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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()
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