Open Chat Studio

Open Chat Studio is a platform for building, deploying, and evaluating AI-powered chat applications. It provides tools for working with various LLMs (Language Learning Models), creating chatbots, managing conversations, and integrating with different messaging platforms.

User Documentation

Developer Documentation

Contributing

We welcome contributions to Open Chat Studio! If you're interested in contributing, please check out our contributing guidelines for more information on how to get started.

Quick Start Setup

Open Chat Studio uses UV and Invoke for dev automation.

Prerequisites

• Python 3.13 (recommended)
• Node.js >= 24.0.0
• Docker and Docker Compose
• Cloned repo

Installation Steps

1. Install dependencies

   uv venv --python 3.13
   source .venv/bin/activate
   uv sync

2. Run the automated setup

   inv setup-dev-env

   This will:

   • Install pre-commit hooks
   • Start database and Redis services
   • Run database migrations
   • Build frontend resources
   • Create a superuser

   OR

   Follow these manual steps

   Install the pre-commit hooks

   prek install --install-hooks

   Set up database

   Start the database and redis services and run the DB migrations:

   inv up  # start the docker services
   cp .env.example .env
   ./manage.py migrate

   Build the front-end resources

   To build JavaScript and CSS files, first install npm packages:

   inv npm --install
   # or
   npm install
   npm run dev

   Note

   You should be using node >= 24.0.0. If you have nvm installed, you can run nvm use to switch to the correct version.

   To check which version you are using use node --version.

   Create a superuser

   ./manage.py createsuperuser

3. Start the development server

   ./manage.py runserver

4. Run Celery for background tasks

   Celery is required to handle LLM interactions. Run it using:

   inv celery

Docker-Only Development Environment

As an alternative to running Django and Celery on the host, you can run the full stack inside Docker. This requires only Docker — no local Python or Node installation needed.

Prerequisites

• Docker and Docker Compose

Setup

1. Create your .env file

   cp .env.example .env

   Edit .env and set at minimum SECRET_KEY. The DATABASE_URL and REDIS_URL values in .env are ignored when running via Docker Compose — those are overridden by the compose file to use the container service names.

2. Build the images

   docker compose build

3. Start everything

   docker compose up

   On first start, Docker Compose will:

   • Start PostgreSQL and wait until it is healthy
   • Start Redis
   • Run python manage.py migrate (the migrate service exits once complete)
   • Start the Django dev server on http://localhost:8000
   • Start a Celery worker and Celery Beat scheduler

4. Create a superuser

   In a separate terminal:

   docker compose run --rm web python manage.py createsuperuser

Services

Service	Description
db	PostgreSQL with pgvector extension
redis	Redis (used as Celery broker and result backend)
migrate	Runs manage.py migrate on startup, then exits
web	Django dev server with auto-reload (runserver)
celery_worker	Celery worker for background tasks
celery_beat	Celery Beat scheduler (uses django_celery_beat database scheduler)