app.py

import os
import gradio as gr
from qdrant_client import QdrantClient
from transformers import ClapModel, ClapProcessor
from dotenv import load_dotenv
import requests

# Charger les variables d'environnement à partir du fichier .env
load_dotenv()

# Récupérer les variables d'environnement
QDRANT_URL = os.getenv('QDRANT_URL')
QDRANT_KEY = os.getenv('QDRANT_KEY')

# Vérifier les valeurs récupérées
print(f"QDRANT_URL: {QDRANT_URL}")
print(f"QDRANT_KEY: {QDRANT_KEY}")

try:
    # 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(QDRANT_URL, api_key=QDRANT_KEY)
    print("[INFO] Client created...")

    # Chargement du modèle
    print("[INFO] Loading the model...")
    model_name = "laion/larger_clap_general"
    model = ClapModel.from_pretrained(model_name)
    processor = ClapProcessor.from_pretrained(model_name)

    # Interface Gradio
    max_results = 10

    def sound_search(query):
        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']

            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?")
        out = [gr.Audio(label=f"{x}") for x in range(max_results)]
        print(sound_search("fun"))
        inp.submit(sound_search, inputs=inp, outputs=out)

    demo.launch()

except Exception as e:
    print(f"[ERROR] Failed to create Qdrant client: {e}")