RAGNarok

combination of large language models (LLM), retrieval-augmented generation (RAG), and super activation

CodeCov

Setup

Please use the makefile to setup your project!

make create_environment  # will create a virtual-env and create an alias to connect
make dev-install  # this will install all required dependencies
pre-commit install

Please use make lint to clean your project, it will run black, isort, and flake8, black is already available in pre-commit hook

Build the doc:

make build_doc
cd docs/_build/html
open  with your browser -> index.html

Variables .env

Please create your .env with command

cp .env.template .env

In order to run properly the project please fill the PINECONE_API_KEY and OPENAI_API_KEY and PINECONE_INDEX and PINECONE_ENV environment variables within .env.

Run the tests

Please use make tox to run your tests, it will create its own python-env and run tests through different python version

or you can use

make test  # to run all test
make test_e2e  # to only run e2e test
test_not_e2e  # to skip e2e test

Using the project

Please use the following commands:

## using your env:
make run_fastapi_uvicorn  # basic app using uvicorn 4 works
make run_fastapi_gunicorn  # to use the production config
## using docker:
make build_linux_image or build_mac_image
make run_docker  # to run the docker locally

Project Organization

├── LICENSE
│
├── Makefile           <- Makefile with commands like `make data` or `make train`
│
├── README.md          <- The top-level README for developers using this project.
│
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures         <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
│
├── src                <- Source code for use in this project.
│   ├── core            <- Scripts to download or generate data
│   │
│   ├── infrastructure  <- Scripts to turn raw data into features for modeling
│   │
│   ├── interface       <- Scripts to train models and then use trained models to make predictions
│   │
│   ├── usecases        <- Scripts to train models and then use trained models to make predictions
│   │
│   └── queries         <- Scripts to train models and then use trained models to make predictions
│
└── tox.ini             <- tox file with settings for running tox; see tox.readthedocs.io

Jwuthri/RAGNarok