Update app.py

app.py

@@ -1,7 +1,66 @@
+import os
+import tempfile
 import gradio as gr
+from pytube import YouTube
+from moviepy.editor import VideoFileClip
+import whisper
+from textblob import TextBlob
 
-def greet(name):
-    return "Hello " + name + "!!"
+# 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")
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+        # 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)