Spaces:
Sleeping
Sleeping
Commit ·
09bad31
1
Parent(s): edaff03
Fix: Update Gradio 6.x API endpoint configuration
Browse files
app.py
CHANGED
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@@ -27,73 +27,7 @@ def recommend_outfit_api(clothes_json: str, preference: str, city: str = "Tunis"
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except Exception as e:
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return json.dumps({"success": False, "error": str(e)})
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# ✅
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iface = gr.Interface(
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fn=recommend_outfit_api,
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inputs=[
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gr.Textbox(
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label="Clothes Data (JSON)",
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placeholder='[{"id":"top1","category":"top","style":"casual",...}]',
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lines=10
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),
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gr.Dropdown(
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choices=["casual", "formal", "sport", "chic"],
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label="Preference",
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value="casual"
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),
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gr.Textbox(label="City", value="Tunis")
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],
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outputs=gr.Textbox(label="Recommended Outfit (JSON)", lines=15),
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title="🎽 Labasni Outfit Recommender",
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description="Recommandations d'outfits basées sur ML (TensorFlow + PyTorch)",
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examples=[
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[
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'[{"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"}]',
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"casual",
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"Tunis"
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]
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],
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# ✅ CRUCIAL : api_name est nécessaire pour Gradio 6.x
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# Cela expose l'endpoint /api/predict
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api_name="predict"
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)
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# ✅ Lancement de l'interface
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# Hugging Face Spaces détecte automatiquement l'interface Gradio
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iface.launch()
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example.com
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Amine
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"""
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Labasni Recommender Service - Hugging Face Space
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Interface Gradio pour les recommandations d'outfits
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Version simplifiée avec gr.Interface
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"""
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import gradio as gr
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import json
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from recommender_model import recommend_outfit_ml
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def recommend_outfit_api(clothes_json: str, preference: str, city: str = "Tunis"):
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"""
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API endpoint pour les recommandations d'outfit
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Args:
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clothes_json: JSON string contenant la liste des vêtements
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preference: Style préféré (casual, formal, sport)
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city: Ville pour la météo
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Returns:
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JSON avec l'outfit recommandé
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"""
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try:
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clothes_data = json.loads(clothes_json)
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result = recommend_outfit_ml(clothes_data, preference, city)
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return json.dumps(result, indent=2)
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except Exception as e:
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return json.dumps({"success": False, "error": str(e)})
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# ✅ Interface Gradio - gr.Interface avec api_name explicite pour Gradio 6.x
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# Hugging Face Spaces détecte automatiquement la variable 'demo'
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demo = gr.Interface(
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fn=recommend_outfit_api,
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inputs=[
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@@ -120,9 +54,9 @@ demo = gr.Interface(
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]
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],
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# ✅ CRUCIAL : api_name est nécessaire pour Gradio 6.x
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# Cela expose l'endpoint /api/predict
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api_name="predict"
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)
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# ✅
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#
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except Exception as e:
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return json.dumps({"success": False, "error": str(e)})
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# ✅ CORRIGEZ CE POINT : Utilisez UNE seule variable 'demo'
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demo = gr.Interface(
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fn=recommend_outfit_api,
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inputs=[
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]
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],
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# ✅ CRUCIAL : api_name est nécessaire pour Gradio 6.x
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# Cela expose l'endpoint /run/predict (NOT /api/predict)
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api_name="predict"
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)
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# ✅ NE PAS appeler demo.launch() sur Hugging Face Spaces
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# Hugging Face s'occupe du lancement automatiquement
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