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https://github.com/tcsenpai/easy-web-summarizer.git
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41 lines
1.4 KiB
Python
41 lines
1.4 KiB
Python
from langchain_community.document_loaders import YoutubeLoader
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from langchain.text_splitter import TokenTextSplitter
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from langchain_community.chat_models import ChatOllama
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from langchain.chains.summarize import load_summarize_chain
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import re
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def check_link(link):
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yt_regex = r"(https?://)?(www\.)?(youtube\.com/watch\?v=|youtu\.be/)[\w-]+"
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return re.match(yt_regex, link) is not None
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def get_transcript(video_link):
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# Get video transcript
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if check_link(video_link):
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loader = YoutubeLoader.from_youtube_url(video_link, language=["en", "en-US"])
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transcript = loader.load()
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return transcript
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return "Invalid YouTube URL."
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def split_chunks(transcript):
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# Split the transcript into chunks
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# Llama 3 model takes up to 8192 input tokens, so I set chunk size to 7500 for leaving some space to model.
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splitter = TokenTextSplitter(chunk_size = 7500, chunk_overlap = 100)
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chunks = splitter.split_documents(transcript)
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return chunks
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def yt_summarization_chain():
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llm = ChatOllama(model="llama3")
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summarize_chain = load_summarize_chain(llm=llm, chain_type="refine", verbose=True)
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return summarize_chain
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def summarize_video(video_link):
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transcript = get_transcript(video_link)
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chunks = split_chunks(transcript)
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sum_chain = yt_summarization_chain()
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result = sum_chain.run(chunks)
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return result
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if __name__ == "__main__":
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#summarize_video() |