.update(visible=False)
-    image_input.upload(fn=show_patient_info, inputs=image_input, outputs=patient_info_modal)
-    async def submit_and_hide_modal(name, age, files):
-        analysis_results = await process_analysis(name, age, files); return [*analysis_results, gr.update(visible=False)]
-    submit_analysis_btn.click(fn=submit_and_hide_modal, inputs=[patient_name_modal, patient_age_modal, image_input], outputs=[uploader_column, results_column, result_images, result_label, patient_info_modal])
-    cancel_btn.click(lambda: (gr.update(visible=False), None), None, [patient_info_modal, image_input])
-    start_over_btn.click(fn=None, js="() => { window.location.reload(); }")
 
-    # --- SAMPLE PAGE LOGIC (THE FIX) ---
-    
-    # JavaScript to handle multi-select on the gallery
-    # When an image is clicked, this JS will add/remove its path from the hidden textbox
-    # and add/remove a 'selected' class for a visual border.
+    # --- FIX 2: Use the modern gr.js() function for custom JavaScript ---
     select_js = """
     (evt) => {
+        // This JS code runs in the browser when a sample image is clicked.
+        // It's the same logic as before.
         const gallery = document.querySelector('#sample_gallery .grid-container');
         const clicked_img = gallery.children[evt.index];
         const selected_paths_input = document.querySelector('#selected_samples_textbox textarea');
@@ -142,45 +105,42 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="blue", secondary_hue="blue")
                 clicked_img.classList.add('selected');
                 selected_paths.push(current_path);
             } else {
-                // This is a simple browser alert. Gradio's gr.Warning is better for the final check.
                 alert("You can select a maximum of 3 images.");
             }
         }
         
-        // Return the updated list of paths to the hidden textbox
+        // The return value of a gr.js function is passed to the next .then()
         return selected_paths.join(',');
     }
     """
     
-    # We need to add a little CSS for the selection border
+    # Add the CSS for the selection border
     demo.css += "#sample_gallery .gallery-item.selected { border: 4px solid var(--primary-500) !important; }"
-    
-    # Hidden textbox to store the paths
-    selected_samples_textbox = gr.Textbox(value="", visible=False, elem_id="selected_samples_textbox")
 
-    sample_gallery.select(fn=None, _js=select_js, outputs=[selected_samples_textbox])
+    # The modern way to link JS to an event:
+    sample_gallery.select(
+        fn=None, # No Python function runs on click
+        js=select_js, # The JS function to run
+        outputs=[selected_samples_textbox] # The JS function's return value updates this component
+    )
+
+    # ... (the rest of the event handlers are correct)
+    def show_patient_info(files): return gr.update(visible=True) if files else gr.update(visible=False)
+    image_input.upload(fn=show_patient_info, inputs=image_input, outputs=patient_info_modal)
+    async def submit_and_hide_modal(name, age, files):
+        analysis_results = await process_analysis(name, age, files); return [*analysis_results, gr.update(visible=False)]
+    submit_analysis_btn.click(fn=submit_and_hide_modal, inputs=[patient_name_modal, patient_age_modal, image_input], outputs=[uploader_column, results_column, result_images, result_label, patient_info_modal])
+    cancel_btn.click(lambda: (gr.update(visible=False), None), None, [patient_info_modal, image_input])
+    start_over_btn.click(fn=None, js="() => { window.location.reload(); }")
 
     async def handle_sample_analysis(selected_paths_str: str):
-        # The input is now a comma-separated string of paths from our hidden textbox
-        selected_images = selected_paths_str.split(',') if selected_paths_str else []
-        
+        selected_images = selected_paths_str.split(',') if selected_paths_str.strip() else []
         if not selected_images: raise gr.Error("Please select at least one sample image.")
         if len(selected_images) > 3: raise gr.Error("Please select no more than 3 sample images.")
-        
         analysis_results = await process_analysis("Sample User", 0, selected_images, is_sample=True)
-        
-        return {
-            main_app: gr.update(visible=True), 
-            samples_page: gr.update(visible=False),
-            # Unpack dictionary updates for specific components
-            uploader_column: analysis_results[0],
-            results_column: analysis_results[1],
-            result_images: analysis_results[2],
-            result_label: analysis_results[3],
-        }
+        return [gr.update(visible=True), gr.update(visible=False), *analysis_results]
     analyze_samples_btn.click(fn=handle_sample_analysis, inputs=[selected_samples_textbox], outputs=[main_app, samples_page, uploader_column, results_column, result_images, result_label])
 
-    # ... (Page Navigation is correct)
     all_pages = [main_app, history_page, samples_page]
     async def show_history_page_and_refresh(): records_update = await refresh_history_table(); return [gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), records_update]
     def show_samples_page(): return [gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)]
@@ -192,6 +152,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue="blue", secondary_hue="blue")
     refresh_history_btn.click(fn=refresh_history_table, outputs=history_df)
     demo.load(fn=refresh_history_table, outputs=history_df)
 
+
 # --- Launch the App ---
 if __name__ == "__main__":
     demo.launch()