Getting started
Introduction
OpenCopilot is a free and open-source tool that allows you to create AI copilots for your SaaS product. The copilot can communicate with your underlying APIs and execute calls as needed. We are open-source under MIT license and also support OpenAPI standards.
Getting started
Update your docs to your brand and add valuable content for the best user conversion.
What is copilots? (start from here)
Introduction to OpenCopilot. start from here for step-by-step guide
Setting up
Install the project locally and make it yours
Create copilots
Create copilots programmatically (APIs, SDKs) or using the dashboard
Authentications and Authorization
Handle Authentications and Authorization to your backend
Embedding copilots on your app
How to use OpenCopilot widget and embed it on your web app
Creating complex flows
Learn how to use OpenCopilot flows definition
Roadmap
See what’s coming next.
Setting up
You can self-host OpenCopilot in a relatively easy way, please make sure you have the following requirements:
- Docker engine and docker compose installed
- Clone the repository
git clone https://github.com/openchatai/opencopilot.git
- Update your llm-server/.env with your OPENAI_API_KEY
OPENAI_API_KEY=YOUR_KEY_GOES_HERE
- Run the installation script
make install
Then your OpenCopilot dashboard will be accessible at http://localhost:8888
You also can see the complete list of commands using make help
➜ OpenCopilot git:(main) make help
Usage: make [target]
Available Targets:
install - Install and set up the Docker environment
db-setup - Set up the database (fresh migration with seeding)
down - Stop and remove all containers
exec-backend - Access the backend container's shell
exec-dashboard - Access the dashboard container's shell
exec-llm-server - Access the llm-server container's shell
restart - Restart all containers
logs - Show container logs
help - Display this help message
Complete list of links:
- http://localhost:8888/backend -> backend APIs (create, update, delete and validate copilots)
- http://localhost:8888 or http://localhost:8888/dashbaord -> dashboard (UI to do the same)