https://github.com/amirhosseinazami1373/scinetific-text-summarizer
This summarizer generates short summaries of scientific articles from Google Scholar using the power of the affordable GPT-3.5-turbo.
https://github.com/amirhosseinazami1373/scinetific-text-summarizer
gpt-35-turbo langchain llms nlp-machine-learning prompt-engineering textsummarization
Last synced: 8 months ago
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This summarizer generates short summaries of scientific articles from Google Scholar using the power of the affordable GPT-3.5-turbo.
- Host: GitHub
- URL: https://github.com/amirhosseinazami1373/scinetific-text-summarizer
- Owner: amirhosseinazami1373
- Created: 2024-08-08T04:29:47.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-08T05:20:36.000Z (almost 2 years ago)
- Last Synced: 2025-01-14T03:28:48.951Z (over 1 year ago)
- Topics: gpt-35-turbo, langchain, llms, nlp-machine-learning, prompt-engineering, textsummarization
- Homepage:
- Size: 14.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
Scientific Text Summarizer
This summarizer generates short summaries of scientific articles from Google Scholar using the power of the affordable GPT-3.5-turbo.
# Requirements:
1- You will need an OpenAi API key to access the LLM model.
2- Install openai, LangChain and scholarly packages using
pip install openai scholarly langchain
3- To generate the summaries, run the code and enter your desired keywords (use ',' to separate the keywords).
4- You can further increase the randomness in the summaries using the 'temperature' parameter.
5- The number of summaries for a set of keywords has been limited to 10; you can easily increase the number by changing the code.