Load AI is an innovative project designed to provide college and university students with a powerful tool for academic assistance. By leveraging cutting-edge technologies like Next.js, Prisma, ChatGPT, LangChain, and Next Auth, Load AI creates a personalized virtual teaching assistant based on uploaded lecture notes.
- Intelligent Assistance: Upload your lecture notes and experience the power of an AI agent that understands and answers your questions.
- Personalized Support: Benefit from a tailored virtual teaching assistant that provides guidance and support based on your specific course materials.
To get Load AI up and running on your local machine, follow these simple steps:
- Clone the Repository: Start by cloning the repository to your local environment.
- Install Dependencies: Use the yarn package manager to install all the required dependencies.
- Configure Credentials: Set up the necessary credentials and configurations for seamless integration.
- Run the Application: Execute the provided script to launch the Next.js application and start using Load AI.
Load AI relies on the following essential technologies and frameworks:
- Prisma
- Next.js
- Yarn
Make sure to have these dependencies installed and properly configured before running the project.
We appreciate and welcome contributions from the community to enhance Load AI further. To contribute, simply fork the repository, make your changes, and submit a pull request. We also encourage you to share your feedback, suggestions, and bug reports by opening an issue on GitHub.
While we strive for excellence, Load AI may have a few known issues and limitations that we are actively addressing. To stay informed about any existing concerns, please refer to the project's issue tracker on GitHub.
To quickly get started with Load AI, follow these steps:
- Clone the Repository: Clone the repository to your local machine.
- Configure Credentials: Set up the necessary credentials and configurations.
- Launch the Application: Run the Next.js application and unlock the power of Load AI.
For detailed instructions and additional information, please refer to the comprehensive project documentation.