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Beavs AI

Beavs AI is an application that provides an AI Chatbot that is knowledgeable about OSU's courses. It allows OSU students to interact with an AI agent that can answer course-specific questions.

Project Prerequisites

  • Node: You should install the latest version of Node
  • Docker: The download link is here, make sure to choose the correct operating system.

Usage

  1. Clone the repository:

    git clone https://github.com/OSU-App-Club/beavsai.git

  2. Navigate to the project directory:

    cd beavsai

  3. Install all the required dependencies to run our Next.js App

    npm install

Note

You may come across an peer dependency error when running this command, try npm install --legacy-peer-deps

  1. Copy the .env.example file to .env.local:

    cp .env.example .env.local

  2. Message @nyumat on Discord to get the required credentials for the .env.local file.

Warning

Do not share these credentials with anyone else. Additionally, you will not be able to run the application without them.

  1. Create an AUTH_SECRET environment variable

    npx auth secret

  2. Start a local instance of our PostgreSQL database using Docker:

    docker-compose up -d

Note

Doing this in VSCode's terminal may present you with an error like: Error: P1010: User postgres was denied access on the database postgres. To fix this, use your system's terminal to run the command.

  1. Run the Next.js App 
    npm run dev

Scripts

Script Description
dev Runs database generation, migration, and starts the Next.js dev server with Turbopack enabled.
build Builds the Next.js application for production.
start Starts the Next.js application in production mode.
lint Runs ESLint to check for code quality issues.
format Formats the codebase with Prettier.
check-format Checks code formatting without making changes.
type-check Runs TypeScript type checks based on the configuration in tsconfig.json.
db:generate Generates Prisma client based on schema and .env.local configuration.
db:migrate Applies migrations for development using .env.local configuration.
db:studio Opens Prisma Studio for database management.
db:seed Seeds the database with initial data.

Troubleshooting

If you encounter any issues while running the application, please refer to the following troubleshooting steps:

  1. Database Connection Issues: If you are unable to connect to the database, ensure that the Docker container is running. You can check the status of the container by running the following command:

    docker ps

    If the container is not running, you can start it using the following command:

    docker-compose up -d

  2. Environment Variables: Ensure that you have copied the .env.example file to .env.local and have filled in the required credentials. If you are missing any credentials, please message @nyumat on Discord.

  3. Prisma Client Generation: If you are encountering issues with the Prisma client, you can regenerate it by running the following command:

    npm run db:generate

For the Noobies

If you are new to web development, git, or any of the tools mentioned above, don't worry! We have a few resources to help you get started:

No one is born a master, so don't be afraid to ask questions!

Level-based Learning for Beavs AI

Choose tasks aligned with your skill level to contribute effectively to Beavs AI:

Beginner

  • Frontend: Build UI components for displaying syllabus content, style the interface to align with OSU branding, or implement basic API calls to fetch syllabus data.
  • Backend: Create straightforward API endpoints for querying file content, validate and handle basic user inputs, or manage simple data interactions with PostgreSQL.

Intermediate

  • Frontend: Implement interactive UI components for search functionality, handle input validation for queries, or manage component state effectively with React hooks.
  • Backend: Integrate with Pinecone for semantic search, manage user sessions with secure practices, or develop API endpoints that retrieve and format contextually relevant content for RAG responses.

Advanced

  • Frontend: Optimize the rendering of search results for low-latency response times, implement advanced state management for caching syllabus queries, or introduce features that enhance user experience (e.g., query history, autocomplete).
  • Backend: Optimize Pinecone and database queries for speed and scalability, implement complex business logic for query preprocessing and RAG workflows, or enhance backend efficiency by streamlining Langchain workflows to dynamically handle complex queries with large language models.

Contributors