Ajouter le script Gradio et les dépendances*

app.py

@@ -2,22 +2,26 @@ import os
 import gradio as gr
 from qdrant_client import QdrantClient
 from transformers import ClapModel, ClapProcessor
-import huggingface_hub
 
-# Retrieve Qdrant URL and API key from environment variables
-secrets = huggingface_hub.get_secret()
-client = QdrantClient(secrets["QDRANT_URL"], secrets["QDRANT_KEY"])
+# Utiliser les secrets définis comme variables d'environnement
+qdrant_url = os.getenv("QDRANT_URL")
+qdrant_key = os.getenv("QDRANT_KEY")
 
-# Loading the Qdrant DB in local ###################################################################
-print("[INFO] Client created...")
+if not qdrant_url or not qdrant_key:
+    raise ValueError("QDRANT_URL and QDRANT_KEY must be set as environment variables.")
 
-# loading the model
-print("[INFO] Loading the model...")
+client = QdrantClient(qdrant_url, qdrant_key)
+
+# Chargement de la base de données Qdrant en local
+print("[INFO] Client créé...")
+
+# Chargement du modèle
+print("[INFO] Chargement du modèle...")
 model_name = "laion/clap-large-v2"
 model = ClapModel.from_pretrained(model_name)
 processor = ClapProcessor.from_pretrained(model_name)
 
-# Gradio Interface #################################################################################
+# Interface Gradio
 max_results = 10
 
 def sound_search(query):
@@ -26,7 +30,7 @@ def sound_search(query):
 
     hits = client.search(
         collection_name="demo_spaces_db",
-        query_vector=text_embed.tolist(),  # Convert tensor to list
+        query_vector=text_embed.tolist(),  # Convertir le tenseur en liste
         limit=max_results,
     )
     return [
@@ -38,10 +42,10 @@ def sound_search(query):
 
 with gr.Blocks() as demo:
     gr.Markdown(
-        """# Sound search database """
+        """# Base de données de recherche de sons """
     )
-    inp = gr.Textbox(placeholder="What sound are you looking for ?")
-    out = [gr.Audio(label=f"{x}") for x in range(max_results)]  # Necessary to have different objs
+    inp = gr.Textbox(placeholder="Quel son recherchez-vous ?")
+    out = [gr.Audio(label=f"{x}") for x in range(max_results)]  # Nécessaire d'avoir des objets différents
     inp.change(fn=sound_search, inputs=inp, outputs=out)
 
 demo.launch()