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langchaindocuments's Introduction

Leveraging Your Own Documents in a Langchain Pipeline

This project highlights how to leverage a ChromaDB vectorstore in a Langchain pipeline to create drumroll please a GPT Investment Banker (ergh, I cringed as I wrote that, but alas it's actually pretty practical). You can load in a pdf based document and use it alongside an LLM without the need for fine tuning.

See it live and in action ๐Ÿ“บ

Tutorial

Startup ๐Ÿš€

  1. Create a virtual environment python -m venv langchainenv
  2. Activate it:
    • Windows:.\langchainenv\Scripts\activate
    • Mac: source langchain/bin/activate
  3. Clone this repo git clone https://github.com/nicknochnack/LangchainDocuments
  4. Go into the directory cd LangchainDocuments
  5. Install the required dependencies pip install -r requirements.txt
  6. Add your OpenAI APIKey to line 22 of app.py
  7. Start the app streamlit run app.py
  8. Go back to my YouTube channel and like and subscribe ๐Ÿ˜‰...no seriously...please! lol

Other References ๐Ÿ”—

The main LG Agent used:Langchain VectorStore Agents

Who, When, Why?

๐Ÿ‘จ๐Ÿพโ€๐Ÿ’ป Author: Nick Renotte
๐Ÿ“… Version: 1.?
๐Ÿ“œ License: This project is licensed under the MIT License

langchaindocuments's People

Contributors

nicknochnack avatar vampirelordseth avatar

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