import gradio as gr
import nemo.collections.asr as nemo_asr
import numpy as np

# Load the pre-trained Kabyle ASR model
asr_model = nemo_asr.models.EncDecRNNTBPEModel.from_pretrained("nvidia/stt_kab_conformer_transducer_large")

# Function to transcribe the audio input
def transcribe(audio):
    # Extract audio data and sample rate
    audio_data, sample_rate = audio
    
    # Convert audio data to numpy array if it's not already
    if isinstance(audio_data, np.ndarray):
        audio_data = np.array(audio_data)
    
    # Transcribe the audio
    return asr_model.transcribe([audio_data])

# Create the Gradio interface with audio input and text output
iface = gr.Interface(fn=transcribe, inputs="audio", outputs="text")

# Launch the Gradio interface
iface.launch()