Tutor-GPT

Tutor-GPT is an LLM powered learning companion developed by Plastic Labs. It dynamically reasons about your learning needs and updates its own prompts to best serve you.

We leaned into theory of mind experiments and it is now more than just a literacy tutor, it’s an expansive learning companion. Read more about how it works here.

Tutor-GPT is powered by Honcho to build robust user representations and create a personalized experience for each user.

The hosted version of tutor-gpt is called Bloom as a nod to Benjamin Bloom's Two Sigma Problem.

Alternatively, you can run your own instance of the bot by following the instructions below.

Project Structure

The tutor-gpt project is split between multiple different modules that split up the backend logic for different clients.

• agent/ - this contains the core logic and prompting architecture
• bot/ - this contains the discord bot implementation
• api/ - this contains a FastAPI API interface that exposes the agent/ logic
• www/ - this contains a FullStack NextJS version of Tutor-GPT
• supabase/ - contains SQL scripts necessary for setting up local supabase

Most of the project is developed using python with the exception of the NextJS application. For python uv is used for dependency management and for the web interface we use pnpm.

The bot/ and api/ modules both use agent/ as a dependency and load it as a local package using uv

NOTE More information about the web interface is available in www/README this README primarily contains information about the backend of tutor-gpt and the core logic of the tutor

The agent, bot, and api modules are all managed using a uv workspace

Installation

This section goes over how to setup a python environment for running Tutor-GPT. This will let you run the discord bot, run the FastAPI application, or develop the agent code.

The below commands will install all the dependencies necessary for running the tutor-gpt project. We recommend using uv to setup a virtual environment for the project.

git clone https://github.com/plastic-labs/tutor-gpt.git && cd tutor-gpt
uv sync # set up the workspace
source .venv/bin/activate # activate the virtual environment

From here you will then need to run uv sync in the appropriate directory depending on what you part of the project you want to run. For example to run the FastAPI application you need to navigate to the directory an re-run sync

cd api/
uv sync

You should see a message indicated that the depenedencies were resolved and/or installed if not already installed before.

Docker

Alternatively (The recommended way) this project can be built and run with docker. Install docker and ensure it's running before proceeding.

The web front end is built and run separately from the remainder of the codebase. Below are the commands for building the core of the tutor-gpt project which includes the necessary dependencies for running either the discord bot or the FastAPI endpoint.

git clone https://github.com/plastic-labs/tutor-gpt.git
cd tutor-gpt
docker build -t tutor-gpt-core .

Similarly, to build the web interface run the below commands

Usage

Each of the interfaces of tutor-gpt require different environment variables to operate properly. Both the bot/ and api/ modules contain a .env.template file that you can use as a starting point. Copy and rename the .env.template to .env

Below are more detailed explanations of environment variables

Common

• OPENAI_API_KEY — The API Key for Openrouter which uses an OpenAI compatibile API
• MODEL — The openrouter model to use

FastAPI

• URL — The URL endpoint for the frontend Next.js application
• HONCHO_URL — The base URL for the instance of Honcho you are using
• HONCHO_APP_NAME — The name of the honcho application to use for Tutor-GPT

Optional Extras

• SENTRY_DSN_API — The Sentry DSN for optional error reporting

Discord

• BOT_TOKEN — This is the discord bot token. You can find instructions on how to create a bot and generate a token in the pycord docs.
• THOUGHT_CHANNEL_ID — This is the discord channel for the bot to output thoughts to. Make a channel in your server and copy the ID by right clicking the channel and copying the link. The channel ID is the last string of numbers in the link.

Docker/Containerization

You can also optionally use the docker containers to run the application locally. Below is the command to run the discord bot locally using a .env file that is not within the docker container. Be careful not to add your .env in the docker container as this is insecure and can leak your secrets.

docker run --env-file .env tutor-gpt-core python bot/app.py

To run the webui you need to run the backend FastAPI and the frontend NextJS containers separately. In two separate terminal instances run the following commands to have both applications run. The current behaviour will utilize the .env file in your local repository and run the bot.

docker run -p 8000:8000 --env-file .env tutor-gpt-core python -m uvicorn api.main:app --host 0.0.0.0 --port 8000 # FastAPI Backend

NOTE: the default run command in the docker file for the core runs the FastAPI backend so you could just run docker run --env-file .env tutor-gpt-core

Contributing

This project is completely open source and welcomes any and all open source contributions. The workflow for contributing is to make a fork of the repository. You can claim an issue in the issues tab or start a new thread to indicate a feature or bug fix you are working on.

Once you have finished your contribution make a PR pointed at the staging branch and it will be reviewed by a project manager. Feel free to join us in our discord to discuss your changes or get help.

Once your changes are accepted and merged into staging they will under go a period of live testing before entering the upstream into main

License

Tutor-GPT is licensed under the GPL-3.0 License. Learn more at the License file