app.py

import os
import tempfile
import gradio as gr
from pytube import YouTube
from moviepy.editor import VideoFileClip
import whisper
from textblob import TextBlob

# Step 1: Transcribe video
def transcribe_video_from_url(url: str) -> str:
    with tempfile.TemporaryDirectory() as tmpdir:
        video_path = os.path.join(tmpdir, "video.mp4")
        audio_path = os.path.join(tmpdir, "audio.wav")

        # Download the video
        yt = YouTube(url)
        stream = yt.streams.filter(file_extension='mp4', only_video=False).first()
        stream.download(output_path=tmpdir, filename="video.mp4")

        # Extract audio
        video_clip = VideoFileClip(video_path)
        video_clip.audio.write_audiofile(audio_path, logger=None)
        video_clip.close()

        # Transcribe with Whisper
        model = whisper.load_model("base")
        result = model.transcribe(audio_path)
        return result["text"]

# Step 2: Analyze sentiment
def sentiment_analysis(text: str) -> dict:
    blob = TextBlob(text)
    sentiment = blob.sentiment
    return {
        "polarity": round(sentiment.polarity, 2),
        "subjectivity": round(sentiment.subjectivity, 2),
        "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
    }

# Step 3: Main function for Gradio
def analyze_sentiment_from_video(url: str) -> dict:
    """
    Transcribe audio from a video URL and analyze sentiment.
    """
    transcription = transcribe_video_from_url(url)
    sentiment = sentiment_analysis(transcription)
    sentiment["transcription"] = transcription
    return sentiment

# Gradio interface
demo = gr.Interface(
    fn=analyze_sentiment_from_video,
    inputs=gr.Textbox(label="YouTube Video URL"),
    outputs={
        "assessment": gr.Textbox(label="Sentiment"),
        "polarity": gr.Number(label="Polarity"),
        "subjectivity": gr.Number(label="Subjectivity"),
        "transcription": gr.Textbox(label="Transcribed Text", lines=10),
    },
    title="🎥 Sentiment Analysis from YouTube Video",
    description="Enter a YouTube video URL. The app will transcribe its audio and analyze the sentiment of the spoken content."
)

# Launch for Hugging Face Space
if __name__ == "__main__":
    demo.launch(mcp_server=True)