Update app.py

app.py

@@ -1,59 +1,2 @@
-import torch
-import soundfile as sf
-import numpy as np
-import gradio as gr
-from transformers import VitsModel, MBartForConditionalGeneration, AutoTokenizer, pipeline
 
-# Load the models and tokenizers
-transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base.en")
-translation_tokenizer = AutoTokenizer.from_pretrained("facebook/mbart-large-50-one-to-many-mmt", use_fast=False)
-translation_model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-one-to-many-mmt")
-tts_tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-hin")
-tts_model = VitsModel.from_pretrained("facebook/mms-tts-hin")
-
-def process_audio(audio):
-    if audio is None:
-        return "No audio provided.", None
-
-    sr, y = audio
-    y = y.astype(np.float32)
-    y /= np.max(np.abs(y))
-
-    # Transcribe the audio
-    transcription = transcriber({"sampling_rate": sr, "raw": y})["text"]
-
-    # Translate from English to Hindi
-    model_inputs = translation_tokenizer(transcription, return_tensors="pt", padding=True, truncation=True)
-    generated_tokens = translation_model.generate(
-        **model_inputs,
-        forced_bos_token_id=translation_tokenizer.lang_code_to_id["hi_IN"]
-    )
-    translated_text = translation_tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
-
-    # Generate Hindi speech from translated text
-    tts_inputs = tts_tokenizer(translated_text, return_tensors="pt")
-    try:
-        with torch.no_grad():
-            tts_output = tts_model(**tts_inputs)
-            waveform = tts_output.waveform.squeeze().cpu().numpy()
-    except RuntimeError as e:
-        return f"Runtime Error: {e}", None
-
-    # Save the waveform to an audio file
-    audio_path = 'output.wav'
-    sf.write(audio_path, waveform, 22050)
-
-    return audio_path
-
-# Create the Gradio interface
-demo = gr.Interface(
-    fn=process_audio,
-    inputs=gr.Audio(sources=["microphone"], type="numpy"),
-    outputs="audio",
-    title="Speech-to-Hindi",
-    description="Record your speech or upload an audio file to transcribe, translate to Hindi, and convert to speech."
-)
-
-# Launch the Gradio app
-demo.launch(debug=True)