updated app.py

app.py

@@ -35,7 +35,7 @@ except Exception as e:
     print(f"❌ Error loading parquet file: {e}")
     db_features = None
 
-# --- 4. CORE SEARCH LOGIC (FIXED) ---
+# --- 4. CORE SEARCH LOGIC (SAFE MODE) ---
 def find_best_matches(query_features, top_k=3):
     if db_features is None:
         return []
@@ -51,17 +51,19 @@ def find_best_matches(query_features, top_k=3):
     for idx, score in zip(indices[0], scores[0]):
         idx = idx.item()
         
-        # CRITICAL FIX: Save image to disk instead of returning raw PIL object
-        # This prevents the "Too much data" error
+        # 1. Get the raw image
         img_data = dataset[idx]['image']
         
-        # Create a unique filename for the cache
-        save_path = f"temp_result_{idx}.jpg"
+        # 2. Resize it to be small & fast (300x300 max)
+        img_data.thumbnail((300, 300))
+        
+        # 3. Save to a temporary path (prevents the "Too much data" crash)
+        save_path = f"/tmp/temp_result_{idx}.jpg"
         img_data.save(save_path)
         
         label = df.iloc[idx]['label_name']
         
-        # Return the PATH (string) instead of the IMAGE (object)
+        # 4. Return the PATH (string), NOT the image object
         results.append((save_path, f"{label} ({score:.2f})"))
         
     return results
@@ -81,87 +83,46 @@ def search_by_text(input_text):
         features = model.get_text_features(**inputs)
     return find_best_matches(features)
 
-# --- 6. BUILD UI (Centered & Fixed) ---
-
-# CSS to center the app and limit width to 1000px
+# --- 6. BUILD UI (Clean & Centered) ---
 custom_css = """
-.gradio-container {
-    width: 100%;
-    max-width: 1000px;
-    margin: 0 auto !important; 
-}
-h1 {
-    text-align: center;
-    color: #E67E22;
-}
+.gradio-container { width: 100%; max-width: 1000px; margin: 0 auto !important; }
+h1 { text-align: center; color: #E67E22; }
 """
 
 with gr.Blocks(theme=gr.themes.Soft(), css=custom_css, title="Food Matcher AI") as demo:
     
-    # --- Header ---
     with gr.Row():
         gr.Markdown("# 🍔 Visual Dish Matcher (SigLIP)")
     
-    gr.Markdown(
-        "Upload a food photo or describe a craving. We'll find the closest matches from our database.",
-        elem_classes=["center-text"]
-    )
+    gr.Markdown("Upload a food photo or describe a craving. We'll find the closest matches.", elem_classes=["center-text"])
 
-    # --- Video Accordion ---
     with gr.Accordion("📺 Watch Demo Video", open=False):
         gr.HTML('<div style="display:flex; justify-content:center;"><iframe width="560" height="315" src="https://www.youtube.com/embed/IXeIxYHi0Es" frameborder="0" allowfullscreen></iframe></div>')
 
-    # --- Main Interface ---
     with gr.Tab("🖼️ Search by Image"):
-        # Split layout: 1/3 Left (Input), 2/3 Right (Results)
         with gr.Row():
-            
-            # --- Left Column: Input ---
             with gr.Column(scale=1): 
-                img_input = gr.Image(
-                    type="pil", 
-                    label="Your Photo", 
-                    height=300  # Fixed height
-                )
+                img_input = gr.Image(type="pil", label="Your Photo", height=300)
                 btn_img = gr.Button("🔍 Find Matches", variant="primary", size="lg")
             
-            # --- Right Column: Output ---
             with gr.Column(scale=2):
-                img_gallery = gr.Gallery(
-                    label="Similar Dishes", 
-                    columns=3,           
-                    height=350,          
-                    object_fit="contain" 
-                )
+                img_gallery = gr.Gallery(label="Similar Dishes", columns=3, height=350, object_fit="contain")
         
         btn_img.click(search_by_image, inputs=img_input, outputs=img_gallery)
 
     with gr.Tab("📝 Search by Text"):
         with gr.Row():
-            
-            # --- Left Column: Input ---
             with gr.Column(scale=1):
-                txt_input = gr.Textbox(
-                    label="Describe it", 
-                    placeholder="e.g. 'Spicy Tacos' or 'Chocolate Cake'",
-                    lines=4
-                )
+                txt_input = gr.Textbox(label="Describe it", placeholder="e.g. 'Spicy Tacos'", lines=4)
                 btn_txt = gr.Button("🔍 Search", variant="primary", size="lg")
             
-            # --- Right Column: Output ---
             with gr.Column(scale=2):
-                txt_gallery = gr.Gallery(
-                    label="Similar Dishes", 
-                    columns=3, 
-                    height=350, 
-                    object_fit="contain"
-                )
+                txt_gallery = gr.Gallery(label="Similar Dishes", columns=3, height=350, object_fit="contain")
 
         btn_txt.click(search_by_text, inputs=txt_input, outputs=txt_gallery)
 
-    # --- Footer ---
     gr.Markdown("---")
-    gr.Markdown("By Matan Kriel & Odeya Shmuel | Powered by Google SigLIP", elem_id="footer")
+    gr.Markdown("By Matan Kriel & Odeya Shmuel | Powered by Google SigLIP")
 
 # Launch
 demo.launch()