app.py

import gradio as gr
import laion_clap
from qdrant_client import QdrantClient
import os

# Utilisez les variables d'environnement pour la configuration
QDRANT_HOST = os.getenv('QDRANT_HOST', 'localhost')
QDRANT_PORT = int(os.getenv('QDRANT_PORT', 6333))

# Connexion à Qdrant
client = QdrantClient(QDRANT_HOST, port=QDRANT_PORT)
print("[INFO] Client created...")

# Charger le modèle
print("[INFO] Loading the model...")
model_name = "laion/larger_clap_music"
model = laion_clap.CLAP_Module(enable_fusion=False)
model.load_ckpt()  # télécharger le checkpoint préentraîné par défaut

# Interface Gradio
max_results = 10

def sound_search(query):
    text_embed = model.get_text_embedding([query, ''])[0]  # trick because can't accept singleton
    hits = client.search(
        collection_name="demo_db7",
        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
    ]

with gr.Blocks() as demo:
    gr.Markdown(
        """# Sound search database """
    )
    inp = gr.Textbox(placeholder="What sound are you looking for ?")
    out = [gr.Audio(label=f"{x}") for x in range(max_results)]  # Nécessaire pour avoir différents objets
    inp.change(sound_search, inp, out)

demo.launch()