Create app.py

app.py

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+import gradio as gr
+from pytube import YouTube
+import whisper
+from transformers import pipeline
+from bark import generate_audio, preload_models
+import os
+import moviepy.editor as mp
+
+# Load models
+asr_model = whisper.load_model("base")
+translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-hi")
+
+# Preload Bark models
+preload_models()
+
+def process_video(link):
+    try:
+        yt = YouTube(link)
+        stream = yt.streams.filter(only_audio=True).first()
+        file_path = stream.download(filename="audio.mp4")
+
+        # Step 2: Transcribe English
+        result = asr_model.transcribe(file_path)
+        english_text = result["text"]
+
+        # Step 3: Translate to Hindi
+        hindi_text = translator(english_text)[0]['translation_text']
+
+        # Step 4: Generate Hindi Audio using Bark
+        hindi_audio = generate_audio(hindi_text)
+        with open("hindi.wav", "wb") as f:
+            f.write(hindi_audio)
+
+        # Step 5: Merge audio with video (optional)
+        original = mp.AudioFileClip("hindi.wav")
+        video = mp.VideoFileClip(file_path.replace(".mp4", ".mp4")).set_audio(original)
+        output_path = "dubbed_video.mp4"
+        video.write_videofile(output_path)
+
+        return hindi_text, output_path
+    except Exception as e:
+        return str(e), None
+
+gr.Interface(
+    fn=process_video,
+    inputs=gr.Textbox(label="Enter YouTube Video URL"),
+    outputs=[
+        gr.Textbox(label="Hindi Translation"),
+        gr.Video(label="Dubbed Hindi Video")
+    ]
+).launch()