uploading the file

app.py

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+import re
+from youtube_transcript_api import YouTubeTranscriptApi
+from youtube_transcript_api.formatters import TextFormatter
+import torch
+import gradio as gr
+from transformers import pipeline
+
+# text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16)
+
+text_summary = pipeline("summarization", model="Falconsai/text_summarization")
+
+def summary(input):
+    output = text_summary(input)
+    return output[0]['summary_text']
+
+
+def extract_video_id(url):
+    # Regex to extract the video ID from various YouTube URL formats
+    regex = r"(?:youtube\.com\/(?:[^\/\n\s]+\/\S+\/|(?:v|e(?:mbed)?)\/|\S*?[?&]v=)|youtu\.be\/)([a-zA-Z0-9_-]{11})"
+    match = re.search(regex, url)
+    if match:
+        return match.group(1)
+    return None
+
+
+def get_youtube_transcript(video_url):
+    video_id = extract_video_id(video_url)
+    if not video_id:
+        return "Video ID could not be extracted."
+
+    try:
+        # Fetch the transcript
+        transcript = YouTubeTranscriptApi.get_transcript(video_id)
+
+        # Format the transcript into plain text
+        formatter = TextFormatter()
+        text_transcript = formatter.format_transcript(transcript)
+        summary_text = summary(text_transcript)
+
+        return summary_text
+    except Exception as e:
+        return f"An error occurred: {e}"
+
+
+gr.close_all()
+
+# demo = gr.Interface(fn=summary, inputs="text",outputs="text")
+demo = gr.Interface(fn=get_youtube_transcript,
+                    inputs=[gr.Textbox(label="Input YouTube Url to summarize", lines=1)],
+                    outputs=[gr.Textbox(label="Summarized text", lines=4)],
+                    title="@GenAILearniverse Project 2: YouTube Script Summarizer",
+                    description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE YOUTUBE VIDEO SCRIPT.")
+demo.launch()