Introduces discriminated unions for time, date, and date-time format selection, supporting both strftime and ISO 8601 (with timezone and microsecond options). Updates schemas, test cases, and block logic to handle the new format types, improving flexibility and standards compliance for time and date outputs. <!-- Clearly explain the need for these changes: --> ### Why these changes are needed Users need to output timestamps in ISO 8601/RFC 3339 format for API integrations and standardized data exchange. The previous implementation only supported strftime formatting, which made it difficult to generate properly formatted timestamps with timezone information. This change enables: - **Standards compliance**: ISO 8601 and RFC 3339 compliant timestamps - **Timezone support**: 38 timezone options covering all UTC offsets globally - **API compatibility**: Many APIs require RFC 3339 timestamps (e.g., "2011-06-03T10:00:00-07:00") - **Backward compatibility**: Existing workflows continue to work with default strftime format ### Changes 🏗️ <!-- Concisely describe all of the changes made in this pull request: --> - **Added discriminated union format types** for all time/date blocks: - `GetCurrentTimeBlock`: Now supports `TimeStrftimeFormat` and `TimeISO8601Format` - `GetCurrentDateBlock`: Now supports `DateStrftimeFormat` and `DateISO8601Format` - `GetCurrentDateAndTimeBlock`: Now supports `StrftimeFormat` and `ISO8601Format` - **Implemented shared timezone support**: - Created `TimezoneLiteral` type with 38 timezone options (all UTC offsets) - Supports fractional offsets (e.g., India UTC+05:30, Nepal UTC+05:45) - Deduplicated timezone lists across all format classes - **Added ISO 8601 format features**: - Timezone-aware timestamps with proper offset formatting - Optional microseconds inclusion - RFC 3339 compliance (subset of ISO 8601 with mandatory timezone) - **Updated test cases** for all three blocks to verify: - Default behavior unchanged (backward compatibility) - Custom strftime formats still work - ISO 8601 format produces correct output ### Checklist 📋 #### For code changes: - [x] I have clearly listed my changes in the PR description - [x] I have made a test plan - [x] I have tested my changes according to the test plan: <!-- Put your test plan here: --> - [x] Verified backward compatibility - default strftime format unchanged - [x] Tested ISO 8601 format with UTC timezone - [x] Tested ISO 8601 format with various timezones (India, New York, etc.) - [x] Tested microseconds option for ISO formats - [x] Verified all existing tests pass for GetCurrentTimeBlock - [x] Verified all existing tests pass for GetCurrentDateBlock - [x] Verified all existing tests pass for GetCurrentDateAndTimeBlock - [x] Manually tested each block with different format configurations - [x] Confirmed RFC 3339 compliance for timestamps with mandatory timezone --------- Co-authored-by: Claude <claude@users.noreply.github.com>
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.