# 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.
- [ ] Offer support for local models with CPU like llama-cpp
## Install
``` sh
pip install nanorag
```
## Learning
You can take a look at the notebooks to understand how it works.
Raw data
{
"_id": null,
"home_page": "https://github.com/antoni0z/nanorag",
"name": "nanorag",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": "",
"keywords": "nbdev jupyter notebook python",
"author": "antoni0z",
"author_email": "antonioprofesional@proton.me",
"download_url": "https://files.pythonhosted.org/packages/df/a5/9db0966ada441ff4ba56271cfa8e81b7324bc891f2721cab776a3b98a6b1/nanorag-0.0.13.tar.gz",
"platform": null,
"description": "# nanorag\n\n\n<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->\n\n## Library Objectives\n\n- [ ] Being a lightweight option of RAG, with just the necessary\n dependencies.\n- [ ] Focused on RAG with local and open source models, not focused on\n API calls.\n- [ ] Try out different strategies and data-structures that can be used\n to have better results. (Such as dataframes, can try out with polars\n as its really performant)\n- [ ] Multimodal support, combine image, text and audio to get the best\n results\n- [ ] Solve some of the storage challenges RAG faces, and provide good\n solutions for updating documents and embeddings as well as loading\n them.\n- [ ] Use it as a educational library to demostrate on some of the main\n concepts llama-index or other RAG framworks use.\n- [ ] The base for the implementation of some agentic strategies I will\n try out on other library.\n- [ ] Offer support for local models with CPU like llama-cpp\n\n## Install\n\n``` sh\npip install nanorag\n```\n\n## Learning\n\nYou can take a look at the notebooks to understand how it works.\n\n\n",
"bugtrack_url": null,
"license": "Apache Software License 2.0",
"summary": "Testing doing nanorag with nbdev to try it out",
"version": "0.0.13",
"project_urls": {
"Homepage": "https://github.com/antoni0z/nanorag"
},
"split_keywords": [
"nbdev",
"jupyter",
"notebook",
"python"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "f4dfbdbe50bc14c37db7ad63cc5abe09dab9e956d1f0f5eb0ebd33eca580f0ef",
"md5": "2ae90db97894125a496af9964b0af5a8",
"sha256": "3b99c8c7a31d60de5ff297ce3fbaf6ef26dd0c34ca4500dd4edc61b32785949c"
},
"downloads": -1,
"filename": "nanorag-0.0.13-py3-none-any.whl",
"has_sig": false,
"md5_digest": "2ae90db97894125a496af9964b0af5a8",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7",
"size": 17229,
"upload_time": "2024-03-06T15:42:01",
"upload_time_iso_8601": "2024-03-06T15:42:01.216688Z",
"url": "https://files.pythonhosted.org/packages/f4/df/bdbe50bc14c37db7ad63cc5abe09dab9e956d1f0f5eb0ebd33eca580f0ef/nanorag-0.0.13-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "dfa59db0966ada441ff4ba56271cfa8e81b7324bc891f2721cab776a3b98a6b1",
"md5": "369b0a8f9bb553374d53ba394e87433f",
"sha256": "7388dd9277db974674ca971069cd7667d4718ff0442434299e7101ffe9988818"
},
"downloads": -1,
"filename": "nanorag-0.0.13.tar.gz",
"has_sig": false,
"md5_digest": "369b0a8f9bb553374d53ba394e87433f",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 16469,
"upload_time": "2024-03-06T15:42:02",
"upload_time_iso_8601": "2024-03-06T15:42:02.328425Z",
"url": "https://files.pythonhosted.org/packages/df/a5/9db0966ada441ff4ba56271cfa8e81b7324bc891f2721cab776a3b98a6b1/nanorag-0.0.13.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-03-06 15:42:02",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "antoni0z",
"github_project": "nanorag",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "nanorag"
}
JSON
