OpenCVPythonRAG is a project aimed at building a Retrieval-Augmented Generation (RAG) system using OpenCV's Python documentation as the knowledge base. The goal is to create an interactive tool that can answer questions and provide code suggestions from the OpenCV documentation, leveraging natural language understanding. One of the RAG's main features is being Python-tailored, meaning that it will do its best to give a relevant answer to Python-related inquiries, avoiding the use of C++.
- Automated extraction of OpenCV's Python documentation.
- Preprocessing of documentation for efficient retrieval.
- Embedding generation for natural language querying.
- RAG pipeline setup for question-answering.
To get started, you'll need Python 3.8+ and a few Python libraries.
- Clone the repository:
git clone https://github.com/SergioPulidoC/OpenCVPythonRAG.git
cd OpenCVPythonRAG- Set up a virtual environment:
python3 -m venv venv
# For Linux:
source venv/bin/activate
# If you're on Windows, use:
# venv\Scripts\activate- Install the required packages:
pip install -r requirements.txt[Work in progress!]
- Basic setup and README
- Documentation extraction
- Embedding generation and storage
- RAG pipeline implementation
- Testing and deployment
Contributions are welcome! Feel free to submit a pull request or open an issue for discussion.
This project is licensed under the MIT License. Check the LICENSE for more information.