Create app.py

app.py

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+import torch
+import gradio as gr
+from youtube_transcript_api import YouTubeTranscriptApi
+from youtube_transcript_api._errors import TranscriptsDisabled, VideoUnavailable, NoTranscriptFound
+from transformers import pipeline
+
+# model_path = "../models/models--sshleifer--distilbart-cnn-12-6/snapshots/a4f8f3ea906ed274767e9906dbaede7531d660ff"
+
+# Load the summarization model
+# text_summary = pipeline("summarization", model=model_path, torch_dtype=torch.float32)
+text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16)
+
+def split_text(text, max_tokens=1024):
+    words = text.split()
+    for i in range(0, len(words), max_tokens):
+        yield " ".join(words[i:i + max_tokens])
+
+def summary(input_text):
+    summarized_chunks = []
+    for chunk in split_text(input_text):
+        output = text_summary(chunk)
+        summarized_chunks.append(output[0]['summary_text'])
+    return " ".join(summarized_chunks)
+
+def extract_video_id(url):
+    if "youtu.be" in url:
+        return url.split("/")[-1]
+    elif "youtube.com/watch?v=" in url:
+        return url.split("v=")[-1].split("&")[0]
+    elif "youtube.com/shorts/" in url:
+        return url.split("/shorts/")[-1].split("?")[0]
+    else:
+        raise ValueError("Invalid YouTube URL format")
+
+def get_youtube_transcript(video_url):
+    try:
+        video_id = extract_video_id(video_url)
+        transcript = YouTubeTranscriptApi.get_transcript(video_id)
+        text_transcript = "\n".join([entry['text'] for entry in transcript])
+        
+        if not text_transcript.strip():
+            return "The transcript is empty or unavailable."
+        
+        return summary(text_transcript)
+
+    except ValueError as e:
+        return f"Error: {e}"
+    except TranscriptsDisabled:
+        return "Transcript is disabled for this video."
+    except VideoUnavailable:
+        return "Video is unavailable."
+    except NoTranscriptFound:
+        return "No transcript found for this video."
+
+# if __name__ == "__main__":
+#     youtube_url = input("Enter YouTube URL: ").strip()
+#     transcript_summary = get_youtube_transcript(youtube_url)
+#     print("\n=== Summary ===\n")
+#     print(transcript_summary)
+
+gr.close_all()
+
+demo = gr.Interface(fn=get_youtube_transcript, inputs=[gr.Textbox(label="Input Youtube video url to summarize", lines=2)],
+                    outputs=[gr.Textbox(label="Summarized text",lines=6)],
+                    title="GenAI Project 2: Video to Text Summarizer",
+                    description="This application is use to summarized the text from youtube video")
+
+demo.launch()