Fix: Update Gradio 6.x API endpoint configuration

app.py

@@ -1,6 +1,7 @@
 """
 Labasni Recommender Service - Hugging Face Space
 Interface Gradio pour les recommandations d'outfits
+Compatible avec Gradio 6.x
 """
 
 import gradio as gr
@@ -26,29 +27,64 @@ def recommend_outfit_api(clothes_json: str, preference: str, city: str = "Tunis"
     except Exception as e:
         return json.dumps({"success": False, "error": str(e)})
 
-# Interface Gradio
-iface = gr.Interface(
-    fn=recommend_outfit_api,
-    inputs=[
-        gr.Textbox(
-            label="Clothes Data (JSON)",
-            placeholder='[{"id":"top1","category":"top","style":"casual",...}]',
-            lines=10
-        ),
-        gr.Dropdown(
-            choices=["casual", "formal", "sport", "chic"],
-            label="Preference",
-            value="casual"
-        ),
-        gr.Textbox(label="City", value="Tunis")
-    ],
-    outputs=gr.Textbox(label="Recommended Outfit (JSON)", lines=15),
-    title="🎽 Labasni Outfit Recommender",
-    description="Recommandations d'outfits basées sur ML (TensorFlow + PyTorch)",
-    examples=[
-        ['[{"id":"top1","category":"top","style":"casual","color":"white","season":"summer"}]', "casual", "Tunis"]
-    ]
-)
+# ✅ CORRECTION : Configuration pour Gradio 6.x
+# Utiliser gr.Blocks au lieu de gr.Interface pour plus de contrôle
+with gr.Blocks(title="🎽 Labasni Outfit Recommender") as demo:
+    gr.Markdown("# 🎽 Labasni Outfit Recommender")
+    gr.Markdown("Recommandations d'outfits basées sur ML (TensorFlow + PyTorch)")
+    
+    with gr.Row():
+        with gr.Column():
+            clothes_input = gr.Textbox(
+                label="Clothes Data (JSON)",
+                placeholder='[{"id":"top1","category":"top","style":"casual",...}]',
+                lines=10,
+                value='[{"id":"top1","category":"top","style":"casual","color":"white","season":"summer","score":0.8,"imageURL":"https://example.com/top.jpg"}]'
+            )
+            
+            preference_input = gr.Dropdown(
+                choices=["casual", "formal", "sport", "chic"],
+                label="Preference",
+                value="casual"
+            )
+            
+            city_input = gr.Textbox(
+                label="City",
+                value="Tunis"
+            )
+            
+            submit_btn = gr.Button("🚀 Générer Recommandation", variant="primary")
+        
+        with gr.Column():
+            output = gr.Textbox(
+                label="Recommended Outfit (JSON)",
+                lines=15,
+                show_copy_button=True
+            )
+    
+    # Event handler
+    submit_btn.click(
+        fn=recommend_outfit_api,
+        inputs=[clothes_input, preference_input, city_input],
+        outputs=output
+    )
+    
+    # Exemples
+    gr.Examples(
+        examples=[
+            [
+                '[{"id":"top1","category":"top","style":"casual","color":"white","season":"summer","score":0.8,"imageURL":"https://example.com/top.jpg"},{"id":"bot1","category":"bottom","style":"casual","color":"blue","season":"summer","score":0.7,"imageURL":"https://example.com/bottom.jpg"},{"id":"shoe1","category":"footwear","style":"casual","color":"black","season":"summer","score":0.9,"imageURL":"https://example.com/shoes.jpg"}]',
+                "casual",
+                "Tunis"
+            ]
+        ],
+        inputs=[clothes_input, preference_input, city_input]
+    )
 
+# ✅ IMPORTANT : api_name="predict" expose l'endpoint pour l'API externe
 if __name__ == "__main__":
-    iface.launch()
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False
+    )