This repository contains the code for building an Agentic Rag (a type of language model) using the LlamaIndex library. The project utilizes various components, including Python files, asset directories, and a virtual environment.

To get started with this project, follow these steps:

1. Clone the repository to your local machine.
2. Create a new virtual environment using your preferred tool (e.g., python -m venv venv for Python's built-in venv module).
3. Activate the virtual environment (e.g., source venv/bin/activate on Unix-based systems or venv\Scripts\activate on Windows).
4. Install the required Python packages by running pip install -r requirements.txt.
5. Set up the necessary environment variables (if applicable) in the .env file.
6. Open the RouterQueryEngine.ipynb Jupyter Notebook and follow the instructions provided to build and interact with the Agentic Rag model.

If you'd like to contribute to this project, please follow the standard Git workflow:

1. Fork the repository
2. Create a new branch for your feature or bug fix
3. Make your changes and commit them with descriptive commit messages
4. Push your changes to your forked repository
5. Submit a pull request to the main repository

This project is licensed under the MIT License. Please see the LICENSE file for more details.

• LlamaIndex - The library used for building the Agentic Rag model.
• Other relevant libraries or resources