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import gradio as gr
from faster_whisper import WhisperModel

# Load the Faster Whisper model
model_name = "Systran/faster-whisper-large-v3"
model = WhisperModel(model_name, device="cpu")  # Use "cuda" if you have a GPU

# Define a transcription function
def transcribe_audio(audio_file):
    try:
        segments, info = model.transcribe(audio_file, beam_size=5)  # Customize parameters as needed
        transcription = " ".join([segment.text for segment in segments])
        return transcription
    except Exception as e:
        return f"Error: {str(e)}"

# Create Gradio interface
interface = gr.Interface(
    fn=transcribe_audio,
    inputs=gr.Audio(source="upload", type="filepath", label="Upload Audio"),
    outputs=gr.Textbox(label="Transcription"),
    title="Sinhala Audio-to-Text Transcription",
    description="Upload an audio file and get the transcription in Sinhala using the Faster Whisper model.",
    allow_flagging="never"
)

# Launch the Gradio app
if __name__ == "__main__":
    interface.launch(server_name="0.0.0.0", server_port=7860, share=True)