### Changes ️
The previous implementation of the `LaunchDarklyProvider` had a race
condition where it would only initialize after the user's authentication
state was fully resolved. This caused two primary issues:
1. A delay in evaluating any feature flags, leading to a "flash of
un-styled/un-flagged content" until the user session was loaded.
2. An unreliable transition from an un-flagged state to a flagged state,
which could cause UI flicker or incorrect flag evaluations upon login.
This pull request refactors the provider to follow a more robust,
industry-standard pattern. It now initializes immediately with an
`anonymous` context, ensuring flags are available from the very start of
the application lifecycle. When the user logs in and their session
becomes available, the provider seamlessly transitions to an
authenticated context, guaranteeing that the correct flags are evaluated
consistently.
### Checklist
#### For code changes:
- I have clearly listed my changes in the PR description
- I have made a test plan
- I have tested my changes according to the test plan:
**Test Plan:**
- [x] **Anonymous User:** Load the application in an incognito window
without logging in. Verify that feature flags are evaluated correctly
for an anonymous user. Check the browser console for the
`[LaunchDarklyProvider] Using anonymous context` message.
- [x] **Login Flow:** While on the site, log in. Verify that the UI
updates with the correct feature flags for the authenticated user. Check
the console for the `[LaunchDarklyProvider] Using authenticated context`
message and confirm the LaunchDarkly client re-initializes.
- [x] **Authenticated User (Page Refresh):** As a logged-in user,
refresh the page. Verify that the application loads directly with the
authenticated user's flags, leveraging the cached session and
bootstrapped flags from `localStorage`.
- [x] **Logout Flow:** While logged in, log out. Verify that the UI
reverts to the anonymous user's state and flags. The provider `key`
should change back to "anonymous", triggering another re-mount.
<details><summary>Summary of Code Changes</summary>
- Refactored `LaunchDarklyProvider` to handle user authentication state
changes gracefully.
- The provider now initializes immediately with an `anonymous` user
context while the Supabase user session is loading.
- Once the user is authenticated, the provider's context is updated to
reflect the logged-in user's details.
- Added a `key` prop to the `<LDProvider>` component, using the user's
ID (or "anonymous"). This forces React to re-mount the provider when the
user's identity changes, ensuring a clean re-initialization of the
LaunchDarkly SDK.
- Enabled `localStorage` bootstrapping (`options={{ bootstrap:
"localStorage" }}`) to cache flags and improve performance on subsequent
page loads.
- Added `console.debug` statements for improved observability into the
provider's state (anonymous vs. authenticated).
</details>
#### For configuration changes:
- `.env.example` is updated or already compatible with my changes
- `docker-compose.yml` is updated or already compatible with my changes
- I have included a list of my configuration changes in the PR
description (under **Changes**)
<details>
<summary>Configuration Changes</summary>
- No configuration changes were made. This PR relies on existing
environment variables (`NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID` and
`NEXT_PUBLIC_LAUNCHDARKLY_ENABLED`).
</details>
---------
Co-authored-by: Lluis Agusti <hi@llu.lu>
AutoGPT Platform
Welcome to the AutoGPT Platform - a powerful system for creating and running AI agents to solve business problems. This platform enables you to harness the power of artificial intelligence to automate tasks, analyze data, and generate insights for your organization.
Getting Started
Prerequisites
- Docker
- Docker Compose V2 (comes with Docker Desktop, or can be installed separately)
- Node.js & NPM (for running the frontend application)
Running the System
To run the AutoGPT Platform, follow these steps:
-
Clone this repository to your local machine and navigate to the
autogpt_platformdirectory within the repository:git clone <https://github.com/Significant-Gravitas/AutoGPT.git | git@github.com:Significant-Gravitas/AutoGPT.git> cd AutoGPT/autogpt_platform -
Run the following command:
cp .env.example .envThis command will copy the
.env.examplefile to.env. You can modify the.envfile to add your own environment variables. -
Run the following command:
docker compose up -dThis command will start all the necessary backend services defined in the
docker-compose.ymlfile in detached mode. -
Navigate to
frontendwithin theautogpt_platformdirectory:cd frontendYou will need to run your frontend application separately on your local machine.
-
Run the following command:
cp .env.example .env.localThis command will copy the
.env.examplefile to.env.localin thefrontenddirectory. You can modify the.env.localwithin this folder to add your own environment variables for the frontend application. -
Run the following command:
Enable corepack and install dependencies by running:
corepack enable pnpm iGenerate the API client (this step is required before running the frontend):
pnpm generate:api-clientThen start the frontend application in development mode:
pnpm dev -
Open your browser and navigate to
http://localhost:3000to access the AutoGPT Platform frontend.
Docker Compose Commands
Here are some useful Docker Compose commands for managing your AutoGPT Platform:
docker compose up -d: Start the services in detached mode.docker compose stop: Stop the running services without removing them.docker compose rm: Remove stopped service containers.docker compose build: Build or rebuild services.docker compose down: Stop and remove containers, networks, and volumes.docker compose watch: Watch for changes in your services and automatically update them.
Sample Scenarios
Here are some common scenarios where you might use multiple Docker Compose commands:
-
Updating and restarting a specific service:
docker compose build api_srv docker compose up -d --no-deps api_srvThis rebuilds the
api_srvservice and restarts it without affecting other services. -
Viewing logs for troubleshooting:
docker compose logs -f api_srv ws_srvThis shows and follows the logs for both
api_srvandws_srvservices. -
Scaling a service for increased load:
docker compose up -d --scale executor=3This scales the
executorservice to 3 instances to handle increased load. -
Stopping the entire system for maintenance:
docker compose stop docker compose rm -f docker compose pull docker compose up -dThis stops all services, removes containers, pulls the latest images, and restarts the system.
-
Developing with live updates:
docker compose watchThis watches for changes in your code and automatically updates the relevant services.
-
Checking the status of services:
docker compose psThis shows the current status of all services defined in your docker-compose.yml file.
These scenarios demonstrate how to use Docker Compose commands in combination to manage your AutoGPT Platform effectively.
Persisting Data
To persist data for PostgreSQL and Redis, you can modify the docker-compose.yml file to add volumes. Here's how:
-
Open the
docker-compose.ymlfile in a text editor. -
Add volume configurations for PostgreSQL and Redis services:
services: postgres: # ... other configurations ... volumes: - postgres_data:/var/lib/postgresql/data redis: # ... other configurations ... volumes: - redis_data:/data volumes: postgres_data: redis_data: -
Save the file and run
docker compose up -dto apply the changes.
This configuration will create named volumes for PostgreSQL and Redis, ensuring that your data persists across container restarts.
API Client Generation
The platform includes scripts for generating and managing the API client:
pnpm fetch:openapi: Fetches the OpenAPI specification from the backend service (requires backend to be running on port 8006)pnpm generate:api-client: Generates the TypeScript API client from the OpenAPI specification using Orvalpnpm generate:api-all: Runs both fetch and generate commands in sequence
Manual API Client Updates
If you need to update the API client after making changes to the backend API:
-
Ensure the backend services are running:
docker compose up -d -
Generate the updated API client:
pnpm generate:api-all
This will fetch the latest OpenAPI specification and regenerate the TypeScript client code.