Ajout

.env

@@ -1,4 +1,4 @@
-QDRANT_URL=https://ebe79742-e3ac-4d09-a2c6-63946024cc7a.us-east4-0.gcp.cloud.qdrant.io
-QDRANT_KEY=_NnGLuSMH4Qwv-ancoFh88YvzuR7WbyidAorVOVQ_eMCbPhxTb2TSw
+QDRANT_URL=https://006817a4-0b45-4db8-a4e5-1f916808e19b.us-east4-0.gcp.cloud.qdrant.io:6333
+QDRANT_KEY=d9MUWQOMUA7JGBdpoFRtmou-h4Pf-e9uCrr0jMtUfAvvk4osqL_JtA
 AWS_ACCESS_KEY_ID=AKIAWOUASMWP5DM6RZG2
 AWS_SECRET_ACCESS_KEY=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

app.py

@@ -17,16 +17,12 @@ print(f"QDRANT_URL: {QDRANT_URL}")
 print(f"QDRANT_KEY: {QDRANT_KEY}")
 
 try:
-    # Tester la connexion à l'URL de Qdrant
-    response = requests.get(QDRANT_URL)
-    print(f"Test de la connexion à Qdrant: {response.status_code}")
-
     # Vérifier que les variables sont correctement récupérées
     if not QDRANT_URL or not QDRANT_KEY:
         raise ValueError("Les variables d'environnement QDRANT_URL ou QDRANT_KEY ne sont pas définies")
 
     # Connexion au client Qdrant
-    client = QdrantClient("https://006817a4-0b45-4db8-a4e5-1f916808e19b.us-east4-0.gcp.cloud.qdrant.io:6333", api_key="d9MUWQOMUA7JGBdpoFRtmou-h4Pf-e9uCrr0jMtUfAvvk4osqL_JtA")
+    client = QdrantClient(QDRANT_URL, api_key=QDRANT_KEY)
     print("[INFO] Client created...")
 
     # Chargement du modèle
@@ -39,26 +35,39 @@ try:
     max_results = 10
 
     def sound_search(query):
-        text_inputs = processor(text=query, return_tensors="pt")
-        text_embed = model.get_text_features(**text_inputs)[0]
+        try:
+            print(f"[DEBUG] Received query: {query}")
+            text_inputs = processor(text=query, return_tensors="pt")
+            print(f"[DEBUG] Text inputs: {text_inputs}")
+            text_embed = model.get_text_features(**text_inputs)[0]
+            print(f"Text embed: {text_embed}")
+
+            hits = client.search(
+                collection_name="demo_spaces_db",
+                query_vector=text_embed.tolist(),
+                limit=max_results,
+            )
+            print(f"Search results: {hits}")
+            print([
+                hit.payload['audio_s3url']
 
-        hits = client.search(
-            collection_name="demo_spaces_db",
-            query_vector=text_embed,
-            limit=max_results,
-        )
-        return [
-            gr.Audio(
-                hit.payload['audio_path'],
-                label=f"style: {hit.payload['style']} -- score: {hit.score}")
-            for hit in hits
-        ]
+            for hit in hits])
+            return [
+                gr.Audio(
+                    hit.payload['audio_s3url'],
+                    label=f"style: {hit.payload['style']} -- score: {hit.score}")
+                for hit in hits
+            ]
+        except Exception as e:
+            print(f"[ERROR] Exception in sound_search: {e}")
+            return []
 
     with gr.Blocks() as demo:
         gr.Markdown("# Sound search database")
-        inp = gr.Textbox(placeholder="What sound are you looking for ?")
+        inp = gr.Textbox(placeholder="What sound are you looking for?")
         out = [gr.Audio(label=f"{x}") for x in range(max_results)]
-        inp.change(sound_search, inp, out)
+        print(sound_search("fun"))
+        inp.submit(sound_search, inputs=inp, outputs=out)
 
     demo.launch()