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https://github.com/humankernel/rag-revamped

Advanced Iterative RAG pipeline + (Gradio UI), local
https://github.com/humankernel/rag-revamped

gradio nlp retrieval-augmented-generation vllm

Last synced: 16 days ago
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Advanced Iterative RAG pipeline + (Gradio UI), local

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README

          

# Advanced RAG Chatbot

This project is a simple prototype developed for a [research paper](https://github.com/humankernel/rag-paper/blob/main/rcci_template.pdf) focused on democratizing AI tools for managing PDF documents in resource-limited contexts. It serves as an advanced Retrieval-Augmented Generation (RAG) pipeline example, showcasing how AI can facilitate document management.

## Features

-

## Installation

To set up the project locally, follow these steps:

1. Clone the repository:

```bash
git clone https://github.com/humankernel/rag.git
cd rag
```

2. Install the dependencies: `uv sync`

(Optional) Setup PyPi cuban repos
```shell
# uv will use the cuban national pypi repos
# if you don't want this open the `pyproject.toml`
# and remove the following:
# [[tool.uv.index]]
# url = "http://nexus.prod.uci.cu/repository/pypi-all/simple"
# default = true
```

3. Setup `.env` variables
4. Execute `uv run main`, this will start the Gradio UI

(Optional) In a local environment (e.g dev mode) you can start a separated `vLLM` instance.
```shell
# https://docs.vllm.ai/en/stable/serving/engine_args.html
❯ vllm serve ./qwen2.5-1.5b-instruct-q8_0.gguf --device cuda --gpu-memory-utilization 0.6 --max-model-len 2048
```

## Tests

```sh
pytest .
```

## License
This project is licensed under the MIT License - see the LICENSE file for details