Create app.py

app.py

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+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()