Update app.py

from transformers import pipeline

asr = pipeline("automatic-speech-recognition", model="ZeeshanGeoPk/haitian-speech-to-text")

def transcribe(audio):
return asr(audio)["text"]

import gradio as gr
gr.Interface(fn=transcribe, inputs=gr.Audio(type="filepath"), outputs="text").launch()

app.py

@@ -1,44 +0,0 @@
-import gradio as gr
-import yt_dlp
-from transformers import pipeline
-from gtts import gTTS
-
-# Load pipelines
-asr = pipeline("automatic-speech-recognition", model="openai/whisper-base", task="transcribe")
-translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-hi")
-
-def youtube_to_hindi_dub(url):
-    # Step 1: Download audio from YouTube
-    ydl_opts = {
-        'format': 'bestaudio/best',
-        'outtmpl': 'audio.%(ext)s',
-        'postprocessors': [{'key': 'FFmpegExtractAudio', 'preferredcodec': 'mp3'}],
-        'quiet': True
-    }
-    with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-        ydl.download([url])
-    audio_path = "audio.mp3"
-
-    # Step 2: Transcribe English
-    result = asr(audio_path)
-    english_text = result["text"]
-
-    # Step 3: Translate to Hindi
-    hindi_text = translator(english_text)[0]['translation_text']
-
-    # Step 4: Convert to Hindi Audio
-    tts = gTTS(hindi_text, lang="hi")
-    tts.save("dubbed.mp3")
-
-    return "dubbed.mp3"
-
-# Gradio UI
-iface = gr.Interface(
-    fn=youtube_to_hindi_dub,
-    inputs=gr.Textbox(label="YouTube Video Link"),
-    outputs=gr.Audio(label="Dubbed Hindi Audio", type="filepath"),
-    title="🎧 YouTube Video to Hindi Dubber",
-    description="Paste an English YouTube link, and get Hindi AI voice dubbing."
-)
-
-iface.launch()