SOLUS

ABOUT

SOLUS is a PDF query project built on top of F.R.I.D.A.Y-v1, using Langchain to create the pipeline for the Retrieval Augmented Generation (RAG)

HOW TO USE

Warning: If langchain still has support only for pydantic v1, skip to the next session

To create and activate the Python virtual environment, use:

• On Linux:

    python -m venv env
    source env/bin/activate
    pip install -r requirements.txt

• On Windows:

    python -m venv env
    .\env\Scripts\activate
    pip install -r requirements.txt

Once the installation is complete, run:

python main.py

Alternatively, for Linux users, you can do:

python setup.py

and the "solus" alias will automatically run main.py from anywhere (as long as the dependencies are installed globally)

ISSUE

Currently, langchain only supports pydantic v1. But gradio (one of the dependencies for training the model) requires pydantic v2. For as long as langchain don't fix their issues, the setting should go as follows:

• On Linux:

    python -m venv env
    source env/bin/activate
    pip install -r requirements.txt
    pip install -U pydantic
    python model_gen.py
    pip install pydantic==1.10.9
    python main.py

• On Windows:

    python -m venv env
    .\env\Scripts\activate
    pip install -r requirements.txt
    pip install -U pydantic
    python model_gen.py
    pip install pydantic==1.10.9
    python main.py

About RAG

Large Language Models nowadays are trained with a large corpus of text, providing them a lot of general information about everything. But, when it comes to factual knowledge, they may not be as accurate, since they were not trained with the data the user has.

It's like a judge in a courtroom. Their decisions rely on both their general understanding of the law and access to specific legal codes and precedents.

Retrieval Augmented Generation (RAG) is a powerful technique that provides the necessary context to the LLM accurately answer you.

For more information, check the original paper