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| from transformers import pipeline | |
| from youtube_transcript_api import YouTubeTranscriptApi | |
| def summarize(youtube_video): | |
| video_id = youtube_video.split("=")[1] | |
| transcript = YouTubeTranscriptApi.get_transcript(video_id) | |
| summarizer = pipeline('summarization') | |
| result = "" | |
| for i in transcript: | |
| result += ' ' + i['text'] | |
| num_iters = int(len(result)/1000) | |
| summarized_text = [] | |
| for i in range(0, num_iters + 1): | |
| start = 0 | |
| start = i * 1000 | |
| end = (i + 1) * 1000 | |
| print("input text \n" + result[start:end]) | |
| out = summarizer(result[start:end]) | |
| out = out[0] | |
| out = out['summary_text'] | |
| print("Summarized text\n"+out) | |
| summarized_text.append(out) | |
| inp = result.replace('\n','') | |
| summary = summarizer(inp) | |
| return summary | |
| import gradio as gr | |
| grad= gr.Interface(fn=summarize, inputs="text", outputs="text") | |
| grad.launch() |