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Merge branch 'dev'

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Swifty
2025-08-20 15:22:08 +02:00
parent c2af8c1a6a 2610c4579f
commit c4483fa6c7
486 changed files with 8757 additions and 26270 deletions
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3
.dockerignore
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@@ -15,6 +15,7 @@
!autogpt_platform/backend/pyproject.toml
!autogpt_platform/backend/poetry.lock
!autogpt_platform/backend/README.md
!autogpt_platform/backend/.env
# Platform - Market
!autogpt_platform/market/market/
@@ -27,6 +28,7 @@
# Platform - Frontend
!autogpt_platform/frontend/src/
!autogpt_platform/frontend/public/
!autogpt_platform/frontend/scripts/
!autogpt_platform/frontend/package.json
!autogpt_platform/frontend/pnpm-lock.yaml
!autogpt_platform/frontend/tsconfig.json
@@ -34,6 +36,7 @@
## config
!autogpt_platform/frontend/*.config.*
!autogpt_platform/frontend/.env.*
!autogpt_platform/frontend/.env
# Classic - AutoGPT
!classic/original_autogpt/autogpt/

3
.github/PULL_REQUEST_TEMPLATE.md vendored
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@@ -24,7 +24,8 @@
</details>
#### For configuration changes:
- [ ] `.env.example` is updated or already compatible with my changes
- [ ] `.env.default` 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**)

46
.github/workflows/platform-frontend-ci.yml vendored
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@@ -82,37 +82,6 @@ jobs:
- name: Run lint
run: pnpm lint
type-check:
runs-on: ubuntu-latest
needs: setup
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: "21"
- name: Enable corepack
run: corepack enable
- name: Restore dependencies cache
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ needs.setup.outputs.cache-key }}
restore-keys: |
${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
${{ runner.os }}-pnpm-
- name: Install dependencies
run: pnpm install --frozen-lockfile
- name: Run tsc check
run: pnpm type-check
chromatic:
runs-on: ubuntu-latest
needs: setup
@@ -176,11 +145,7 @@ jobs:
- name: Copy default supabase .env
run: |
cp ../.env.example ../.env
- name: Copy backend .env
run: |
cp ../backend/.env.example ../backend/.env
cp ../.env.default ../.env
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
@@ -252,15 +217,6 @@ jobs:
- name: Install dependencies
run: pnpm install --frozen-lockfile
- name: Setup .env
run: cp .env.example .env
- name: Build frontend
run: pnpm build --turbo
# uses Turbopack, much faster and safe enough for a test pipeline
env:
NEXT_PUBLIC_PW_TEST: true
- name: Install Browser 'chromium'
run: pnpm playwright install --with-deps chromium

132
.github/workflows/platform-fullstack-ci.yml vendored Normal file
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@@ -0,0 +1,132 @@
name: AutoGPT Platform - Frontend CI
on:
push:
branches: [master, dev]
paths:
- ".github/workflows/platform-fullstack-ci.yml"
- "autogpt_platform/**"
pull_request:
paths:
- ".github/workflows/platform-fullstack-ci.yml"
- "autogpt_platform/**"
merge_group:
defaults:
run:
shell: bash
working-directory: autogpt_platform/frontend
jobs:
setup:
runs-on: ubuntu-latest
outputs:
cache-key: ${{ steps.cache-key.outputs.key }}
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: "21"
- name: Enable corepack
run: corepack enable
- name: Generate cache key
id: cache-key
run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
- name: Cache dependencies
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ steps.cache-key.outputs.key }}
restore-keys: |
${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
${{ runner.os }}-pnpm-
- name: Install dependencies
run: pnpm install --frozen-lockfile
types:
runs-on: ubuntu-latest
needs: setup
strategy:
fail-fast: false
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
submodules: recursive
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: "21"
- name: Enable corepack
run: corepack enable
- name: Copy default supabase .env
run: |
cp ../.env.default ../.env
- name: Copy backend .env
run: |
cp ../backend/.env.default ../backend/.env
- name: Run docker compose
run: |
docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
- name: Restore dependencies cache
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ needs.setup.outputs.cache-key }}
restore-keys: |
${{ runner.os }}-pnpm-
- name: Install dependencies
run: pnpm install --frozen-lockfile
- name: Setup .env
run: cp .env.default .env
- name: Wait for services to be ready
run: |
echo "Waiting for rest_server to be ready..."
timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
echo "Waiting for database to be ready..."
timeout 60 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
- name: Generate API queries
run: pnpm generate:api:force
- name: Check for API schema changes
run: |
if ! git diff --exit-code src/app/api/openapi.json; then
echo "❌ API schema changes detected in src/app/api/openapi.json"
echo ""
echo "The openapi.json file has been modified after running 'pnpm generate:api-all'."
echo "This usually means changes have been made in the BE endpoints without updating the Frontend."
echo "The API schema is now out of sync with the Front-end queries."
echo ""
echo "To fix this:"
echo "1. Pull the backend 'docker compose pull && docker compose up -d --build --force-recreate'"
echo "2. Run 'pnpm generate:api' locally"
echo "3. Run 'pnpm types' locally"
echo "4. Fix any TypeScript errors that may have been introduced"
echo "5. Commit and push your changes"
echo ""
exit 1
else
echo "✅ No API schema changes detected"
fi
- name: Run Typescript checks
run: pnpm types

3
.gitignore vendored
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@@ -5,6 +5,8 @@ classic/original_autogpt/*.json
auto_gpt_workspace/*
*.mpeg
.env
# Root .env files
/.env
azure.yaml
.vscode
.idea/*
@@ -121,7 +123,6 @@ celerybeat.pid
# Environments
.direnv/
.env
.venv
env/
venv*/

2
.pre-commit-config.yaml
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@@ -235,7 +235,7 @@ repos:
hooks:
- id: tsc
name: Typecheck - AutoGPT Platform - Frontend
entry: bash -c 'cd autogpt_platform/frontend && pnpm type-check'
entry: bash -c 'cd autogpt_platform/frontend && pnpm types'
files: ^autogpt_platform/frontend/
types: [file]
language: system

10
README.md
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@@ -3,6 +3,16 @@
[![Discord Follow](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Finvites%2Fautogpt%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&label=total%20members&logo=discord&logoColor=white&color=7289da)](https://discord.gg/autogpt) &ensp;
[![Twitter Follow](https://img.shields.io/twitter/follow/Auto_GPT?style=social)](https://twitter.com/Auto_GPT) &ensp;
<!-- Keep these links. Translations will automatically update with the README. -->
[Deutsch](https://zdoc.app/de/Significant-Gravitas/AutoGPT) |
[Español](https://zdoc.app/es/Significant-Gravitas/AutoGPT) |
[français](https://zdoc.app/fr/Significant-Gravitas/AutoGPT) |
[日本語](https://zdoc.app/ja/Significant-Gravitas/AutoGPT) |
[한국어](https://zdoc.app/ko/Significant-Gravitas/AutoGPT) |
[Português](https://zdoc.app/pt/Significant-Gravitas/AutoGPT) |
[Русский](https://zdoc.app/ru/Significant-Gravitas/AutoGPT) |
[中文](https://zdoc.app/zh/Significant-Gravitas/AutoGPT)
**AutoGPT** is a powerful platform that allows you to create, deploy, and manage continuous AI agents that automate complex workflows.
## Hosting Options

0
autogpt_platform/.env.example → autogpt_platform/.env.default
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49
autogpt_platform/CLAUDE.md
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@@ -1,9 +1,11 @@
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Repository Overview
AutoGPT Platform is a monorepo containing:
- **Backend** (`/backend`): Python FastAPI server with async support
- **Frontend** (`/frontend`): Next.js React application
- **Shared Libraries** (`/autogpt_libs`): Common Python utilities
@@ -11,6 +13,7 @@ AutoGPT Platform is a monorepo containing:
## Essential Commands
### Backend Development
```bash
# Install dependencies
cd backend && poetry install
@@ -41,6 +44,7 @@ poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[GetC
poetry run format # Black + isort
poetry run lint # ruff
```
More details can be found in TESTING.md
#### Creating/Updating Snapshots
@@ -53,8 +57,8 @@ poetry run pytest path/to/test.py --snapshot-update
⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.
### Frontend Development
```bash
# Install dependencies
cd frontend && npm install
@@ -72,12 +76,13 @@ npm run storybook
npm run build
# Type checking
npm run type-check
npm run types
```
## Architecture Overview
### Backend Architecture
- **API Layer**: FastAPI with REST and WebSocket endpoints
- **Database**: PostgreSQL with Prisma ORM, includes pgvector for embeddings
- **Queue System**: RabbitMQ for async task processing
@@ -86,6 +91,7 @@ npm run type-check
- **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies
### Frontend Architecture
- **Framework**: Next.js App Router with React Server Components
- **State Management**: React hooks + Supabase client for real-time updates
- **Workflow Builder**: Visual graph editor using @xyflow/react
@@ -93,6 +99,7 @@ npm run type-check
- **Feature Flags**: LaunchDarkly integration
### Key Concepts
1. **Agent Graphs**: Workflow definitions stored as JSON, executed by the backend
2. **Blocks**: Reusable components in `/backend/blocks/` that perform specific tasks
3. **Integrations**: OAuth and API connections stored per user
@@ -100,13 +107,16 @@ npm run type-check
5. **Virus Scanning**: ClamAV integration for file upload security
### Testing Approach
- Backend uses pytest with snapshot testing for API responses
- Test files are colocated with source files (`*_test.py`)
- Frontend uses Playwright for E2E tests
- Component testing via Storybook
### Database Schema
Key models (defined in `/backend/schema.prisma`):
- `User`: Authentication and profile data
- `AgentGraph`: Workflow definitions with version control
- `AgentGraphExecution`: Execution history and results
@@ -114,13 +124,31 @@ Key models (defined in `/backend/schema.prisma`):
- `StoreListing`: Marketplace listings for sharing agents
### Environment Configuration
- Backend: `.env` file in `/backend`
- Frontend: `.env.local` file in `/frontend`
- Both require Supabase credentials and API keys for various services
#### Configuration Files
- **Backend**: `/backend/.env.default` (defaults) → `/backend/.env` (user overrides)
- **Frontend**: `/frontend/.env.default` (defaults) → `/frontend/.env` (user overrides)
- **Platform**: `/.env.default` (Supabase/shared defaults) → `/.env` (user overrides)
#### Docker Environment Loading Order
1. `.env.default` files provide base configuration (tracked in git)
2. `.env` files provide user-specific overrides (gitignored)
3. Docker Compose `environment:` sections provide service-specific overrides
4. Shell environment variables have highest precedence
#### Key Points
- All services use hardcoded defaults in docker-compose files (no `${VARIABLE}` substitutions)
- The `env_file` directive loads variables INTO containers at runtime
- Backend/Frontend services use YAML anchors for consistent configuration
- Supabase services (`db/docker/docker-compose.yml`) follow the same pattern
### Common Development Tasks
**Adding a new block:**
1. Create new file in `/backend/backend/blocks/`
2. Inherit from `Block` base class
3. Define input/output schemas
@@ -132,12 +160,14 @@ Note: when making many new blocks analyze the interfaces for each of these blcok
ex: do the inputs and outputs tie well together?
**Modifying the API:**
1. Update route in `/backend/backend/server/routers/`
2. Add/update Pydantic models in same directory
3. Write tests alongside the route file
4. Run `poetry run test` to verify
**Frontend feature development:**
1. Components go in `/frontend/src/components/`
2. Use existing UI components from `/frontend/src/components/ui/`
3. Add Storybook stories for new components
@@ -146,6 +176,7 @@ ex: do the inputs and outputs tie well together?
### Security Implementation
**Cache Protection Middleware:**
- Located in `/backend/backend/server/middleware/security.py`
- Default behavior: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses an allow list approach - only explicitly permitted paths can be cached
@@ -154,14 +185,20 @@ ex: do the inputs and outputs tie well together?
- To allow caching for a new endpoint, add it to `CACHEABLE_PATHS` in the middleware
- Applied to both main API server and external API applications
### Creating Pull Requests
- Create the PR aginst the `dev` branch of the repository.
- Ensure the branch name is descriptive (e.g., `feature/add-new-block`)/
- Use conventional commit messages (see below)/
- Fill out the .github/PULL_REQUEST_TEMPLATE.md template as the PR description/
- Run the github pre-commit hooks to ensure code quality.
### Reviewing/Revising Pull Requests
- When the user runs /pr-comments or tries to fetch them, also run gh api /repos/Significant-Gravitas/AutoGPT/pulls/[issuenum]/reviews to get the reviews
- Use gh api /repos/Significant-Gravitas/AutoGPT/pulls/[issuenum]/reviews/[review_id]/comments to get the review contents
- Use gh api /repos/Significant-Gravitas/AutoGPT/issues/9924/comments to get the pr specific comments
### Conventional Commits
Use this format for commit messages and Pull Request titles:

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autogpt_platform/README.md
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@@ -8,7 +8,6 @@ Welcome to the AutoGPT Platform - a powerful system for creating and running AI
- Docker
- Docker Compose V2 (comes with Docker Desktop, or can be installed separately)
- Node.js & NPM (for running the frontend application)
### Running the System
@@ -24,10 +23,10 @@ To run the AutoGPT Platform, follow these steps:
2. Run the following command:
```
cp .env.example .env
cp .env.default .env
```
This command will copy the `.env.example` file to `.env`. You can modify the `.env` file to add your own environment variables.
This command will copy the `.env.default` file to `.env`. You can modify the `.env` file to add your own environment variables.
3. Run the following command:
@@ -37,44 +36,7 @@ To run the AutoGPT Platform, follow these steps:
This command will start all the necessary backend services defined in the `docker-compose.yml` file in detached mode.
4. Navigate to `frontend` within the `autogpt_platform` directory:
```
cd frontend
```
You will need to run your frontend application separately on your local machine.
5. Run the following command:
```
cp .env.example .env.local
```
This command will copy the `.env.example` file to `.env.local` in the `frontend` directory. You can modify the `.env.local` within this folder to add your own environment variables for the frontend application.
6. Run the following command:
Enable corepack and install dependencies by running:
```
corepack enable
pnpm i
```
Generate the API client (this step is required before running the frontend):
```
pnpm generate:api-client
```
Then start the frontend application in development mode:
```
pnpm dev
```
7. Open your browser and navigate to `http://localhost:3000` to access the AutoGPT Platform frontend.
4. After all the services are in ready state, open your browser and navigate to `http://localhost:3000` to access the AutoGPT Platform frontend.
### Docker Compose Commands
@@ -177,20 +139,21 @@ 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 Orval
- `pnpm generate:api-all`: Runs both fetch and generate commands in sequence
- `pnpm generate:api`: 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:
1. Ensure the backend services are running:
```
docker compose up -d
```
2. Generate the updated API client:
```
pnpm generate:api-all
pnpm generate:api
```
This will fetch the latest OpenAPI specification and regenerate the TypeScript client code.

52
autogpt_platform/backend/.dockerignore Normal file
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@@ -0,0 +1,52 @@
# Development and testing files
**/__pycache__
**/*.pyc
**/*.pyo
**/*.pyd
**/.Python
**/env/
**/venv/
**/.venv/
**/pip-log.txt
**/.pytest_cache/
**/test-results/
**/snapshots/
**/test/
# IDE and editor files
**/.vscode/
**/.idea/
**/*.swp
**/*.swo
*~
# OS files
.DS_Store
Thumbs.db
# Logs
**/*.log
**/logs/
# Git
.git/
.gitignore
# Documentation
**/*.md
!README.md
# Local development files
.env
.env.local
**/.env.test
# Build artifacts
**/dist/
**/build/
**/target/
# Docker files (avoid recursion)
Dockerfile*
docker-compose*
.dockerignore

223
autogpt_platform/backend/.env.example → autogpt_platform/backend/.env.default
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@@ -1,3 +1,9 @@
# Backend Configuration
# This file contains environment variables that MUST be set for the AutoGPT platform
# Variables with working defaults in settings.py are not included here
## ===== REQUIRED DATABASE CONFIGURATION ===== ##
# PostgreSQL Database Connection
DB_USER=postgres
DB_PASS=your-super-secret-and-long-postgres-password
DB_NAME=postgres
@@ -10,74 +16,50 @@ DB_SCHEMA=platform
DATABASE_URL="postgresql://${DB_USER}:${DB_PASS}@${DB_HOST}:${DB_PORT}/${DB_NAME}?schema=${DB_SCHEMA}&connect_timeout=${DB_CONNECT_TIMEOUT}"
DIRECT_URL="postgresql://${DB_USER}:${DB_PASS}@${DB_HOST}:${DB_PORT}/${DB_NAME}?schema=${DB_SCHEMA}&connect_timeout=${DB_CONNECT_TIMEOUT}"
PRISMA_SCHEMA="postgres/schema.prisma"
ENABLE_AUTH=true
# EXECUTOR
NUM_GRAPH_WORKERS=10
BACKEND_CORS_ALLOW_ORIGINS=["http://localhost:3000"]
# generate using `from cryptography.fernet import Fernet;Fernet.generate_key().decode()`
ENCRYPTION_KEY='dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw='
UNSUBSCRIBE_SECRET_KEY = 'HlP8ivStJjmbf6NKi78m_3FnOogut0t5ckzjsIqeaio='
## ===== REQUIRED SERVICE CREDENTIALS ===== ##
# Redis Configuration
REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_PASSWORD=password
ENABLE_CREDIT=false
STRIPE_API_KEY=
STRIPE_WEBHOOK_SECRET=
# RabbitMQ Credentials
RABBITMQ_DEFAULT_USER=rabbitmq_user_default
RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
# What environment things should be logged under: local dev or prod
APP_ENV=local
# What environment to behave as: "local" or "cloud"
BEHAVE_AS=local
PYRO_HOST=localhost
SENTRY_DSN=
# Email For Postmark so we can send emails
POSTMARK_SERVER_API_TOKEN=
POSTMARK_SENDER_EMAIL=invalid@invalid.com
POSTMARK_WEBHOOK_TOKEN=
## User auth with Supabase is required for any of the 3rd party integrations with auth to work.
ENABLE_AUTH=true
# Supabase Authentication
SUPABASE_URL=http://localhost:8000
SUPABASE_SERVICE_ROLE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
SUPABASE_JWT_SECRET=your-super-secret-jwt-token-with-at-least-32-characters-long
# RabbitMQ credentials -- Used for communication between services
RABBITMQ_HOST=localhost
RABBITMQ_PORT=5672
RABBITMQ_DEFAULT_USER=rabbitmq_user_default
RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
## ===== REQUIRED SECURITY KEYS ===== ##
# Generate using: from cryptography.fernet import Fernet;Fernet.generate_key().decode()
ENCRYPTION_KEY=dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=
UNSUBSCRIBE_SECRET_KEY=HlP8ivStJjmbf6NKi78m_3FnOogut0t5ckzjsIqeaio=
## GCS bucket is required for marketplace and library functionality
## ===== IMPORTANT OPTIONAL CONFIGURATION ===== ##
# Platform URLs (set these for webhooks and OAuth to work)
PLATFORM_BASE_URL=http://localhost:8000
FRONTEND_BASE_URL=http://localhost:3000
# Media Storage (required for marketplace and library functionality)
MEDIA_GCS_BUCKET_NAME=
## For local development, you may need to set FRONTEND_BASE_URL for the OAuth flow
## for integrations to work. Defaults to the value of PLATFORM_BASE_URL if not set.
# FRONTEND_BASE_URL=http://localhost:3000
## ===== API KEYS AND OAUTH CREDENTIALS ===== ##
# All API keys below are optional - only add what you need
## PLATFORM_BASE_URL must be set to a *publicly accessible* URL pointing to your backend
## to use the platform's webhook-related functionality.
## If you are developing locally, you can use something like ngrok to get a publc URL
## and tunnel it to your locally running backend.
PLATFORM_BASE_URL=http://localhost:3000
## Cloudflare Turnstile (CAPTCHA) Configuration
## Get these from the Cloudflare Turnstile dashboard: https://dash.cloudflare.com/?to=/:account/turnstile
## This is the backend secret key
TURNSTILE_SECRET_KEY=
## This is the verify URL
TURNSTILE_VERIFY_URL=https://challenges.cloudflare.com/turnstile/v0/siteverify
LAUNCH_DARKLY_SDK_KEY=
## == INTEGRATION CREDENTIALS == ##
# Each set of server side credentials is required for the corresponding 3rd party
# integration to work.
# AI/LLM Services
OPENAI_API_KEY=
ANTHROPIC_API_KEY=
GROQ_API_KEY=
LLAMA_API_KEY=
AIML_API_KEY=
V0_API_KEY=
OPEN_ROUTER_API_KEY=
NVIDIA_API_KEY=
# OAuth Credentials
# For the OAuth callback URL, use <your_frontend_url>/auth/integrations/oauth_callback,
# e.g. http://localhost:3000/auth/integrations/oauth_callback
@@ -87,7 +69,6 @@ GITHUB_CLIENT_SECRET=
# Google OAuth App server credentials - https://console.cloud.google.com/apis/credentials, and enable gmail api and set scopes
# https://console.cloud.google.com/apis/credentials/consent ?project=<your_project_id>
# You'll need to add/enable the following scopes (minimum):
# https://console.developers.google.com/apis/api/gmail.googleapis.com/overview ?project=<your_project_id>
# https://console.cloud.google.com/apis/library/sheets.googleapis.com/ ?project=<your_project_id>
@@ -123,104 +104,66 @@ LINEAR_CLIENT_SECRET=
TODOIST_CLIENT_ID=
TODOIST_CLIENT_SECRET=
## ===== OPTIONAL API KEYS ===== ##
# LLM
OPENAI_API_KEY=
ANTHROPIC_API_KEY=
AIML_API_KEY=
GROQ_API_KEY=
OPEN_ROUTER_API_KEY=
LLAMA_API_KEY=
# Reddit
# Go to https://www.reddit.com/prefs/apps and create a new app
# Choose "script" for the type
# Fill in the redirect uri as <your_frontend_url>/auth/integrations/oauth_callback, e.g. http://localhost:3000/auth/integrations/oauth_callback
NOTION_CLIENT_ID=
NOTION_CLIENT_SECRET=
REDDIT_CLIENT_ID=
REDDIT_CLIENT_SECRET=
REDDIT_USER_AGENT="AutoGPT:1.0 (by /u/autogpt)"
# Discord
DISCORD_BOT_TOKEN=
# Payment Processing
STRIPE_API_KEY=
STRIPE_WEBHOOK_SECRET=
# SMTP/Email
SMTP_SERVER=
SMTP_PORT=
SMTP_USERNAME=
SMTP_PASSWORD=
# Email Service (for sending notifications and confirmations)
POSTMARK_SERVER_API_TOKEN=
POSTMARK_SENDER_EMAIL=invalid@invalid.com
POSTMARK_WEBHOOK_TOKEN=
# D-ID
# Error Tracking
SENTRY_DSN=
# Cloudflare Turnstile (CAPTCHA) Configuration
# Get these from the Cloudflare Turnstile dashboard: https://dash.cloudflare.com/?to=/:account/turnstile
# This is the backend secret key
TURNSTILE_SECRET_KEY=
# This is the verify URL
TURNSTILE_VERIFY_URL=https://challenges.cloudflare.com/turnstile/v0/siteverify
# Feature Flags
LAUNCH_DARKLY_SDK_KEY=
# Content Generation & Media
DID_API_KEY=
FAL_API_KEY=
IDEOGRAM_API_KEY=
REPLICATE_API_KEY=
REVID_API_KEY=
SCREENSHOTONE_API_KEY=
UNREAL_SPEECH_API_KEY=
# Open Weather Map
# Data & Search Services
E2B_API_KEY=
EXA_API_KEY=
JINA_API_KEY=
MEM0_API_KEY=
OPENWEATHERMAP_API_KEY=
# SMTP
SMTP_SERVER=
SMTP_PORT=
SMTP_USERNAME=
SMTP_PASSWORD=
# Medium
MEDIUM_API_KEY=
MEDIUM_AUTHOR_ID=
# Google Maps
GOOGLE_MAPS_API_KEY=
# Replicate
REPLICATE_API_KEY=
# Communication Services
DISCORD_BOT_TOKEN=
MEDIUM_API_KEY=
MEDIUM_AUTHOR_ID=
SMTP_SERVER=
SMTP_PORT=
SMTP_USERNAME=
SMTP_PASSWORD=
# Ideogram
IDEOGRAM_API_KEY=
# Fal
FAL_API_KEY=
# Exa
EXA_API_KEY=
# E2B
E2B_API_KEY=
# Mem0
MEM0_API_KEY=
# Nvidia
NVIDIA_API_KEY=
# Apollo
# Business & Marketing Tools
APOLLO_API_KEY=
# SmartLead
SMARTLEAD_API_KEY=
# ZeroBounce
ZEROBOUNCE_API_KEY=
# Ayrshare
ENRICHLAYER_API_KEY=
AYRSHARE_API_KEY=
AYRSHARE_JWT_KEY=
SMARTLEAD_API_KEY=
ZEROBOUNCE_API_KEY=
## ===== OPTIONAL API KEYS END ===== ##
# Block Error Rate Monitoring
BLOCK_ERROR_RATE_THRESHOLD=0.5
BLOCK_ERROR_RATE_CHECK_INTERVAL_SECS=86400
# Logging Configuration
LOG_LEVEL=INFO
ENABLE_CLOUD_LOGGING=false
ENABLE_FILE_LOGGING=false
# Use to manually set the log directory
# LOG_DIR=./logs
# Example Blocks Configuration
# Set to true to enable example blocks in development
# These blocks are disabled by default in production
ENABLE_EXAMPLE_BLOCKS=false
# Cloud Storage Configuration
# Cleanup interval for expired files (hours between cleanup runs, 1-24 hours)
CLOUD_STORAGE_CLEANUP_INTERVAL_HOURS=6
# Other Services
AUTOMOD_API_KEY=

1
autogpt_platform/backend/.gitignore vendored
View File

@@ -1,3 +1,4 @@
.env
database.db
database.db-journal
dev.db

22
autogpt_platform/backend/Dockerfile
View File

@@ -8,14 +8,14 @@ WORKDIR /app
RUN echo 'Acquire::http::Pipeline-Depth 0;\nAcquire::http::No-Cache true;\nAcquire::BrokenProxy true;\n' > /etc/apt/apt.conf.d/99fixbadproxy
RUN apt-get update --allow-releaseinfo-change --fix-missing
# Install build dependencies
RUN apt-get install -y build-essential
RUN apt-get install -y libpq5
RUN apt-get install -y libz-dev
RUN apt-get install -y libssl-dev
RUN apt-get install -y postgresql-client
# Update package list and install build dependencies in a single layer
RUN apt-get update --allow-releaseinfo-change --fix-missing \
&& apt-get install -y \
build-essential \
libpq5 \
libz-dev \
libssl-dev \
postgresql-client
ENV POETRY_HOME=/opt/poetry
ENV POETRY_NO_INTERACTION=1
@@ -68,6 +68,12 @@ COPY autogpt_platform/backend/poetry.lock autogpt_platform/backend/pyproject.tom
WORKDIR /app/autogpt_platform/backend
FROM server_dependencies AS migrate
# Migration stage only needs schema and migrations - much lighter than full backend
COPY autogpt_platform/backend/schema.prisma /app/autogpt_platform/backend/
COPY autogpt_platform/backend/migrations /app/autogpt_platform/backend/migrations
FROM server_dependencies AS server
COPY autogpt_platform/backend /app/autogpt_platform/backend

408
autogpt_platform/backend/backend/blocks/enrichlayer/_api.py Normal file
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@@ -0,0 +1,408 @@
"""
API module for Enrichlayer integration.
This module provides a client for interacting with the Enrichlayer API,
which allows fetching LinkedIn profile data and related information.
"""
import datetime
import enum
import logging
from json import JSONDecodeError
from typing import Any, Optional, TypeVar
from pydantic import BaseModel, Field
from backend.data.model import APIKeyCredentials
from backend.util.request import Requests
logger = logging.getLogger(__name__)
T = TypeVar("T")
class EnrichlayerAPIException(Exception):
"""Exception raised for Enrichlayer API errors."""
def __init__(self, message: str, status_code: int):
super().__init__(message)
self.status_code = status_code
class FallbackToCache(enum.Enum):
ON_ERROR = "on-error"
NEVER = "never"
class UseCache(enum.Enum):
IF_PRESENT = "if-present"
NEVER = "never"
class SocialMediaProfiles(BaseModel):
"""Social media profiles model."""
twitter: Optional[str] = None
facebook: Optional[str] = None
github: Optional[str] = None
class Experience(BaseModel):
"""Experience model for LinkedIn profiles."""
company: Optional[str] = None
title: Optional[str] = None
description: Optional[str] = None
location: Optional[str] = None
starts_at: Optional[dict[str, int]] = None
ends_at: Optional[dict[str, int]] = None
company_linkedin_profile_url: Optional[str] = None
class Education(BaseModel):
"""Education model for LinkedIn profiles."""
school: Optional[str] = None
degree_name: Optional[str] = None
field_of_study: Optional[str] = None
starts_at: Optional[dict[str, int]] = None
ends_at: Optional[dict[str, int]] = None
school_linkedin_profile_url: Optional[str] = None
class PersonProfileResponse(BaseModel):
"""Response model for LinkedIn person profile.
This model represents the response from Enrichlayer's LinkedIn profile API.
The API returns comprehensive profile data including work experience,
education, skills, and contact information (when available).
Example API Response:
{
"public_identifier": "johnsmith",
"full_name": "John Smith",
"occupation": "Software Engineer at Tech Corp",
"experiences": [
{
"company": "Tech Corp",
"title": "Software Engineer",
"starts_at": {"year": 2020, "month": 1}
}
],
"education": [...],
"skills": ["Python", "JavaScript", ...]
}
"""
public_identifier: Optional[str] = None
profile_pic_url: Optional[str] = None
full_name: Optional[str] = None
first_name: Optional[str] = None
last_name: Optional[str] = None
occupation: Optional[str] = None
headline: Optional[str] = None
summary: Optional[str] = None
country: Optional[str] = None
country_full_name: Optional[str] = None
city: Optional[str] = None
state: Optional[str] = None
experiences: Optional[list[Experience]] = None
education: Optional[list[Education]] = None
languages: Optional[list[str]] = None
skills: Optional[list[str]] = None
inferred_salary: Optional[dict[str, Any]] = None
personal_email: Optional[str] = None
personal_contact_number: Optional[str] = None
social_media_profiles: Optional[SocialMediaProfiles] = None
extra: Optional[dict[str, Any]] = None
class SimilarProfile(BaseModel):
"""Similar profile model for LinkedIn person lookup."""
similarity: float
linkedin_profile_url: str
class PersonLookupResponse(BaseModel):
"""Response model for LinkedIn person lookup.
This model represents the response from Enrichlayer's person lookup API.
The API returns a LinkedIn profile URL and similarity scores when
searching for a person by name and company.
Example API Response:
{
"url": "https://www.linkedin.com/in/johnsmith/",
"name_similarity_score": 0.95,
"company_similarity_score": 0.88,
"title_similarity_score": 0.75,
"location_similarity_score": 0.60
}
"""
url: str | None = None
name_similarity_score: float | None
company_similarity_score: float | None
title_similarity_score: float | None
location_similarity_score: float | None
last_updated: datetime.datetime | None = None
profile: PersonProfileResponse | None = None
class RoleLookupResponse(BaseModel):
"""Response model for LinkedIn role lookup.
This model represents the response from Enrichlayer's role lookup API.
The API returns LinkedIn profile data for a specific role at a company.
Example API Response:
{
"linkedin_profile_url": "https://www.linkedin.com/in/johnsmith/",
"profile_data": {...} // Full PersonProfileResponse data when enrich_profile=True
}
"""
linkedin_profile_url: Optional[str] = None
profile_data: Optional[PersonProfileResponse] = None
class ProfilePictureResponse(BaseModel):
"""Response model for LinkedIn profile picture.
This model represents the response from Enrichlayer's profile picture API.
The API returns a URL to the person's LinkedIn profile picture.
Example API Response:
{
"tmp_profile_pic_url": "https://media.licdn.com/dms/image/..."
}
"""
tmp_profile_pic_url: str = Field(
..., description="URL of the profile picture", alias="tmp_profile_pic_url"
)
@property
def profile_picture_url(self) -> str:
"""Backward compatibility property for profile_picture_url."""
return self.tmp_profile_pic_url
class EnrichlayerClient:
"""Client for interacting with the Enrichlayer API."""
API_BASE_URL = "https://enrichlayer.com/api/v2"
def __init__(
self,
credentials: Optional[APIKeyCredentials] = None,
custom_requests: Optional[Requests] = None,
):
"""
Initialize the Enrichlayer client.
Args:
credentials: The credentials to use for authentication.
custom_requests: Custom Requests instance for testing.
"""
if custom_requests:
self._requests = custom_requests
else:
headers: dict[str, str] = {
"Content-Type": "application/json",
}
if credentials:
headers["Authorization"] = (
f"Bearer {credentials.api_key.get_secret_value()}"
)
self._requests = Requests(
extra_headers=headers,
raise_for_status=False,
)
async def _handle_response(self, response) -> Any:
"""
Handle API response and check for errors.
Args:
response: The response object from the request.
Returns:
The response data.
Raises:
EnrichlayerAPIException: If the API request fails.
"""
if not response.ok:
try:
error_data = response.json()
error_message = error_data.get("message", "")
except JSONDecodeError:
error_message = response.text
raise EnrichlayerAPIException(
f"Enrichlayer API request failed ({response.status_code}): {error_message}",
response.status_code,
)
return response.json()
async def fetch_profile(
self,
linkedin_url: str,
fallback_to_cache: FallbackToCache = FallbackToCache.ON_ERROR,
use_cache: UseCache = UseCache.IF_PRESENT,
include_skills: bool = False,
include_inferred_salary: bool = False,
include_personal_email: bool = False,
include_personal_contact_number: bool = False,
include_social_media: bool = False,
include_extra: bool = False,
) -> PersonProfileResponse:
"""
Fetch a LinkedIn profile with optional parameters.
Args:
linkedin_url: The LinkedIn profile URL to fetch.
fallback_to_cache: Cache usage if live fetch fails ('on-error' or 'never').
use_cache: Cache utilization ('if-present' or 'never').
include_skills: Whether to include skills data.
include_inferred_salary: Whether to include inferred salary data.
include_personal_email: Whether to include personal email.
include_personal_contact_number: Whether to include personal contact number.
include_social_media: Whether to include social media profiles.
include_extra: Whether to include additional data.
Returns:
The LinkedIn profile data.
Raises:
EnrichlayerAPIException: If the API request fails.
"""
params = {
"url": linkedin_url,
"fallback_to_cache": fallback_to_cache.value.lower(),
"use_cache": use_cache.value.lower(),
}
if include_skills:
params["skills"] = "include"
if include_inferred_salary:
params["inferred_salary"] = "include"
if include_personal_email:
params["personal_email"] = "include"
if include_personal_contact_number:
params["personal_contact_number"] = "include"
if include_social_media:
params["twitter_profile_id"] = "include"
params["facebook_profile_id"] = "include"
params["github_profile_id"] = "include"
if include_extra:
params["extra"] = "include"
response = await self._requests.get(
f"{self.API_BASE_URL}/profile", params=params
)
return PersonProfileResponse(**await self._handle_response(response))
async def lookup_person(
self,
first_name: str,
company_domain: str,
last_name: str | None = None,
location: Optional[str] = None,
title: Optional[str] = None,
include_similarity_checks: bool = False,
enrich_profile: bool = False,
) -> PersonLookupResponse:
"""
Look up a LinkedIn profile by person's information.
Args:
first_name: The person's first name.
last_name: The person's last name.
company_domain: The domain of the company they work for.
location: The person's location.
title: The person's job title.
include_similarity_checks: Whether to include similarity checks.
enrich_profile: Whether to enrich the profile.
Returns:
The LinkedIn profile lookup result.
Raises:
EnrichlayerAPIException: If the API request fails.
"""
params = {"first_name": first_name, "company_domain": company_domain}
if last_name:
params["last_name"] = last_name
if location:
params["location"] = location
if title:
params["title"] = title
if include_similarity_checks:
params["similarity_checks"] = "include"
if enrich_profile:
params["enrich_profile"] = "enrich"
response = await self._requests.get(
f"{self.API_BASE_URL}/profile/resolve", params=params
)
return PersonLookupResponse(**await self._handle_response(response))
async def lookup_role(
self, role: str, company_name: str, enrich_profile: bool = False
) -> RoleLookupResponse:
"""
Look up a LinkedIn profile by role in a company.
Args:
role: The role title (e.g., CEO, CTO).
company_name: The name of the company.
enrich_profile: Whether to enrich the profile.
Returns:
The LinkedIn profile lookup result.
Raises:
EnrichlayerAPIException: If the API request fails.
"""
params = {
"role": role,
"company_name": company_name,
}
if enrich_profile:
params["enrich_profile"] = "enrich"
response = await self._requests.get(
f"{self.API_BASE_URL}/find/company/role", params=params
)
return RoleLookupResponse(**await self._handle_response(response))
async def get_profile_picture(
self, linkedin_profile_url: str
) -> ProfilePictureResponse:
"""
Get a LinkedIn profile picture URL.
Args:
linkedin_profile_url: The LinkedIn profile URL.
Returns:
The profile picture URL.
Raises:
EnrichlayerAPIException: If the API request fails.
"""
params = {
"linkedin_person_profile_url": linkedin_profile_url,
}
response = await self._requests.get(
f"{self.API_BASE_URL}/person/profile-picture", params=params
)
return ProfilePictureResponse(**await self._handle_response(response))

34
autogpt_platform/backend/backend/blocks/enrichlayer/_auth.py Normal file
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@@ -0,0 +1,34 @@
"""
Authentication module for Enrichlayer API integration.
This module provides credential types and test credentials for the Enrichlayer API.
"""
from typing import Literal
from pydantic import SecretStr
from backend.data.model import APIKeyCredentials, CredentialsMetaInput
from backend.integrations.providers import ProviderName
# Define the type of credentials input expected for Enrichlayer API
EnrichlayerCredentialsInput = CredentialsMetaInput[
Literal[ProviderName.ENRICHLAYER], Literal["api_key"]
]
# Mock credentials for testing Enrichlayer API integration
TEST_CREDENTIALS = APIKeyCredentials(
id="1234a567-89bc-4def-ab12-3456cdef7890",
provider="enrichlayer",
api_key=SecretStr("mock-enrichlayer-api-key"),
title="Mock Enrichlayer API key",
expires_at=None,
)
# Dictionary representation of test credentials for input fields
TEST_CREDENTIALS_INPUT = {
"provider": TEST_CREDENTIALS.provider,
"id": TEST_CREDENTIALS.id,
"type": TEST_CREDENTIALS.type,
"title": TEST_CREDENTIALS.title,
}

527
autogpt_platform/backend/backend/blocks/enrichlayer/linkedin.py Normal file
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@@ -0,0 +1,527 @@
"""
Block definitions for Enrichlayer API integration.
This module implements blocks for interacting with the Enrichlayer API,
which provides access to LinkedIn profile data and related information.
"""
import logging
from typing import Optional
from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
from backend.data.model import APIKeyCredentials, CredentialsField, SchemaField
from backend.util.type import MediaFileType
from ._api import (
EnrichlayerClient,
Experience,
FallbackToCache,
PersonLookupResponse,
PersonProfileResponse,
RoleLookupResponse,
UseCache,
)
from ._auth import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT, EnrichlayerCredentialsInput
logger = logging.getLogger(__name__)
class GetLinkedinProfileBlock(Block):
"""Block to fetch LinkedIn profile data using Enrichlayer API."""
class Input(BlockSchema):
"""Input schema for GetLinkedinProfileBlock."""
linkedin_url: str = SchemaField(
description="LinkedIn profile URL to fetch data from",
placeholder="https://www.linkedin.com/in/username/",
)
fallback_to_cache: FallbackToCache = SchemaField(
description="Cache usage if live fetch fails",
default=FallbackToCache.ON_ERROR,
advanced=True,
)
use_cache: UseCache = SchemaField(
description="Cache utilization strategy",
default=UseCache.IF_PRESENT,
advanced=True,
)
include_skills: bool = SchemaField(
description="Include skills data",
default=False,
advanced=True,
)
include_inferred_salary: bool = SchemaField(
description="Include inferred salary data",
default=False,
advanced=True,
)
include_personal_email: bool = SchemaField(
description="Include personal email",
default=False,
advanced=True,
)
include_personal_contact_number: bool = SchemaField(
description="Include personal contact number",
default=False,
advanced=True,
)
include_social_media: bool = SchemaField(
description="Include social media profiles",
default=False,
advanced=True,
)
include_extra: bool = SchemaField(
description="Include additional data",
default=False,
advanced=True,
)
credentials: EnrichlayerCredentialsInput = CredentialsField(
description="Enrichlayer API credentials"
)
class Output(BlockSchema):
"""Output schema for GetLinkedinProfileBlock."""
profile: PersonProfileResponse = SchemaField(
description="LinkedIn profile data"
)
error: str = SchemaField(description="Error message if the request failed")
def __init__(self):
"""Initialize GetLinkedinProfileBlock."""
super().__init__(
id="f6e0ac73-4f1d-4acb-b4b7-b67066c5984e",
description="Fetch LinkedIn profile data using Enrichlayer",
categories={BlockCategory.SOCIAL},
input_schema=GetLinkedinProfileBlock.Input,
output_schema=GetLinkedinProfileBlock.Output,
test_input={
"linkedin_url": "https://www.linkedin.com/in/williamhgates/",
"include_skills": True,
"include_social_media": True,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[
(
"profile",
PersonProfileResponse(
public_identifier="williamhgates",
full_name="Bill Gates",
occupation="Co-chair at Bill & Melinda Gates Foundation",
experiences=[
Experience(
company="Bill & Melinda Gates Foundation",
title="Co-chair",
starts_at={"year": 2000},
)
],
),
)
],
test_credentials=TEST_CREDENTIALS,
test_mock={
"_fetch_profile": lambda *args, **kwargs: PersonProfileResponse(
public_identifier="williamhgates",
full_name="Bill Gates",
occupation="Co-chair at Bill & Melinda Gates Foundation",
experiences=[
Experience(
company="Bill & Melinda Gates Foundation",
title="Co-chair",
starts_at={"year": 2000},
)
],
),
},
)
@staticmethod
async def _fetch_profile(
credentials: APIKeyCredentials,
linkedin_url: str,
fallback_to_cache: FallbackToCache = FallbackToCache.ON_ERROR,
use_cache: UseCache = UseCache.IF_PRESENT,
include_skills: bool = False,
include_inferred_salary: bool = False,
include_personal_email: bool = False,
include_personal_contact_number: bool = False,
include_social_media: bool = False,
include_extra: bool = False,
):
client = EnrichlayerClient(credentials)
profile = await client.fetch_profile(
linkedin_url=linkedin_url,
fallback_to_cache=fallback_to_cache,
use_cache=use_cache,
include_skills=include_skills,
include_inferred_salary=include_inferred_salary,
include_personal_email=include_personal_email,
include_personal_contact_number=include_personal_contact_number,
include_social_media=include_social_media,
include_extra=include_extra,
)
return profile
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
"""
Run the block to fetch LinkedIn profile data.
Args:
input_data: Input parameters for the block
credentials: API key credentials for Enrichlayer
**kwargs: Additional keyword arguments
Yields:
Tuples of (output_name, output_value)
"""
try:
profile = await self._fetch_profile(
credentials=credentials,
linkedin_url=input_data.linkedin_url,
fallback_to_cache=input_data.fallback_to_cache,
use_cache=input_data.use_cache,
include_skills=input_data.include_skills,
include_inferred_salary=input_data.include_inferred_salary,
include_personal_email=input_data.include_personal_email,
include_personal_contact_number=input_data.include_personal_contact_number,
include_social_media=input_data.include_social_media,
include_extra=input_data.include_extra,
)
yield "profile", profile
except Exception as e:
logger.error(f"Error fetching LinkedIn profile: {str(e)}")
yield "error", str(e)
class LinkedinPersonLookupBlock(Block):
"""Block to look up LinkedIn profiles by person's information using Enrichlayer API."""
class Input(BlockSchema):
"""Input schema for LinkedinPersonLookupBlock."""
first_name: str = SchemaField(
description="Person's first name",
placeholder="John",
advanced=False,
)
last_name: str | None = SchemaField(
description="Person's last name",
placeholder="Doe",
default=None,
advanced=False,
)
company_domain: str = SchemaField(
description="Domain of the company they work for (optional)",
placeholder="example.com",
advanced=False,
)
location: Optional[str] = SchemaField(
description="Person's location (optional)",
placeholder="San Francisco",
default=None,
)
title: Optional[str] = SchemaField(
description="Person's job title (optional)",
placeholder="CEO",
default=None,
)
include_similarity_checks: bool = SchemaField(
description="Include similarity checks",
default=False,
advanced=True,
)
enrich_profile: bool = SchemaField(
description="Enrich the profile with additional data",
default=False,
advanced=True,
)
credentials: EnrichlayerCredentialsInput = CredentialsField(
description="Enrichlayer API credentials"
)
class Output(BlockSchema):
"""Output schema for LinkedinPersonLookupBlock."""
lookup_result: PersonLookupResponse = SchemaField(
description="LinkedIn profile lookup result"
)
error: str = SchemaField(description="Error message if the request failed")
def __init__(self):
"""Initialize LinkedinPersonLookupBlock."""
super().__init__(
id="d237a98a-5c4b-4a1c-b9e3-e6f9a6c81df7",
description="Look up LinkedIn profiles by person information using Enrichlayer",
categories={BlockCategory.SOCIAL},
input_schema=LinkedinPersonLookupBlock.Input,
output_schema=LinkedinPersonLookupBlock.Output,
test_input={
"first_name": "Bill",
"last_name": "Gates",
"company_domain": "gatesfoundation.org",
"include_similarity_checks": True,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[
(
"lookup_result",
PersonLookupResponse(
url="https://www.linkedin.com/in/williamhgates/",
name_similarity_score=0.93,
company_similarity_score=0.83,
title_similarity_score=0.3,
location_similarity_score=0.20,
),
)
],
test_credentials=TEST_CREDENTIALS,
test_mock={
"_lookup_person": lambda *args, **kwargs: PersonLookupResponse(
url="https://www.linkedin.com/in/williamhgates/",
name_similarity_score=0.93,
company_similarity_score=0.83,
title_similarity_score=0.3,
location_similarity_score=0.20,
)
},
)
@staticmethod
async def _lookup_person(
credentials: APIKeyCredentials,
first_name: str,
company_domain: str,
last_name: str | None = None,
location: Optional[str] = None,
title: Optional[str] = None,
include_similarity_checks: bool = False,
enrich_profile: bool = False,
):
client = EnrichlayerClient(credentials=credentials)
lookup_result = await client.lookup_person(
first_name=first_name,
last_name=last_name,
company_domain=company_domain,
location=location,
title=title,
include_similarity_checks=include_similarity_checks,
enrich_profile=enrich_profile,
)
return lookup_result
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
"""
Run the block to look up LinkedIn profiles.
Args:
input_data: Input parameters for the block
credentials: API key credentials for Enrichlayer
**kwargs: Additional keyword arguments
Yields:
Tuples of (output_name, output_value)
"""
try:
lookup_result = await self._lookup_person(
credentials=credentials,
first_name=input_data.first_name,
last_name=input_data.last_name,
company_domain=input_data.company_domain,
location=input_data.location,
title=input_data.title,
include_similarity_checks=input_data.include_similarity_checks,
enrich_profile=input_data.enrich_profile,
)
yield "lookup_result", lookup_result
except Exception as e:
logger.error(f"Error looking up LinkedIn profile: {str(e)}")
yield "error", str(e)
class LinkedinRoleLookupBlock(Block):
"""Block to look up LinkedIn profiles by role in a company using Enrichlayer API."""
class Input(BlockSchema):
"""Input schema for LinkedinRoleLookupBlock."""
role: str = SchemaField(
description="Role title (e.g., CEO, CTO)",
placeholder="CEO",
)
company_name: str = SchemaField(
description="Name of the company",
placeholder="Microsoft",
)
enrich_profile: bool = SchemaField(
description="Enrich the profile with additional data",
default=False,
advanced=True,
)
credentials: EnrichlayerCredentialsInput = CredentialsField(
description="Enrichlayer API credentials"
)
class Output(BlockSchema):
"""Output schema for LinkedinRoleLookupBlock."""
role_lookup_result: RoleLookupResponse = SchemaField(
description="LinkedIn role lookup result"
)
error: str = SchemaField(description="Error message if the request failed")
def __init__(self):
"""Initialize LinkedinRoleLookupBlock."""
super().__init__(
id="3b9fc742-06d4-49c7-b5ce-7e302dd7c8a7",
description="Look up LinkedIn profiles by role in a company using Enrichlayer",
categories={BlockCategory.SOCIAL},
input_schema=LinkedinRoleLookupBlock.Input,
output_schema=LinkedinRoleLookupBlock.Output,
test_input={
"role": "Co-chair",
"company_name": "Gates Foundation",
"enrich_profile": True,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[
(
"role_lookup_result",
RoleLookupResponse(
linkedin_profile_url="https://www.linkedin.com/in/williamhgates/",
),
)
],
test_credentials=TEST_CREDENTIALS,
test_mock={
"_lookup_role": lambda *args, **kwargs: RoleLookupResponse(
linkedin_profile_url="https://www.linkedin.com/in/williamhgates/",
),
},
)
@staticmethod
async def _lookup_role(
credentials: APIKeyCredentials,
role: str,
company_name: str,
enrich_profile: bool = False,
):
client = EnrichlayerClient(credentials=credentials)
role_lookup_result = await client.lookup_role(
role=role,
company_name=company_name,
enrich_profile=enrich_profile,
)
return role_lookup_result
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
"""
Run the block to look up LinkedIn profiles by role.
Args:
input_data: Input parameters for the block
credentials: API key credentials for Enrichlayer
**kwargs: Additional keyword arguments
Yields:
Tuples of (output_name, output_value)
"""
try:
role_lookup_result = await self._lookup_role(
credentials=credentials,
role=input_data.role,
company_name=input_data.company_name,
enrich_profile=input_data.enrich_profile,
)
yield "role_lookup_result", role_lookup_result
except Exception as e:
logger.error(f"Error looking up role in company: {str(e)}")
yield "error", str(e)
class GetLinkedinProfilePictureBlock(Block):
"""Block to get LinkedIn profile pictures using Enrichlayer API."""
class Input(BlockSchema):
"""Input schema for GetLinkedinProfilePictureBlock."""
linkedin_profile_url: str = SchemaField(
description="LinkedIn profile URL",
placeholder="https://www.linkedin.com/in/username/",
)
credentials: EnrichlayerCredentialsInput = CredentialsField(
description="Enrichlayer API credentials"
)
class Output(BlockSchema):
"""Output schema for GetLinkedinProfilePictureBlock."""
profile_picture_url: MediaFileType = SchemaField(
description="LinkedIn profile picture URL"
)
error: str = SchemaField(description="Error message if the request failed")
def __init__(self):
"""Initialize GetLinkedinProfilePictureBlock."""
super().__init__(
id="68d5a942-9b3f-4e9a-b7c1-d96ea4321f0d",
description="Get LinkedIn profile pictures using Enrichlayer",
categories={BlockCategory.SOCIAL},
input_schema=GetLinkedinProfilePictureBlock.Input,
output_schema=GetLinkedinProfilePictureBlock.Output,
test_input={
"linkedin_profile_url": "https://www.linkedin.com/in/williamhgates/",
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[
(
"profile_picture_url",
"https://media.licdn.com/dms/image/C4D03AQFj-xjuXrLFSQ/profile-displayphoto-shrink_800_800/0/1576881858598?e=1686787200&v=beta&t=zrQC76QwsfQQIWthfOnrKRBMZ5D-qIAvzLXLmWgYvTk",
)
],
test_credentials=TEST_CREDENTIALS,
test_mock={
"_get_profile_picture": lambda *args, **kwargs: "https://media.licdn.com/dms/image/C4D03AQFj-xjuXrLFSQ/profile-displayphoto-shrink_800_800/0/1576881858598?e=1686787200&v=beta&t=zrQC76QwsfQQIWthfOnrKRBMZ5D-qIAvzLXLmWgYvTk",
},
)
@staticmethod
async def _get_profile_picture(
credentials: APIKeyCredentials, linkedin_profile_url: str
):
client = EnrichlayerClient(credentials=credentials)
profile_picture_response = await client.get_profile_picture(
linkedin_profile_url=linkedin_profile_url,
)
return profile_picture_response.profile_picture_url
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
"""
Run the block to get LinkedIn profile pictures.
Args:
input_data: Input parameters for the block
credentials: API key credentials for Enrichlayer
**kwargs: Additional keyword arguments
Yields:
Tuples of (output_name, output_value)
"""
try:
profile_picture = await self._get_profile_picture(
credentials=credentials,
linkedin_profile_url=input_data.linkedin_profile_url,
)
yield "profile_picture_url", profile_picture
except Exception as e:
logger.error(f"Error getting profile picture: {str(e)}")
yield "error", str(e)

5
autogpt_platform/backend/backend/blocks/firecrawl/extract.py Normal file → Executable file
View File

@@ -29,8 +29,8 @@ class FirecrawlExtractBlock(Block):
prompt: str | None = SchemaField(
description="The prompt to use for the crawl", default=None, advanced=False
)
output_schema: str | None = SchemaField(
description="A more rigid structure if you already know the JSON layout.",
output_schema: dict | None = SchemaField(
description="A Json Schema describing the output structure if more rigid structure is desired.",
default=None,
)
enable_web_search: bool = SchemaField(
@@ -56,7 +56,6 @@ class FirecrawlExtractBlock(Block):
app = FirecrawlApp(api_key=credentials.api_key.get_secret_value())
# Sync call
extract_result = app.extract(
urls=input_data.urls,
prompt=input_data.prompt,

45
autogpt_platform/backend/backend/blocks/llm.py
View File

@@ -37,6 +37,7 @@ LLMProviderName = Literal[
ProviderName.OPENAI,
ProviderName.OPEN_ROUTER,
ProviderName.LLAMA_API,
ProviderName.V0,
]
AICredentials = CredentialsMetaInput[LLMProviderName, Literal["api_key"]]
@@ -155,6 +156,10 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
LLAMA_API_LLAMA4_MAVERICK = "Llama-4-Maverick-17B-128E-Instruct-FP8"
LLAMA_API_LLAMA3_3_8B = "Llama-3.3-8B-Instruct"
LLAMA_API_LLAMA3_3_70B = "Llama-3.3-70B-Instruct"
# v0 by Vercel models
V0_1_5_MD = "v0-1.5-md"
V0_1_5_LG = "v0-1.5-lg"
V0_1_0_MD = "v0-1.0-md"
@property
def metadata(self) -> ModelMetadata:
@@ -280,6 +285,10 @@ MODEL_METADATA = {
LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata("llama_api", 128000, 4028),
LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata("llama_api", 128000, 4028),
LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata("llama_api", 128000, 4028),
# v0 by Vercel models
LlmModel.V0_1_5_MD: ModelMetadata("v0", 128000, 64000),
LlmModel.V0_1_5_LG: ModelMetadata("v0", 512000, 64000),
LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000),
}
for model in LlmModel:
@@ -700,6 +709,42 @@ async def llm_call(
),
reasoning=None,
)
elif provider == "v0":
tools_param = tools if tools else openai.NOT_GIVEN
client = openai.AsyncOpenAI(
base_url="https://api.v0.dev/v1",
api_key=credentials.api_key.get_secret_value(),
)
response_format = None
if json_format:
response_format = {"type": "json_object"}
parallel_tool_calls_param = get_parallel_tool_calls_param(
llm_model, parallel_tool_calls
)
response = await client.chat.completions.create(
model=llm_model.value,
messages=prompt, # type: ignore
response_format=response_format, # type: ignore
max_tokens=max_tokens,
tools=tools_param, # type: ignore
parallel_tool_calls=parallel_tool_calls_param,
)
tool_calls = extract_openai_tool_calls(response)
reasoning = extract_openai_reasoning(response)
return LLMResponse(
raw_response=response.choices[0].message,
prompt=prompt,
response=response.choices[0].message.content or "",
tool_calls=tool_calls,
prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
completion_tokens=response.usage.completion_tokens if response.usage else 0,
reasoning=reasoning,
)
else:
raise ValueError(f"Unsupported LLM provider: {provider}")

77
autogpt_platform/backend/backend/data/block_cost_config.py
View File

@@ -5,6 +5,12 @@ from backend.blocks.ai_shortform_video_block import AIShortformVideoCreatorBlock
from backend.blocks.apollo.organization import SearchOrganizationsBlock
from backend.blocks.apollo.people import SearchPeopleBlock
from backend.blocks.apollo.person import GetPersonDetailBlock
from backend.blocks.enrichlayer.linkedin import (
GetLinkedinProfileBlock,
GetLinkedinProfilePictureBlock,
LinkedinPersonLookupBlock,
LinkedinRoleLookupBlock,
)
from backend.blocks.flux_kontext import AIImageEditorBlock, FluxKontextModelName
from backend.blocks.ideogram import IdeogramModelBlock
from backend.blocks.jina.embeddings import JinaEmbeddingBlock
@@ -30,6 +36,7 @@ from backend.integrations.credentials_store import (
anthropic_credentials,
apollo_credentials,
did_credentials,
enrichlayer_credentials,
groq_credentials,
ideogram_credentials,
jina_credentials,
@@ -39,6 +46,7 @@ from backend.integrations.credentials_store import (
replicate_credentials,
revid_credentials,
unreal_credentials,
v0_credentials,
)
# =============== Configure the cost for each LLM Model call =============== #
@@ -115,6 +123,10 @@ MODEL_COST: dict[LlmModel, int] = {
LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: 1,
LlmModel.GEMINI_2_0_FLASH_LITE: 1,
LlmModel.DEEPSEEK_R1_0528: 1,
# v0 by Vercel models
LlmModel.V0_1_5_MD: 1,
LlmModel.V0_1_5_LG: 2,
LlmModel.V0_1_0_MD: 1,
}
for model in LlmModel:
@@ -204,6 +216,23 @@ LLM_COST = (
for model, cost in MODEL_COST.items()
if MODEL_METADATA[model].provider == "llama_api"
]
# v0 by Vercel Models
+ [
BlockCost(
cost_type=BlockCostType.RUN,
cost_filter={
"model": model,
"credentials": {
"id": v0_credentials.id,
"provider": v0_credentials.provider,
"type": v0_credentials.type,
},
},
cost_amount=cost,
)
for model, cost in MODEL_COST.items()
if MODEL_METADATA[model].provider == "v0"
]
# AI/ML Api Models
+ [
BlockCost(
@@ -376,6 +405,54 @@ BLOCK_COSTS: dict[Type[Block], list[BlockCost]] = {
},
)
],
GetLinkedinProfileBlock: [
BlockCost(
cost_amount=1,
cost_filter={
"credentials": {
"id": enrichlayer_credentials.id,
"provider": enrichlayer_credentials.provider,
"type": enrichlayer_credentials.type,
}
},
)
],
LinkedinPersonLookupBlock: [
BlockCost(
cost_amount=2,
cost_filter={
"credentials": {
"id": enrichlayer_credentials.id,
"provider": enrichlayer_credentials.provider,
"type": enrichlayer_credentials.type,
}
},
)
],
LinkedinRoleLookupBlock: [
BlockCost(
cost_amount=3,
cost_filter={
"credentials": {
"id": enrichlayer_credentials.id,
"provider": enrichlayer_credentials.provider,
"type": enrichlayer_credentials.type,
}
},
)
],
GetLinkedinProfilePictureBlock: [
BlockCost(
cost_amount=3,
cost_filter={
"credentials": {
"id": enrichlayer_credentials.id,
"provider": enrichlayer_credentials.provider,
"type": enrichlayer_credentials.type,
}
},
)
],
SmartDecisionMakerBlock: LLM_COST,
SearchOrganizationsBlock: [
BlockCost(

10
autogpt_platform/backend/backend/data/credit.py
View File

@@ -34,10 +34,10 @@ from backend.data.model import (
from backend.data.notifications import NotificationEventModel, RefundRequestData
from backend.data.user import get_user_by_id, get_user_email_by_id
from backend.notifications.notifications import queue_notification_async
from backend.server.model import Pagination
from backend.server.v2.admin.model import UserHistoryResponse
from backend.util.exceptions import InsufficientBalanceError
from backend.util.json import SafeJson
from backend.util.models import Pagination
from backend.util.retry import func_retry
from backend.util.settings import Settings
@@ -286,11 +286,17 @@ class UserCreditBase(ABC):
transaction = await CreditTransaction.prisma().find_first_or_raise(
where={"transactionKey": transaction_key, "userId": user_id}
)
if transaction.isActive:
return
async with db.locked_transaction(f"usr_trx_{user_id}"):
transaction = await CreditTransaction.prisma().find_first_or_raise(
where={"transactionKey": transaction_key, "userId": user_id}
)
if transaction.isActive:
return
user_balance, _ = await self._get_credits(user_id)
await CreditTransaction.prisma().update(
where={

109
autogpt_platform/backend/backend/data/generate_data.py Normal file
View File

@@ -0,0 +1,109 @@
import logging
from collections import defaultdict
from datetime import datetime
from prisma.enums import AgentExecutionStatus
from backend.data.execution import get_graph_executions
from backend.data.graph import get_graph_metadata
from backend.data.model import UserExecutionSummaryStats
from backend.server.v2.store.exceptions import DatabaseError
from backend.util.logging import TruncatedLogger
logger = TruncatedLogger(logging.getLogger(__name__), prefix="[SummaryData]")
async def get_user_execution_summary_data(
user_id: str, start_time: datetime, end_time: datetime
) -> UserExecutionSummaryStats:
"""Gather all summary data for a user in a time range.
This function fetches graph executions once and aggregates all required
statistics in a single pass for efficiency.
"""
try:
# Fetch graph executions once
executions = await get_graph_executions(
user_id=user_id,
created_time_gte=start_time,
created_time_lte=end_time,
)
# Initialize aggregation variables
total_credits_used = 0.0
total_executions = len(executions)
successful_runs = 0
failed_runs = 0
terminated_runs = 0
execution_times = []
agent_usage = defaultdict(int)
cost_by_graph_id = defaultdict(float)
# Single pass through executions to aggregate all stats
for execution in executions:
# Count execution statuses (including TERMINATED as failed)
if execution.status == AgentExecutionStatus.COMPLETED:
successful_runs += 1
elif execution.status == AgentExecutionStatus.FAILED:
failed_runs += 1
elif execution.status == AgentExecutionStatus.TERMINATED:
terminated_runs += 1
# Aggregate costs from stats
if execution.stats and hasattr(execution.stats, "cost"):
cost_in_dollars = execution.stats.cost / 100
total_credits_used += cost_in_dollars
cost_by_graph_id[execution.graph_id] += cost_in_dollars
# Collect execution times
if execution.stats and hasattr(execution.stats, "duration"):
execution_times.append(execution.stats.duration)
# Count agent usage
agent_usage[execution.graph_id] += 1
# Calculate derived stats
total_execution_time = sum(execution_times)
average_execution_time = (
total_execution_time / len(execution_times) if execution_times else 0
)
# Find most used agent
most_used_agent = "No agents used"
if agent_usage:
most_used_agent_id = max(agent_usage, key=lambda k: agent_usage[k])
try:
graph_meta = await get_graph_metadata(graph_id=most_used_agent_id)
most_used_agent = (
graph_meta.name if graph_meta else f"Agent {most_used_agent_id[:8]}"
)
except Exception:
logger.warning(f"Could not get metadata for graph {most_used_agent_id}")
most_used_agent = f"Agent {most_used_agent_id[:8]}"
# Convert graph_ids to agent names for cost breakdown
cost_breakdown = {}
for graph_id, cost in cost_by_graph_id.items():
try:
graph_meta = await get_graph_metadata(graph_id=graph_id)
agent_name = graph_meta.name if graph_meta else f"Agent {graph_id[:8]}"
except Exception:
logger.warning(f"Could not get metadata for graph {graph_id}")
agent_name = f"Agent {graph_id[:8]}"
cost_breakdown[agent_name] = cost
# Build the summary stats object (include terminated runs as failed)
return UserExecutionSummaryStats(
total_credits_used=total_credits_used,
total_executions=total_executions,
successful_runs=successful_runs,
failed_runs=failed_runs + terminated_runs,
most_used_agent=most_used_agent,
total_execution_time=total_execution_time,
average_execution_time=average_execution_time,
cost_breakdown=cost_breakdown,
)
except Exception as e:
logger.error(f"Failed to get user summary data: {e}")
raise DatabaseError(f"Failed to get user summary data: {e}") from e

18
autogpt_platform/backend/backend/data/model.py
View File

@@ -821,3 +821,21 @@ class GraphExecutionStats(BaseModel):
activity_status: Optional[str] = Field(
default=None, description="AI-generated summary of what the agent did"
)
class UserExecutionSummaryStats(BaseModel):
"""Summary of user statistics for a specific user."""
model_config = ConfigDict(
extra="allow",
arbitrary_types_allowed=True,
)
total_credits_used: float = Field(default=0)
total_executions: int = Field(default=0)
successful_runs: int = Field(default=0)
failed_runs: int = Field(default=0)
most_used_agent: str = Field(default="")
total_execution_time: float = Field(default=0)
average_execution_time: float = Field(default=0)
cost_breakdown: dict[str, float] = Field(default_factory=dict)

10
autogpt_platform/backend/backend/executor/database.py
View File

@@ -20,6 +20,7 @@ from backend.data.execution import (
upsert_execution_input,
upsert_execution_output,
)
from backend.data.generate_data import get_user_execution_summary_data
from backend.data.graph import (
get_connected_output_nodes,
get_graph,
@@ -144,6 +145,9 @@ class DatabaseManager(AppService):
get_user_notification_oldest_message_in_batch
)
# Summary data - async
get_user_execution_summary_data = _(get_user_execution_summary_data)
class DatabaseManagerClient(AppServiceClient):
d = DatabaseManager
@@ -169,6 +173,9 @@ class DatabaseManagerClient(AppServiceClient):
spend_credits = _(d.spend_credits)
get_credits = _(d.get_credits)
# Summary data - async
get_user_execution_summary_data = _(d.get_user_execution_summary_data)
# Block error monitoring
get_block_error_stats = _(d.get_block_error_stats)
@@ -215,3 +222,6 @@ class DatabaseManagerAsyncClient(AppServiceClient):
get_user_notification_oldest_message_in_batch = (
d.get_user_notification_oldest_message_in_batch
)
# Summary data
get_user_execution_summary_data = d.get_user_execution_summary_data

3
autogpt_platform/backend/backend/executor/scheduler.py
View File

@@ -307,9 +307,10 @@ class Scheduler(AppService):
if self.register_system_tasks:
# Notification PROCESS WEEKLY SUMMARY
# Runs every Monday at 9 AM UTC
self.scheduler.add_job(
process_weekly_summary,
CronTrigger.from_crontab("0 * * * *"),
CronTrigger.from_crontab("0 9 * * 1"),
id="process_weekly_summary",
kwargs={},
replace_existing=True,

22
autogpt_platform/backend/backend/integrations/credentials_store.py
View File

@@ -182,6 +182,15 @@ zerobounce_credentials = APIKeyCredentials(
expires_at=None,
)
enrichlayer_credentials = APIKeyCredentials(
id="d9fce73a-6c1d-4e8b-ba2e-12a456789def",
provider="enrichlayer",
api_key=SecretStr(settings.secrets.enrichlayer_api_key),
title="Use Credits for Enrichlayer",
expires_at=None,
)
llama_api_credentials = APIKeyCredentials(
id="d44045af-1c33-4833-9e19-752313214de2",
provider="llama_api",
@@ -190,6 +199,14 @@ llama_api_credentials = APIKeyCredentials(
expires_at=None,
)
v0_credentials = APIKeyCredentials(
id="c4e6d1a0-3b5f-4789-a8e2-9b123456789f",
provider="v0",
api_key=SecretStr(settings.secrets.v0_api_key),
title="Use Credits for v0 by Vercel",
expires_at=None,
)
DEFAULT_CREDENTIALS = [
ollama_credentials,
revid_credentials,
@@ -203,6 +220,7 @@ DEFAULT_CREDENTIALS = [
jina_credentials,
unreal_credentials,
open_router_credentials,
enrichlayer_credentials,
fal_credentials,
exa_credentials,
e2b_credentials,
@@ -213,6 +231,8 @@ DEFAULT_CREDENTIALS = [
smartlead_credentials,
zerobounce_credentials,
google_maps_credentials,
llama_api_credentials,
v0_credentials,
]
@@ -279,6 +299,8 @@ class IntegrationCredentialsStore:
all_credentials.append(unreal_credentials)
if settings.secrets.open_router_api_key:
all_credentials.append(open_router_credentials)
if settings.secrets.enrichlayer_api_key:
all_credentials.append(enrichlayer_credentials)
if settings.secrets.fal_api_key:
all_credentials.append(fal_credentials)
if settings.secrets.exa_api_key:

2
autogpt_platform/backend/backend/integrations/providers.py
View File

@@ -25,6 +25,7 @@ class ProviderName(str, Enum):
GROQ = "groq"
HTTP = "http"
HUBSPOT = "hubspot"
ENRICHLAYER = "enrichlayer"
IDEOGRAM = "ideogram"
JINA = "jina"
LLAMA_API = "llama_api"
@@ -47,6 +48,7 @@ class ProviderName(str, Enum):
TWITTER = "twitter"
TODOIST = "todoist"
UNREAL_SPEECH = "unreal_speech"
V0 = "v0"
ZEROBOUNCE = "zerobounce"
@classmethod

168
autogpt_platform/backend/backend/notifications/notifications.py
View File

@@ -223,10 +223,14 @@ class NotificationManager(AppService):
processed_count = 0
current_time = datetime.now(tz=timezone.utc)
start_time = current_time - timedelta(days=7)
logger.info(
f"Querying for active users between {start_time} and {current_time}"
)
users = await get_database_manager_async_client().get_active_user_ids_in_timerange(
end_time=current_time.isoformat(),
start_time=start_time.isoformat(),
)
logger.info(f"Found {len(users)} active users in the last 7 days")
for user in users:
await self._queue_scheduled_notification(
SummaryParamsEventModel(
@@ -384,10 +388,13 @@ class NotificationManager(AppService):
async def _queue_scheduled_notification(self, event: SummaryParamsEventModel):
"""Queue a scheduled notification - exposed method for other services to call"""
try:
logger.debug(f"Received Request to queue scheduled notification {event=}")
logger.info(
f"Queueing scheduled notification type={event.type} user_id={event.user_id}"
)
exchange = "notifications"
routing_key = get_routing_key(event.type)
logger.info(f"Using routing key: {routing_key}")
# Publish to RabbitMQ
await self.rabbit.publish_message(
@@ -395,6 +402,7 @@ class NotificationManager(AppService):
message=event.model_dump_json(),
exchange=next(ex for ex in EXCHANGES if ex.name == exchange),
)
logger.info(f"Successfully queued notification for user {event.user_id}")
except Exception as e:
logger.exception(f"Error queueing notification: {e}")
@@ -416,85 +424,99 @@ class NotificationManager(AppService):
# only if both are true, should we email this person
return validated_email and preference
def _gather_summary_data(
async def _gather_summary_data(
self, user_id: str, event_type: NotificationType, params: BaseSummaryParams
) -> BaseSummaryData:
"""Gathers the data to build a summary notification"""
logger.info(
f"Gathering summary data for {user_id} and {event_type} wiht {params=}"
f"Gathering summary data for {user_id} and {event_type} with {params=}"
)
# total_credits_used = self.run_and_wait(
# get_total_credits_used(user_id, start_time, end_time)
# )
# total_executions = self.run_and_wait(
# get_total_executions(user_id, start_time, end_time)
# )
# most_used_agent = self.run_and_wait(
# get_most_used_agent(user_id, start_time, end_time)
# )
# execution_times = self.run_and_wait(
# get_execution_time(user_id, start_time, end_time)
# )
# runs = self.run_and_wait(
# get_runs(user_id, start_time, end_time)
# )
total_credits_used = 3.0
total_executions = 2
most_used_agent = {"name": "Some"}
execution_times = [1, 2, 3]
runs = [{"status": "COMPLETED"}, {"status": "FAILED"}]
successful_runs = len([run for run in runs if run["status"] == "COMPLETED"])
failed_runs = len([run for run in runs if run["status"] != "COMPLETED"])
average_execution_time = (
sum(execution_times) / len(execution_times) if execution_times else 0
)
# cost_breakdown = self.run_and_wait(
# get_cost_breakdown(user_id, start_time, end_time)
# )
cost_breakdown = {
"agent1": 1.0,
"agent2": 2.0,
}
if event_type == NotificationType.DAILY_SUMMARY and isinstance(
params, DailySummaryParams
):
return DailySummaryData(
total_credits_used=total_credits_used,
total_executions=total_executions,
most_used_agent=most_used_agent["name"],
total_execution_time=sum(execution_times),
successful_runs=successful_runs,
failed_runs=failed_runs,
average_execution_time=average_execution_time,
cost_breakdown=cost_breakdown,
date=params.date,
try:
# Get summary data from the database
summary_data = await get_database_manager_async_client().get_user_execution_summary_data(
user_id=user_id,
start_time=params.start_date,
end_time=params.end_date,
)
elif event_type == NotificationType.WEEKLY_SUMMARY and isinstance(
params, WeeklySummaryParams
):
return WeeklySummaryData(
total_credits_used=total_credits_used,
total_executions=total_executions,
most_used_agent=most_used_agent["name"],
total_execution_time=sum(execution_times),
successful_runs=successful_runs,
failed_runs=failed_runs,
average_execution_time=average_execution_time,
cost_breakdown=cost_breakdown,
start_date=params.start_date,
end_date=params.end_date,
)
else:
raise ValueError("Invalid event type or params")
# Extract data from summary
total_credits_used = summary_data.total_credits_used
total_executions = summary_data.total_executions
most_used_agent = summary_data.most_used_agent
successful_runs = summary_data.successful_runs
failed_runs = summary_data.failed_runs
total_execution_time = summary_data.total_execution_time
average_execution_time = summary_data.average_execution_time
cost_breakdown = summary_data.cost_breakdown
if event_type == NotificationType.DAILY_SUMMARY and isinstance(
params, DailySummaryParams
):
return DailySummaryData(
total_credits_used=total_credits_used,
total_executions=total_executions,
most_used_agent=most_used_agent,
total_execution_time=total_execution_time,
successful_runs=successful_runs,
failed_runs=failed_runs,
average_execution_time=average_execution_time,
cost_breakdown=cost_breakdown,
date=params.date,
)
elif event_type == NotificationType.WEEKLY_SUMMARY and isinstance(
params, WeeklySummaryParams
):
return WeeklySummaryData(
total_credits_used=total_credits_used,
total_executions=total_executions,
most_used_agent=most_used_agent,
total_execution_time=total_execution_time,
successful_runs=successful_runs,
failed_runs=failed_runs,
average_execution_time=average_execution_time,
cost_breakdown=cost_breakdown,
start_date=params.start_date,
end_date=params.end_date,
)
else:
raise ValueError("Invalid event type or params")
except Exception as e:
logger.error(f"Failed to gather summary data: {e}")
# Return sensible defaults in case of error
if event_type == NotificationType.DAILY_SUMMARY and isinstance(
params, DailySummaryParams
):
return DailySummaryData(
total_credits_used=0.0,
total_executions=0,
most_used_agent="No data available",
total_execution_time=0.0,
successful_runs=0,
failed_runs=0,
average_execution_time=0.0,
cost_breakdown={},
date=params.date,
)
elif event_type == NotificationType.WEEKLY_SUMMARY and isinstance(
params, WeeklySummaryParams
):
return WeeklySummaryData(
total_credits_used=0.0,
total_executions=0,
most_used_agent="No data available",
total_execution_time=0.0,
successful_runs=0,
failed_runs=0,
average_execution_time=0.0,
cost_breakdown={},
start_date=params.start_date,
end_date=params.end_date,
)
else:
raise ValueError("Invalid event type or params") from e
async def _should_batch(
self, user_id: str, event_type: NotificationType, event: NotificationEventModel
@@ -764,7 +786,7 @@ class NotificationManager(AppService):
)
return True
summary_data = self._gather_summary_data(
summary_data = await self._gather_summary_data(
event.user_id, event.type, model.data
)

67
autogpt_platform/backend/backend/notifications/templates/weekly_summary.html.jinja2
View File

@@ -5,23 +5,64 @@ data.start_date: the start date of the summary
data.end_date: the end date of the summary
data.total_credits_used: the total credits used during the summary
data.total_executions: the total number of executions during the summary
data.most_used_agent: the most used agent's nameduring the summary
data.most_used_agent: the most used agent's name during the summary
data.total_execution_time: the total execution time during the summary
data.successful_runs: the total number of successful runs during the summary
data.failed_runs: the total number of failed runs during the summary
data.average_execution_time: the average execution time during the summary
data.cost_breakdown: the cost breakdown during the summary
data.cost_breakdown: the cost breakdown during the summary (dict mapping agent names to credit amounts)
#}
<h1>Weekly Summary</h1>
<h1 style="color: #5D23BB; font-size: 32px; font-weight: 600; margin-bottom: 25px; margin-top: 0;">
Weekly Summary
</h1>
<p>Start Date: {{ data.start_date }}</p>
<p>End Date: {{ data.end_date }}</p>
<p>Total Credits Used: {{ data.total_credits_used }}</p>
<p>Total Executions: {{ data.total_executions }}</p>
<p>Most Used Agent: {{ data.most_used_agent }}</p>
<p>Total Execution Time: {{ data.total_execution_time }}</p>
<p>Successful Runs: {{ data.successful_runs }}</p>
<p>Failed Runs: {{ data.failed_runs }}</p>
<p>Average Execution Time: {{ data.average_execution_time }}</p>
<p>Cost Breakdown: {{ data.cost_breakdown }}</p>
<h2 style="color: #070629; font-size: 24px; font-weight: 500; margin-bottom: 20px;">
Your Agent Activity: {{ data.start_date.strftime('%B %-d') }} – {{ data.end_date.strftime('%B %-d') }}
</h2>
<div style="background-color: #ffffff; border-radius: 8px; padding: 20px; margin-bottom: 25px;">
<ul style="list-style-type: disc; padding-left: 20px; margin: 0;">
<li style="font-size: 16px; line-height: 1.8; margin-bottom: 8px;">
<strong>Total Executions:</strong> {{ data.total_executions }}
</li>
<li style="font-size: 16px; line-height: 1.8; margin-bottom: 8px;">
<strong>Total Credits Used:</strong> {{ data.total_credits_used|format("%.2f") }}
</li>
<li style="font-size: 16px; line-height: 1.8; margin-bottom: 8px;">
<strong>Total Execution Time:</strong> {{ data.total_execution_time|format("%.1f") }} seconds
</li>
<li style="font-size: 16px; line-height: 1.8; margin-bottom: 8px;">
<strong>Successful Runs:</strong> {{ data.successful_runs }}
</li>
<li style="font-size: 16px; line-height: 1.8; margin-bottom: 8px;">
<strong>Failed Runs:</strong> {{ data.failed_runs }}
</li>
<li style="font-size: 16px; line-height: 1.8; margin-bottom: 8px;">
<strong>Average Execution Time:</strong> {{ data.average_execution_time|format("%.1f") }} seconds
</li>
<li style="font-size: 16px; line-height: 1.8; margin-bottom: 8px;">
<strong>Most Used Agent:</strong> {{ data.most_used_agent }}
</li>
{% if data.cost_breakdown %}
<li style="font-size: 16px; line-height: 1.8; margin-bottom: 8px;">
<strong>Cost Breakdown:</strong>
<ul style="list-style-type: disc; padding-left: 40px; margin-top: 8px;">
{% for agent_name, credits in data.cost_breakdown.items() %}
<li style="font-size: 16px; line-height: 1.8; margin-bottom: 4px;">
{{ agent_name }}: {{ credits|format("%.2f") }} credits
</li>
{% endfor %}
</ul>
</li>
{% endif %}
</ul>
</div>
<p style="font-size: 16px; line-height: 165%; margin-top: 20px; margin-bottom: 10px;">
Thank you for being a part of the AutoGPT community! 🎉
</p>
<p style="font-size: 16px; line-height: 165%; margin-bottom: 0;">
Join the conversation on <a href="https://discord.gg/autogpt" style="color: #4285F4; text-decoration: underline;">Discord here</a>.
</p>

15
autogpt_platform/backend/backend/server/model.py
View File

@@ -60,21 +60,6 @@ class UpdatePermissionsRequest(pydantic.BaseModel):
permissions: list[APIKeyPermission]
class Pagination(pydantic.BaseModel):
total_items: int = pydantic.Field(
description="Total number of items.", examples=[42]
)
total_pages: int = pydantic.Field(
description="Total number of pages.", examples=[2]
)
current_page: int = pydantic.Field(
description="Current_page page number.", examples=[1]
)
page_size: int = pydantic.Field(
description="Number of items per page.", examples=[25]
)
class RequestTopUp(pydantic.BaseModel):
credit_amount: int

15
autogpt_platform/backend/backend/server/routers/v1.py
View File

@@ -458,12 +458,16 @@ async def stripe_webhook(request: Request):
event = stripe.Webhook.construct_event(
payload, sig_header, settings.secrets.stripe_webhook_secret
)
except ValueError:
except ValueError as e:
# Invalid payload
raise HTTPException(status_code=400)
except stripe.SignatureVerificationError:
raise HTTPException(
status_code=400, detail=f"Invalid payload: {str(e) or type(e).__name__}"
)
except stripe.SignatureVerificationError as e:
# Invalid signature
raise HTTPException(status_code=400)
raise HTTPException(
status_code=400, detail=f"Invalid signature: {str(e) or type(e).__name__}"
)
if (
event["type"] == "checkout.session.completed"
@@ -1067,7 +1071,6 @@ async def get_api_key(
tags=["api-keys"],
dependencies=[Depends(auth_middleware)],
)
@feature_flag("api-keys-enabled")
async def delete_api_key(
key_id: str, user_id: Annotated[str, Depends(get_user_id)]
) -> Optional[APIKeyWithoutHash]:
@@ -1096,7 +1099,6 @@ async def delete_api_key(
tags=["api-keys"],
dependencies=[Depends(auth_middleware)],
)
@feature_flag("api-keys-enabled")
async def suspend_key(
key_id: str, user_id: Annotated[str, Depends(get_user_id)]
) -> Optional[APIKeyWithoutHash]:
@@ -1122,7 +1124,6 @@ async def suspend_key(
tags=["api-keys"],
dependencies=[Depends(auth_middleware)],
)
@feature_flag("api-keys-enabled")
async def update_permissions(
key_id: str,
request: UpdatePermissionsRequest,

2
autogpt_platform/backend/backend/server/v2/admin/credit_admin_routes_test.py
View File

@@ -14,7 +14,7 @@ import backend.server.v2.admin.credit_admin_routes as credit_admin_routes
import backend.server.v2.admin.model as admin_model
from backend.data.model import UserTransaction
from backend.server.conftest import ADMIN_USER_ID, TARGET_USER_ID
from backend.server.model import Pagination
from backend.util.models import Pagination
app = fastapi.FastAPI()
app.include_router(credit_admin_routes.router)

2
autogpt_platform/backend/backend/server/v2/admin/model.py
View File

@@ -1,7 +1,7 @@
from pydantic import BaseModel
from backend.data.model import UserTransaction
from backend.server.model import Pagination
from backend.util.models import Pagination
class UserHistoryResponse(BaseModel):

6
autogpt_platform/backend/backend/server/v2/library/db.py
View File

@@ -9,7 +9,6 @@ import prisma.models
import prisma.types
import backend.data.graph as graph_db
import backend.server.model
import backend.server.v2.library.model as library_model
import backend.server.v2.store.exceptions as store_exceptions
import backend.server.v2.store.image_gen as store_image_gen
@@ -23,6 +22,7 @@ from backend.integrations.creds_manager import IntegrationCredentialsManager
from backend.integrations.webhooks.graph_lifecycle_hooks import on_graph_activate
from backend.util.exceptions import NotFoundError
from backend.util.json import SafeJson
from backend.util.models import Pagination
from backend.util.settings import Config
logger = logging.getLogger(__name__)
@@ -131,7 +131,7 @@ async def list_library_agents(
# Return the response with only valid agents
return library_model.LibraryAgentResponse(
agents=valid_library_agents,
pagination=backend.server.model.Pagination(
pagination=Pagination(
total_items=agent_count,
total_pages=(agent_count + page_size - 1) // page_size,
current_page=page,
@@ -629,7 +629,7 @@ async def list_presets(
return library_model.LibraryAgentPresetResponse(
presets=presets,
pagination=backend.server.model.Pagination(
pagination=Pagination(
total_items=total_items,
total_pages=total_pages,
current_page=page,

6
autogpt_platform/backend/backend/server/v2/library/model.py
View File

@@ -8,9 +8,9 @@ import pydantic
import backend.data.block as block_model
import backend.data.graph as graph_model
import backend.server.model as server_model
from backend.data.model import CredentialsMetaInput, is_credentials_field_name
from backend.integrations.providers import ProviderName
from backend.util.models import Pagination
class LibraryAgentStatus(str, Enum):
@@ -213,7 +213,7 @@ class LibraryAgentResponse(pydantic.BaseModel):
"""Response schema for a list of library agents and pagination info."""
agents: list[LibraryAgent]
pagination: server_model.Pagination
pagination: Pagination
class LibraryAgentPresetCreatable(pydantic.BaseModel):
@@ -317,7 +317,7 @@ class LibraryAgentPresetResponse(pydantic.BaseModel):
"""Response schema for a list of agent presets and pagination info."""
presets: list[LibraryAgentPreset]
pagination: server_model.Pagination
pagination: Pagination
class LibraryAgentFilter(str, Enum):

4
autogpt_platform/backend/backend/server/v2/library/routes_test.py
View File

@@ -7,9 +7,9 @@ import pytest
import pytest_mock
from pytest_snapshot.plugin import Snapshot
import backend.server.model as server_model
import backend.server.v2.library.model as library_model
from backend.server.v2.library.routes import router as library_router
from backend.util.models import Pagination
app = fastapi.FastAPI()
app.include_router(library_router)
@@ -77,7 +77,7 @@ async def test_get_library_agents_success(
updated_at=datetime.datetime(2023, 1, 1, 0, 0, 0),
),
],
pagination=server_model.Pagination(
pagination=Pagination(
total_items=2, total_pages=1, current_page=1, page_size=50
),
)

160
autogpt_platform/backend/backend/server/v2/store/db.py
View File

@@ -466,6 +466,8 @@ async def get_store_submissions(
# internal_comments omitted for regular users
reviewed_at=sub.reviewed_at,
changes_summary=sub.changes_summary,
video_url=sub.video_url,
categories=sub.categories,
)
submission_models.append(submission_model)
@@ -546,7 +548,7 @@ async def create_store_submission(
description: str = "",
sub_heading: str = "",
categories: list[str] = [],
changes_summary: str = "Initial Submission",
changes_summary: str | None = "Initial Submission",
) -> backend.server.v2.store.model.StoreSubmission:
"""
Create the first (and only) store listing and thus submission as a normal user
@@ -685,6 +687,160 @@ async def create_store_submission(
) from e
async def edit_store_submission(
user_id: str,
store_listing_version_id: str,
name: str,
video_url: str | None = None,
image_urls: list[str] = [],
description: str = "",
sub_heading: str = "",
categories: list[str] = [],
changes_summary: str | None = "Update submission",
) -> backend.server.v2.store.model.StoreSubmission:
"""
Edit an existing store listing submission.
Args:
user_id: ID of the authenticated user editing the submission
store_listing_version_id: ID of the store listing version to edit
agent_id: ID of the agent being submitted
agent_version: Version of the agent being submitted
slug: URL slug for the listing (only changeable for PENDING submissions)
name: Name of the agent
video_url: Optional URL to video demo
image_urls: List of image URLs for the listing
description: Description of the agent
sub_heading: Optional sub-heading for the agent
categories: List of categories for the agent
changes_summary: Summary of changes made in this submission
Returns:
StoreSubmission: The updated store submission
Raises:
SubmissionNotFoundError: If the submission is not found
UnauthorizedError: If the user doesn't own the submission
InvalidOperationError: If trying to edit a submission that can't be edited
"""
try:
# Get the current version and verify ownership
current_version = await prisma.models.StoreListingVersion.prisma().find_first(
where=prisma.types.StoreListingVersionWhereInput(
id=store_listing_version_id
),
include={
"StoreListing": {
"include": {
"Versions": {"order_by": {"version": "desc"}, "take": 1}
}
}
},
)
if not current_version:
raise backend.server.v2.store.exceptions.SubmissionNotFoundError(
f"Store listing version not found: {store_listing_version_id}"
)
# Verify the user owns this submission
if (
not current_version.StoreListing
or current_version.StoreListing.owningUserId != user_id
):
raise backend.server.v2.store.exceptions.UnauthorizedError(
f"User {user_id} does not own submission {store_listing_version_id}"
)
# Currently we are not allowing user to update the agent associated with a submission
# If we allow it in future, then we need a check here to verify the agent belongs to this user.
# Check if we can edit this submission
if current_version.submissionStatus == prisma.enums.SubmissionStatus.REJECTED:
raise backend.server.v2.store.exceptions.InvalidOperationError(
"Cannot edit a rejected submission"
)
# For APPROVED submissions, we need to create a new version
if current_version.submissionStatus == prisma.enums.SubmissionStatus.APPROVED:
# Create a new version for the existing listing
return await create_store_version(
user_id=user_id,
agent_id=current_version.agentGraphId,
agent_version=current_version.agentGraphVersion,
store_listing_id=current_version.storeListingId,
name=name,
video_url=video_url,
image_urls=image_urls,
description=description,
sub_heading=sub_heading,
categories=categories,
changes_summary=changes_summary,
)
# For PENDING submissions, we can update the existing version
elif current_version.submissionStatus == prisma.enums.SubmissionStatus.PENDING:
# Update the existing version
updated_version = await prisma.models.StoreListingVersion.prisma().update(
where={"id": store_listing_version_id},
data=prisma.types.StoreListingVersionUpdateInput(
name=name,
videoUrl=video_url,
imageUrls=image_urls,
description=description,
categories=categories,
subHeading=sub_heading,
changesSummary=changes_summary,
),
)
logger.debug(
f"Updated existing version {store_listing_version_id} for agent {current_version.agentGraphId}"
)
if not updated_version:
raise backend.server.v2.store.exceptions.DatabaseError(
"Failed to update store listing version"
)
return backend.server.v2.store.model.StoreSubmission(
agent_id=current_version.agentGraphId,
agent_version=current_version.agentGraphVersion,
name=name,
sub_heading=sub_heading,
slug=current_version.StoreListing.slug,
description=description,
image_urls=image_urls,
date_submitted=updated_version.submittedAt or updated_version.createdAt,
status=updated_version.submissionStatus,
runs=0,
rating=0.0,
store_listing_version_id=updated_version.id,
changes_summary=changes_summary,
video_url=video_url,
categories=categories,
version=updated_version.version,
)
else:
raise backend.server.v2.store.exceptions.InvalidOperationError(
f"Cannot edit submission with status: {current_version.submissionStatus}"
)
except (
backend.server.v2.store.exceptions.SubmissionNotFoundError,
backend.server.v2.store.exceptions.UnauthorizedError,
backend.server.v2.store.exceptions.AgentNotFoundError,
backend.server.v2.store.exceptions.ListingExistsError,
backend.server.v2.store.exceptions.InvalidOperationError,
):
raise
except prisma.errors.PrismaError as e:
logger.error(f"Database error editing store submission: {e}")
raise backend.server.v2.store.exceptions.DatabaseError(
"Failed to edit store submission"
) from e
async def create_store_version(
user_id: str,
agent_id: str,
@@ -696,7 +852,7 @@ async def create_store_version(
description: str = "",
sub_heading: str = "",
categories: list[str] = [],
changes_summary: str = "Update Submission",
changes_summary: str | None = "Initial submission",
) -> backend.server.v2.store.model.StoreSubmission:
"""
Create a new version for an existing store listing

12
autogpt_platform/backend/backend/server/v2/store/exceptions.py
View File

@@ -94,3 +94,15 @@ class SubmissionNotFoundError(StoreError):
"""Raised when a submission is not found"""
pass
class InvalidOperationError(StoreError):
"""Raised when an operation is not valid for the current state"""
pass
class UnauthorizedError(StoreError):
"""Raised when a user is not authorized to perform an action"""
pass

20
autogpt_platform/backend/backend/server/v2/store/model.py
View File

@@ -4,7 +4,7 @@ from typing import List
import prisma.enums
import pydantic
from backend.server.model import Pagination
from backend.util.models import Pagination
class MyAgent(pydantic.BaseModel):
@@ -115,11 +115,9 @@ class StoreSubmission(pydantic.BaseModel):
reviewed_at: datetime.datetime | None = None
changes_summary: str | None = None
reviewer_id: str | None = None
review_comments: str | None = None # External comments visible to creator
internal_comments: str | None = None # Private notes for admin use only
reviewed_at: datetime.datetime | None = None
changes_summary: str | None = None
# Additional fields for editing
video_url: str | None = None
categories: list[str] = []
class StoreSubmissionsResponse(pydantic.BaseModel):
@@ -161,6 +159,16 @@ class StoreSubmissionRequest(pydantic.BaseModel):
changes_summary: str | None = None
class StoreSubmissionEditRequest(pydantic.BaseModel):
name: str
sub_heading: str
video_url: str | None = None
image_urls: list[str] = []
description: str = ""
categories: list[str] = []
changes_summary: str | None = None
class ProfileDetails(pydantic.BaseModel):
name: str
username: str

41
autogpt_platform/backend/backend/server/v2/store/routes.py
View File

@@ -564,6 +564,47 @@ async def create_submission(
)
@router.put(
"/submissions/{store_listing_version_id}",
summary="Edit store submission",
tags=["store", "private"],
dependencies=[fastapi.Depends(autogpt_libs.auth.middleware.auth_middleware)],
response_model=backend.server.v2.store.model.StoreSubmission,
)
async def edit_submission(
store_listing_version_id: str,
submission_request: backend.server.v2.store.model.StoreSubmissionEditRequest,
user_id: typing.Annotated[
str, fastapi.Depends(autogpt_libs.auth.depends.get_user_id)
],
):
"""
Edit an existing store listing submission.
Args:
store_listing_version_id (str): ID of the store listing version to edit
submission_request (StoreSubmissionRequest): The updated submission details
user_id (str): ID of the authenticated user editing the listing
Returns:
StoreSubmission: The updated store submission
Raises:
HTTPException: If there is an error editing the submission
"""
return await backend.server.v2.store.db.edit_store_submission(
user_id=user_id,
store_listing_version_id=store_listing_version_id,
name=submission_request.name,
video_url=submission_request.video_url,
image_urls=submission_request.image_urls,
description=submission_request.description,
sub_heading=submission_request.sub_heading,
categories=submission_request.categories,
changes_summary=submission_request.changes_summary,
)
@router.post(
"/submissions/media",
summary="Upload submission media",

2
autogpt_platform/backend/backend/server/v2/store/routes_test.py
View File

@@ -551,6 +551,8 @@ def test_get_submissions_success(
agent_version=1,
sub_heading="Test agent subheading",
slug="test-agent",
video_url="test.mp4",
categories=["test-category"],
)
],
pagination=backend.server.v2.store.model.Pagination(

20
autogpt_platform/backend/backend/util/models.py Normal file
View File

@@ -0,0 +1,20 @@
"""
Shared models and types used across the backend to avoid circular imports.
"""
import pydantic
class Pagination(pydantic.BaseModel):
total_items: int = pydantic.Field(
description="Total number of items.", examples=[42]
)
total_pages: int = pydantic.Field(
description="Total number of pages.", examples=[2]
)
current_page: int = pydantic.Field(
description="Current_page page number.", examples=[1]
)
page_size: int = pydantic.Field(
description="Number of items per page.", examples=[25]
)

5
autogpt_platform/backend/backend/util/settings.py
View File

@@ -360,7 +360,7 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
description="Maximum message size limit for communication with the message bus",
)
backend_cors_allow_origins: List[str] = Field(default_factory=list)
backend_cors_allow_origins: List[str] = Field(default=["http://localhost:3000"])
@field_validator("backend_cors_allow_origins")
@classmethod
@@ -472,6 +472,7 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
groq_api_key: str = Field(default="", description="Groq API key")
open_router_api_key: str = Field(default="", description="Open Router API Key")
llama_api_key: str = Field(default="", description="Llama API Key")
v0_api_key: str = Field(default="", description="v0 by Vercel API key")
reddit_client_id: str = Field(default="", description="Reddit client ID")
reddit_client_secret: str = Field(default="", description="Reddit client secret")
@@ -521,6 +522,7 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
apollo_api_key: str = Field(default="", description="Apollo API Key")
smartlead_api_key: str = Field(default="", description="SmartLead API Key")
zerobounce_api_key: str = Field(default="", description="ZeroBounce API Key")
enrichlayer_api_key: str = Field(default="", description="Enrichlayer API Key")
# AutoMod API credentials
automod_api_key: str = Field(default="", description="AutoMod API key")
@@ -534,7 +536,6 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
ayrshare_api_key: str = Field(default="", description="Ayrshare API Key")
ayrshare_jwt_key: str = Field(default="", description="Ayrshare private Key")
# Add more secret fields as needed
model_config = SettingsConfigDict(
env_file=".env",
env_file_encoding="utf-8",

41
autogpt_platform/backend/migrations/20250805111135_add_video_url_and_categories_to_store_submission_view/migration.sql Normal file
View File

@@ -0,0 +1,41 @@
-- Drop the existing view
DROP VIEW IF EXISTS "StoreSubmission";
-- Recreate the view with the new fields
CREATE VIEW "StoreSubmission" AS
SELECT
sl.id AS listing_id,
sl."owningUserId" AS user_id,
slv."agentGraphId" AS agent_id,
slv.version AS agent_version,
sl.slug,
COALESCE(slv.name, '') AS name,
slv."subHeading" AS sub_heading,
slv.description,
slv."imageUrls" AS image_urls,
slv."submittedAt" AS date_submitted,
slv."submissionStatus" AS status,
COALESCE(ar.run_count, 0::bigint) AS runs,
COALESCE(avg(sr.score::numeric), 0.0)::double precision AS rating,
slv.id AS store_listing_version_id,
slv."reviewerId" AS reviewer_id,
slv."reviewComments" AS review_comments,
slv."internalComments" AS internal_comments,
slv."reviewedAt" AS reviewed_at,
slv."changesSummary" AS changes_summary,
-- Add the two new fields:
slv."videoUrl" AS video_url,
slv.categories
FROM "StoreListing" sl
JOIN "StoreListingVersion" slv ON slv."storeListingId" = sl.id
LEFT JOIN "StoreListingReview" sr ON sr."storeListingVersionId" = slv.id
LEFT JOIN (
SELECT "AgentGraphExecution"."agentGraphId", count(*) AS run_count
FROM "AgentGraphExecution"
GROUP BY "AgentGraphExecution"."agentGraphId"
) ar ON ar."agentGraphId" = slv."agentGraphId"
WHERE sl."isDeleted" = false
GROUP BY sl.id, sl."owningUserId", slv.id, slv."agentGraphId", slv.version, sl.slug, slv.name,
slv."subHeading", slv.description, slv."imageUrls", slv."submittedAt",
slv."submissionStatus", slv."reviewerId", slv."reviewComments", slv."internalComments",
slv."reviewedAt", slv."changesSummary", slv."videoUrl", slv.categories, ar.run_count;

2
autogpt_platform/backend/schema.prisma
View File

@@ -659,6 +659,8 @@ view StoreSubmission {
internal_comments String?
reviewed_at DateTime?
changes_summary String?
video_url String?
categories String[]
// Index or unique are not applied to views
}

6
autogpt_platform/backend/snapshots/sub_success
View File

@@ -20,7 +20,11 @@
"review_comments": null,
"internal_comments": null,
"reviewed_at": null,
"changes_summary": null
"changes_summary": null,
"video_url": "test.mp4",
"categories": [
"test-category"
]
}
],
"pagination": {

201
autogpt_platform/backend/test/e2e_test_data.py
View File

@@ -39,20 +39,20 @@ faker = Faker()
# Constants for data generation limits (reduced for E2E tests)
NUM_USERS = 10
NUM_AGENT_BLOCKS = 20
MIN_GRAPHS_PER_USER = 10
MAX_GRAPHS_PER_USER = 10
MIN_NODES_PER_GRAPH = 2
MAX_NODES_PER_GRAPH = 4
MIN_PRESETS_PER_USER = 1
MAX_PRESETS_PER_USER = 2
MIN_AGENTS_PER_USER = 10
MAX_AGENTS_PER_USER = 10
MIN_EXECUTIONS_PER_GRAPH = 1
MAX_EXECUTIONS_PER_GRAPH = 5
MIN_REVIEWS_PER_VERSION = 1
MAX_REVIEWS_PER_VERSION = 3
NUM_USERS = 15
NUM_AGENT_BLOCKS = 30
MIN_GRAPHS_PER_USER = 15
MAX_GRAPHS_PER_USER = 15
MIN_NODES_PER_GRAPH = 3
MAX_NODES_PER_GRAPH = 6
MIN_PRESETS_PER_USER = 2
MAX_PRESETS_PER_USER = 3
MIN_AGENTS_PER_USER = 15
MAX_AGENTS_PER_USER = 15
MIN_EXECUTIONS_PER_GRAPH = 2
MAX_EXECUTIONS_PER_GRAPH = 8
MIN_REVIEWS_PER_VERSION = 2
MAX_REVIEWS_PER_VERSION = 5
def get_image():
@@ -76,6 +76,23 @@ def get_video_url():
return f"https://www.youtube.com/watch?v={video_id}"
def get_category():
"""Generate a random category from the predefined list."""
categories = [
"productivity",
"writing",
"development",
"data",
"marketing",
"research",
"creative",
"business",
"personal",
"other",
]
return random.choice(categories)
class TestDataCreator:
"""Creates test data using API functions for E2E tests."""
@@ -559,24 +576,37 @@ class TestDataCreator:
submissions.append(test_submission.model_dump())
print("✅ Created special test store submission for test123@gmail.com")
# Auto-approve the test submission
# Randomly approve, reject, or leave pending the test submission
if test_submission.store_listing_version_id:
approved_submission = await review_store_submission(
store_listing_version_id=test_submission.store_listing_version_id,
is_approved=True,
external_comments="Test submission approved",
internal_comments="Auto-approved test submission",
reviewer_id=test_user["id"],
)
approved_submissions.append(approved_submission.model_dump())
print("✅ Approved test store submission")
random_value = random.random()
if random_value < 0.4: # 40% chance to approve
approved_submission = await review_store_submission(
store_listing_version_id=test_submission.store_listing_version_id,
is_approved=True,
external_comments="Test submission approved",
internal_comments="Auto-approved test submission",
reviewer_id=test_user["id"],
)
approved_submissions.append(approved_submission.model_dump())
print("✅ Approved test store submission")
# Mark test submission as featured
await prisma.storelistingversion.update(
where={"id": test_submission.store_listing_version_id},
data={"isFeatured": True},
)
print("🌟 Marked test agent as FEATURED")
# Mark approved submission as featured
await prisma.storelistingversion.update(
where={"id": test_submission.store_listing_version_id},
data={"isFeatured": True},
)
print("🌟 Marked test agent as FEATURED")
elif random_value < 0.7: # 30% chance to reject (40% to 70%)
await review_store_submission(
store_listing_version_id=test_submission.store_listing_version_id,
is_approved=False,
external_comments="Test submission rejected - needs improvements",
internal_comments="Auto-rejected test submission for E2E testing",
reviewer_id=test_user["id"],
)
print("❌ Rejected test store submission")
else: # 30% chance to leave pending (70% to 100%)
print("⏳ Left test submission pending for review")
except Exception as e:
print(f"Error creating test store submission: {e}")
@@ -617,58 +647,87 @@ class TestDataCreator:
video_url=get_video_url() if random.random() < 0.3 else None,
image_urls=[get_image() for _ in range(3)],
description=faker.text(),
categories=[faker.word() for _ in range(3)],
categories=[
get_category()
], # Single category from predefined list
changes_summary="Initial E2E test submission",
)
submissions.append(submission.model_dump())
print(f"✅ Created store submission: {submission.name}")
# Approve the submission so it appears in the store
# Randomly approve, reject, or leave pending the submission
if submission.store_listing_version_id:
try:
# Pick a random user as the reviewer (admin)
reviewer_id = random.choice(self.users)["id"]
random_value = random.random()
if random_value < 0.4: # 40% chance to approve
try:
# Pick a random user as the reviewer (admin)
reviewer_id = random.choice(self.users)["id"]
approved_submission = await review_store_submission(
store_listing_version_id=submission.store_listing_version_id,
is_approved=True,
external_comments="Auto-approved for E2E testing",
internal_comments="Automatically approved by E2E test data script",
reviewer_id=reviewer_id,
)
approved_submissions.append(
approved_submission.model_dump()
)
print(f"✅ Approved store submission: {submission.name}")
approved_submission = await review_store_submission(
store_listing_version_id=submission.store_listing_version_id,
is_approved=True,
external_comments="Auto-approved for E2E testing",
internal_comments="Automatically approved by E2E test data script",
reviewer_id=reviewer_id,
)
approved_submissions.append(
approved_submission.model_dump()
)
print(
f"✅ Approved store submission: {submission.name}"
)
# Mark some agents as featured during creation (30% chance)
# More likely for creators and first submissions
is_creator = user["id"] in [
p.get("userId") for p in self.profiles
]
feature_chance = (
0.5 if is_creator else 0.2
) # 50% for creators, 20% for others
# Mark some agents as featured during creation (30% chance)
# More likely for creators and first submissions
is_creator = user["id"] in [
p.get("userId") for p in self.profiles
]
feature_chance = (
0.5 if is_creator else 0.2
) # 50% for creators, 20% for others
if random.random() < feature_chance:
try:
await prisma.storelistingversion.update(
where={
"id": submission.store_listing_version_id
},
data={"isFeatured": True},
)
print(
f"🌟 Marked agent as FEATURED: {submission.name}"
)
except Exception as e:
print(
f"Warning: Could not mark submission as featured: {e}"
)
if random.random() < feature_chance:
try:
await prisma.storelistingversion.update(
where={
"id": submission.store_listing_version_id
},
data={"isFeatured": True},
)
print(
f"🌟 Marked agent as FEATURED: {submission.name}"
)
except Exception as e:
print(
f"Warning: Could not mark submission as featured: {e}"
)
except Exception as e:
except Exception as e:
print(
f"Warning: Could not approve submission {submission.name}: {e}"
)
elif random_value < 0.7: # 30% chance to reject (40% to 70%)
try:
# Pick a random user as the reviewer (admin)
reviewer_id = random.choice(self.users)["id"]
await review_store_submission(
store_listing_version_id=submission.store_listing_version_id,
is_approved=False,
external_comments="Submission rejected - needs improvements",
internal_comments="Automatically rejected by E2E test data script",
reviewer_id=reviewer_id,
)
print(
f"❌ Rejected store submission: {submission.name}"
)
except Exception as e:
print(
f"Warning: Could not reject submission {submission.name}: {e}"
)
else: # 30% chance to leave pending (70% to 100%)
print(
f"Warning: Could not approve submission {submission.name}: {e}"
f"⏳ Left submission pending for review: {submission.name}"
)
except Exception as e:

123
autogpt_platform/db/docker/.env.example
View File

@@ -1,123 +0,0 @@
############
# Secrets
# YOU MUST CHANGE THESE BEFORE GOING INTO PRODUCTION
############
POSTGRES_PASSWORD=your-super-secret-and-long-postgres-password
JWT_SECRET=your-super-secret-jwt-token-with-at-least-32-characters-long
ANON_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE
SERVICE_ROLE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
DASHBOARD_USERNAME=supabase
DASHBOARD_PASSWORD=this_password_is_insecure_and_should_be_updated
SECRET_KEY_BASE=UpNVntn3cDxHJpq99YMc1T1AQgQpc8kfYTuRgBiYa15BLrx8etQoXz3gZv1/u2oq
VAULT_ENC_KEY=your-encryption-key-32-chars-min
############
# Database - You can change these to any PostgreSQL database that has logical replication enabled.
############
POSTGRES_HOST=db
POSTGRES_DB=postgres
POSTGRES_PORT=5432
# default user is postgres
############
# Supavisor -- Database pooler
############
POOLER_PROXY_PORT_TRANSACTION=6543
POOLER_DEFAULT_POOL_SIZE=20
POOLER_MAX_CLIENT_CONN=100
POOLER_TENANT_ID=your-tenant-id
############
# API Proxy - Configuration for the Kong Reverse proxy.
############
KONG_HTTP_PORT=8000
KONG_HTTPS_PORT=8443
############
# API - Configuration for PostgREST.
############
PGRST_DB_SCHEMAS=public,storage,graphql_public
############
# Auth - Configuration for the GoTrue authentication server.
############
## General
SITE_URL=http://localhost:3000
ADDITIONAL_REDIRECT_URLS=
JWT_EXPIRY=3600
DISABLE_SIGNUP=false
API_EXTERNAL_URL=http://localhost:8000
## Mailer Config
MAILER_URLPATHS_CONFIRMATION="/auth/v1/verify"
MAILER_URLPATHS_INVITE="/auth/v1/verify"
MAILER_URLPATHS_RECOVERY="/auth/v1/verify"
MAILER_URLPATHS_EMAIL_CHANGE="/auth/v1/verify"
## Email auth
ENABLE_EMAIL_SIGNUP=true
ENABLE_EMAIL_AUTOCONFIRM=false
SMTP_ADMIN_EMAIL=admin@example.com
SMTP_HOST=supabase-mail
SMTP_PORT=2500
SMTP_USER=fake_mail_user
SMTP_PASS=fake_mail_password
SMTP_SENDER_NAME=fake_sender
ENABLE_ANONYMOUS_USERS=false
## Phone auth
ENABLE_PHONE_SIGNUP=true
ENABLE_PHONE_AUTOCONFIRM=true
############
# Studio - Configuration for the Dashboard
############
STUDIO_DEFAULT_ORGANIZATION=Default Organization
STUDIO_DEFAULT_PROJECT=Default Project
STUDIO_PORT=3000
# replace if you intend to use Studio outside of localhost
SUPABASE_PUBLIC_URL=http://localhost:8000
# Enable webp support
IMGPROXY_ENABLE_WEBP_DETECTION=true
# Add your OpenAI API key to enable SQL Editor Assistant
OPENAI_API_KEY=
############
# Functions - Configuration for Functions
############
# NOTE: VERIFY_JWT applies to all functions. Per-function VERIFY_JWT is not supported yet.
FUNCTIONS_VERIFY_JWT=false
############
# Logs - Configuration for Logflare
# Please refer to https://supabase.com/docs/reference/self-hosting-analytics/introduction
############
LOGFLARE_LOGGER_BACKEND_API_KEY=your-super-secret-and-long-logflare-key
# Change vector.toml sinks to reflect this change
LOGFLARE_API_KEY=your-super-secret-and-long-logflare-key
# Docker socket location - this value will differ depending on your OS
DOCKER_SOCKET_LOCATION=/var/run/docker.sock
# Google Cloud Project details
GOOGLE_PROJECT_ID=GOOGLE_PROJECT_ID
GOOGLE_PROJECT_NUMBER=GOOGLE_PROJECT_NUMBER

1
autogpt_platform/db/docker/.gitignore vendored
View File

@@ -1,5 +1,4 @@
volumes/db/data
volumes/storage
.env
test.http
docker-compose.override.yml

338
autogpt_platform/db/docker/docker-compose.yml
View File

@@ -5,8 +5,101 @@
# Destroy: docker compose -f docker-compose.yml -f ./dev/docker-compose.dev.yml down -v --remove-orphans
# Reset everything: ./reset.sh
# Environment Variable Loading Order (first → last, later overrides earlier):
# 1. ../../.env.default - Default values for all Supabase settings
# 2. ../../.env - User's custom configuration (if exists)
# 3. ./.env - Local overrides specific to db/docker (if exists)
# 4. environment key - Service-specific overrides defined below
# 5. Shell environment - Variables exported before running docker compose
name: supabase
# Common env_file configuration for all Supabase services
x-supabase-env-files: &supabase-env-files
env_file:
- ../../.env.default # Base defaults from platform root
- path: ../../.env # User overrides from platform root (optional)
required: false
- path: ./.env # Local overrides for db/docker (optional)
required: false
# Common Supabase environment - hardcoded defaults to avoid variable substitution
x-supabase-env: &supabase-env
# Core PostgreSQL settings
POSTGRES_PASSWORD: your-super-secret-and-long-postgres-password
POSTGRES_HOST: db
POSTGRES_PORT: "5432"
POSTGRES_DB: postgres
# Authentication & Security
JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
ANON_KEY: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE
SERVICE_ROLE_KEY: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
DASHBOARD_USERNAME: supabase
DASHBOARD_PASSWORD: this_password_is_insecure_and_should_be_updated
SECRET_KEY_BASE: UpNVntn3cDxHJpq99YMc1T1AQgQpc8kfYTuRgBiYa15BLrx8etQoXz3gZv1/u2oq
VAULT_ENC_KEY: your-encryption-key-32-chars-min
# URLs and Endpoints
SITE_URL: http://localhost:3000
API_EXTERNAL_URL: http://localhost:8000
SUPABASE_PUBLIC_URL: http://localhost:8000
ADDITIONAL_REDIRECT_URLS: ""
# Feature Flags
DISABLE_SIGNUP: "false"
ENABLE_EMAIL_SIGNUP: "true"
ENABLE_EMAIL_AUTOCONFIRM: "false"
ENABLE_ANONYMOUS_USERS: "false"
ENABLE_PHONE_SIGNUP: "true"
ENABLE_PHONE_AUTOCONFIRM: "true"
FUNCTIONS_VERIFY_JWT: "false"
IMGPROXY_ENABLE_WEBP_DETECTION: "true"
# Email/SMTP Configuration
SMTP_ADMIN_EMAIL: admin@example.com
SMTP_HOST: supabase-mail
SMTP_PORT: "2500"
SMTP_USER: fake_mail_user
SMTP_PASS: fake_mail_password
SMTP_SENDER_NAME: fake_sender
# Mailer URLs
MAILER_URLPATHS_CONFIRMATION: /auth/v1/verify
MAILER_URLPATHS_INVITE: /auth/v1/verify
MAILER_URLPATHS_RECOVERY: /auth/v1/verify
MAILER_URLPATHS_EMAIL_CHANGE: /auth/v1/verify
# JWT Settings
JWT_EXPIRY: "3600"
# Database Schemas
PGRST_DB_SCHEMAS: public,storage,graphql_public
# Studio Settings
STUDIO_DEFAULT_ORGANIZATION: Default Organization
STUDIO_DEFAULT_PROJECT: Default Project
# Logging
LOGFLARE_API_KEY: your-super-secret-and-long-logflare-key
# Pooler Settings
POOLER_DEFAULT_POOL_SIZE: "20"
POOLER_MAX_CLIENT_CONN: "100"
POOLER_TENANT_ID: your-tenant-id
POOLER_PROXY_PORT_TRANSACTION: "6543"
# Kong Ports
KONG_HTTP_PORT: "8000"
KONG_HTTPS_PORT: "8443"
# Docker
DOCKER_SOCKET_LOCATION: /var/run/docker.sock
# Google Cloud (if needed)
GOOGLE_PROJECT_ID: GOOGLE_PROJECT_ID
GOOGLE_PROJECT_NUMBER: GOOGLE_PROJECT_NUMBER
services:
studio:
@@ -24,24 +117,24 @@ services:
timeout: 10s
interval: 5s
retries: 3
depends_on:
analytics:
condition: service_healthy
<<: *supabase-env-files
environment:
<<: *supabase-env
# Keep any existing environment variables specific to that service
STUDIO_PG_META_URL: http://meta:8080
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
POSTGRES_PASSWORD: your-super-secret-and-long-postgres-password
DEFAULT_ORGANIZATION_NAME: ${STUDIO_DEFAULT_ORGANIZATION}
DEFAULT_PROJECT_NAME: ${STUDIO_DEFAULT_PROJECT}
OPENAI_API_KEY: ${OPENAI_API_KEY:-}
DEFAULT_ORGANIZATION_NAME: Default Organization
DEFAULT_PROJECT_NAME: Default Project
OPENAI_API_KEY: ""
SUPABASE_URL: http://kong:8000
SUPABASE_PUBLIC_URL: ${SUPABASE_PUBLIC_URL}
SUPABASE_ANON_KEY: ${ANON_KEY}
SUPABASE_SERVICE_KEY: ${SERVICE_ROLE_KEY}
AUTH_JWT_SECRET: ${JWT_SECRET}
SUPABASE_PUBLIC_URL: http://localhost:8000
SUPABASE_ANON_KEY: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE
SUPABASE_SERVICE_KEY: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
AUTH_JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
LOGFLARE_API_KEY: ${LOGFLARE_API_KEY}
LOGFLARE_API_KEY: your-super-secret-and-long-logflare-key
LOGFLARE_URL: http://analytics:4000
NEXT_PUBLIC_ENABLE_LOGS: true
# Comment to use Big Query backend for analytics
@@ -54,15 +147,15 @@ services:
image: kong:2.8.1
restart: unless-stopped
ports:
- ${KONG_HTTP_PORT}:8000/tcp
- ${KONG_HTTPS_PORT}:8443/tcp
- 8000:8000/tcp
- 8443:8443/tcp
volumes:
# https://github.com/supabase/supabase/issues/12661
- ./volumes/api/kong.yml:/home/kong/temp.yml:ro
depends_on:
analytics:
condition: service_healthy
<<: *supabase-env-files
environment:
<<: *supabase-env
# Keep any existing environment variables specific to that service
KONG_DATABASE: "off"
KONG_DECLARATIVE_CONFIG: /home/kong/kong.yml
# https://github.com/supabase/cli/issues/14
@@ -70,10 +163,10 @@ services:
KONG_PLUGINS: request-transformer,cors,key-auth,acl,basic-auth
KONG_NGINX_PROXY_PROXY_BUFFER_SIZE: 160k
KONG_NGINX_PROXY_PROXY_BUFFERS: 64 160k
SUPABASE_ANON_KEY: ${ANON_KEY}
SUPABASE_SERVICE_KEY: ${SERVICE_ROLE_KEY}
DASHBOARD_USERNAME: ${DASHBOARD_USERNAME}
DASHBOARD_PASSWORD: ${DASHBOARD_PASSWORD}
SUPABASE_ANON_KEY: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE
SUPABASE_SERVICE_KEY: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
DASHBOARD_USERNAME: supabase
DASHBOARD_PASSWORD: this_password_is_insecure_and_should_be_updated
# https://unix.stackexchange.com/a/294837
entrypoint: bash -c 'eval "echo \"$$(cat ~/temp.yml)\"" > ~/kong.yml && /docker-entrypoint.sh kong docker-start'
@@ -98,48 +191,49 @@ services:
db:
# Disable this if you are using an external Postgres database
condition: service_healthy
analytics:
condition: service_healthy
<<: *supabase-env-files
environment:
<<: *supabase-env
# Keep any existing environment variables specific to that service
GOTRUE_API_HOST: 0.0.0.0
GOTRUE_API_PORT: 9999
API_EXTERNAL_URL: ${API_EXTERNAL_URL}
API_EXTERNAL_URL: http://localhost:8000
GOTRUE_DB_DRIVER: postgres
GOTRUE_DB_DATABASE_URL: postgres://supabase_auth_admin:${POSTGRES_PASSWORD}@${POSTGRES_HOST}:${POSTGRES_PORT}/${POSTGRES_DB}
GOTRUE_DB_DATABASE_URL: postgres://supabase_auth_admin:your-super-secret-and-long-postgres-password@db:5432/postgres
GOTRUE_SITE_URL: ${SITE_URL}
GOTRUE_URI_ALLOW_LIST: ${ADDITIONAL_REDIRECT_URLS}
GOTRUE_DISABLE_SIGNUP: ${DISABLE_SIGNUP}
GOTRUE_SITE_URL: http://localhost:3000
GOTRUE_URI_ALLOW_LIST: ""
GOTRUE_DISABLE_SIGNUP: false
GOTRUE_JWT_ADMIN_ROLES: service_role
GOTRUE_JWT_AUD: authenticated
GOTRUE_JWT_DEFAULT_GROUP_NAME: authenticated
GOTRUE_JWT_EXP: ${JWT_EXPIRY}
GOTRUE_JWT_SECRET: ${JWT_SECRET}
GOTRUE_JWT_EXP: 3600
GOTRUE_JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
GOTRUE_EXTERNAL_EMAIL_ENABLED: ${ENABLE_EMAIL_SIGNUP}
GOTRUE_EXTERNAL_ANONYMOUS_USERS_ENABLED: ${ENABLE_ANONYMOUS_USERS}
GOTRUE_MAILER_AUTOCONFIRM: ${ENABLE_EMAIL_AUTOCONFIRM}
GOTRUE_EXTERNAL_EMAIL_ENABLED: true
GOTRUE_EXTERNAL_ANONYMOUS_USERS_ENABLED: false
GOTRUE_MAILER_AUTOCONFIRM: false
# Uncomment to bypass nonce check in ID Token flow. Commonly set to true when using Google Sign In on mobile.
# GOTRUE_EXTERNAL_SKIP_NONCE_CHECK: true
# GOTRUE_MAILER_SECURE_EMAIL_CHANGE_ENABLED: true
# GOTRUE_SMTP_MAX_FREQUENCY: 1s
GOTRUE_SMTP_ADMIN_EMAIL: ${SMTP_ADMIN_EMAIL}
GOTRUE_SMTP_HOST: ${SMTP_HOST}
GOTRUE_SMTP_PORT: ${SMTP_PORT}
GOTRUE_SMTP_USER: ${SMTP_USER}
GOTRUE_SMTP_PASS: ${SMTP_PASS}
GOTRUE_SMTP_SENDER_NAME: ${SMTP_SENDER_NAME}
GOTRUE_MAILER_URLPATHS_INVITE: ${MAILER_URLPATHS_INVITE}
GOTRUE_MAILER_URLPATHS_CONFIRMATION: ${MAILER_URLPATHS_CONFIRMATION}
GOTRUE_MAILER_URLPATHS_RECOVERY: ${MAILER_URLPATHS_RECOVERY}
GOTRUE_MAILER_URLPATHS_EMAIL_CHANGE: ${MAILER_URLPATHS_EMAIL_CHANGE}
GOTRUE_SMTP_ADMIN_EMAIL: admin@example.com
GOTRUE_SMTP_HOST: supabase-mail
GOTRUE_SMTP_PORT: 2500
GOTRUE_SMTP_USER: fake_mail_user
GOTRUE_SMTP_PASS: fake_mail_password
GOTRUE_SMTP_SENDER_NAME: fake_sender
GOTRUE_MAILER_URLPATHS_INVITE: /auth/v1/verify
GOTRUE_MAILER_URLPATHS_CONFIRMATION: /auth/v1/verify
GOTRUE_MAILER_URLPATHS_RECOVERY: /auth/v1/verify
GOTRUE_MAILER_URLPATHS_EMAIL_CHANGE: /auth/v1/verify
GOTRUE_EXTERNAL_PHONE_ENABLED: ${ENABLE_PHONE_SIGNUP}
GOTRUE_SMS_AUTOCONFIRM: ${ENABLE_PHONE_AUTOCONFIRM}
GOTRUE_EXTERNAL_PHONE_ENABLED: true
GOTRUE_SMS_AUTOCONFIRM: true
# Uncomment to enable custom access token hook. Please see: https://supabase.com/docs/guides/auth/auth-hooks for full list of hooks and additional details about custom_access_token_hook
# GOTRUE_HOOK_CUSTOM_ACCESS_TOKEN_ENABLED: "true"
@@ -168,16 +262,17 @@ services:
db:
# Disable this if you are using an external Postgres database
condition: service_healthy
analytics:
condition: service_healthy
<<: *supabase-env-files
environment:
PGRST_DB_URI: postgres://authenticator:${POSTGRES_PASSWORD}@${POSTGRES_HOST}:${POSTGRES_PORT}/${POSTGRES_DB}
PGRST_DB_SCHEMAS: ${PGRST_DB_SCHEMAS}
<<: *supabase-env
# Keep any existing environment variables specific to that service
PGRST_DB_URI: postgres://authenticator:your-super-secret-and-long-postgres-password@db:5432/postgres
PGRST_DB_SCHEMAS: public,storage,graphql_public
PGRST_DB_ANON_ROLE: anon
PGRST_JWT_SECRET: ${JWT_SECRET}
PGRST_JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
PGRST_DB_USE_LEGACY_GUCS: "false"
PGRST_APP_SETTINGS_JWT_SECRET: ${JWT_SECRET}
PGRST_APP_SETTINGS_JWT_EXP: ${JWT_EXPIRY}
PGRST_APP_SETTINGS_JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
PGRST_APP_SETTINGS_JWT_EXP: 3600
command:
[
"postgrest"
@@ -192,8 +287,6 @@ services:
db:
# Disable this if you are using an external Postgres database
condition: service_healthy
analytics:
condition: service_healthy
healthcheck:
test:
[
@@ -204,23 +297,26 @@ services:
"-o",
"/dev/null",
"-H",
"Authorization: Bearer ${ANON_KEY}",
"Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE",
"http://localhost:4000/api/tenants/realtime-dev/health"
]
timeout: 5s
interval: 5s
retries: 3
<<: *supabase-env-files
environment:
<<: *supabase-env
# Keep any existing environment variables specific to that service
PORT: 4000
DB_HOST: ${POSTGRES_HOST}
DB_PORT: ${POSTGRES_PORT}
DB_HOST: db
DB_PORT: 5432
DB_USER: supabase_admin
DB_PASSWORD: ${POSTGRES_PASSWORD}
DB_NAME: ${POSTGRES_DB}
DB_PASSWORD: your-super-secret-and-long-postgres-password
DB_NAME: postgres
DB_AFTER_CONNECT_QUERY: 'SET search_path TO _realtime'
DB_ENC_KEY: supabaserealtime
API_JWT_SECRET: ${JWT_SECRET}
SECRET_KEY_BASE: ${SECRET_KEY_BASE}
API_JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
SECRET_KEY_BASE: UpNVntn3cDxHJpq99YMc1T1AQgQpc8kfYTuRgBiYa15BLrx8etQoXz3gZv1/u2oq
ERL_AFLAGS: -proto_dist inet_tcp
DNS_NODES: "''"
RLIMIT_NOFILE: "10000"
@@ -256,12 +352,15 @@ services:
condition: service_started
imgproxy:
condition: service_started
<<: *supabase-env-files
environment:
ANON_KEY: ${ANON_KEY}
SERVICE_KEY: ${SERVICE_ROLE_KEY}
<<: *supabase-env
# Keep any existing environment variables specific to that service
ANON_KEY: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE
SERVICE_KEY: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
POSTGREST_URL: http://rest:3000
PGRST_JWT_SECRET: ${JWT_SECRET}
DATABASE_URL: postgres://supabase_storage_admin:${POSTGRES_PASSWORD}@${POSTGRES_HOST}:${POSTGRES_PORT}/${POSTGRES_DB}
PGRST_JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
DATABASE_URL: postgres://supabase_storage_admin:your-super-secret-and-long-postgres-password@db:5432/postgres
FILE_SIZE_LIMIT: 52428800
STORAGE_BACKEND: file
FILE_STORAGE_BACKEND_PATH: /var/lib/storage
@@ -288,11 +387,14 @@ services:
timeout: 5s
interval: 5s
retries: 3
<<: *supabase-env-files
environment:
<<: *supabase-env
# Keep any existing environment variables specific to that service
IMGPROXY_BIND: ":5001"
IMGPROXY_LOCAL_FILESYSTEM_ROOT: /
IMGPROXY_USE_ETAG: "true"
IMGPROXY_ENABLE_WEBP_DETECTION: ${IMGPROXY_ENABLE_WEBP_DETECTION}
IMGPROXY_ENABLE_WEBP_DETECTION: true
meta:
container_name: supabase-meta
@@ -302,15 +404,16 @@ services:
db:
# Disable this if you are using an external Postgres database
condition: service_healthy
analytics:
condition: service_healthy
<<: *supabase-env-files
environment:
<<: *supabase-env
# Keep any existing environment variables specific to that service
PG_META_PORT: 8080
PG_META_DB_HOST: ${POSTGRES_HOST}
PG_META_DB_PORT: ${POSTGRES_PORT}
PG_META_DB_NAME: ${POSTGRES_DB}
PG_META_DB_HOST: db
PG_META_DB_PORT: 5432
PG_META_DB_NAME: postgres
PG_META_DB_USER: supabase_admin
PG_META_DB_PASSWORD: ${POSTGRES_PASSWORD}
PG_META_DB_PASSWORD: your-super-secret-and-long-postgres-password
functions:
container_name: supabase-edge-functions
@@ -318,17 +421,17 @@ services:
restart: unless-stopped
volumes:
- ./volumes/functions:/home/deno/functions:Z
depends_on:
analytics:
condition: service_healthy
<<: *supabase-env-files
environment:
JWT_SECRET: ${JWT_SECRET}
<<: *supabase-env
# Keep any existing environment variables specific to that service
JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
SUPABASE_URL: http://kong:8000
SUPABASE_ANON_KEY: ${ANON_KEY}
SUPABASE_SERVICE_ROLE_KEY: ${SERVICE_ROLE_KEY}
SUPABASE_DB_URL: postgresql://postgres:${POSTGRES_PASSWORD}@${POSTGRES_HOST}:${POSTGRES_PORT}/${POSTGRES_DB}
SUPABASE_ANON_KEY: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE
SUPABASE_SERVICE_ROLE_KEY: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
SUPABASE_DB_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres
# TODO: Allow configuring VERIFY_JWT per function. This PR might help: https://github.com/supabase/cli/pull/786
VERIFY_JWT: "${FUNCTIONS_VERIFY_JWT}"
VERIFY_JWT: "false"
command:
[
"start",
@@ -362,26 +465,29 @@ services:
db:
# Disable this if you are using an external Postgres database
condition: service_healthy
<<: *supabase-env-files
environment:
<<: *supabase-env
# Keep any existing environment variables specific to that service
LOGFLARE_NODE_HOST: 127.0.0.1
DB_USERNAME: supabase_admin
DB_DATABASE: _supabase
DB_HOSTNAME: ${POSTGRES_HOST}
DB_PORT: ${POSTGRES_PORT}
DB_PASSWORD: ${POSTGRES_PASSWORD}
DB_HOSTNAME: db
DB_PORT: 5432
DB_PASSWORD: your-super-secret-and-long-postgres-password
DB_SCHEMA: _analytics
LOGFLARE_API_KEY: ${LOGFLARE_API_KEY}
LOGFLARE_API_KEY: your-super-secret-and-long-logflare-key
LOGFLARE_SINGLE_TENANT: true
LOGFLARE_SUPABASE_MODE: true
LOGFLARE_MIN_CLUSTER_SIZE: 1
# Comment variables to use Big Query backend for analytics
POSTGRES_BACKEND_URL: postgresql://supabase_admin:${POSTGRES_PASSWORD}@${POSTGRES_HOST}:${POSTGRES_PORT}/_supabase
POSTGRES_BACKEND_URL: postgresql://supabase_admin:your-super-secret-and-long-postgres-password@db:5432/_supabase
POSTGRES_BACKEND_SCHEMA: _analytics
LOGFLARE_FEATURE_FLAG_OVERRIDE: multibackend=true
# Uncomment to use Big Query backend for analytics
# GOOGLE_PROJECT_ID: ${GOOGLE_PROJECT_ID}
# GOOGLE_PROJECT_NUMBER: ${GOOGLE_PROJECT_NUMBER}
# GOOGLE_PROJECT_ID: GOOGLE_PROJECT_ID
# GOOGLE_PROJECT_NUMBER: GOOGLE_PROJECT_NUMBER
# Comment out everything below this point if you are using an external Postgres database
db:
@@ -419,19 +525,19 @@ services:
interval: 5s
timeout: 5s
retries: 10
depends_on:
vector:
condition: service_healthy
<<: *supabase-env-files
environment:
<<: *supabase-env
# Keep any existing environment variables specific to that service
POSTGRES_HOST: /var/run/postgresql
PGPORT: ${POSTGRES_PORT}
POSTGRES_PORT: ${POSTGRES_PORT}
PGPASSWORD: ${POSTGRES_PASSWORD}
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
PGDATABASE: ${POSTGRES_DB}
POSTGRES_DB: ${POSTGRES_DB}
JWT_SECRET: ${JWT_SECRET}
JWT_EXP: ${JWT_EXPIRY}
PGPORT: 5432
POSTGRES_PORT: 5432
PGPASSWORD: your-super-secret-and-long-postgres-password
POSTGRES_PASSWORD: your-super-secret-and-long-postgres-password
PGDATABASE: postgres
POSTGRES_DB: postgres
JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
JWT_EXP: 3600
command:
[
"postgres",
@@ -447,7 +553,7 @@ services:
restart: unless-stopped
volumes:
- ./volumes/logs/vector.yml:/etc/vector/vector.yml:ro
- ${DOCKER_SOCKET_LOCATION}:/var/run/docker.sock:ro
- /var/run/docker.sock:/var/run/docker.sock:ro
healthcheck:
test:
[
@@ -461,8 +567,11 @@ services:
timeout: 5s
interval: 5s
retries: 3
<<: *supabase-env-files
environment:
LOGFLARE_API_KEY: ${LOGFLARE_API_KEY}
<<: *supabase-env
# Keep any existing environment variables specific to that service
LOGFLARE_API_KEY: your-super-secret-and-long-logflare-key
command:
[
"--config",
@@ -475,8 +584,8 @@ services:
image: supabase/supavisor:2.4.12
restart: unless-stopped
ports:
- ${POSTGRES_PORT}:5432
- ${POOLER_PROXY_PORT_TRANSACTION}:6543
- 5432:5432
- 6543:6543
volumes:
- ./volumes/pooler/pooler.exs:/etc/pooler/pooler.exs:ro
healthcheck:
@@ -498,22 +607,25 @@ services:
condition: service_healthy
analytics:
condition: service_healthy
<<: *supabase-env-files
environment:
<<: *supabase-env
# Keep any existing environment variables specific to that service
PORT: 4000
POSTGRES_PORT: ${POSTGRES_PORT}
POSTGRES_DB: ${POSTGRES_DB}
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
DATABASE_URL: ecto://supabase_admin:${POSTGRES_PASSWORD}@db:${POSTGRES_PORT}/_supabase
POSTGRES_PORT: 5432
POSTGRES_DB: postgres
POSTGRES_PASSWORD: your-super-secret-and-long-postgres-password
DATABASE_URL: ecto://supabase_admin:your-super-secret-and-long-postgres-password@db:5432/_supabase
CLUSTER_POSTGRES: true
SECRET_KEY_BASE: ${SECRET_KEY_BASE}
VAULT_ENC_KEY: ${VAULT_ENC_KEY}
API_JWT_SECRET: ${JWT_SECRET}
METRICS_JWT_SECRET: ${JWT_SECRET}
SECRET_KEY_BASE: UpNVntn3cDxHJpq99YMc1T1AQgQpc8kfYTuRgBiYa15BLrx8etQoXz3gZv1/u2oq
VAULT_ENC_KEY: your-encryption-key-32-chars-min
API_JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
METRICS_JWT_SECRET: your-super-secret-jwt-token-with-at-least-32-characters-long
REGION: local
ERL_AFLAGS: -proto_dist inet_tcp
POOLER_TENANT_ID: ${POOLER_TENANT_ID}
POOLER_DEFAULT_POOL_SIZE: ${POOLER_DEFAULT_POOL_SIZE}
POOLER_MAX_CLIENT_CONN: ${POOLER_MAX_CLIENT_CONN}
POOLER_TENANT_ID: your-tenant-id
POOLER_DEFAULT_POOL_SIZE: 20
POOLER_MAX_CLIENT_CONN: 100
POOLER_POOL_MODE: transaction
command:
[

8
autogpt_platform/db/docker/reset.sh
View File

@@ -34,11 +34,11 @@ else
echo "No .env file found. Skipping .env removal step..."
fi
if [ -f ".env.example" ]; then
echo "Copying .env.example to .env..."
cp .env.example .env
if [ -f ".env.default" ]; then
echo "Copying .env.default to .env..."
cp .env.default .env
else
echo ".env.example file not found. Skipping .env reset step..."
echo ".env.default file not found. Skipping .env reset step..."
fi
echo "Cleanup complete!"

211
autogpt_platform/docker-compose.platform.yml
View File

@@ -1,9 +1,39 @@
# Environment Variable Loading Order (first → last, later overrides earlier):
# 1. backend/.env.default - Default values for all settings
# 2. backend/.env - User's custom configuration (if exists)
# 3. environment key - Docker-specific overrides defined below
# 4. Shell environment - Variables exported before running docker compose
# 5. CLI arguments - docker compose run -e VAR=value
# Common backend environment - Docker service names
x-backend-env:
&backend-env # Docker internal service hostnames (override localhost defaults)
PYRO_HOST: "0.0.0.0"
AGENTSERVER_HOST: rest_server
SCHEDULER_HOST: scheduler_server
DATABASEMANAGER_HOST: database_manager
EXECUTIONMANAGER_HOST: executor
NOTIFICATIONMANAGER_HOST: notification_server
CLAMAV_SERVICE_HOST: clamav
DB_HOST: db
REDIS_HOST: redis
RABBITMQ_HOST: rabbitmq
# Override Supabase URL for Docker network
SUPABASE_URL: http://kong:8000
# Common env_file configuration for backend services
x-backend-env-files: &backend-env-files
env_file:
- backend/.env.default # Base defaults (always exists)
- path: backend/.env # User overrides (optional)
required: false
services:
migrate:
build:
context: ../
dockerfile: autogpt_platform/backend/Dockerfile
target: server
target: migrate
command: ["sh", "-c", "poetry run prisma migrate deploy"]
develop:
watch:
@@ -20,10 +50,11 @@ services:
- app-network
restart: on-failure
healthcheck:
test: ["CMD", "poetry", "run", "prisma", "migrate", "status"]
interval: 10s
timeout: 5s
retries: 5
test: ["CMD-SHELL", "poetry run prisma migrate status | grep -q 'No pending migrations' || exit 1"]
interval: 30s
timeout: 10s
retries: 3
start_period: 5s
redis:
image: redis:latest
@@ -73,29 +104,12 @@ services:
condition: service_completed_successfully
rabbitmq:
condition: service_healthy
<<: *backend-env-files
environment:
- SUPABASE_URL=http://kong:8000
- SUPABASE_JWT_SECRET=your-super-secret-jwt-token-with-at-least-32-characters-long
- SUPABASE_SERVICE_ROLE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
- DATABASE_URL=postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
- DIRECT_URL=postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
- REDIS_HOST=redis
- REDIS_PORT=6379
- RABBITMQ_HOST=rabbitmq
- RABBITMQ_PORT=5672
- RABBITMQ_DEFAULT_USER=rabbitmq_user_default
- RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
- REDIS_PASSWORD=password
- ENABLE_AUTH=true
- PYRO_HOST=0.0.0.0
- SCHEDULER_HOST=scheduler_server
- EXECUTIONMANAGER_HOST=executor
- NOTIFICATIONMANAGER_HOST=notification_server
- CLAMAV_SERVICE_HOST=clamav
- NEXT_PUBLIC_FRONTEND_BASE_URL=http://localhost:3000
- BACKEND_CORS_ALLOW_ORIGINS=["http://localhost:3000"]
- ENCRYPTION_KEY=dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw= # DO NOT USE IN PRODUCTION!!
- UNSUBSCRIBE_SECRET_KEY=HlP8ivStJjmbf6NKi78m_3FnOogut0t5ckzjsIqeaio= # DO NOT USE IN PRODUCTION!!
<<: *backend-env
# Service-specific overrides
DATABASE_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
DIRECT_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
ports:
- "8006:8006"
networks:
@@ -123,26 +137,12 @@ services:
condition: service_completed_successfully
database_manager:
condition: service_started
<<: *backend-env-files
environment:
- DATABASEMANAGER_HOST=database_manager
- SUPABASE_URL=http://kong:8000
- SUPABASE_JWT_SECRET=your-super-secret-jwt-token-with-at-least-32-characters-long
- SUPABASE_SERVICE_ROLE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
- DATABASE_URL=postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
- DIRECT_URL=postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
- REDIS_HOST=redis
- REDIS_PORT=6379
- REDIS_PASSWORD=password
- RABBITMQ_HOST=rabbitmq
- RABBITMQ_PORT=5672
- RABBITMQ_DEFAULT_USER=rabbitmq_user_default
- RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
- ENABLE_AUTH=true
- PYRO_HOST=0.0.0.0
- AGENTSERVER_HOST=rest_server
- NOTIFICATIONMANAGER_HOST=notification_server
- CLAMAV_SERVICE_HOST=clamav
- ENCRYPTION_KEY=dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw= # DO NOT USE IN PRODUCTION!!
<<: *backend-env
# Service-specific overrides
DATABASE_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
DIRECT_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
ports:
- "8002:8002"
networks:
@@ -168,22 +168,12 @@ services:
condition: service_completed_successfully
database_manager:
condition: service_started
<<: *backend-env-files
environment:
- DATABASEMANAGER_HOST=database_manager
- SUPABASE_JWT_SECRET=your-super-secret-jwt-token-with-at-least-32-characters-long
- DATABASE_URL=postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
- DIRECT_URL=postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
- REDIS_HOST=redis
- REDIS_PORT=6379
- REDIS_PASSWORD=password
# - RABBITMQ_HOST=rabbitmq
# - RABBITMQ_PORT=5672
# - RABBITMQ_DEFAULT_USER=rabbitmq_user_default
# - RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
- ENABLE_AUTH=true
- PYRO_HOST=0.0.0.0
- BACKEND_CORS_ALLOW_ORIGINS=["http://localhost:3000"]
<<: *backend-env
# Service-specific overrides
DATABASE_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
DIRECT_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
ports:
- "8001:8001"
networks:
@@ -205,11 +195,12 @@ services:
condition: service_healthy
migrate:
condition: service_completed_successfully
<<: *backend-env-files
environment:
- DATABASE_URL=postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
- DIRECT_URL=postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
- PYRO_HOST=0.0.0.0
- ENCRYPTION_KEY=dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw= # DO NOT USE IN PRODUCTION!!
<<: *backend-env
# Service-specific overrides
DATABASE_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
DIRECT_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
ports:
- "8005:8005"
networks:
@@ -250,23 +241,12 @@ services:
# interval: 10s
# timeout: 10s
# retries: 5
<<: *backend-env-files
environment:
- DATABASEMANAGER_HOST=database_manager
- NOTIFICATIONMANAGER_HOST=notification_server
- SUPABASE_JWT_SECRET=your-super-secret-jwt-token-with-at-least-32-characters-long
- DATABASE_URL=postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
- DIRECT_URL=postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
- REDIS_HOST=redis
- REDIS_PORT=6379
- REDIS_PASSWORD=password
- RABBITMQ_HOST=rabbitmq
- RABBITMQ_PORT=5672
- RABBITMQ_DEFAULT_USER=rabbitmq_user_default
- RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
- ENABLE_AUTH=true
- PYRO_HOST=0.0.0.0
- BACKEND_CORS_ALLOW_ORIGINS=["http://localhost:3000"]
<<: *backend-env
# Service-specific overrides
DATABASE_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
DIRECT_URL: postgresql://postgres:your-super-secret-and-long-postgres-password@db:5432/postgres?connect_timeout=60&schema=platform
ports:
- "8003:8003"
networks:
@@ -292,52 +272,39 @@ services:
condition: service_completed_successfully
database_manager:
condition: service_started
<<: *backend-env-files
environment:
- DATABASEMANAGER_HOST=database_manager
- REDIS_HOST=redis
- REDIS_PORT=6379
- REDIS_PASSWORD=password
- RABBITMQ_HOST=rabbitmq
- RABBITMQ_PORT=5672
- RABBITMQ_DEFAULT_USER=rabbitmq_user_default
- RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
- ENABLE_AUTH=true
- PYRO_HOST=0.0.0.0
- BACKEND_CORS_ALLOW_ORIGINS=["http://localhost:3000"]
<<: *backend-env
ports:
- "8007:8007"
networks:
- app-network
# frontend:
# build:
# context: ../
# dockerfile: autogpt_platform/frontend/Dockerfile
# target: dev
# depends_on:
# db:
# condition: service_healthy
# rest_server:
# condition: service_started
# websocket_server:
# condition: service_started
# migrate:
# condition: service_completed_successfully
# environment:
# - NEXT_PUBLIC_SUPABASE_URL=http://kong:8000
# - NEXT_PUBLIC_SUPABASE_ANON_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE
# - DATABASE_URL=postgresql://agpt_user:pass123@postgres:5432/postgres?connect_timeout=60&schema=platform
# - DIRECT_URL=postgresql://agpt_user:pass123@postgres:5432/postgres?connect_timeout=60&schema=platform
# - NEXT_PUBLIC_AGPT_SERVER_URL=http://localhost:8006/api
# - NEXT_PUBLIC_AGPT_WS_SERVER_URL=ws://localhost:8001/ws
# - NEXT_PUBLIC_AGPT_MARKETPLACE_URL=http://localhost:8015/api/v1/market
# - NEXT_PUBLIC_BEHAVE_AS=LOCAL
# ports:
# - "3000:3000"
# networks:
# - app-network
frontend:
build:
context: ../
dockerfile: autogpt_platform/frontend/Dockerfile
target: prod
depends_on:
db:
condition: service_healthy
migrate:
condition: service_completed_successfully
ports:
- "3000:3000"
networks:
- app-network
# Load environment variables in order (later overrides earlier)
env_file:
- path: ./frontend/.env.default # Base defaults (always exists)
- path: ./frontend/.env # User overrides (optional)
required: false
environment:
# Server-side environment variables (Docker service names)
# These override the localhost URLs from env files when running in Docker
AUTH_CALLBACK_URL: http://rest_server:8006/auth/callback
SUPABASE_URL: http://kong:8000
AGPT_SERVER_URL: http://rest_server:8006/api
AGPT_WS_SERVER_URL: ws://websocket_server:8001/ws
networks:
app-network:
driver: bridge

100
autogpt_platform/docker-compose.yml
View File

@@ -20,6 +20,7 @@ x-supabase-services:
- app-network
- shared-network
services:
# AGPT services
migrate:
@@ -96,19 +97,13 @@ services:
timeout: 10s
retries: 3
# frontend:
# <<: *agpt-services
# extends:
# file: ./docker-compose.platform.yml
# service: frontend
# Supabase services
studio:
<<: *supabase-services
frontend:
<<: *agpt-services
extends:
file: ./db/docker/docker-compose.yml
service: studio
file: ./docker-compose.platform.yml
service: frontend
# Supabase services (minimal: auth + db + kong)
kong:
<<: *supabase-services
extends:
@@ -123,61 +118,35 @@ services:
environment:
GOTRUE_MAILER_AUTOCONFIRM: true
rest:
<<: *supabase-services
extends:
file: ./db/docker/docker-compose.yml
service: rest
realtime:
<<: *supabase-services
extends:
file: ./db/docker/docker-compose.yml
service: realtime
storage:
<<: *supabase-services
extends:
file: ./db/docker/docker-compose.yml
service: storage
imgproxy:
<<: *supabase-services
extends:
file: ./db/docker/docker-compose.yml
service: imgproxy
meta:
<<: *supabase-services
extends:
file: ./db/docker/docker-compose.yml
service: meta
functions:
<<: *supabase-services
extends:
file: ./db/docker/docker-compose.yml
service: functions
analytics:
<<: *supabase-services
extends:
file: ./db/docker/docker-compose.yml
service: analytics
db:
<<: *supabase-services
extends:
file: ./db/docker/docker-compose.yml
service: db
ports:
- ${POSTGRES_PORT}:5432 # We don't use Supavisor locally, so we expose the db directly.
- 5432:5432 # We don't use Supavisor locally, so we expose the db directly.
vector:
# Studio and its dependencies for local development only
meta:
<<: *supabase-services
profiles:
- local
extends:
file: ./db/docker/docker-compose.yml
service: vector
service: meta
studio:
<<: *supabase-services
profiles:
- local
extends:
file: ./db/docker/docker-compose.yml
service: studio
depends_on:
meta:
condition: service_healthy
# environment:
# NEXT_PUBLIC_ENABLE_LOGS: false # Disable analytics/logging features
deps:
<<: *supabase-services
@@ -186,13 +155,24 @@ services:
image: busybox
command: /bin/true
depends_on:
- studio
- kong
- auth
- meta
- analytics
- db
- vector
- studio
- redis
- rabbitmq
- clamav
- migrate
deps_backend:
<<: *agpt-services
profiles:
- local
image: busybox
command: /bin/true
depends_on:
- deps
- rest_server
- executor
- websocket_server
- database_manager

20
autogpt_platform/frontend/.env.default Normal file
View File

@@ -0,0 +1,20 @@
NEXT_PUBLIC_SUPABASE_URL=http://localhost:8000
NEXT_PUBLIC_SUPABASE_ANON_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE
NEXT_PUBLIC_AGPT_SERVER_URL=http://localhost:8006/api
NEXT_PUBLIC_AGPT_WS_SERVER_URL=ws://localhost:8001/ws
NEXT_PUBLIC_FRONTEND_BASE_URL=http://localhost:3000
NEXT_PUBLIC_APP_ENV=local
NEXT_PUBLIC_BEHAVE_AS=LOCAL
NEXT_PUBLIC_LAUNCHDARKLY_ENABLED=false
NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID=687ab1372f497809b131e06e
NEXT_PUBLIC_SHOW_BILLING_PAGE=false
NEXT_PUBLIC_TURNSTILE=disabled
NEXT_PUBLIC_REACT_QUERY_DEVTOOL=true
NEXT_PUBLIC_GA_MEASUREMENT_ID=G-FH2XK2W4GN
NEXT_PUBLIC_PW_TEST=true

44
autogpt_platform/frontend/.env.example
View File

@@ -1,44 +0,0 @@
NEXT_PUBLIC_FRONTEND_BASE_URL=http://localhost:3000
NEXT_PUBLIC_AUTH_CALLBACK_URL=http://localhost:8006/auth/callback
NEXT_PUBLIC_AGPT_SERVER_URL=http://localhost:8006/api
NEXT_PUBLIC_AGPT_WS_SERVER_URL=ws://localhost:8001/ws
NEXT_PUBLIC_AGPT_MARKETPLACE_URL=http://localhost:8015/api/v1/market
NEXT_PUBLIC_LAUNCHDARKLY_ENABLED=false
NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID=687ab1372f497809b131e06e # Local environment on Launch darkly
NEXT_PUBLIC_APP_ENV=local
NEXT_PUBLIC_AGPT_SERVER_BASE_URL=http://localhost:8006
## Locale settings
NEXT_PUBLIC_DEFAULT_LOCALE=en
NEXT_PUBLIC_LOCALES=en,es
## Supabase credentials
NEXT_PUBLIC_SUPABASE_URL=http://localhost:8000
NEXT_PUBLIC_SUPABASE_ANON_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE
## OAuth Callback URL
## This should be {domain}/auth/callback
## Only used if you're using Supabase and OAuth
AUTH_CALLBACK_URL="${NEXT_PUBLIC_FRONTEND_BASE_URL}/auth/callback"
GA_MEASUREMENT_ID=G-FH2XK2W4GN
# When running locally, set NEXT_PUBLIC_BEHAVE_AS=CLOUD to use the a locally hosted marketplace (as is typical in development, and the cloud deployment), otherwise set it to LOCAL to have the marketplace open in a new tab
NEXT_PUBLIC_BEHAVE_AS=LOCAL
NEXT_PUBLIC_SHOW_BILLING_PAGE=false
## Cloudflare Turnstile (CAPTCHA) Configuration
## Get these from the Cloudflare Turnstile dashboard: https://dash.cloudflare.com/?to=/:account/turnstile
## This is the frontend site key
NEXT_PUBLIC_CLOUDFLARE_TURNSTILE_SITE_KEY=
NEXT_PUBLIC_TURNSTILE=disabled
# Devtools
NEXT_PUBLIC_REACT_QUERY_DEVTOOL=true
# In case you are running Playwright locally
# NEXT_PUBLIC_PW_TEST=true

6
autogpt_platform/frontend/.gitignore vendored
View File

@@ -31,6 +31,7 @@ yarn.lock
package-lock.json
# local env files
.env
.env*.local
# vercel
@@ -53,4 +54,7 @@ storybook-static
*.ignore.*
*.ign.*
!.npmrc
.cursorrules
.cursorrules
# Generated API files
src/app/api/__generated__/

16
autogpt_platform/frontend/Dockerfile
View File

@@ -5,18 +5,16 @@ RUN corepack enable
COPY autogpt_platform/frontend/package.json autogpt_platform/frontend/pnpm-lock.yaml ./
RUN --mount=type=cache,target=/root/.local/share/pnpm pnpm install --frozen-lockfile
# Dev stage
FROM base AS dev
ENV NODE_ENV=development
ENV HOSTNAME=0.0.0.0
COPY autogpt_platform/frontend/ .
EXPOSE 3000
CMD ["pnpm", "run", "dev", "--hostname", "0.0.0.0"]
# Build stage for prod
FROM base AS build
COPY autogpt_platform/frontend/ .
ENV SKIP_STORYBOOK_TESTS=true
RUN if [ -f .env ]; then \
cat .env.default .env > .env.merged && mv .env.merged .env; \
else \
cp .env.default .env; \
fi
RUN pnpm run generate:api
RUN pnpm build
# Prod stage - based on NextJS reference Dockerfile https://github.com/vercel/next.js/blob/64271354533ed16da51be5dce85f0dbd15f17517/examples/with-docker/Dockerfile

63
autogpt_platform/frontend/README.md
View File

@@ -18,31 +18,58 @@ Make sure you have Node.js 16.10+ installed. Corepack is included with Node.js b
>
> Then follow the setup steps below.
### Setup
## Setup
1. **Enable corepack** (run this once on your system):
### 1. **Enable corepack** (run this once on your system):
```bash
corepack enable
```
```bash
corepack enable
```
This enables corepack to automatically manage pnpm based on the `packageManager` field in `package.json`.
This enables corepack to automatically manage pnpm based on the `packageManager` field in `package.json`.
2. **Install dependencies**:
### 2. **Install dependencies**:
```bash
pnpm i
```
```bash
pnpm i
```
3. **Start the development server**:
```bash
pnpm dev
```
### 3. **Start the development server**:
Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.
#### Running the Front-end & Back-end separately
We recommend this approach if you are doing active development on the project. First spin up the Back-end:
```bash
# on `autogpt_platform`
docker compose --profile local up deps_backend -d
# on `autogpt_platform/backend`
poetry run app
```
Then start the Front-end:
```bash
# on `autogpt_platform/frontend`
pnpm dev
```
Open [http://localhost:3000](http://localhost:3000) with your browser to see the result. If the server starts on `http://localhost:3001` it means the Front-end is already running via Docker. You have to kill the container then or do `docker compose down`.
You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file.
#### Running both the Front-end and Back-end via Docker
If you run:
```bash
# on `autogpt_platform`
docker compose up -d
```
It will spin up the Back-end and Front-end via Docker. The Front-end will start on port `3000`. This might not be
what you want when actively contributing to the Front-end as you won't have direct/easy access to the Next.js dev server.
### Subsequent Runs
For subsequent development sessions, you only need to run:
@@ -60,12 +87,12 @@ Every time a new Front-end dependency is added by you or others, you will need t
- `pnpm start` - Start production server
- `pnpm lint` - Run ESLint and Prettier checks
- `pnpm format` - Format code with Prettier
- `pnpm type-check` - Run TypeScript type checking
- `pnpm types` - Run TypeScript type checking
- `pnpm test` - Run Playwright tests
- `pnpm test-ui` - Run Playwright tests with UI
- `pnpm fetch:openapi` - Fetch OpenAPI spec from backend
- `pnpm generate:api-client` - Generate API client from OpenAPI spec
- `pnpm generate:api-all` - Fetch OpenAPI spec and generate API client
- `pnpm generate:api` - Fetch OpenAPI spec and generate API client
This project uses [`next/font`](https://nextjs.org/docs/basic-features/font-optimization) to automatically optimize and load Inter, a custom Google Font.
@@ -88,7 +115,7 @@ This project uses an auto-generated API client powered by [**Orval**](https://or
```bash
# Fetch OpenAPI spec from backend and generate client
pnpm generate:api-all
pnpm generate:api
# Only fetch the OpenAPI spec
pnpm fetch:openapi

95
autogpt_platform/frontend/package.json
View File

@@ -3,13 +3,13 @@
"version": "0.3.4",
"private": true,
"scripts": {
"dev": "next dev --turbo",
"build": "cross-env pnpm run generate:api-client && SKIP_STORYBOOK_TESTS=true next build",
"dev": "pnpm run generate:api:force && next dev --turbo",
"build": "next build",
"start": "next start",
"start:standalone": "cd .next/standalone && node server.js",
"lint": "next lint && prettier --check .",
"format": "prettier --write .",
"type-check": "tsc --noEmit",
"format": "next lint --fix; prettier --write .",
"types": "tsc --noEmit",
"test": "next build --turbo && playwright test",
"test-ui": "next build --turbo && playwright test --ui",
"test:no-build": "playwright test",
@@ -18,44 +18,43 @@
"build-storybook": "storybook build",
"test-storybook": "test-storybook",
"test-storybook:ci": "concurrently -k -s first -n \"SB,TEST\" -c \"magenta,blue\" \"pnpm run build-storybook -- --quiet && npx http-server storybook-static --port 6006 --silent\" \"wait-on tcp:6006 && pnpm run test-storybook\"",
"fetch:openapi": "curl http://localhost:8006/openapi.json > ./src/app/api/openapi.json && prettier --write ./src/app/api/openapi.json",
"generate:api-client": "orval --config ./orval.config.ts",
"generate:api-all": "pnpm run fetch:openapi && pnpm run generate:api-client"
"generate:api": "npx --yes tsx ./scripts/generate-api-queries.ts && orval --config ./orval.config.ts",
"generate:api:force": "npx --yes tsx ./scripts/generate-api-queries.ts --force && orval --config ./orval.config.ts"
},
"browserslist": [
"defaults"
],
"dependencies": {
"@faker-js/faker": "9.9.0",
"@hookform/resolvers": "5.2.0",
"@next/third-parties": "15.4.4",
"@hookform/resolvers": "5.2.1",
"@next/third-parties": "15.4.6",
"@phosphor-icons/react": "2.1.10",
"@radix-ui/react-alert-dialog": "1.1.14",
"@radix-ui/react-alert-dialog": "1.1.15",
"@radix-ui/react-avatar": "1.1.10",
"@radix-ui/react-checkbox": "1.3.2",
"@radix-ui/react-collapsible": "1.1.11",
"@radix-ui/react-context-menu": "2.2.15",
"@radix-ui/react-dialog": "1.1.14",
"@radix-ui/react-dropdown-menu": "2.1.15",
"@radix-ui/react-checkbox": "1.3.3",
"@radix-ui/react-collapsible": "1.1.12",
"@radix-ui/react-context-menu": "2.2.16",
"@radix-ui/react-dialog": "1.1.15",
"@radix-ui/react-dropdown-menu": "2.1.16",
"@radix-ui/react-icons": "1.3.2",
"@radix-ui/react-label": "2.1.7",
"@radix-ui/react-popover": "1.1.14",
"@radix-ui/react-radio-group": "1.3.7",
"@radix-ui/react-scroll-area": "1.2.9",
"@radix-ui/react-select": "2.2.5",
"@radix-ui/react-popover": "1.1.15",
"@radix-ui/react-radio-group": "1.3.8",
"@radix-ui/react-scroll-area": "1.2.10",
"@radix-ui/react-select": "2.2.6",
"@radix-ui/react-separator": "1.1.7",
"@radix-ui/react-slot": "1.2.3",
"@radix-ui/react-switch": "1.2.5",
"@radix-ui/react-tabs": "1.1.12",
"@radix-ui/react-toast": "1.2.14",
"@radix-ui/react-tooltip": "1.2.7",
"@radix-ui/react-switch": "1.2.6",
"@radix-ui/react-tabs": "1.1.13",
"@radix-ui/react-toast": "1.2.15",
"@radix-ui/react-tooltip": "1.2.8",
"@sentry/nextjs": "9.42.0",
"@supabase/ssr": "0.6.1",
"@supabase/supabase-js": "2.52.1",
"@tanstack/react-query": "5.83.0",
"@supabase/supabase-js": "2.55.0",
"@tanstack/react-query": "5.85.3",
"@tanstack/react-table": "8.21.3",
"@types/jaro-winkler": "0.2.4",
"@xyflow/react": "12.8.2",
"@xyflow/react": "12.8.3",
"boring-avatars": "1.11.2",
"class-variance-authority": "0.7.1",
"clsx": "2.1.1",
@@ -65,22 +64,22 @@
"dotenv": "17.2.1",
"elliptic": "6.6.1",
"embla-carousel-react": "8.6.0",
"framer-motion": "12.23.9",
"framer-motion": "12.23.12",
"geist": "1.4.2",
"jaro-winkler": "0.2.8",
"launchdarkly-react-client-sdk": "3.8.1",
"lodash": "4.17.21",
"lucide-react": "0.525.0",
"lucide-react": "0.539.0",
"moment": "2.30.1",
"next": "15.4.4",
"next": "15.4.6",
"next-themes": "0.4.6",
"nuqs": "2.4.3",
"party-js": "2.2.0",
"react": "18.3.1",
"react-day-picker": "9.8.0",
"react-day-picker": "9.8.1",
"react-dom": "18.3.1",
"react-drag-drop-files": "2.4.0",
"react-hook-form": "7.61.1",
"react-hook-form": "7.62.0",
"react-icons": "5.5.0",
"react-markdown": "9.0.3",
"react-modal": "3.16.3",
@@ -88,7 +87,7 @@
"react-window": "1.8.11",
"recharts": "2.15.3",
"shepherd.js": "14.5.1",
"sonner": "2.0.6",
"sonner": "2.0.7",
"tailwind-merge": "2.6.0",
"tailwindcss-animate": "1.0.7",
"uuid": "11.1.0",
@@ -96,42 +95,42 @@
"zod": "3.25.76"
},
"devDependencies": {
"@chromatic-com/storybook": "4.0.1",
"@playwright/test": "1.54.1",
"@storybook/addon-a11y": "9.0.17",
"@storybook/addon-docs": "9.0.17",
"@storybook/addon-links": "9.0.17",
"@storybook/addon-onboarding": "9.0.17",
"@storybook/nextjs": "9.0.17",
"@tanstack/eslint-plugin-query": "5.81.2",
"@tanstack/react-query-devtools": "5.83.0",
"@chromatic-com/storybook": "4.1.0",
"@playwright/test": "1.54.2",
"@storybook/addon-a11y": "9.1.2",
"@storybook/addon-docs": "9.1.2",
"@storybook/addon-links": "9.1.2",
"@storybook/addon-onboarding": "9.1.2",
"@storybook/nextjs": "9.1.2",
"@tanstack/eslint-plugin-query": "5.83.1",
"@tanstack/react-query-devtools": "5.84.2",
"@types/canvas-confetti": "1.9.0",
"@types/lodash": "4.17.20",
"@types/negotiator": "0.6.4",
"@types/node": "24.0.15",
"@types/node": "24.2.1",
"@types/react": "18.3.17",
"@types/react-dom": "18.3.5",
"@types/react-modal": "3.16.3",
"@types/react-window": "1.8.8",
"axe-playwright": "2.1.0",
"chromatic": "13.1.2",
"chromatic": "13.1.3",
"concurrently": "9.2.0",
"cross-env": "7.0.3",
"eslint": "8.57.1",
"eslint-config-next": "15.4.2",
"eslint-plugin-storybook": "9.0.17",
"eslint-config-next": "15.4.6",
"eslint-plugin-storybook": "9.1.2",
"import-in-the-middle": "1.14.2",
"msw": "2.10.4",
"msw-storybook-addon": "2.0.5",
"orval": "7.10.0",
"orval": "7.11.2",
"pbkdf2": "3.1.3",
"postcss": "8.5.6",
"prettier": "3.6.2",
"prettier-plugin-tailwindcss": "0.6.14",
"require-in-the-middle": "7.5.2",
"storybook": "9.0.17",
"storybook": "9.1.2",
"tailwindcss": "3.4.17",
"typescript": "5.8.3"
"typescript": "5.9.2"
},
"msw": {
"workerDirectory": [

2
autogpt_platform/frontend/playwright.config.ts
View File

@@ -45,7 +45,7 @@ export default defineConfig({
webServer: {
command: "pnpm start",
url: "http://localhost:3000",
reuseExistingServer: !process.env.CI,
reuseExistingServer: true,
},
/* Configure projects for major browsers */

2651
autogpt_platform/frontend/pnpm-lock.yaml generated
View File

File diff suppressed because it is too large Load Diff

61
autogpt_platform/frontend/scripts/generate-api-queries.ts Normal file
View File

@@ -0,0 +1,61 @@
#!/usr/bin/env node
import { getAgptServerBaseUrl } from "@/lib/env-config";
import { execSync } from "child_process";
import * as path from "path";
import * as fs from "fs";
function fetchOpenApiSpec(): void {
const args = process.argv.slice(2);
const forceFlag = args.includes("--force");
const baseUrl = getAgptServerBaseUrl();
const openApiUrl = `${baseUrl}/openapi.json`;
const outputPath = path.join(
__dirname,
"..",
"src",
"app",
"api",
"openapi.json",
);
console.log(`Output path: ${outputPath}`);
console.log(`Force flag: ${forceFlag}`);
// Check if local file exists
const localFileExists = fs.existsSync(outputPath);
if (!forceFlag && localFileExists) {
console.log("✅ Using existing local OpenAPI spec file");
console.log("💡 Use --force flag to fetch from server");
return;
}
if (!localFileExists) {
console.log("📄 No local OpenAPI spec found, fetching from server...");
} else {
console.log(
"🔄 Force flag detected, fetching fresh OpenAPI spec from server...",
);
}
console.log(`Fetching OpenAPI spec from: ${openApiUrl}`);
try {
// Fetch the OpenAPI spec
execSync(`curl "${openApiUrl}" > "${outputPath}"`, { stdio: "inherit" });
// Format with prettier
execSync(`prettier --write "${outputPath}"`, { stdio: "inherit" });
console.log("✅ OpenAPI spec fetched and formatted successfully");
} catch (error) {
console.error("❌ Failed to fetch OpenAPI spec:", error);
process.exit(1);
}
}
if (require.main === module) {
fetchOpenApiSpec();
}

7
autogpt_platform/frontend/src/app/(platform)/admin/spending/actions.ts
View File

@@ -14,12 +14,7 @@ export async function addDollars(formData: FormData) {
comments: formData.get("comments") as string,
};
const api = new BackendApi();
const resp = await api.addUserCredits(
data.user_id,
data.amount,
data.comments,
);
console.log(resp);
await api.addUserCredits(data.user_id, data.amount, data.comments);
revalidatePath("/admin/spending");
}

1
autogpt_platform/frontend/src/app/(platform)/admin/spending/page.tsx
View File

@@ -29,6 +29,7 @@ function SpendingDashboard({
</div>
<Suspense
key={`${page}-${status}-${search}`}
fallback={
<div className="py-10 text-center">Loading submissions...</div>
}

63
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/AiBlock.tsx Normal file
View File

@@ -0,0 +1,63 @@
import { Button } from "@/components/ui/button";
import { cn } from "@/lib/utils";
import { Plus } from "lucide-react";
import { ButtonHTMLAttributes } from "react";
interface Props extends ButtonHTMLAttributes<HTMLButtonElement> {
title?: string;
description?: string;
ai_name?: string;
}
export const AiBlock: React.FC<Props> = ({
title,
description,
className,
ai_name,
...rest
}) => {
return (
<Button
className={cn(
"group flex h-[5.625rem] w-full min-w-[7.5rem] items-center justify-start space-x-3 whitespace-normal rounded-[0.75rem] bg-zinc-50 px-[0.875rem] py-[0.625rem] text-start shadow-none",
"hover:bg-zinc-100 focus:ring-0 active:bg-zinc-100 active:ring-1 active:ring-zinc-300 disabled:pointer-events-none",
className,
)}
{...rest}
>
<div className="flex flex-1 flex-col items-start gap-1.5">
<div className="space-y-0.5">
<span
className={cn(
"line-clamp-1 font-sans text-sm font-medium leading-[1.375rem] text-zinc-700 group-disabled:text-zinc-400",
)}
>
{title}
</span>
<span
className={cn(
"line-clamp-1 font-sans text-xs font-normal leading-5 text-zinc-500 group-disabled:text-zinc-400",
)}
>
{description}
</span>
</div>
<span
className={cn(
"rounded-[0.75rem] bg-zinc-200 px-[0.5rem] font-sans text-xs leading-[1.25rem] text-zinc-500",
)}
>
Supports {ai_name}
</span>
</div>
<div
className={cn(
"flex h-7 w-7 items-center justify-center rounded-[0.5rem] bg-zinc-700 group-disabled:bg-zinc-400",
)}
>
<Plus className="h-5 w-5 text-zinc-50" strokeWidth={2} />
</div>
</Button>
);
};

77
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/Block.tsx Normal file
View File

@@ -0,0 +1,77 @@
import { Button } from "@/components/ui/button";
import { Skeleton } from "@/components/ui/skeleton";
import { beautifyString, cn } from "@/lib/utils";
import { Plus } from "lucide-react";
import React, { ButtonHTMLAttributes } from "react";import { highlightText } from "./helpers";
;
interface Props extends ButtonHTMLAttributes<HTMLButtonElement> {
title?: string;
description?: string;
highlightedText?: string;
}
interface BlockComponent extends React.FC<Props> {
Skeleton: React.FC<{ className?: string }>;
}
export const Block: BlockComponent = ({
title,
description,
highlightedText,
className,
...rest
}) => {
return (
<Button
className={cn(
"group flex h-16 w-full min-w-[7.5rem] items-center justify-start space-x-3 whitespace-normal rounded-[0.75rem] bg-zinc-50 px-[0.875rem] py-[0.625rem] text-start shadow-none",
"hover:cursor-default hover:bg-zinc-100 focus:ring-0 active:bg-zinc-100 active:ring-1 active:ring-zinc-300 disabled:cursor-not-allowed",
className,
)}
{...rest}
>
<div className="flex flex-1 flex-col items-start gap-0.5">
{title && (
<span
className={cn(
"line-clamp-1 font-sans text-sm font-medium leading-[1.375rem] text-zinc-800 group-disabled:text-zinc-400",
)}
>
{highlightText(beautifyString(title), highlightedText)}
</span>
)}
{description && (
<span
className={cn(
"line-clamp-1 font-sans text-xs font-normal leading-5 text-zinc-500 group-disabled:text-zinc-400",
)}
>
{highlightText(description, highlightedText)}
</span>
)}
</div>
<div
className={cn(
"flex h-7 w-7 items-center justify-center rounded-[0.5rem] bg-zinc-700 group-disabled:bg-zinc-400",
)}
>
<Plus className="h-5 w-5 text-zinc-50" strokeWidth={2} />
</div>
</Button>
);
};
const BlockSkeleton = () => {
return (
<Skeleton className="flex h-16 w-full min-w-[7.5rem] animate-pulse items-center justify-start space-x-3 rounded-[0.75rem] bg-zinc-100 px-[0.875rem] py-[0.625rem]">
<div className="flex flex-1 flex-col items-start gap-0.5">
<Skeleton className="h-[1.375rem] w-24 rounded bg-zinc-200" />
<Skeleton className="h-5 w-32 rounded bg-zinc-200" />
</div>
<Skeleton className="h-7 w-7 rounded-[0.5rem] bg-zinc-200" />
</Skeleton>
);
};
Block.Skeleton = BlockSkeleton;

51
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/BlockMenu/BlockMenu.tsx Normal file
View File

@@ -0,0 +1,51 @@
import React from "react";
import {
Popover,
PopoverContent,
PopoverTrigger,
} from "@/components/ui/popover";
import { ToyBrick } from "lucide-react";
import { BlockMenuContent } from "../BlockMenuContent/BlockMenuContent";
import { ControlPanelButton } from "../ControlPanelButton";
import { useBlockMenu } from "./useBlockMenu";
interface BlockMenuProps {
pinBlocksPopover: boolean;
blockMenuSelected: "save" | "block" | "";
setBlockMenuSelected: React.Dispatch<
React.SetStateAction<"" | "save" | "block">
>;
}
export const BlockMenu: React.FC<BlockMenuProps> = ({
pinBlocksPopover,
blockMenuSelected,
setBlockMenuSelected,
}) => {
const {open, onOpen} = useBlockMenu({pinBlocksPopover, setBlockMenuSelected});
return (
<Popover open={pinBlocksPopover ? true : open} onOpenChange={onOpen}>
<PopoverTrigger className="hover:cursor-pointer">
<ControlPanelButton
data-id="blocks-control-popover-trigger"
data-testid="blocks-control-blocks-button"
selected={blockMenuSelected === "block"}
className="rounded-none"
>
{/* Need to find phosphor icon alternative for this lucide icon */}
<ToyBrick className="h-5 w-6" strokeWidth={2} />
</ControlPanelButton>
</PopoverTrigger>
<PopoverContent
side="right"
align="start"
sideOffset={16}
className="absolute h-[75vh] w-[46.625rem] overflow-hidden rounded-[1rem] border-none p-0 shadow-[0_2px_6px_0_rgba(0,0,0,0.05)]"
data-id="blocks-control-popover-content"
>
<BlockMenuContent />
</PopoverContent>
</Popover>
);
};

23
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/BlockMenu/useBlockMenu.ts Normal file
View File

@@ -0,0 +1,23 @@
import { useState } from "react";
interface useBlockMenuProps {
pinBlocksPopover: boolean;
setBlockMenuSelected: React.Dispatch<
React.SetStateAction<"" | "save" | "block">
>;
}
export const useBlockMenu = ({pinBlocksPopover, setBlockMenuSelected}: useBlockMenuProps) => {
const [open, setOpen] = useState(false);
const onOpen = (newOpen: boolean) => {
if (!pinBlocksPopover) {
setOpen(newOpen);
setBlockMenuSelected(newOpen ? "block" : "");
}
};
return {
open,
onOpen,
};
};

10
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/BlockMenuContent/BlockMenuContent.tsx Normal file
View File

@@ -0,0 +1,10 @@
"use client";
import React from "react";
export const BlockMenuContent = () => {
return (
<div className="flex h-full w-full flex-col items-center justify-center">
This is the block menu content
</div>
);
};

35
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/ControlPanelButton.tsx Normal file
View File

@@ -0,0 +1,35 @@
// BLOCK MENU TODO: We need a disable state in this, currently it's not in design.
import { cn } from "@/lib/utils";
import React from "react";
interface Props extends React.HTMLAttributes<HTMLDivElement> {
selected?: boolean;
children?: React.ReactNode; // For icon purpose
disabled?: boolean;
}
export const ControlPanelButton: React.FC<Props> = ({
selected = false,
children,
disabled,
className,
...rest
}) => {
return (
// Using div instead of button, because it's only for design purposes. We are using this to give design to PopoverTrigger.
<div
role="button"
className={cn(
"flex h-[4.25rem] w-[4.25rem] items-center justify-center whitespace-normal bg-white p-[1.38rem] text-zinc-800 shadow-none hover:cursor-pointer hover:bg-zinc-100 hover:text-zinc-950 focus:ring-0",
selected &&
"bg-violet-50 text-violet-700 hover:cursor-default hover:bg-violet-50 hover:text-violet-700 active:bg-violet-50 active:text-violet-700",
disabled && "cursor-not-allowed",
className,
)}
{...rest}
>
{children}
</div>
);
};

54
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/FilterChip.tsx Normal file
View File

@@ -0,0 +1,54 @@
import { Button } from "@/components/ui/button";
import { cn } from "@/lib/utils";
import { X } from "lucide-react";
import React, { ButtonHTMLAttributes } from "react";
interface Props extends ButtonHTMLAttributes<HTMLButtonElement> {
selected?: boolean;
number?: number;
name?: string;
}
export const FilterChip: React.FC<Props> = ({
selected = false,
number,
name,
className,
...rest
}) => {
return (
<Button
className={cn(
"group w-fit space-x-1 rounded-[1.5rem] border border-zinc-300 bg-transparent px-[0.625rem] py-[0.375rem] shadow-none transition-transform duration-300 ease-in-out",
"hover:border-violet-500 hover:bg-transparent focus:ring-0 disabled:cursor-not-allowed",
selected && "border-0 bg-violet-700 hover:border",
className,
)}
{...rest}
>
<span
className={cn(
"font-sans text-sm font-medium leading-[1.375rem] text-zinc-600 group-hover:text-zinc-600 group-disabled:text-zinc-400",
selected && "text-zinc-50",
)}
>
{name}
</span>
{selected && (
<>
<span className="flex h-4 w-4 items-center justify-center rounded-full bg-zinc-50 transition-all duration-300 ease-in-out group-hover:hidden">
<X
className="h-3 w-3 rounded-full text-violet-700"
strokeWidth={2}
/>
</span>
{number !== undefined && (
<span className="hidden h-[1.375rem] items-center rounded-[1.25rem] bg-violet-700 p-[0.375rem] text-zinc-50 transition-all duration-300 ease-in-out animate-in fade-in zoom-in group-hover:flex">
{number > 100 ? "100+" : number}
</span>
)}
</>
)}
</Button>
);
};

88
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/Integration.tsx Normal file
View File

@@ -0,0 +1,88 @@
import { Button } from "@/components/ui/button";
import { Skeleton } from "@/components/ui/skeleton";
import { beautifyString, cn } from "@/lib/utils";
import Image from "next/image";
import React, { ButtonHTMLAttributes } from "react";
interface Props extends ButtonHTMLAttributes<HTMLButtonElement> {
title?: string;
description?: string;
icon_url?: string;
number_of_blocks?: number;
}
interface IntegrationComponent extends React.FC<Props> {
Skeleton: React.FC<{ className?: string }>;
}
export const Integration: IntegrationComponent = ({
title,
icon_url,
description,
className,
number_of_blocks,
...rest
}) => {
return (
<Button
className={cn(
"group flex h-16 w-full min-w-[7.5rem] items-center justify-start space-x-3 whitespace-normal rounded-[0.75rem] bg-zinc-50 px-[0.875rem] py-[0.625rem] text-start shadow-none",
"hover:cursor-default hover:bg-zinc-100 focus:ring-0 active:bg-zinc-50 active:ring-1 active:ring-zinc-300 disabled:pointer-events-none",
className,
)}
{...rest}
>
<div className="relative h-[2.625rem] w-[2.625rem] overflow-hidden rounded-[0.5rem] bg-white">
{icon_url && (
<Image
src={icon_url}
alt="integration-icon"
fill
sizes="2.25rem"
className="w-full rounded-[0.5rem] object-contain group-disabled:opacity-50"
/>
)}
</div>
<div className="w-full">
<div className="flex items-center justify-between gap-2">
{title && (
<p className="line-clamp-1 flex-1 font-sans text-sm font-medium leading-[1.375rem] text-zinc-700 group-disabled:text-zinc-400">
{beautifyString(title)}
</p>
)}
<span className="flex h-[1.375rem] w-[1.6875rem] items-center justify-center rounded-[1.25rem] bg-[#f0f0f0] p-1.5 font-sans text-sm leading-[1.375rem] text-zinc-500 group-disabled:text-zinc-400">
{number_of_blocks}
</span>
</div>
<span className="line-clamp-1 font-sans text-xs font-normal leading-5 text-zinc-500 group-disabled:text-zinc-400">
{description}
</span>
</div>
</Button>
);
};
const IntegrationSkeleton: React.FC<{ className?: string }> = ({
className,
}) => {
return (
<Skeleton
className={cn(
"flex h-16 w-full min-w-[7.5rem] animate-pulse items-center justify-start space-x-3 rounded-[0.75rem] bg-zinc-100 px-[0.875rem] py-[0.625rem]",
className,
)}
>
<Skeleton className="h-[2.625rem] w-[2.625rem] rounded-[0.5rem] bg-zinc-200" />
<div className="flex flex-1 flex-col items-start gap-0.5">
<div className="flex w-full items-center justify-between">
<Skeleton className="h-[1.375rem] w-24 rounded bg-zinc-200" />
<Skeleton className="h-[1.375rem] w-[1.6875rem] rounded-[1.25rem] bg-zinc-200" />
</div>
<Skeleton className="h-5 w-[80%] rounded bg-zinc-200" />
</div>
</Skeleton>
);
};
Integration.Skeleton = IntegrationSkeleton;

60
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/IntegrationChip.tsx Normal file
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import { Button } from "@/components/ui/button";
import { Skeleton } from "@/components/ui/skeleton";
import { beautifyString, cn } from "@/lib/utils";
import Image from "next/image";
import React, { ButtonHTMLAttributes } from "react";
interface Props extends ButtonHTMLAttributes<HTMLButtonElement> {
name?: string;
icon_url?: string;
}
interface IntegrationChipComponent extends React.FC<Props> {
Skeleton: React.FC;
}
export const IntegrationChip: IntegrationChipComponent = ({
icon_url,
name,
className,
...rest
}) => {
return (
<Button
className={cn(
"flex h-[3.25rem] w-full min-w-[7.5rem] justify-start gap-2 whitespace-normal rounded-[0.5rem] bg-zinc-50 p-2 pr-3 shadow-none",
"hover:cursor-default hover:bg-zinc-100 focus:ring-0 active:bg-zinc-100 active:ring-1 active:ring-zinc-300",
className,
)}
{...rest}
>
<div className="relative h-9 w-9 rounded-[0.5rem] bg-transparent">
{icon_url && (
<Image
src={icon_url}
alt="integration-icon"
fill
sizes="2.25rem"
className="w-full object-contain"
/>
)}
</div>
{name && (
<span className="truncate font-sans text-sm font-normal leading-[1.375rem] text-zinc-800">
{beautifyString(name)}
</span>
)}
</Button>
);
};
const IntegrationChipSkeleton: React.FC = () => {
return (
<Skeleton className="flex h-[3.25rem] w-full min-w-[7.5rem] gap-2 rounded-[0.5rem] bg-zinc-100 p-2 pr-3">
<Skeleton className="h-9 w-12 rounded-[0.5rem] bg-zinc-200" />
<Skeleton className="h-5 w-24 self-center rounded-sm bg-zinc-200" />
</Skeleton>
);
};
IntegrationChip.Skeleton = IntegrationChipSkeleton;

99
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/IntergrationBlock.tsx Normal file
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import { Button } from "@/components/ui/button";
import { Skeleton } from "@/components/ui/skeleton";
import { beautifyString, cn } from "@/lib/utils";
import { Plus } from "lucide-react";
import Image from "next/image";
import React, { ButtonHTMLAttributes } from "react";
import { highlightText } from "./helpers";
interface Props extends ButtonHTMLAttributes<HTMLButtonElement> {
title?: string;
description?: string;
icon_url?: string;
highlightedText?: string;
}
interface IntegrationBlockComponent extends React.FC<Props> {
Skeleton: React.FC<{ className?: string }>;
}
export const IntegrationBlock: IntegrationBlockComponent = ({
title,
icon_url,
description,
className,
highlightedText,
...rest
}) => {
return (
<Button
className={cn(
"group flex h-16 w-full min-w-[7.5rem] items-center justify-start gap-3 whitespace-normal rounded-[0.75rem] bg-zinc-50 px-[0.875rem] py-[0.625rem] text-start shadow-none",
"hover:cursor-default hover:bg-zinc-100 focus:ring-0 active:bg-zinc-100 active:ring-1 active:ring-zinc-300 disabled:cursor-not-allowed",
className,
)}
{...rest}
>
<div className="relative h-[2.625rem] w-[2.625rem] rounded-[0.5rem] bg-white">
{icon_url && (
<Image
src={icon_url}
alt="integration-icon"
fill
sizes="2.25rem"
className="w-full object-contain group-disabled:opacity-50"
/>
)}
</div>
<div className="flex flex-1 flex-col items-start gap-0.5">
{title && (
<span
className={cn(
"line-clamp-1 font-sans text-sm font-medium leading-[1.375rem] text-zinc-800 group-disabled:text-zinc-400",
)}
>
{highlightText(beautifyString(title), highlightedText)}
</span>
)}
{description && (
<span
className={cn(
"line-clamp-1 font-sans text-xs font-normal leading-5 text-zinc-500 group-disabled:text-zinc-400",
)}
>
{highlightText(description, highlightedText)}
</span>
)}
</div>
<div
className={cn(
"flex h-7 w-7 items-center justify-center rounded-[0.5rem] bg-zinc-700 group-disabled:bg-zinc-400",
)}
>
<Plus className="h-5 w-5 text-zinc-50" strokeWidth={2} />
</div>
</Button>
);
};
const IntegrationBlockSkeleton = ({ className }: { className?: string }) => {
return (
<Skeleton
className={cn(
"flex h-16 w-full min-w-[7.5rem] animate-pulse items-center justify-start gap-3 rounded-[0.75rem] bg-zinc-100 px-[0.875rem] py-[0.625rem]",
className,
)}
>
<Skeleton className="h-[2.625rem] w-[2.625rem] rounded-[0.5rem] bg-zinc-200" />
<div className="flex flex-1 flex-col items-start gap-0.5">
<Skeleton className="h-[1.375rem] w-24 rounded bg-zinc-200" />
<Skeleton className="h-5 w-32 rounded bg-zinc-200" />
</div>
<Skeleton className="h-7 w-7 rounded-[0.5rem] bg-zinc-200" />
</Skeleton>
);
};
IntegrationBlock.Skeleton = IntegrationBlockSkeleton;

135
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/MarketplaceAgentBlock.tsx Normal file
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import { Button } from "@/components/ui/button";
import { Skeleton } from "@/components/ui/skeleton";
import { cn } from "@/lib/utils";
import { ExternalLink, Loader2, Plus } from "lucide-react";
import Image from "next/image";
import React, { ButtonHTMLAttributes } from "react";
import Link from "next/link";
import { highlightText } from "./helpers";
interface Props extends ButtonHTMLAttributes<HTMLButtonElement> {
title?: string;
creator_name?: string;
number_of_runs?: number;
image_url?: string;
highlightedText?: string;
slug: string;
loading: boolean;
}
interface MarketplaceAgentBlockComponent extends React.FC<Props> {
Skeleton: React.FC<{ className?: string }>;
}
export const MarketplaceAgentBlock: MarketplaceAgentBlockComponent = ({
title,
image_url,
creator_name,
number_of_runs,
className,
loading,
highlightedText,
slug,
...rest
}) => {
return (
<Button
className={cn(
"group flex h-[4.375rem] w-full min-w-[7.5rem] items-center justify-start gap-3 whitespace-normal rounded-[0.75rem] bg-zinc-50 p-[0.625rem] pr-[0.875rem] text-start shadow-none",
"hover:cursor-default hover:bg-zinc-100 focus:ring-0 active:bg-zinc-100 active:ring-1 active:ring-zinc-300 disabled:pointer-events-none",
className,
)}
{...rest}
>
<div className="relative h-[3.125rem] w-[5.625rem] overflow-hidden rounded-[0.375rem] bg-white">
{image_url && (
<Image
src={image_url}
alt="integration-icon"
fill
sizes="5.625rem"
className="w-full object-contain group-disabled:opacity-50"
/>
)}
</div>
<div className="flex flex-1 flex-col items-start gap-0.5">
{title && (
<span
className={cn(
"line-clamp-1 font-sans text-sm font-medium leading-[1.375rem] text-zinc-800 group-disabled:text-zinc-400",
)}
>
{highlightText(title, highlightedText)}
</span>
)}
<div className="flex items-center space-x-2.5">
<span
className={cn(
"truncate font-sans text-xs font-normal leading-5 text-zinc-500 group-disabled:text-zinc-400",
)}
>
By {creator_name}
</span>
<span className="font-sans text-zinc-400">•</span>
<span
className={cn(
"truncate font-sans text-xs font-normal leading-5 text-zinc-500 group-disabled:text-zinc-400",
)}
>
{number_of_runs} runs
</span>
<span className="font-sans text-zinc-400">•</span>
<Link
href={`/marketplace/agent/${creator_name}/${slug}`}
className="flex gap-0.5 truncate"
onClick={(e) => e.stopPropagation()}
>
<span className="font-sans text-xs leading-5 text-blue-700 underline">
Agent page
</span>
<ExternalLink className="h-4 w-4 text-blue-700" strokeWidth={1} />
</Link>
</div>
</div>
<div
className={cn(
"flex h-7 min-w-7 items-center justify-center rounded-[0.5rem] bg-zinc-700 group-disabled:bg-zinc-400",
)}
>
{!loading ? (
<Plus className="h-5 w-5 text-zinc-50" strokeWidth={2} />
) : (
<Loader2 className="h-5 w-5 animate-spin" />
)}
</div>
</Button>
);
};
const MarketplaceAgentBlockSkeleton: React.FC<{ className?: string }> = ({
className,
}) => {
return (
<Skeleton
className={cn(
"flex h-[4.375rem] w-full min-w-[7.5rem] animate-pulse items-center justify-start gap-3 rounded-[0.75rem] bg-zinc-100 p-[0.625rem] pr-[0.875rem]",
className,
)}
>
<Skeleton className="h-[3.125rem] w-[5.625rem] rounded-[0.375rem] bg-zinc-200" />
<div className="flex flex-1 flex-col items-start gap-0.5">
<Skeleton className="h-[1.375rem] w-24 rounded bg-zinc-200" />
<div className="flex items-center gap-1">
<Skeleton className="h-5 w-16 rounded bg-zinc-200" />
<Skeleton className="h-5 w-16 rounded bg-zinc-200" />
</div>
</div>
<Skeleton className="h-7 w-7 rounded-[0.5rem] bg-zinc-200" />
</Skeleton>
);
};
MarketplaceAgentBlock.Skeleton = MarketplaceAgentBlockSkeleton;

40
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/MenuItem.tsx Normal file
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// BLOCK MENU TODO: We need to add a better hover state to it; currently it's not in the design either.
import { Button } from "@/components/ui/button";
import { cn } from "@/lib/utils";
import React, { ButtonHTMLAttributes } from "react";
interface Props extends ButtonHTMLAttributes<HTMLButtonElement> {
selected?: boolean;
number?: number;
name?: string;
}
export const MenuItem: React.FC<Props> = ({
selected = false,
number,
name,
className,
...rest
}) => {
return (
<Button
className={cn(
"flex h-[2.375rem] w-[12.875rem] justify-between whitespace-normal rounded-[0.5rem] bg-transparent p-2 pl-3 shadow-none",
"hover:cursor-default hover:bg-zinc-100 focus:ring-0",
selected && "bg-zinc-100",
className,
)}
{...rest}
>
<span className="truncate font-sans text-sm font-medium leading-[1.375rem] text-zinc-800">
{name}
</span>
{number && (
<span className="font-sans text-sm font-normal leading-[1.375rem] text-zinc-600">
{number > 100 ? "100+" : number}
</span>
)}
</Button>
);
};

110
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/NewControlPanel/NewControlPanel.tsx Normal file
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import { Separator } from "@/components/ui/separator";
import { cn } from "@/lib/utils";
import React, { useMemo } from "react";
import { BlockMenu } from "../BlockMenu/BlockMenu";
import { useNewControlPanel } from "./useNewControlPanel";
import { NewSaveControl } from "../SaveControl/NewSaveControl";
import { GraphExecutionID } from "@/lib/autogpt-server-api";
import { history } from "@/components/history";
import { ControlPanelButton } from "../ControlPanelButton";
import { ArrowUUpLeftIcon, ArrowUUpRightIcon } from "@phosphor-icons/react";
export type Control = {
icon: React.ReactNode;
label: string;
disabled?: boolean;
onClick: () => void;
};
interface ControlPanelProps {
className?: string;
flowExecutionID: GraphExecutionID | undefined;
visualizeBeads: "no" | "static" | "animate";
pinSavePopover: boolean;
pinBlocksPopover: boolean;
}
export const NewControlPanel = ({
flowExecutionID,
visualizeBeads,
pinSavePopover,
pinBlocksPopover,
className,
}: ControlPanelProps) => {
const {
blockMenuSelected,
setBlockMenuSelected,
agentDescription,
setAgentDescription,
saveAgent,
agentName,
setAgentName,
savedAgent,
isSaving,
isRunning,
isStopping,
} = useNewControlPanel({ flowExecutionID, visualizeBeads });
const controls: Control[] = useMemo(
() => [
{
label: "Undo",
icon: <ArrowUUpLeftIcon size={20} weight="bold" />,
onClick: history.undo,
disabled: !history.canUndo(),
},
{
label: "Redo",
icon: <ArrowUUpRightIcon size={20} weight="bold" />,
onClick: history.redo,
disabled: !history.canRedo(),
},
],
[]
);
return (
<section
className={cn(
"absolute left-4 top-24 z-10 w-[4.25rem] overflow-hidden rounded-[1rem] border-none bg-white p-0 shadow-[0_1px_5px_0_rgba(0,0,0,0.1)]",
className
)}
>
<div className="flex flex-col items-center justify-center rounded-[1rem] p-0">
<BlockMenu
pinBlocksPopover={pinBlocksPopover}
blockMenuSelected={blockMenuSelected}
setBlockMenuSelected={setBlockMenuSelected}
/>
<Separator className="text-[#E1E1E1]" />
{controls.map((control, index) => (
<ControlPanelButton
key={index}
onClick={() => control.onClick()}
data-id={`control-button-${index}`}
data-testid={`blocks-control-${control.label.toLowerCase()}-button`}
disabled={control.disabled || false}
className="rounded-none"
>
{control.icon}
</ControlPanelButton>
))}
<Separator className="text-[#E1E1E1]" />
<NewSaveControl
agentMeta={savedAgent}
canSave={!isSaving && !isRunning && !isStopping}
onSave={saveAgent}
agentDescription={agentDescription}
onDescriptionChange={setAgentDescription}
agentName={agentName}
onNameChange={setAgentName}
pinSavePopover={pinSavePopover}
blockMenuSelected={blockMenuSelected}
setBlockMenuSelected={setBlockMenuSelected}
/>
</div>
</section>
);
};
export default NewControlPanel;

35
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/NewControlPanel/useNewControlPanel.ts Normal file
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import useAgentGraph from "@/hooks/useAgentGraph";
import { GraphExecutionID, GraphID } from "@/lib/autogpt-server-api";
import { useSearchParams } from "next/navigation";
import { useState } from "react";
export interface NewControlPanelProps {
flowExecutionID: GraphExecutionID | undefined;
visualizeBeads: "no" | "static" | "animate";
}
export const useNewControlPanel = ({flowExecutionID, visualizeBeads}: NewControlPanelProps) => {
const [blockMenuSelected, setBlockMenuSelected] = useState<
"save" | "block" | ""
>("");
const query = useSearchParams();
const _graphVersion = query.get("flowVersion");
const graphVersion = _graphVersion ? parseInt(_graphVersion) : undefined;
const flowID = query.get("flowID") as GraphID | null ?? undefined;
const {agentDescription, setAgentDescription, saveAgent, agentName, setAgentName, savedAgent, isSaving, isRunning, isStopping} = useAgentGraph(flowID, graphVersion, flowExecutionID, visualizeBeads !== "no")
return {
blockMenuSelected,
setBlockMenuSelected,
agentDescription,
setAgentDescription,
saveAgent,
agentName,
setAgentName,
savedAgent,
isSaving,
isRunning,
isStopping,
}
};

17
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/NoSearchResult.tsx Normal file
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import { SmileySadIcon } from "@phosphor-icons/react";
export const NoSearchResult = () => {
return (
<div className="flex h-full w-full flex-col items-center justify-center text-center">
<SmileySadIcon size={64} className="mb-10 text-zinc-400" />
<div className="space-y-1">
<p className="font-sans text-sm font-medium leading-[1.375rem] text-zinc-800">
No match found
</p>
<p className="font-sans text-sm font-normal leading-[1.375rem] text-zinc-600">
Try adjusting your search terms
</p>
</div>
</div>
);
};

158
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/SaveControl/NewSaveControl.tsx Normal file
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import React, { useCallback, useEffect } from "react";
import {
Popover,
PopoverContent,
PopoverTrigger,
} from "@/components/ui/popover";
import { Card, CardContent, CardFooter } from "@/components/ui/card";
import { Input } from "@/components/ui/input";
import { Button } from "@/components/ui/button";
import { GraphMeta } from "@/lib/autogpt-server-api";
import { Label } from "@/components/ui/label";
import { IconSave } from "@/components/ui/icons";
import { useToast } from "@/components/molecules/Toast/use-toast";
import { ControlPanelButton } from "../ControlPanelButton";
interface SaveControlProps {
agentMeta: GraphMeta | null;
agentName: string;
agentDescription: string;
canSave: boolean;
onSave: () => void;
onNameChange: (name: string) => void;
onDescriptionChange: (description: string) => void;
pinSavePopover: boolean;
blockMenuSelected: "save" | "block" | "";
setBlockMenuSelected: React.Dispatch<
React.SetStateAction<"" | "save" | "block">
>;
}
export const NewSaveControl = ({
agentMeta,
canSave,
onSave,
agentName,
onNameChange,
agentDescription,
onDescriptionChange,
blockMenuSelected,
setBlockMenuSelected,
pinSavePopover,
}: SaveControlProps) => {
const handleSave = useCallback(() => {
onSave();
}, [onSave]);
const { toast } = useToast();
useEffect(() => {
const handleKeyDown = (event: KeyboardEvent) => {
if ((event.ctrlKey || event.metaKey) && event.key === "s") {
event.preventDefault();
handleSave();
toast({
duration: 2000,
title: "All changes saved successfully!",
});
}
};
window.addEventListener("keydown", handleKeyDown);
return () => {
window.removeEventListener("keydown", handleKeyDown);
};
}, [handleSave, toast]);
return (
<Popover
open={pinSavePopover ? true : undefined}
onOpenChange={(open) => open || setBlockMenuSelected("")}
>
<PopoverTrigger>
<ControlPanelButton
data-id="save-control-popover-trigger"
data-testid="blocks-control-save-button"
selected={blockMenuSelected === "save"}
onClick={() => {
setBlockMenuSelected("save");
}}
className="rounded-none"
>
{/* Need to find phosphor icon alternative for this lucide icon */}
<IconSave className="h-5 w-5" strokeWidth={2} />
</ControlPanelButton>
</PopoverTrigger>
<PopoverContent
side="right"
sideOffset={16}
align="start"
className="w-[17rem] rounded-xl border-none p-0 shadow-none md:w-[30rem]"
data-id="save-control-popover-content"
>
<Card className="border-none shadow-none dark:bg-slate-900">
<CardContent className="p-4">
<div className="grid gap-3">
<Label htmlFor="name" className="dark:text-gray-300">
Name
</Label>
<Input
id="name"
placeholder="Enter your agent name"
className="col-span-3"
value={agentName}
onChange={(e) => onNameChange(e.target.value)}
data-id="save-control-name-input"
data-testid="save-control-name-input"
maxLength={100}
/>
<Label htmlFor="description" className="dark:text-gray-300">
Description
</Label>
<Input
id="description"
placeholder="Your agent description"
className="col-span-3"
value={agentDescription}
onChange={(e) => onDescriptionChange(e.target.value)}
data-id="save-control-description-input"
data-testid="save-control-description-input"
maxLength={500}
/>
{agentMeta?.version && (
<>
<Label htmlFor="version" className="dark:text-gray-300">
Version
</Label>
<Input
id="version"
placeholder="Version"
className="col-span-3"
value={agentMeta?.version || "-"}
disabled
data-testid="save-control-version-output"
/>
</>
)}
</div>
</CardContent>
<CardFooter className="flex flex-col items-stretch gap-2">
<Button
className="w-full dark:bg-slate-700 dark:text-slate-100 dark:hover:bg-slate-800"
onClick={handleSave}
data-id="save-control-save-agent"
data-testid="save-control-save-agent-button"
disabled={!canSave}
>
Save Agent
</Button>
</CardFooter>
</Card>
</PopoverContent>
</Popover>
);
};

47
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/SearchHistoryChip.tsx Normal file
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import { Button } from "@/components/ui/button";
import { Skeleton } from "@/components/ui/skeleton";
import { cn } from "@/lib/utils";
import { ArrowUpRight } from "lucide-react";
import React, { ButtonHTMLAttributes } from "react";
interface Props extends ButtonHTMLAttributes<HTMLButtonElement> {
content?: string;
}
interface SearchHistoryChipComponent extends React.FC<Props> {
Skeleton: React.FC<{ className?: string }>;
}
export const SearchHistoryChip: SearchHistoryChipComponent = ({
content,
className,
...rest
}) => {
return (
<Button
className={cn(
"my-[1px] h-[2.25rem] space-x-1 rounded-[1.5rem] bg-zinc-50 p-[0.375rem] pr-[0.625rem] shadow-none",
"hover:cursor-default hover:bg-zinc-100 focus:ring-0 active:bg-zinc-100 active:ring-1 active:ring-zinc-300",
className,
)}
{...rest}
>
<ArrowUpRight className="h-6 w-6 text-zinc-500" strokeWidth={1.25} />
<span className="font-sans text-sm font-normal leading-[1.375rem] text-zinc-800">
{content}
</span>
</Button>
);
};
const SearchHistoryChipSkeleton: React.FC<{ className?: string }> = ({
className,
}) => {
return (
<Skeleton
className={cn("h-[2.25rem] w-32 rounded-[1.5rem] bg-zinc-100", className)}
/>
);
};
SearchHistoryChip.Skeleton = SearchHistoryChipSkeleton;

117
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/UGCAgentBlock.tsx Normal file
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import { Button } from "@/components/ui/button";
import { Skeleton } from "@/components/ui/skeleton";
import { cn } from "@/lib/utils";
import { Plus } from "lucide-react";
import Image from "next/image";
import React, { ButtonHTMLAttributes } from "react";
import { highlightText } from "./helpers";
import { formatTimeAgo } from "@/lib/utils/time";
interface Props extends ButtonHTMLAttributes<HTMLButtonElement> {
title?: string;
edited_time?: Date;
version?: number;
image_url?: string;
highlightedText?: string;
}
interface UGCAgentBlockComponent extends React.FC<Props> {
Skeleton: React.FC<{ className?: string }>;
}
export const UGCAgentBlock: UGCAgentBlockComponent = ({
title,
image_url,
edited_time = new Date(),
version,
className,
highlightedText,
...rest
}) => {
return (
<Button
className={cn(
"group flex h-[4.375rem] w-full min-w-[7.5rem] items-center justify-start gap-3 whitespace-normal rounded-[0.75rem] bg-zinc-50 p-[0.625rem] pr-[0.875rem] text-start shadow-none",
"hover:cursor-default hover:bg-zinc-100 focus:ring-0 active:bg-zinc-100 active:ring-1 active:ring-zinc-300 disabled:cursor-not-allowed",
className,
)}
{...rest}
>
{image_url && (
<div className="relative h-[3.125rem] w-[5.625rem] overflow-hidden rounded-[0.375rem] bg-white">
<Image
src={image_url}
alt="integration-icon"
fill
sizes="5.625rem"
className="w-full object-contain group-disabled:opacity-50"
/>
</div>
)}
<div className="flex flex-1 flex-col items-start gap-0.5">
{title && (
<span
className={cn(
"line-clamp-1 font-sans text-sm font-medium leading-[1.375rem] text-zinc-800 group-disabled:text-zinc-400",
)}
>
{highlightText(title, highlightedText)}
</span>
)}
<div className="flex items-center space-x-1.5">
{edited_time && (
<span
className={cn(
"line-clamp-1 font-sans text-xs font-normal leading-5 text-zinc-500 group-disabled:text-zinc-400",
)}
>
Edited {formatTimeAgo(edited_time.toISOString())}
</span>
)}
<span className="font-sans text-zinc-400">•</span>
<span
className={cn(
"line-clamp-1 font-sans text-xs font-normal leading-5 text-zinc-500 group-disabled:text-zinc-400",
)}
>
Version {version}
</span>
</div>
</div>
<div
className={cn(
"flex h-7 w-7 items-center justify-center rounded-[0.5rem] bg-zinc-700 group-disabled:bg-zinc-400",
)}
>
<Plus className="h-5 w-5 text-zinc-50" strokeWidth={2} />
</div>
</Button>
);
};
const UGCAgentBlockSkeleton: React.FC<{ className?: string }> = ({
className,
}) => {
return (
<Skeleton
className={cn(
"flex h-[4.375rem] w-full min-w-[7.5rem] animate-pulse items-center justify-start gap-3 rounded-[0.75rem] bg-zinc-100 p-[0.625rem] pr-[0.875rem]",
className,
)}
>
<Skeleton className="h-[3.125rem] w-[5.625rem] rounded-[0.375rem] bg-zinc-200" />
<div className="flex flex-1 flex-col items-start gap-0.5">
<Skeleton className="h-[1.375rem] w-24 rounded bg-zinc-200" />
<div className="flex items-center gap-1">
<Skeleton className="h-5 w-16 rounded bg-zinc-200" />
<Skeleton className="h-5 w-16 rounded bg-zinc-200" />
</div>
</div>
<Skeleton className="h-7 w-7 rounded-[0.5rem] bg-zinc-200" />
</Skeleton>
);
};
UGCAgentBlock.Skeleton = UGCAgentBlockSkeleton;

22
autogpt_platform/frontend/src/app/(platform)/build/components/NewBlockMenu/helpers.tsx Normal file
View File

@@ -0,0 +1,22 @@
export const highlightText = (
text: string | undefined,
highlight: string | undefined,
) => {
if (!text || !highlight) return text;
function escapeRegExp(s: string) {
return s.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
}
const escaped = escapeRegExp(highlight);
const parts = text.split(new RegExp(`(${escaped})`, "gi"));
return parts.map((part, i) =>
part.toLowerCase() === highlight?.toLowerCase() ? (
<mark key={i} className="bg-transparent font-bold">
{part}
</mark>
) : (
part
),
);
};

74
autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/AgentRunsView/AgentRunsView.tsx Normal file
View File

@@ -0,0 +1,74 @@
"use client";
import { Breadcrumbs } from "@/components/molecules/Breadcrumbs/Breadcrumbs";
import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
import { useAgentRunsView } from "./useAgentRunsView";
import { AgentRunsLoading } from "./components/AgentRunsLoading";
import { Button } from "@/components/atoms/Button/Button";
import { Plus } from "@phosphor-icons/react";
export function AgentRunsView() {
const { response, ready, error, agentId } = useAgentRunsView();
// Handle loading state
if (!ready) {
return <AgentRunsLoading />;
}
// Handle errors - check for query error first, then response errors
if (error || (response && response.status !== 200)) {
return (
<ErrorCard
isSuccess={false}
responseError={error || undefined}
httpError={
response?.status !== 200
? {
status: response?.status,
statusText: "Request failed",
}
: undefined
}
context="agent"
onRetry={() => window.location.reload()}
/>
);
}
// Handle missing data
if (!response?.data) {
return (
<ErrorCard
isSuccess={false}
responseError={{ message: "No agent data found" }}
context="agent"
onRetry={() => window.location.reload()}
/>
);
}
const agent = response.data;
return (
<div className="grid h-screen grid-cols-[25%_85%] gap-4 pt-8">
{/* Left Sidebar - 30% */}
<div className="bg-gray-50 p-4">
<Button variant="primary" size="large" className="w-full">
<Plus size={20} /> New Run
</Button>
</div>
{/* Main Content - 70% */}
<div className="p-4">
<Breadcrumbs
items={[
{ name: "My Library", link: "/library" },
{ name: agent.name, link: `/library/agents/${agentId}` },
]}
/>
{/* Main content will go here */}
<div className="mt-4 text-gray-600">Main content area</div>
</div>
</div>
);
}

25
autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/AgentRunsView/components/AgentRunsLoading.tsx Normal file
View File

@@ -0,0 +1,25 @@
import React from "react";
import { Skeleton } from "@/components/ui/skeleton";
export function AgentRunsLoading() {
return (
<div className="px-6 py-6">
<div className="flex h-screen w-full gap-4">
{/* Left Sidebar */}
<div className="w-80 space-y-4">
<Skeleton className="h-12 w-full" />
<Skeleton className="h-32 w-full" />
<Skeleton className="h-24 w-full" />
</div>
{/* Main Content */}
<div className="flex-1 space-y-4">
<Skeleton className="h-8 w-full" />
<Skeleton className="h-12 w-full" />
<Skeleton className="h-64 w-full" />
<Skeleton className="h-32 w-full" />
</div>
</div>
</div>
);
}

15
autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/AgentRunsView/useAgentRunsView.ts Normal file
View File

@@ -0,0 +1,15 @@
import { useGetV2GetLibraryAgent } from "@/app/api/__generated__/endpoints/library/library";
import { useParams } from "next/navigation";
export function useAgentRunsView() {
const { id } = useParams();
const agentId = id as string;
const { data: response, isSuccess, error } = useGetV2GetLibraryAgent(agentId);
return {
agentId: id,
ready: isSuccess,
error,
response,
};
}

622
autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/OldAgentLibraryView.tsx Normal file
View File

@@ -0,0 +1,622 @@
"use client";
import { useParams, useRouter } from "next/navigation";
import { useQueryState } from "nuqs";
import React, {
useCallback,
useEffect,
useMemo,
useRef,
useState,
} from "react";
import {
Graph,
GraphExecution,
GraphExecutionID,
GraphExecutionMeta,
GraphID,
LibraryAgent,
LibraryAgentID,
LibraryAgentPreset,
LibraryAgentPresetID,
Schedule,
ScheduleID,
} from "@/lib/autogpt-server-api";
import { useBackendAPI } from "@/lib/autogpt-server-api/context";
import { exportAsJSONFile } from "@/lib/utils";
import DeleteConfirmDialog from "@/components/agptui/delete-confirm-dialog";
import type { ButtonAction } from "@/components/agptui/types";
import { useOnboarding } from "@/components/onboarding/onboarding-provider";
import { Button } from "@/components/ui/button";
import {
Dialog,
DialogContent,
DialogDescription,
DialogFooter,
DialogHeader,
DialogTitle,
} from "@/components/ui/dialog";
import LoadingBox, { LoadingSpinner } from "@/components/ui/loading";
import { useToast } from "@/components/molecules/Toast/use-toast";
import { AgentRunDetailsView } from "./components/agent-run-details-view";
import { AgentRunDraftView } from "./components/agent-run-draft-view";
import { AgentRunsSelectorList } from "./components/agent-runs-selector-list";
import { AgentScheduleDetailsView } from "./components/agent-schedule-details-view";
export function OldAgentLibraryView() {
const { id: agentID }: { id: LibraryAgentID } = useParams();
const [executionId, setExecutionId] = useQueryState("executionId");
const { toast } = useToast();
const router = useRouter();
const api = useBackendAPI();
// ============================ STATE =============================
const [graph, setGraph] = useState<Graph | null>(null); // Graph version corresponding to LibraryAgent
const [agent, setAgent] = useState<LibraryAgent | null>(null);
const [agentRuns, setAgentRuns] = useState<GraphExecutionMeta[]>([]);
const [agentPresets, setAgentPresets] = useState<LibraryAgentPreset[]>([]);
const [schedules, setSchedules] = useState<Schedule[]>([]);
const [selectedView, selectView] = useState<
| { type: "run"; id?: GraphExecutionID }
| { type: "preset"; id: LibraryAgentPresetID }
| { type: "schedule"; id: ScheduleID }
>({ type: "run" });
const [selectedRun, setSelectedRun] = useState<
GraphExecution | GraphExecutionMeta | null
>(null);
const selectedSchedule =
selectedView.type == "schedule"
? schedules.find((s) => s.id == selectedView.id)
: null;
const [isFirstLoad, setIsFirstLoad] = useState<boolean>(true);
const [agentDeleteDialogOpen, setAgentDeleteDialogOpen] =
useState<boolean>(false);
const [confirmingDeleteAgentRun, setConfirmingDeleteAgentRun] =
useState<GraphExecutionMeta | null>(null);
const [confirmingDeleteAgentPreset, setConfirmingDeleteAgentPreset] =
useState<LibraryAgentPresetID | null>(null);
const {
state: onboardingState,
updateState: updateOnboardingState,
incrementRuns,
} = useOnboarding();
const [copyAgentDialogOpen, setCopyAgentDialogOpen] = useState(false);
// Set page title with agent name
useEffect(() => {
if (agent) {
document.title = `${agent.name} - Library - AutoGPT Platform`;
}
}, [agent]);
const openRunDraftView = useCallback(() => {
selectView({ type: "run" });
}, []);
const selectRun = useCallback((id: GraphExecutionID) => {
selectView({ type: "run", id });
}, []);
const selectPreset = useCallback((id: LibraryAgentPresetID) => {
selectView({ type: "preset", id });
}, []);
const selectSchedule = useCallback((id: ScheduleID) => {
selectView({ type: "schedule", id });
}, []);
const graphVersions = useRef<Record<number, Graph>>({});
const loadingGraphVersions = useRef<Record<number, Promise<Graph>>>({});
const getGraphVersion = useCallback(
async (graphID: GraphID, version: number) => {
if (version in graphVersions.current)
return graphVersions.current[version];
if (version in loadingGraphVersions.current)
return loadingGraphVersions.current[version];
const pendingGraph = api.getGraph(graphID, version).then((graph) => {
graphVersions.current[version] = graph;
return graph;
});
// Cache promise as well to avoid duplicate requests
loadingGraphVersions.current[version] = pendingGraph;
return pendingGraph;
},
[api, graphVersions, loadingGraphVersions],
);
// Reward user for viewing results of their onboarding agent
useEffect(() => {
if (
!onboardingState ||
!selectedRun ||
onboardingState.completedSteps.includes("GET_RESULTS")
)
return;
if (selectedRun.id === onboardingState.onboardingAgentExecutionId) {
updateOnboardingState({
completedSteps: [...onboardingState.completedSteps, "GET_RESULTS"],
});
}
}, [selectedRun, onboardingState, updateOnboardingState]);
const lastRefresh = useRef<number>(0);
const refreshPageData = useCallback(() => {
if (Date.now() - lastRefresh.current < 2e3) return; // 2 second debounce
lastRefresh.current = Date.now();
api.getLibraryAgent(agentID).then((agent) => {
setAgent(agent);
getGraphVersion(agent.graph_id, agent.graph_version).then(
(_graph) =>
(graph && graph.version == _graph.version) || setGraph(_graph),
);
Promise.all([
api.getGraphExecutions(agent.graph_id),
api.listLibraryAgentPresets({
graph_id: agent.graph_id,
page_size: 100,
}),
]).then(([runs, presets]) => {
setAgentRuns(runs);
setAgentPresets(presets.presets);
// Preload the corresponding graph versions for the latest 10 runs
new Set(runs.slice(0, 10).map((run) => run.graph_version)).forEach(
(version) => getGraphVersion(agent.graph_id, version),
);
});
});
}, [api, agentID, getGraphVersion, graph]);
// On first load: select the latest run
useEffect(() => {
// Only for first load or first execution
if (selectedView.id || !isFirstLoad) return;
if (agentRuns.length == 0 && agentPresets.length == 0) return;
setIsFirstLoad(false);
if (agentRuns.length > 0) {
// select latest run
const latestRun = agentRuns.reduce((latest, current) => {
if (latest.started_at && !current.started_at) return current;
else if (!latest.started_at) return latest;
return latest.started_at > current.started_at ? latest : current;
}, agentRuns[0]);
selectRun(latestRun.id);
} else {
// select top preset
const latestPreset = agentPresets.toSorted(
(a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
)[0];
selectPreset(latestPreset.id);
}
}, [
isFirstLoad,
selectedView.id,
agentRuns,
agentPresets,
selectRun,
selectPreset,
]);
useEffect(() => {
if (executionId) {
selectRun(executionId as GraphExecutionID);
setExecutionId(null);
}
}, [executionId, selectRun, setExecutionId]);
// Initial load
useEffect(() => {
refreshPageData();
// Show a toast when the WebSocket connection disconnects
let connectionToast: ReturnType<typeof toast> | null = null;
const cancelDisconnectHandler = api.onWebSocketDisconnect(() => {
connectionToast ??= toast({
title: "Connection to server was lost",
variant: "destructive",
description: (
<div className="flex items-center">
Trying to reconnect...
<LoadingSpinner className="ml-1.5 size-3.5" />
</div>
),
duration: Infinity,
dismissable: true,
});
});
const cancelConnectHandler = api.onWebSocketConnect(() => {
if (connectionToast)
connectionToast.update({
id: connectionToast.id,
title: "✅ Connection re-established",
variant: "default",
description: (
<div className="flex items-center">
Refreshing data...
<LoadingSpinner className="ml-1.5 size-3.5" />
</div>
),
duration: 2000,
dismissable: true,
});
connectionToast = null;
});
return () => {
cancelDisconnectHandler();
cancelConnectHandler();
};
}, []);
// Subscribe to WebSocket updates for agent runs
useEffect(() => {
if (!agent?.graph_id) return;
return api.onWebSocketConnect(() => {
refreshPageData(); // Sync up on (re)connect
// Subscribe to all executions for this agent
api.subscribeToGraphExecutions(agent.graph_id);
});
}, [api, agent?.graph_id, refreshPageData]);
// Handle execution updates
useEffect(() => {
const detachExecUpdateHandler = api.onWebSocketMessage(
"graph_execution_event",
(data) => {
if (data.graph_id != agent?.graph_id) return;
if (data.status == "COMPLETED") {
incrementRuns();
}
setAgentRuns((prev) => {
const index = prev.findIndex((run) => run.id === data.id);
if (index === -1) {
return [...prev, data];
}
const newRuns = [...prev];
newRuns[index] = { ...newRuns[index], ...data };
return newRuns;
});
if (data.id === selectedView.id) {
setSelectedRun((prev) => ({ ...prev, ...data }));
}
},
);
return () => {
detachExecUpdateHandler();
};
}, [api, agent?.graph_id, selectedView.id, incrementRuns]);
// Pre-load selectedRun based on selectedView
useEffect(() => {
if (selectedView.type != "run" || !selectedView.id) return;
const newSelectedRun = agentRuns.find((run) => run.id == selectedView.id);
if (selectedView.id !== selectedRun?.id) {
// Pull partial data from "cache" while waiting for the rest to load
setSelectedRun(newSelectedRun ?? null);
}
}, [api, selectedView, agentRuns, selectedRun?.id]);
// Load selectedRun based on selectedView; refresh on agent refresh
useEffect(() => {
if (selectedView.type != "run" || !selectedView.id || !agent) return;
api
.getGraphExecutionInfo(agent.graph_id, selectedView.id)
.then(async (run) => {
// Ensure corresponding graph version is available before rendering I/O
await getGraphVersion(run.graph_id, run.graph_version);
setSelectedRun(run);
});
}, [api, selectedView, agent, getGraphVersion]);
const fetchSchedules = useCallback(async () => {
if (!agent) return;
setSchedules(await api.listGraphExecutionSchedules(agent.graph_id));
}, [api, agent?.graph_id]);
useEffect(() => {
fetchSchedules();
}, [fetchSchedules]);
// =========================== ACTIONS ============================
const deleteRun = useCallback(
async (run: GraphExecutionMeta) => {
if (run.status == "RUNNING" || run.status == "QUEUED") {
await api.stopGraphExecution(run.graph_id, run.id);
}
await api.deleteGraphExecution(run.id);
setConfirmingDeleteAgentRun(null);
if (selectedView.type == "run" && selectedView.id == run.id) {
openRunDraftView();
}
setAgentRuns((runs) => runs.filter((r) => r.id !== run.id));
},
[api, selectedView, openRunDraftView],
);
const deletePreset = useCallback(
async (presetID: LibraryAgentPresetID) => {
await api.deleteLibraryAgentPreset(presetID);
setConfirmingDeleteAgentPreset(null);
if (selectedView.type == "preset" && selectedView.id == presetID) {
openRunDraftView();
}
setAgentPresets((presets) => presets.filter((p) => p.id !== presetID));
},
[api, selectedView, openRunDraftView],
);
const deleteSchedule = useCallback(
async (scheduleID: ScheduleID) => {
const removedSchedule =
await api.deleteGraphExecutionSchedule(scheduleID);
setSchedules((schedules) => {
const newSchedules = schedules.filter(
(s) => s.id !== removedSchedule.id,
);
if (
selectedView.type == "schedule" &&
selectedView.id == removedSchedule.id
) {
if (newSchedules.length > 0) {
// Select next schedule if available
selectSchedule(newSchedules[0].id);
} else {
// Reset to draft view if current schedule was deleted
openRunDraftView();
}
}
return newSchedules;
});
openRunDraftView();
},
[schedules, api],
);
const downloadGraph = useCallback(
async () =>
agent &&
// Export sanitized graph from backend
api
.getGraph(agent.graph_id, agent.graph_version, true)
.then((graph) =>
exportAsJSONFile(graph, `${graph.name}_v${graph.version}.json`),
),
[api, agent],
);
const copyAgent = useCallback(async () => {
setCopyAgentDialogOpen(false);
api
.forkLibraryAgent(agentID)
.then((newAgent) => {
router.push(`/library/agents/${newAgent.id}`);
})
.catch((error) => {
console.error("Error copying agent:", error);
toast({
title: "Error copying agent",
description: `An error occurred while copying the agent: ${error.message}`,
variant: "destructive",
});
});
}, [agentID, api, router, toast]);
const agentActions: ButtonAction[] = useMemo(
() => [
{
label: "Customize agent",
href: `/build?flowID=${agent?.graph_id}&flowVersion=${agent?.graph_version}`,
disabled: !agent?.can_access_graph,
},
{ label: "Export agent to file", callback: downloadGraph },
...(!agent?.can_access_graph
? [
{
label: "Edit a copy",
callback: () => setCopyAgentDialogOpen(true),
},
]
: []),
{
label: "Delete agent",
callback: () => setAgentDeleteDialogOpen(true),
},
],
[agent, downloadGraph],
);
const runGraph =
graphVersions.current[selectedRun?.graph_version ?? 0] ?? graph;
const onCreateSchedule = useCallback(
(schedule: Schedule) => {
setSchedules((prev) => [...prev, schedule]);
selectSchedule(schedule.id);
},
[selectView],
);
const onCreatePreset = useCallback(
(preset: LibraryAgentPreset) => {
setAgentPresets((prev) => [...prev, preset]);
selectPreset(preset.id);
},
[selectPreset],
);
const onUpdatePreset = useCallback(
(updated: LibraryAgentPreset) => {
setAgentPresets((prev) =>
prev.map((p) => (p.id === updated.id ? updated : p)),
);
selectPreset(updated.id);
},
[selectPreset],
);
if (!agent || !graph) {
return <LoadingBox className="h-[90vh]" />;
}
return (
<div className="container justify-stretch p-0 pt-16 lg:flex">
{/* Sidebar w/ list of runs */}
{/* TODO: render this below header in sm and md layouts */}
<AgentRunsSelectorList
className="agpt-div w-full border-b lg:w-auto lg:border-b-0 lg:border-r"
agent={agent}
agentRuns={agentRuns}
agentPresets={agentPresets}
schedules={schedules}
selectedView={selectedView}
onSelectRun={selectRun}
onSelectPreset={selectPreset}
onSelectSchedule={selectSchedule}
onSelectDraftNewRun={openRunDraftView}
doDeleteRun={setConfirmingDeleteAgentRun}
doDeletePreset={setConfirmingDeleteAgentPreset}
doDeleteSchedule={deleteSchedule}
/>
<div className="flex-1">
{/* Header */}
<div className="agpt-div w-full border-b">
<h1
data-testid="agent-title"
className="font-poppins text-3xl font-medium"
>
{
agent.name /* TODO: use dynamic/custom run title - https://github.com/Significant-Gravitas/AutoGPT/issues/9184 */
}
</h1>
</div>
{/* Run / Schedule views */}
{(selectedView.type == "run" && selectedView.id ? (
selectedRun && runGraph ? (
<AgentRunDetailsView
agent={agent}
graph={runGraph}
run={selectedRun}
agentActions={agentActions}
onRun={selectRun}
deleteRun={() => setConfirmingDeleteAgentRun(selectedRun)}
/>
) : null
) : selectedView.type == "run" ? (
/* Draft new runs / Create new presets */
<AgentRunDraftView
graph={graph}
triggerSetupInfo={agent.trigger_setup_info}
onRun={selectRun}
onCreateSchedule={onCreateSchedule}
onCreatePreset={onCreatePreset}
agentActions={agentActions}
/>
) : selectedView.type == "preset" ? (
/* Edit & update presets */
<AgentRunDraftView
graph={graph}
triggerSetupInfo={agent.trigger_setup_info}
agentPreset={
agentPresets.find((preset) => preset.id == selectedView.id)!
}
onRun={selectRun}
onCreateSchedule={onCreateSchedule}
onUpdatePreset={onUpdatePreset}
doDeletePreset={setConfirmingDeleteAgentPreset}
agentActions={agentActions}
/>
) : selectedView.type == "schedule" ? (
selectedSchedule &&
graph && (
<AgentScheduleDetailsView
graph={graph}
schedule={selectedSchedule}
// agent={agent}
agentActions={agentActions}
onForcedRun={selectRun}
doDeleteSchedule={deleteSchedule}
/>
)
) : null) || <LoadingBox className="h-[70vh]" />}
<DeleteConfirmDialog
entityType="agent"
open={agentDeleteDialogOpen}
onOpenChange={setAgentDeleteDialogOpen}
onDoDelete={() =>
agent &&
api.deleteLibraryAgent(agent.id).then(() => router.push("/library"))
}
/>
<DeleteConfirmDialog
entityType="agent run"
open={!!confirmingDeleteAgentRun}
onOpenChange={(open) => !open && setConfirmingDeleteAgentRun(null)}
onDoDelete={() =>
confirmingDeleteAgentRun && deleteRun(confirmingDeleteAgentRun)
}
/>
<DeleteConfirmDialog
entityType={agent.has_external_trigger ? "trigger" : "agent preset"}
open={!!confirmingDeleteAgentPreset}
onOpenChange={(open) => !open && setConfirmingDeleteAgentPreset(null)}
onDoDelete={() =>
confirmingDeleteAgentPreset &&
deletePreset(confirmingDeleteAgentPreset)
}
/>
{/* Copy agent confirmation dialog */}
<Dialog
onOpenChange={setCopyAgentDialogOpen}
open={copyAgentDialogOpen}
>
<DialogContent>
<DialogHeader>
<DialogTitle>You&apos;re making an editable copy</DialogTitle>
<DialogDescription className="pt-2">
The original Marketplace agent stays the same and cannot be
edited. We&apos;ll save a new version of this agent to your
Library. From there, you can customize it however you&apos;d
like by clicking &quot;Customize agent&quot; — this will open
the builder where you can see and modify the inner workings.
</DialogDescription>
</DialogHeader>
<DialogFooter className="justify-end">
<Button
type="button"
variant="outline"
onClick={() => setCopyAgentDialogOpen(false)}
>
Cancel
</Button>
<Button type="button" onClick={copyAgent}>
Continue
</Button>
</DialogFooter>
</DialogContent>
</Dialog>
</div>
</div>
);
}

2
autogpt_platform/frontend/src/components/agents/agent-run-details-view.tsx → autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-details-view.tsx
View File

@@ -36,7 +36,7 @@ import {
} from "@/components/agents/agent-run-status-chip";
import useCredits from "@/hooks/useCredits";
export default function AgentRunDetailsView({
export function AgentRunDetailsView({
agent,
graph,
run,

2
autogpt_platform/frontend/src/components/agents/agent-run-draft-view.tsx → autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx
View File

@@ -30,7 +30,7 @@ import {
useToastOnFail,
} from "@/components/molecules/Toast/use-toast";
export default function AgentRunDraftView({
export function AgentRunDraftView({
graph,
agentPreset,
triggerSetupInfo,

4
autogpt_platform/frontend/src/components/agents/agent-runs-selector-list.tsx → autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-runs-selector-list.tsx
View File

@@ -19,7 +19,7 @@ import { Separator } from "@/components/ui/separator";
import { agentRunStatusMap } from "@/components/agents/agent-run-status-chip";
import AgentRunSummaryCard from "@/components/agents/agent-run-summary-card";
import { Button } from "../atoms/Button/Button";
import { Button } from "../../../../../../../../components/atoms/Button/Button";
interface AgentRunsSelectorListProps {
agent: LibraryAgent;
@@ -38,7 +38,7 @@ interface AgentRunsSelectorListProps {
className?: string;
}
export default function AgentRunsSelectorList({
export function AgentRunsSelectorList({
agent,
agentRuns,
agentPresets,

2
autogpt_platform/frontend/src/components/agents/agent-schedule-details-view.tsx → autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-schedule-details-view.tsx
View File

@@ -20,7 +20,7 @@ import { useToastOnFail } from "@/components/molecules/Toast/use-toast";
import { humanizeCronExpression } from "@/lib/cron-expression-utils";
import { PlayIcon } from "lucide-react";
export default function AgentScheduleDetailsView({
export function AgentScheduleDetailsView({
graph,
schedule,
agentActions,

22
autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/loading.tsx
View File

@@ -1,21 +1,3 @@
import AgentFlowListSkeleton from "@/components/monitor/skeletons/AgentFlowListSkeleton";
import React from "react";
import FlowRunsListSkeleton from "@/components/monitor/skeletons/FlowRunsListSkeleton";
import FlowRunsStatusSkeleton from "@/components/monitor/skeletons/FlowRunsStatusSkeleton";
import { AgentRunsLoading } from "./components/AgentRunsView/components/AgentRunsLoading";
export default function MonitorLoadingSkeleton() {
return (
<div className="space-y-4 p-4">
<div className="grid grid-cols-1 gap-4 md:grid-cols-3">
{/* Agents Section */}
<AgentFlowListSkeleton />
{/* Runs Section */}
<FlowRunsListSkeleton />
{/* Stats Section */}
<FlowRunsStatusSkeleton />
</div>
</div>
);
}
export default AgentRunsLoading;

622
autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/page.tsx
View File

@@ -1,622 +1,16 @@
"use client";
import { useParams, useRouter } from "next/navigation";
import { useQueryState } from "nuqs";
import React, {
useCallback,
useEffect,
useMemo,
useRef,
useState,
} from "react";
import {
Graph,
GraphExecution,
GraphExecutionID,
GraphExecutionMeta,
GraphID,
LibraryAgent,
LibraryAgentID,
LibraryAgentPreset,
LibraryAgentPresetID,
Schedule,
ScheduleID,
} from "@/lib/autogpt-server-api";
import { useBackendAPI } from "@/lib/autogpt-server-api/context";
import { exportAsJSONFile } from "@/lib/utils";
import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
import AgentRunDetailsView from "@/components/agents/agent-run-details-view";
import AgentRunDraftView from "@/components/agents/agent-run-draft-view";
import AgentRunsSelectorList from "@/components/agents/agent-runs-selector-list";
import AgentScheduleDetailsView from "@/components/agents/agent-schedule-details-view";
import DeleteConfirmDialog from "@/components/agptui/delete-confirm-dialog";
import type { ButtonAction } from "@/components/agptui/types";
import { useOnboarding } from "@/components/onboarding/onboarding-provider";
import { Button } from "@/components/ui/button";
import {
Dialog,
DialogContent,
DialogDescription,
DialogFooter,
DialogHeader,
DialogTitle,
} from "@/components/ui/dialog";
import LoadingBox, { LoadingSpinner } from "@/components/ui/loading";
import { useToast } from "@/components/molecules/Toast/use-toast";
import { OldAgentLibraryView } from "./components/OldAgentLibraryView/OldAgentLibraryView";
import { AgentRunsView } from "./components/AgentRunsView/AgentRunsView";
export default function AgentRunsPage(): React.ReactElement {
const { id: agentID }: { id: LibraryAgentID } = useParams();
const [executionId, setExecutionId] = useQueryState("executionId");
const { toast } = useToast();
const router = useRouter();
const api = useBackendAPI();
export default function AgentLibraryPage() {
const isNewAgentRunsEnabled = useGetFlag(Flag.NEW_AGENT_RUNS);
// ============================ STATE =============================
const [graph, setGraph] = useState<Graph | null>(null); // Graph version corresponding to LibraryAgent
const [agent, setAgent] = useState<LibraryAgent | null>(null);
const [agentRuns, setAgentRuns] = useState<GraphExecutionMeta[]>([]);
const [agentPresets, setAgentPresets] = useState<LibraryAgentPreset[]>([]);
const [schedules, setSchedules] = useState<Schedule[]>([]);
const [selectedView, selectView] = useState<
| { type: "run"; id?: GraphExecutionID }
| { type: "preset"; id: LibraryAgentPresetID }
| { type: "schedule"; id: ScheduleID }
>({ type: "run" });
const [selectedRun, setSelectedRun] = useState<
GraphExecution | GraphExecutionMeta | null
>(null);
const selectedSchedule =
selectedView.type == "schedule"
? schedules.find((s) => s.id == selectedView.id)
: null;
const [isFirstLoad, setIsFirstLoad] = useState<boolean>(true);
const [agentDeleteDialogOpen, setAgentDeleteDialogOpen] =
useState<boolean>(false);
const [confirmingDeleteAgentRun, setConfirmingDeleteAgentRun] =
useState<GraphExecutionMeta | null>(null);
const [confirmingDeleteAgentPreset, setConfirmingDeleteAgentPreset] =
useState<LibraryAgentPresetID | null>(null);
const {
state: onboardingState,
updateState: updateOnboardingState,
incrementRuns,
} = useOnboarding();
const [copyAgentDialogOpen, setCopyAgentDialogOpen] = useState(false);
// Set page title with agent name
useEffect(() => {
if (agent) {
document.title = `${agent.name} - Library - AutoGPT Platform`;
}
}, [agent]);
const openRunDraftView = useCallback(() => {
selectView({ type: "run" });
}, []);
const selectRun = useCallback((id: GraphExecutionID) => {
selectView({ type: "run", id });
}, []);
const selectPreset = useCallback((id: LibraryAgentPresetID) => {
selectView({ type: "preset", id });
}, []);
const selectSchedule = useCallback((id: ScheduleID) => {
selectView({ type: "schedule", id });
}, []);
const graphVersions = useRef<Record<number, Graph>>({});
const loadingGraphVersions = useRef<Record<number, Promise<Graph>>>({});
const getGraphVersion = useCallback(
async (graphID: GraphID, version: number) => {
if (version in graphVersions.current)
return graphVersions.current[version];
if (version in loadingGraphVersions.current)
return loadingGraphVersions.current[version];
const pendingGraph = api.getGraph(graphID, version).then((graph) => {
graphVersions.current[version] = graph;
return graph;
});
// Cache promise as well to avoid duplicate requests
loadingGraphVersions.current[version] = pendingGraph;
return pendingGraph;
},
[api, graphVersions, loadingGraphVersions],
);
// Reward user for viewing results of their onboarding agent
useEffect(() => {
if (
!onboardingState ||
!selectedRun ||
onboardingState.completedSteps.includes("GET_RESULTS")
)
return;
if (selectedRun.id === onboardingState.onboardingAgentExecutionId) {
updateOnboardingState({
completedSteps: [...onboardingState.completedSteps, "GET_RESULTS"],
});
}
}, [selectedRun, onboardingState, updateOnboardingState]);
const lastRefresh = useRef<number>(0);
const refreshPageData = useCallback(() => {
if (Date.now() - lastRefresh.current < 2e3) return; // 2 second debounce
lastRefresh.current = Date.now();
api.getLibraryAgent(agentID).then((agent) => {
setAgent(agent);
getGraphVersion(agent.graph_id, agent.graph_version).then(
(_graph) =>
(graph && graph.version == _graph.version) || setGraph(_graph),
);
Promise.all([
api.getGraphExecutions(agent.graph_id),
api.listLibraryAgentPresets({
graph_id: agent.graph_id,
page_size: 100,
}),
]).then(([runs, presets]) => {
setAgentRuns(runs);
setAgentPresets(presets.presets);
// Preload the corresponding graph versions for the latest 10 runs
new Set(runs.slice(0, 10).map((run) => run.graph_version)).forEach(
(version) => getGraphVersion(agent.graph_id, version),
);
});
});
}, [api, agentID, getGraphVersion, graph]);
// On first load: select the latest run
useEffect(() => {
// Only for first load or first execution
if (selectedView.id || !isFirstLoad) return;
if (agentRuns.length == 0 && agentPresets.length == 0) return;
setIsFirstLoad(false);
if (agentRuns.length > 0) {
// select latest run
const latestRun = agentRuns.reduce((latest, current) => {
if (latest.started_at && !current.started_at) return current;
else if (!latest.started_at) return latest;
return latest.started_at > current.started_at ? latest : current;
}, agentRuns[0]);
selectRun(latestRun.id);
} else {
// select top preset
const latestPreset = agentPresets.toSorted(
(a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
)[0];
selectPreset(latestPreset.id);
}
}, [
isFirstLoad,
selectedView.id,
agentRuns,
agentPresets,
selectRun,
selectPreset,
]);
useEffect(() => {
if (executionId) {
selectRun(executionId as GraphExecutionID);
setExecutionId(null);
}
}, [executionId, selectRun, setExecutionId]);
// Initial load
useEffect(() => {
refreshPageData();
// Show a toast when the WebSocket connection disconnects
let connectionToast: ReturnType<typeof toast> | null = null;
const cancelDisconnectHandler = api.onWebSocketDisconnect(() => {
connectionToast ??= toast({
title: "Connection to server was lost",
variant: "destructive",
description: (
<div className="flex items-center">
Trying to reconnect...
<LoadingSpinner className="ml-1.5 size-3.5" />
</div>
),
duration: Infinity,
dismissable: true,
});
});
const cancelConnectHandler = api.onWebSocketConnect(() => {
if (connectionToast)
connectionToast.update({
id: connectionToast.id,
title: "✅ Connection re-established",
variant: "default",
description: (
<div className="flex items-center">
Refreshing data...
<LoadingSpinner className="ml-1.5 size-3.5" />
</div>
),
duration: 2000,
dismissable: true,
});
connectionToast = null;
});
return () => {
cancelDisconnectHandler();
cancelConnectHandler();
};
}, []);
// Subscribe to WebSocket updates for agent runs
useEffect(() => {
if (!agent?.graph_id) return;
return api.onWebSocketConnect(() => {
refreshPageData(); // Sync up on (re)connect
// Subscribe to all executions for this agent
api.subscribeToGraphExecutions(agent.graph_id);
});
}, [api, agent?.graph_id, refreshPageData]);
// Handle execution updates
useEffect(() => {
const detachExecUpdateHandler = api.onWebSocketMessage(
"graph_execution_event",
(data) => {
if (data.graph_id != agent?.graph_id) return;
if (data.status == "COMPLETED") {
incrementRuns();
}
setAgentRuns((prev) => {
const index = prev.findIndex((run) => run.id === data.id);
if (index === -1) {
return [...prev, data];
}
const newRuns = [...prev];
newRuns[index] = { ...newRuns[index], ...data };
return newRuns;
});
if (data.id === selectedView.id) {
setSelectedRun((prev) => ({ ...prev, ...data }));
}
},
);
return () => {
detachExecUpdateHandler();
};
}, [api, agent?.graph_id, selectedView.id, incrementRuns]);
// Pre-load selectedRun based on selectedView
useEffect(() => {
if (selectedView.type != "run" || !selectedView.id) return;
const newSelectedRun = agentRuns.find((run) => run.id == selectedView.id);
if (selectedView.id !== selectedRun?.id) {
// Pull partial data from "cache" while waiting for the rest to load
setSelectedRun(newSelectedRun ?? null);
}
}, [api, selectedView, agentRuns, selectedRun?.id]);
// Load selectedRun based on selectedView; refresh on agent refresh
useEffect(() => {
if (selectedView.type != "run" || !selectedView.id || !agent) return;
api
.getGraphExecutionInfo(agent.graph_id, selectedView.id)
.then(async (run) => {
// Ensure corresponding graph version is available before rendering I/O
await getGraphVersion(run.graph_id, run.graph_version);
setSelectedRun(run);
});
}, [api, selectedView, agent, getGraphVersion]);
const fetchSchedules = useCallback(async () => {
if (!agent) return;
setSchedules(await api.listGraphExecutionSchedules(agent.graph_id));
}, [api, agent?.graph_id]);
useEffect(() => {
fetchSchedules();
}, [fetchSchedules]);
// =========================== ACTIONS ============================
const deleteRun = useCallback(
async (run: GraphExecutionMeta) => {
if (run.status == "RUNNING" || run.status == "QUEUED") {
await api.stopGraphExecution(run.graph_id, run.id);
}
await api.deleteGraphExecution(run.id);
setConfirmingDeleteAgentRun(null);
if (selectedView.type == "run" && selectedView.id == run.id) {
openRunDraftView();
}
setAgentRuns((runs) => runs.filter((r) => r.id !== run.id));
},
[api, selectedView, openRunDraftView],
);
const deletePreset = useCallback(
async (presetID: LibraryAgentPresetID) => {
await api.deleteLibraryAgentPreset(presetID);
setConfirmingDeleteAgentPreset(null);
if (selectedView.type == "preset" && selectedView.id == presetID) {
openRunDraftView();
}
setAgentPresets((presets) => presets.filter((p) => p.id !== presetID));
},
[api, selectedView, openRunDraftView],
);
const deleteSchedule = useCallback(
async (scheduleID: ScheduleID) => {
const removedSchedule =
await api.deleteGraphExecutionSchedule(scheduleID);
setSchedules((schedules) => {
const newSchedules = schedules.filter(
(s) => s.id !== removedSchedule.id,
);
if (
selectedView.type == "schedule" &&
selectedView.id == removedSchedule.id
) {
if (newSchedules.length > 0) {
// Select next schedule if available
selectSchedule(newSchedules[0].id);
} else {
// Reset to draft view if current schedule was deleted
openRunDraftView();
}
}
return newSchedules;
});
openRunDraftView();
},
[schedules, api],
);
const downloadGraph = useCallback(
async () =>
agent &&
// Export sanitized graph from backend
api
.getGraph(agent.graph_id, agent.graph_version, true)
.then((graph) =>
exportAsJSONFile(graph, `${graph.name}_v${graph.version}.json`),
),
[api, agent],
);
const copyAgent = useCallback(async () => {
setCopyAgentDialogOpen(false);
api
.forkLibraryAgent(agentID)
.then((newAgent) => {
router.push(`/library/agents/${newAgent.id}`);
})
.catch((error) => {
console.error("Error copying agent:", error);
toast({
title: "Error copying agent",
description: `An error occurred while copying the agent: ${error.message}`,
variant: "destructive",
});
});
}, [agentID, api, router, toast]);
const agentActions: ButtonAction[] = useMemo(
() => [
{
label: "Customize agent",
href: `/build?flowID=${agent?.graph_id}&flowVersion=${agent?.graph_version}`,
disabled: !agent?.can_access_graph,
},
{ label: "Export agent to file", callback: downloadGraph },
...(!agent?.can_access_graph
? [
{
label: "Edit a copy",
callback: () => setCopyAgentDialogOpen(true),
},
]
: []),
{
label: "Delete agent",
callback: () => setAgentDeleteDialogOpen(true),
},
],
[agent, downloadGraph],
);
const runGraph =
graphVersions.current[selectedRun?.graph_version ?? 0] ?? graph;
const onCreateSchedule = useCallback(
(schedule: Schedule) => {
setSchedules((prev) => [...prev, schedule]);
selectSchedule(schedule.id);
},
[selectView],
);
const onCreatePreset = useCallback(
(preset: LibraryAgentPreset) => {
setAgentPresets((prev) => [...prev, preset]);
selectPreset(preset.id);
},
[selectPreset],
);
const onUpdatePreset = useCallback(
(updated: LibraryAgentPreset) => {
setAgentPresets((prev) =>
prev.map((p) => (p.id === updated.id ? updated : p)),
);
selectPreset(updated.id);
},
[selectPreset],
);
if (!agent || !graph) {
return <LoadingBox className="h-[90vh]" />;
if (isNewAgentRunsEnabled) {
return <AgentRunsView />;
}
return (
<div className="container justify-stretch p-0 pt-16 lg:flex">
{/* Sidebar w/ list of runs */}
{/* TODO: render this below header in sm and md layouts */}
<AgentRunsSelectorList
className="agpt-div w-full border-b lg:w-auto lg:border-b-0 lg:border-r"
agent={agent}
agentRuns={agentRuns}
agentPresets={agentPresets}
schedules={schedules}
selectedView={selectedView}
onSelectRun={selectRun}
onSelectPreset={selectPreset}
onSelectSchedule={selectSchedule}
onSelectDraftNewRun={openRunDraftView}
doDeleteRun={setConfirmingDeleteAgentRun}
doDeletePreset={setConfirmingDeleteAgentPreset}
doDeleteSchedule={deleteSchedule}
/>
<div className="flex-1">
{/* Header */}
<div className="agpt-div w-full border-b">
<h1
data-testid="agent-title"
className="font-poppins text-3xl font-medium"
>
{
agent.name /* TODO: use dynamic/custom run title - https://github.com/Significant-Gravitas/AutoGPT/issues/9184 */
}
</h1>
</div>
{/* Run / Schedule views */}
{(selectedView.type == "run" && selectedView.id ? (
selectedRun && runGraph ? (
<AgentRunDetailsView
agent={agent}
graph={runGraph}
run={selectedRun}
agentActions={agentActions}
onRun={selectRun}
deleteRun={() => setConfirmingDeleteAgentRun(selectedRun)}
/>
) : null
) : selectedView.type == "run" ? (
/* Draft new runs / Create new presets */
<AgentRunDraftView
graph={graph}
triggerSetupInfo={agent.trigger_setup_info}
onRun={selectRun}
onCreateSchedule={onCreateSchedule}
onCreatePreset={onCreatePreset}
agentActions={agentActions}
/>
) : selectedView.type == "preset" ? (
/* Edit & update presets */
<AgentRunDraftView
graph={graph}
triggerSetupInfo={agent.trigger_setup_info}
agentPreset={
agentPresets.find((preset) => preset.id == selectedView.id)!
}
onRun={selectRun}
onCreateSchedule={onCreateSchedule}
onUpdatePreset={onUpdatePreset}
doDeletePreset={setConfirmingDeleteAgentPreset}
agentActions={agentActions}
/>
) : selectedView.type == "schedule" ? (
selectedSchedule &&
graph && (
<AgentScheduleDetailsView
graph={graph}
schedule={selectedSchedule}
// agent={agent}
agentActions={agentActions}
onForcedRun={selectRun}
doDeleteSchedule={deleteSchedule}
/>
)
) : null) || <LoadingBox className="h-[70vh]" />}
<DeleteConfirmDialog
entityType="agent"
open={agentDeleteDialogOpen}
onOpenChange={setAgentDeleteDialogOpen}
onDoDelete={() =>
agent &&
api.deleteLibraryAgent(agent.id).then(() => router.push("/library"))
}
/>
<DeleteConfirmDialog
entityType="agent run"
open={!!confirmingDeleteAgentRun}
onOpenChange={(open) => !open && setConfirmingDeleteAgentRun(null)}
onDoDelete={() =>
confirmingDeleteAgentRun && deleteRun(confirmingDeleteAgentRun)
}
/>
<DeleteConfirmDialog
entityType={agent.has_external_trigger ? "trigger" : "agent preset"}
open={!!confirmingDeleteAgentPreset}
onOpenChange={(open) => !open && setConfirmingDeleteAgentPreset(null)}
onDoDelete={() =>
confirmingDeleteAgentPreset &&
deletePreset(confirmingDeleteAgentPreset)
}
/>
{/* Copy agent confirmation dialog */}
<Dialog
onOpenChange={setCopyAgentDialogOpen}
open={copyAgentDialogOpen}
>
<DialogContent>
<DialogHeader>
<DialogTitle>You&apos;re making an editable copy</DialogTitle>
<DialogDescription className="pt-2">
The original Marketplace agent stays the same and cannot be
edited. We&apos;ll save a new version of this agent to your
Library. From there, you can customize it however you&apos;d
like by clicking &quot;Customize agent&quot; — this will open
the builder where you can see and modify the inner workings.
</DialogDescription>
</DialogHeader>
<DialogFooter className="justify-end">
<Button
type="button"
variant="outline"
onClick={() => setCopyAgentDialogOpen(false)}
>
Cancel
</Button>
<Button type="button" onClick={copyAgent}>
Continue
</Button>
</DialogFooter>
</DialogContent>
</Dialog>
</div>
</div>
);
return <OldAgentLibraryView />;
}

4
autogpt_platform/frontend/src/app/(platform)/marketplace/agent/[creator]/[slug]/page.tsx
View File

@@ -1,5 +1,5 @@
import BackendAPI from "@/lib/autogpt-server-api";
import { BreadCrumbs } from "@/components/agptui/BreadCrumbs";
import { Breadcrumbs } from "@/components/molecules/Breadcrumbs/Breadcrumbs";
import { AgentInfo } from "@/components/agptui/AgentInfo";
import { AgentImages } from "@/components/agptui/AgentImages";
import { AgentsSection } from "@/components/agptui/composite/AgentsSection";
@@ -73,7 +73,7 @@ export default async function MarketplaceAgentPage({
return (
<div className="mx-auto w-screen max-w-[1360px]">
<main className="mt-5 px-4">
<BreadCrumbs items={breadcrumbs} />
<Breadcrumbs items={breadcrumbs} />
<div className="mt-4 flex flex-col items-start gap-4 sm:mt-6 sm:gap-6 md:mt-8 md:flex-row md:gap-8">
<div className="w-full md:w-auto md:shrink-0">

4
autogpt_platform/frontend/src/app/(platform)/marketplace/creator/[creator]/page.tsx
View File

@@ -1,6 +1,6 @@
import BackendAPI from "@/lib/autogpt-server-api";
import { AgentsSection } from "@/components/agptui/composite/AgentsSection";
import { BreadCrumbs } from "@/components/agptui/BreadCrumbs";
import { Breadcrumbs } from "@/components/molecules/Breadcrumbs/Breadcrumbs";
import { Metadata } from "next";
import { CreatorInfoCard } from "@/components/agptui/CreatorInfoCard";
import { CreatorLinks } from "@/components/agptui/CreatorLinks";
@@ -49,7 +49,7 @@ export default async function Page({
return (
<div className="mx-auto w-screen max-w-[1360px]">
<main className="mt-5 px-4">
<BreadCrumbs
<Breadcrumbs
items={[
{ name: "Store", link: "/marketplace" },
{ name: creator.name, link: "#" },

10
autogpt_platform/frontend/src/app/(platform)/profile/(user)/api_keys/components/APIKeySection/APIKeySection.tsx
View File

@@ -44,9 +44,9 @@ export function APIKeysSection() {
</TableHeader>
<TableBody>
{apiKeys.map((key) => (
<TableRow key={key.id}>
<TableRow key={key.id} data-testid="api-key-row">
<TableCell>{key.name}</TableCell>
<TableCell>
<TableCell data-testid="api-key-id">
<div className="rounded-md border p-1 px-2 text-xs">
{`${key.prefix}******************${key.postfix}`}
</div>
@@ -76,7 +76,11 @@ export function APIKeysSection() {
<TableCell>
<DropdownMenu>
<DropdownMenuTrigger asChild>
<Button variant="ghost" size="sm">
<Button
data-testid="api-key-actions"
variant="ghost"
size="sm"
>
<MoreVertical className="h-4 w-4" />
</Button>
</DropdownMenuTrigger>

10
autogpt_platform/frontend/src/app/(platform)/profile/(user)/dashboard/components/AgentTable/AgentTable.tsx
View File

@@ -7,6 +7,7 @@ import {
AgentTableRow,
AgentTableRowProps,
} from "../AgentTableRow/AgentTableRow";
import { StoreSubmissionEditRequest } from "@/app/api/__generated__/models/storeSubmissionEditRequest";
export interface AgentTableProps {
agents: Omit<
@@ -15,15 +16,23 @@ export interface AgentTableProps {
| "selectedAgents"
| "onViewSubmission"
| "onDeleteSubmission"
| "onEditSubmission"
>[];
onViewSubmission: (submission: StoreSubmission) => void;
onDeleteSubmission: (submission_id: string) => void;
onEditSubmission: (
submission: StoreSubmissionEditRequest & {
store_listing_version_id: string | undefined;
agent_id: string;
},
) => void;
}
export const AgentTable: React.FC<AgentTableProps> = ({
agents,
onViewSubmission,
onDeleteSubmission,
onEditSubmission,
}) => {
return (
<div className="w-full" data-testid="agent-table">
@@ -62,6 +71,7 @@ export const AgentTable: React.FC<AgentTableProps> = ({
{...agent}
onViewSubmission={onViewSubmission}
onDeleteSubmission={onDeleteSubmission}
onEditSubmission={onEditSubmission}
/>
<div className="block md:hidden">
<AgentTableCard

7
autogpt_platform/frontend/src/app/(platform)/profile/(user)/dashboard/components/AgentTableCard/AgentTableCard.tsx
View File

@@ -3,8 +3,8 @@
import Image from "next/image";
import { IconStarFilled, IconMore } from "@/components/ui/icons";
import { StoreSubmission } from "@/app/api/__generated__/models/storeSubmission";
import { Status, StatusType } from "@/components/agptui/Status";
import { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
import { Status } from "@/components/agptui/Status";
export interface AgentTableCardProps {
agent_id: string;
@@ -14,7 +14,7 @@ export interface AgentTableCardProps {
description: string;
imageSrc: string[];
dateSubmitted: string;
status: StatusType;
status: SubmissionStatus;
runs: number;
rating: number;
id: number;
@@ -44,8 +44,7 @@ export const AgentTableCard = ({
description,
image_urls: imageSrc,
date_submitted: dateSubmitted,
// SafeCast: status is a string from the API...
status: status.toUpperCase() as SubmissionStatus,
status: status,
runs,
rating,
});

59
autogpt_platform/frontend/src/app/(platform)/profile/(user)/dashboard/components/AgentTableRow/AgentTableRow.tsx
View File

@@ -4,7 +4,7 @@ import Image from "next/image";
import { Text } from "@/components/atoms/Text/Text";
import * as DropdownMenu from "@radix-ui/react-dropdown-menu";
import { Status, StatusType } from "@/components/agptui/Status";
import { Status } from "@/components/agptui/Status";
import { useAgentTableRow } from "./useAgentTableRow";
import { StoreSubmission } from "@/app/api/__generated__/models/storeSubmission";
import {
@@ -13,7 +13,10 @@ import {
ImageBroken,
Star,
Trash,
PencilSimple,
} from "@phosphor-icons/react/dist/ssr";
import { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
import { StoreSubmissionEditRequest } from "@/app/api/__generated__/models/storeSubmissionEditRequest";
export interface AgentTableRowProps {
agent_id: string;
@@ -23,13 +26,22 @@ export interface AgentTableRowProps {
description: string;
imageSrc: string[];
date_submitted: string;
status: StatusType;
status: SubmissionStatus;
runs: number;
rating: number;
dateSubmitted: string;
id: number;
video_url?: string;
categories?: string[];
store_listing_version_id?: string;
onViewSubmission: (submission: StoreSubmission) => void;
onDeleteSubmission: (submission_id: string) => void;
onEditSubmission: (
submission: StoreSubmissionEditRequest & {
store_listing_version_id: string | undefined;
agent_id: string;
},
) => void;
}
export const AgentTableRow = ({
@@ -44,13 +56,18 @@ export const AgentTableRow = ({
runs,
rating,
id,
video_url,
categories,
store_listing_version_id,
onViewSubmission,
onDeleteSubmission,
onEditSubmission,
}: AgentTableRowProps) => {
const { handleView, handleDelete } = useAgentTableRow({
const { handleView, handleDelete, handleEdit } = useAgentTableRow({
id,
onViewSubmission,
onDeleteSubmission,
onEditSubmission,
agent_id,
agent_version,
agentName,
@@ -58,15 +75,23 @@ export const AgentTableRow = ({
description,
imageSrc,
dateSubmitted,
status: status.toUpperCase(),
status,
runs,
rating,
video_url,
categories,
store_listing_version_id,
});
// Determine if we should show Edit or View button
const canEdit =
status === SubmissionStatus.APPROVED || status === SubmissionStatus.PENDING;
return (
<div
data-testid="agent-table-row"
data-agent-name={agentName}
data-agent-id={agent_id}
data-submission-id={store_listing_version_id}
className="hidden items-center border-b border-neutral-300 px-4 py-4 hover:bg-neutral-50 dark:border-neutral-700 dark:hover:bg-neutral-800 md:flex"
>
<div className="grid w-full grid-cols-[minmax(400px,1fr),180px,140px,100px,100px,40px] items-center gap-4">
@@ -139,13 +164,23 @@ export const AgentTableRow = ({
<DotsThreeVerticalIcon className="h-5 w-5 text-neutral-800" />
</DropdownMenu.Trigger>
<DropdownMenu.Content className="z-10 rounded-xl border bg-white p-1 shadow-md dark:bg-gray-800">
<DropdownMenu.Item
onSelect={handleView}
className="flex cursor-pointer items-center rounded-md px-3 py-2 hover:bg-gray-100 dark:hover:bg-gray-700"
>
<Eye className="mr-2 h-4 w-4 dark:text-gray-100" />
<span className="dark:text-gray-100">View</span>
</DropdownMenu.Item>
{canEdit ? (
<DropdownMenu.Item
onSelect={handleEdit}
className="flex cursor-pointer items-center rounded-md px-3 py-2 hover:bg-gray-100 dark:hover:bg-gray-700"
>
<PencilSimple className="mr-2 h-4 w-4 dark:text-gray-100" />
<span className="dark:text-gray-100">Edit</span>
</DropdownMenu.Item>
) : (
<DropdownMenu.Item
onSelect={handleView}
className="flex cursor-pointer items-center rounded-md px-3 py-2 hover:bg-gray-100 dark:hover:bg-gray-700"
>
<Eye className="mr-2 h-4 w-4 dark:text-gray-100" />
<span className="dark:text-gray-100">View</span>
</DropdownMenu.Item>
)}
<DropdownMenu.Separator className="my-1 h-px bg-gray-300 dark:bg-gray-600" />
<DropdownMenu.Item
onSelect={handleDelete}

38
autogpt_platform/frontend/src/app/(platform)/profile/(user)/dashboard/components/AgentTableRow/useAgentTableRow.ts
View File

@@ -1,10 +1,17 @@
import { StoreSubmission } from "@/app/api/__generated__/models/storeSubmission";
import { StoreSubmissionEditRequest } from "@/app/api/__generated__/models/storeSubmissionEditRequest";
import { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
interface useAgentTableRowProps {
id: number;
onViewSubmission: (submission: StoreSubmission) => void;
onDeleteSubmission: (submission_id: string) => void;
onEditSubmission: (
submission: StoreSubmissionEditRequest & {
store_listing_version_id: string | undefined;
agent_id: string;
},
) => void;
agent_id: string;
agent_version: number;
agentName: string;
@@ -12,14 +19,18 @@ interface useAgentTableRowProps {
description: string;
imageSrc: string[];
dateSubmitted: string;
status: string;
status: SubmissionStatus;
runs: number;
rating: number;
video_url?: string;
categories?: string[];
store_listing_version_id?: string;
}
export const useAgentTableRow = ({
onViewSubmission,
onDeleteSubmission,
onEditSubmission,
agent_id,
agent_version,
agentName,
@@ -30,6 +41,9 @@ export const useAgentTableRow = ({
status,
runs,
rating,
video_url,
categories,
store_listing_version_id,
}: useAgentTableRowProps) => {
const handleView = () => {
onViewSubmission({
@@ -41,16 +55,32 @@ export const useAgentTableRow = ({
description,
image_urls: imageSrc,
date_submitted: dateSubmitted,
// SafeCast: status is a string from the API...
status: status.toUpperCase() as SubmissionStatus,
status: status,
runs,
rating,
video_url,
categories,
store_listing_version_id,
} satisfies StoreSubmission);
};
const handleEdit = () => {
onEditSubmission({
name: agentName,
sub_heading,
description,
image_urls: imageSrc,
video_url,
categories,
changes_summary: "Update Submission",
store_listing_version_id,
agent_id,
});
};
const handleDelete = () => {
onDeleteSubmission(agent_id);
};
return { handleView, handleDelete };
return { handleView, handleDelete, handleEdit };
};

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