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import gradio as gr
import laion_clap
from qdrant_client import QdrantClient
from settings import QDRANT_KEY, QDRANT_URL, ENVIRONMENT
# Loading the Qdrant DB in local ###################################################################
if ENVIRONMENT == "PROD":
qdrant_client = QdrantClient(url=QDRANT_URL, api_key=QDRANT_KEY)
else:
qdrant_client = QdrantClient("localhost", port=6333)
print("[INFO] Client created...")
# loading the model
print("[INFO] Loading the model...")
model_name = "laion/larger_clap_music"
model = laion_clap.CLAP_Module(enable_fusion=False)
model.load_ckpt() # download the default pretrained checkpoint.
# Gradio Interface #################################################################################
max_results = 10
def sound_search(query):
text_embed = model.get_text_embedding([query, ''])[0] # trick because can't accept singleton
hits = qdrant_client.search(
collection_name="music_db",
query_vector=text_embed,
limit=max_results,
)
return [
gr.Audio(
hit.payload['s3_url'],
label=f"score: {hit.score}")
for hit in hits
] * 3
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(3)] # Necessary to have different objs
inp.change(sound_search, inp, out)
demo.launch()
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