app.py

import gradio as gr
import torch
from transformers import AutoProcessor, AutoModel

model_name = "MERaLiON/MERaLiON-SpeechEncoder-v1"

processor = AutoProcessor.from_pretrained(model_name, trust_remote_code=True)
model = AutoModel.from_pretrained(model_name, trust_remote_code=True)

def encode_audio(audio):
    # audio = (sample_rate, numpy array)
    sr, data = audio

    inputs = processor(
        data,
        sampling_rate=sr,
        return_tensors="pt",
        padding=True
    )

    with torch.no_grad():
        embeddings = model(**inputs).last_hidden_state.mean(dim=1).squeeze().tolist()

    return {
        "embeddings": embeddings
    }

demo = gr.Interface(
    fn=encode_audio,
    inputs=gr.Audio(type="numpy", label="Upload audio"),
    outputs=gr.JSON(label="Embeddings")
)

demo.launch()