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Streamlit app to chat with Nairobi Stock Exchange annual report PDF using Retrieval Augmented Generation (RAG) and LLM

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Leveraging Nairobi Stock Exchange (NSE) and OpenAI or any Large Language Model (LLM).

Demo

Video: https://www.linkedin.com/feed/update/urn:li:activity:7104426282465005569/ test This project is an NSE project where you can interact with the NSE 2017 annual report. You can ask any kind of question to the PDF using Retrieval Augmented Generation (RAG).

Technologies used

How to run the project

    1. Install the required dependencies: pip install -r requirements.txt
    1. Add your: OpenAI APIKey to line 22 of app.py
    1. Start the app: streamlit run app.py

Reference:

https://github.com/nicknochnack

License

The MIT License is a permissive software license that originated at the Massachusetts Institute of Technology (MIT). It allows users to reuse the code for any purpose, including in proprietary software, as long as they include the original copyright and license notice in any copy of the software/source123. It puts very few restrictions on reuse and has high license compatibility2.

For the current version of the MIT License, you can refer to the official MIT License website.

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Streamlit app to chat with Nairobi Stock Exchange annual report PDF using Retrieval Augmented Generation (RAG) and LLM

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