Create app.py

app.py

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+from youtube_transcript_api import YouTubeTranscriptApi
+from youtube_transcript_api.formatters import TextFormatter
+import re
+import torch
+import gradio as gr
+from transformers import pipeline
+
+# model_path = ("../Model/models--sshleifer--distilbart-cnn-12-6/snapshots"
+#               "/a4f8f3ea906ed274767e9906dbaede7531d660ff")
+# text_summary = pipeline("summarization", model=model_path
+#                 ,torch_dtype=torch.bfloat16)
+
+text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16)
+
+def summary(input):
+    output = text_summary(input)
+    return output[0]['summary_text']
+
+# Function to extract video ID from the YouTube URL
+def extract_video_id(url):
+    video_id = None
+    # Updated regex to handle extra parameters in the YouTube URL
+    regex = r"(?:https?:\/\/)?(?:www\.)?(?:youtube\.com\/(?:[^\/\n\s]+\/\S+\/|\S*[\?&]v=|\S*[\?&]v%2F)?([\w-]+))|(?:youtu\.be\/([\w-]+))"
+    match = re.search(regex, url)
+    if match:
+        video_id = match.group(1) if match.group(1) else match.group(2)
+    return video_id
+
+# Function to get transcript for a YouTube video
+def get_transcript(video_url):
+    video_id = extract_video_id(video_url)
+    if video_id:
+        try:
+            transcript = YouTubeTranscriptApi.get_transcript(video_id)
+
+            # Formatting transcript into plain text
+            formatter = TextFormatter()
+            formatted_transcript = formatter.format_transcript(transcript)
+            summary_text = summary(formatted_transcript)
+            return summary_text
+
+        except Exception as e:
+            return f"Error retrieving transcript: {e}"
+    else:
+        return "Invalid YouTube URL."
+
+# Main function to take URL input and fetch the transcript
+# if __name__ == "__main__":
+#     youtube_url = input("Enter the YouTube video URL: ")
+#     transcript = get_transcript(youtube_url)
+#     print("\nTranscript:\n")
+#     print(transcript)
+
+
+gr.close_all()
+
+# demo = gr.Interface(fn=summary,inputs=["text"],outputs=["text"])
+
+demo = gr.Interface(fn = get_transcript,
+                    inputs=[gr.Textbox(label="Input youtube url to summarize",lines=1)],
+                    outputs=[gr.Textbox(label="Summarized Text ",lines=4)],
+                    title="@SherryAhuja Project : Youtube Video Summarizer",
+                    description="This AI application will be used to summarize the Youtube Video Script")
+demo.launch()