Metadata-Version: 2.1
Name: nanorag
Version: 0.0.12
Summary: Testing doing nanorag with nbdev to try it out
Home-page: https://github.com/antoni0z/nanorag
Author: antoni0z
Author-email: antonioprofesional@proton.me
License: Apache Software License 2.0
Keywords: nbdev jupyter notebook python
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: Apache Software License
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
License-File: LICENSE

# nanorag

<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->

## Library Objectives

- [ ] Being a lightweight option of RAG, with just the necessary
  dependencies.
- [ ] Focused on RAG with local and open source models, not focused on
  API calls.
- [ ] Try out different strategies and data-structures that can be used
  to have better results. (Such as dataframes, can try out with polars
  as its really performant)
- [ ] Multimodal support, combine image, text and audio to get the best
  results
- [ ] Solve some of the storage challenges RAG faces, and provide good
  solutions for updating documents and embeddings as well as loading
  them.
- [ ] Use it as a educational library to demostrate on some of the main
  concepts llama-index or other RAG framworks use.
- [ ] The base for the implementation of some agentic strategies I will
  try out on other library.

## Install

``` sh
pip install nanorag
```

## Learning

You can take a look at the notebooks to understand how it works.


