Update app.py

app.py

@@ -5,29 +5,19 @@ from pytubefix import YouTube
 from moviepy.editor import VideoFileClip
 from transformers import pipeline
 
-# Ensure no unexpected input prompts
-os.environ["PYTHONUNBUFFERED"] = "1"
-os.environ["PYTHONIOENCODING"] = "utf-8"
-
-# Load Whisper model for transcription
+# Whisper model
 asr = pipeline("automatic-speech-recognition", model="distil-whisper/distil-small.en")
 
-# Load Summarization model
+# Summarization model
 summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 
 def process_youtube_link(youtube_url):
     try:
-        time.sleep(3)  # Prevents rate limiting
-        
-        # Use OAuth for restricted videos
         yt = YouTube(youtube_url, use_oauth=True, allow_oauth_cache=True)
         title = yt.title
         print(f"Downloading: {title}")
 
         video_stream = yt.streams.get_highest_resolution()
-        if not video_stream:
-            return "Error: No available video stream", ""
-
         video_path = f"{title}.mp4"
         video_stream.download(filename=video_path)
 
@@ -43,22 +33,18 @@ def process_youtube_link(youtube_url):
         # Summarize Transcription
         summary = summarizer(transcribed_text, max_length=150, min_length=50, do_sample=False)[0]["summary_text"]
 
-        # Clean up files after processing
-        os.remove(video_path)
-        os.remove(audio_path)
-
         return transcribed_text, summary
 
     except Exception as e:
         return f"Error: {str(e)}", ""
 
-# Create Gradio Interface
+# Gradio Interface
 iface = gr.Interface(
     fn=process_youtube_link,
     inputs=gr.Textbox(label="Enter YouTube URL"),
     outputs=[gr.Textbox(label="Transcription"), gr.Textbox(label="Summary")],
-    title="YouTube Video Transcriber & Summarizer",
-    description="Enter a YouTube link, and this app will transcribe and summarize the audio.",
+    title="YouTube Video Summarizer",
+    description="Enter a YouTube link, and this app will summarize the content of the video.",
 )
 
 iface.launch()