title	emoji	colorFrom	colorTo	sdk	app_file	pinned	license
GnosisPages	📝	red	pink	streamlit	GnosisPages.py	false	mit

GnosisPages

GnosisPages is a tool that helps you to create your own knowledge base for retrieval information when interacting with a LLM. The app take advantage of the frameworks Streamlit and Langchain and uses a client-side ChromaDB.

Features

GnosisPages offers you the following key features:

• Upload PDF files: Upload PDF files until 200MB size. PDF files should be programmatically created or processed by an OCR tool.
• Extract and split text: Extract the content of your PDF files and split them for a better querying.
• Store in a client-side VectorDB: GnosisPages uses ChromaDB for storing the content of your pdf files on vectors (ChromaDB use by default "all-MiniLM-L6-v2" for embeddings)
• Consult the info of your knowledge base: Ask questions to the Intelligent Assitant about the content of your knowledge base. The Langchain Agent will use ChromaDB query functions as a tool.

Demo

Try the GnosisPages's demo!!!

Watch a demo here

Architecture

Prerrequisites

For using the demo, you only need an OpenAI API Key.

If you prefer to clone the project and run on local environment, you will require:

• Python ( developed with v3.11)
• OpenAI API Key
• Langchain
• ChromaDB
• Streamlit
• A code editor

Setup

Follow the next steps to set up GnosisPages in your local environment:

1. Clone this repository

    git clone https://github.com/maclenn77/pdf-explainer.git

3. Navigate to the project directory

   cd pdf-explainer

4. Create your .env file

   touch .env
   nano .env # or your prefered text editor

And add your OpenAI API Key.

   OPENAI_API_KEY=YOUR_OPENAI_API_KEY

5. Install dependencies.

   pip install -r requirements.txt

6. Run on your local environment

   streamlit run GnosisPages.py

Deployment

GnosisPages's repo includes workflows for deploying to HuggingFace.

1. Check file size: Prevents to merge and deploy files over the limit provided by HuggingFace 🤗.
2. Check lints: Analize the code with pylint.
3. Deploy to HuggingFace: Once a branch is merged into main, the last version is deployed on a HuggingFace Space.

For deploying, you need to add HF_TOKEN as secret in the settings of your fork and add a HuggingFace user with the variable name HF_USERNAME.

Feedback and Contributions

If you have any feedback or would like to contribute to GnosisPages's development, please feel free to open issues or submit pull requests in the GitHub repository.

License

This project is licensed under the MIT License. See the LICENSE file for details.

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Enjoy using GnosisPages to create and consult your knowled base! If you have any questions or encounter issues during the setup process, please don't hesitate to reach out for assistance.