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app.py

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+import gradio as gr
+from transformers import pipeline
+import numpy as np
+import moviepy.editor as mp
+
+transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base.en")
+translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-fr")  # Example for English to French
+
+def transcribe(video_file):
+    # Load video file and extract audio
+    audio_file = mp.AudioFileClip(video_file).write_audiofile("temp_audio.wav")
+    result = transcriber("temp_audio.wav")
+    return result['text']
+
+def translate(text):
+    return translator(text)[0]['translation_text']
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Curify Studio Demo")
+    
+    with gr.Tab("Transcription"):
+        video_input = gr.File(label="Upload Video File")
+        transcribe_output = gr.Textbox(label="Transcription Output", lines=10)
+        transcribe_button = gr.Button("Transcribe")
+        
+        transcribe_button.click(fn=transcribe, inputs=video_input, outputs=transcribe_output)
+        
+    with gr.Tab("Translation"):
+        text_input = gr.Textbox(label="Text to Translate")
+        translate_output = gr.Textbox(label="Translation Output", lines=10)
+        translate_button = gr.Button("Translate")
+        
+        translate_button.click(fn=translate, inputs=text_input, outputs=translate_output)
+
+demo.launch(debug=True)

requirements.txt

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+qrcode
+flask
+gradio
+newspaper3k
+transformers
+sentence-transformers
+openai
+todoist-api-python
+flask
+twilio
+fastapi
+uvicorn
+moviepy
+ffmpy
+google-cloud-storage
+fpdf
+markdown
+nest_asyncio
+reportlab