A lightweight program for testing Retrieval Augmented Generation using DeepSeek. If you'd like to see what's going on under the hood, you can check out my blog post.

1. Python 3.12.X, Python 3.13 currently has versioning conflicts
2. DeepSeek API key

1. Clone this repository: git clone https://github.com/danielgeiszler/EzRAG.git
2. Install the requirements: uv pip install -r pyproject.toml
3. Create a .env file containing your DeepSeek or OpenAI API key: API_KEY=your_key_here
4. Run the script: python EzRag.py
5. Open the given url in your browser
6. If the model produces incorrect information about where the Changzhou dialect is spoken, that means it is reading local data and it worked!

Currenly, only .txt, .docx, and .pdf files are supported. Adding your files to the data directory is sufficient for them to be included in the system.

• Support for more models
• Python 3.13 support