Merge branch 'dev' into gmail-reply-draft

Backend for the Blocks Menu Redesign.

### Changes 🏗️

- Add optional `agent_name` to the `AgentExecutorBlock` - displayed as
the block name in the Builder
- Include `output_schema` in the `LibraryAgent` model
- Make `v2.store.db.py:get_store_agents` accept multiple creators filter
- Add `api/builder` router with endpoints (and accompanying logic in
`v2/builder/db` and models in `v2/builder/models`)
  - `/suggestions`: elements for the suggestions tab
  - `/categories`: categories with a number of blocks per each
  - `/blocks`: blocks based on category, type or provider
  - `/providers`: integration providers with their block counts
- `/serach`: search blocks (including integrations), marketplace agents
and user library agents
  - `/counts`: element counts for each category in the Blocks Menu.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Modified function `get_store_agents` works in existing code paths
  - [x] Agent executor block works
  - [x] New endpoints work
  - [x] Existing Builder menu is unaffected

---------

Co-authored-by: Abhimanyu Yadav <abhimanyu1992002@gmail.com>
Co-authored-by: Abhimanyu Yadav <122007096+Abhi1992002@users.noreply.github.com>

.github/copilot-instructions.md

@@ -0,0 +1,244 @@
+# GitHub Copilot Instructions for AutoGPT
+
+This file provides comprehensive onboarding information for GitHub Copilot coding agent to work efficiently with the AutoGPT repository.
+
+## Repository Overview
+
+**AutoGPT** is a powerful platform for creating, deploying, and managing continuous AI agents that automate complex workflows. This is a large monorepo (~150MB) containing multiple components:
+
+- **AutoGPT Platform** (`autogpt_platform/`) - Main focus: Modern AI agent platform (Polyform Shield License)
+- **Classic AutoGPT** (`classic/`) - Legacy agent system (MIT License)
+- **Documentation** (`docs/`) - MkDocs-based documentation site
+- **Infrastructure** - Docker configurations, CI/CD, and development tools
+
+**Primary Languages & Frameworks:**
+- **Backend**: Python 3.10-3.13, FastAPI, Prisma ORM, PostgreSQL, RabbitMQ
+- **Frontend**: TypeScript, Next.js 15, React, Tailwind CSS, Radix UI
+- **Development**: Docker, Poetry, pnpm, Playwright, Storybook
+
+## Build and Validation Instructions
+
+### Essential Setup Commands
+
+**Always run these commands in the correct directory and in this order:**
+
+1. **Initial Setup** (required once):
+   ```bash
+   # Clone and enter repository
+   git clone <repo> && cd AutoGPT
+   
+   # Start all services (database, redis, rabbitmq, clamav)
+   cd autogpt_platform && docker compose --profile local up deps --build --detach
+   ```
+
+2. **Backend Setup** (always run before backend development):
+   ```bash
+   cd autogpt_platform/backend
+   poetry install                    # Install dependencies
+   poetry run prisma migrate dev     # Run database migrations
+   poetry run prisma generate        # Generate Prisma client
+   ```
+
+3. **Frontend Setup** (always run before frontend development):
+   ```bash
+   cd autogpt_platform/frontend
+   pnpm install                      # Install dependencies
+   ```
+
+### Runtime Requirements
+
+**Critical:** Always ensure Docker services are running before starting development:
+```bash
+cd autogpt_platform && docker compose --profile local up deps --build --detach
+```
+
+**Python Version:** Use Python 3.11 (required; managed by Poetry via pyproject.toml)
+**Node.js Version:** Use Node.js 21+ with pnpm package manager
+
+### Development Commands
+
+**Backend Development:**
+```bash
+cd autogpt_platform/backend
+poetry run serve                     # Start development server (port 8000)
+poetry run test                      # Run all tests (requires ~5 minutes)
+poetry run pytest path/to/test.py    # Run specific test
+poetry run format                    # Format code (Black + isort) - always run first
+poetry run lint                      # Lint code (ruff) - run after format
+```
+
+**Frontend Development:**
+```bash
+cd autogpt_platform/frontend
+pnpm dev                            # Start development server (port 3000) - use for active development
+pnpm build                          # Build for production (only needed for E2E tests or deployment)
+pnpm test                           # Run Playwright E2E tests (requires build first)
+pnpm test-ui                        # Run tests with UI
+pnpm format                         # Format and lint code
+pnpm storybook                      # Start component development server
+```
+
+### Testing Strategy
+
+**Backend Tests:**
+- **Block Tests**: `poetry run pytest backend/blocks/test/test_block.py -xvs` (validates all blocks)
+- **Specific Block**: `poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[BlockName]' -xvs`
+- **Snapshot Tests**: Use `--snapshot-update` when output changes, always review with `git diff`
+
+**Frontend Tests:**
+- **E2E Tests**: Always run `pnpm dev` before `pnpm test` (Playwright requires running instance)
+- **Component Tests**: Use Storybook for isolated component development
+
+### Critical Validation Steps
+
+**Before committing changes:**
+1. Run `poetry run format` (backend) and `pnpm format` (frontend)
+2. Ensure all tests pass in modified areas
+3. Verify Docker services are still running
+4. Check that database migrations apply cleanly
+
+**Common Issues & Workarounds:**
+- **Prisma issues**: Run `poetry run prisma generate` after schema changes
+- **Permission errors**: Ensure Docker has proper permissions
+- **Port conflicts**: Check the `docker-compose.yml` file for the current list of exposed ports. You can list all mapped ports with:
+- **Test timeouts**: Backend tests can take 5+ minutes, use `-x` flag to stop on first failure
+
+## Project Layout & Architecture
+
+### Core Architecture
+
+**AutoGPT Platform** (`autogpt_platform/`):
+- `backend/` - FastAPI server with async support
+  - `backend/backend/` - Core API logic
+  - `backend/blocks/` - Agent execution blocks
+  - `backend/data/` - Database models and schemas
+  - `schema.prisma` - Database schema definition
+- `frontend/` - Next.js application
+  - `src/app/` - App Router pages and layouts
+  - `src/components/` - Reusable React components
+  - `src/lib/` - Utilities and configurations
+- `autogpt_libs/` - Shared Python utilities
+- `docker-compose.yml` - Development stack orchestration
+
+**Key Configuration Files:**
+- `pyproject.toml` - Python dependencies and tooling
+- `package.json` - Node.js dependencies and scripts
+- `schema.prisma` - Database schema and migrations
+- `next.config.mjs` - Next.js configuration
+- `tailwind.config.ts` - Styling configuration
+
+### Security & Middleware
+
+**Cache Protection**: Backend includes middleware preventing sensitive data caching in browsers/proxies
+**Authentication**: JWT-based with Supabase integration
+**User ID Validation**: All data access requires user ID checks - verify this for any `data/*.py` changes
+
+### Development Workflow
+
+**GitHub Actions**: Multiple CI/CD workflows in `.github/workflows/`
+- `platform-backend-ci.yml` - Backend testing and validation
+- `platform-frontend-ci.yml` - Frontend testing and validation
+- `platform-fullstack-ci.yml` - End-to-end integration tests
+
+**Pre-commit Hooks**: Run linting and formatting checks
+**Conventional Commits**: Use format `type(scope): description` (e.g., `feat(backend): add API`)
+
+### Key Source Files
+
+**Backend Entry Points:**
+- `backend/backend/server/server.py` - FastAPI application setup
+- `backend/backend/data/` - Database models and user management
+- `backend/blocks/` - Agent execution blocks and logic
+
+**Frontend Entry Points:**
+- `frontend/src/app/layout.tsx` - Root application layout
+- `frontend/src/app/page.tsx` - Home page
+- `frontend/src/lib/supabase/` - Authentication and database client
+
+**Protected Routes**: Update `frontend/lib/supabase/middleware.ts` when adding protected routes
+
+### Agent Block System
+
+Agents are built using a visual block-based system where each block performs a single action. Blocks are defined in `backend/blocks/` and must include:
+- Block definition with input/output schemas
+- Execution logic with proper error handling
+- Tests validating functionality
+
+### Database & ORM
+
+**Prisma ORM** with PostgreSQL backend including pgvector for embeddings:
+- Schema in `schema.prisma`
+- Migrations in `backend/migrations/`
+- Always run `prisma migrate dev` and `prisma generate` after schema changes
+
+## Environment Configuration
+
+### Configuration Files Priority Order
+1. **Backend**: `/backend/.env.default` → `/backend/.env` (user overrides)
+2. **Frontend**: `/frontend/.env.default` → `/frontend/.env` (user overrides)  
+3. **Platform**: `/.env.default` (Supabase/shared) → `/.env` (user overrides)
+4. Docker Compose `environment:` sections override file-based config
+5. Shell environment variables have highest precedence
+
+### Docker Environment Setup
+- All services use hardcoded defaults (no `${VARIABLE}` substitutions)
+- The `env_file` directive loads variables INTO containers at runtime
+- Backend/Frontend services use YAML anchors for consistent configuration
+- Copy `.env.default` files to `.env` for local development customization
+
+## Advanced Development Patterns
+
+### Adding New Blocks
+1. Create file in `/backend/backend/blocks/`
+2. Inherit from `Block` base class with input/output schemas
+3. Implement `run` method with proper error handling
+4. Generate block UUID using `uuid.uuid4()`
+5. Register in block registry
+6. Write tests alongside block implementation
+7. Consider how inputs/outputs connect with other blocks in graph editor
+
+### API Development
+1. Update routes in `/backend/backend/server/routers/`
+2. Add/update Pydantic models in same directory
+3. Write tests alongside route files
+4. For `data/*.py` changes, validate user ID checks
+5. Run `poetry run test` to verify changes
+
+### Frontend Development
+1. Components in `/frontend/src/components/`
+2. Use existing UI components from `/frontend/src/components/ui/`
+3. Add Storybook stories for component development
+4. Test user-facing features with Playwright E2E tests
+5. Update protected routes in middleware when needed
+
+### Security Guidelines
+**Cache Protection Middleware** (`/backend/backend/server/middleware/security.py`):
+- Default: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
+- Uses allow list approach for cacheable paths (static assets, health checks, public pages)
+- Prevents sensitive data caching in browsers/proxies
+- Add new cacheable endpoints to `CACHEABLE_PATHS`
+
+### CI/CD Alignment
+The repository has comprehensive CI workflows that test:
+- **Backend**: Python 3.11-3.13, services (Redis/RabbitMQ/ClamAV), Prisma migrations, Poetry lock validation
+- **Frontend**: Node.js 21, pnpm, Playwright with Docker Compose stack, API schema validation
+- **Integration**: Full-stack type checking and E2E testing
+
+Match these patterns when developing locally - the copilot setup environment mirrors these CI configurations.
+
+## Collaboration with Other AI Assistants
+
+This repository is actively developed with assistance from Claude (via CLAUDE.md files). When working on this codebase:
+- Check for existing CLAUDE.md files that provide additional context
+- Follow established patterns and conventions already in the codebase
+- Maintain consistency with existing code style and architecture
+- Consider that changes may be reviewed and extended by both human developers and AI assistants
+
+## Trust These Instructions
+
+These instructions are comprehensive and tested. Only perform additional searches if:
+1. Information here is incomplete for your specific task
+2. You encounter errors not covered by the workarounds
+3. You need to understand implementation details not covered above
+
+For detailed platform development patterns, refer to `autogpt_platform/CLAUDE.md` and `AGENTS.md` in the repository root.

.github/workflows/copilot-setup-steps.yml

@@ -0,0 +1,302 @@
+name: "Copilot Setup Steps"
+
+# Automatically run the setup steps when they are changed to allow for easy validation, and
+# allow manual testing through the repository's "Actions" tab
+on:
+  workflow_dispatch:
+  push:
+    paths:
+      - .github/workflows/copilot-setup-steps.yml
+  pull_request:
+    paths:
+      - .github/workflows/copilot-setup-steps.yml
+
+jobs:
+  # The job MUST be called `copilot-setup-steps` or it will not be picked up by Copilot.
+  copilot-setup-steps:
+    runs-on: ubuntu-latest
+    timeout-minutes: 45
+
+    # Set the permissions to the lowest permissions possible needed for your steps.
+    # Copilot will be given its own token for its operations.
+    permissions:
+      # If you want to clone the repository as part of your setup steps, for example to install dependencies, you'll need the `contents: read` permission. If you don't clone the repository in your setup steps, Copilot will do this for you automatically after the steps complete.
+      contents: read
+
+    # You can define any steps you want, and they will run before the agent starts.
+    # If you do not check out your code, Copilot will do this for you.
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          submodules: true
+
+      # Backend Python/Poetry setup (mirrors platform-backend-ci.yml)
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"  # Use standard version matching CI
+
+      - name: Set up Python dependency cache
+        uses: actions/cache@v4
+        with:
+          path: ~/.cache/pypoetry
+          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
+
+      - name: Install Poetry
+        run: |
+          # Extract Poetry version from backend/poetry.lock (matches CI)
+          cd autogpt_platform/backend
+          HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
+          echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
+          
+          # Install Poetry
+          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
+          
+          # Add Poetry to PATH
+          echo "$HOME/.local/bin" >> $GITHUB_PATH
+
+      - name: Check poetry.lock
+        working-directory: autogpt_platform/backend
+        run: |
+          poetry lock
+          if ! git diff --quiet --ignore-matching-lines="^# " poetry.lock; then
+            echo "Warning: poetry.lock not up to date, but continuing for setup"
+            git checkout poetry.lock  # Reset for clean setup
+          fi
+
+      - name: Install Python dependencies
+        working-directory: autogpt_platform/backend
+        run: poetry install
+
+      - name: Generate Prisma Client
+        working-directory: autogpt_platform/backend
+        run: poetry run prisma generate
+
+      # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: "21"
+
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Set pnpm store directory
+        run: |
+          pnpm config set store-dir ~/.pnpm-store
+          echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
+
+      - name: Cache frontend dependencies
+        uses: actions/cache@v4
+        with:
+          path: ~/.pnpm-store
+          key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
+            ${{ runner.os }}-pnpm-
+
+      - name: Install JavaScript dependencies
+        working-directory: autogpt_platform/frontend
+        run: pnpm install --frozen-lockfile
+
+      # Install Playwright browsers for frontend testing
+      # NOTE: Disabled to save ~1 minute of setup time. Re-enable if Copilot needs browser automation (e.g., for MCP)
+      # - name: Install Playwright browsers
+      #   working-directory: autogpt_platform/frontend
+      #   run: pnpm playwright install --with-deps chromium
+
+      # Docker setup for development environment
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Copy default environment files
+        working-directory: autogpt_platform
+        run: |
+          # Copy default environment files for development
+          cp .env.default .env
+          cp backend/.env.default backend/.env
+          cp frontend/.env.default frontend/.env
+
+      # Phase 1: Cache and load Docker images for faster setup
+      - name: Set up Docker image cache
+        id: docker-cache
+        uses: actions/cache@v4
+        with:
+          path: ~/docker-cache
+          # Use a versioned key for cache invalidation when image list changes
+          key: docker-images-v2-${{ runner.os }}-${{ hashFiles('.github/workflows/copilot-setup-steps.yml') }}
+          restore-keys: |
+            docker-images-v2-${{ runner.os }}-
+            docker-images-v1-${{ runner.os }}-
+
+      - name: Load or pull Docker images
+        working-directory: autogpt_platform
+        run: |
+          mkdir -p ~/docker-cache
+          
+          # Define image list for easy maintenance
+          IMAGES=(
+            "redis:latest"
+            "rabbitmq:management"
+            "clamav/clamav-debian:latest"
+            "busybox:latest"
+            "kong:2.8.1"
+            "supabase/gotrue:v2.170.0"
+            "supabase/postgres:15.8.1.049"
+            "supabase/postgres-meta:v0.86.1"
+            "supabase/studio:20250224-d10db0f"
+          )
+          
+          # Check if any cached tar files exist (more reliable than cache-hit)
+          if ls ~/docker-cache/*.tar 1> /dev/null 2>&1; then
+            echo "Docker cache found, loading images in parallel..."
+            for image in "${IMAGES[@]}"; do
+              # Convert image name to filename (replace : and / with -)
+              filename=$(echo "$image" | tr ':/' '--')
+              if [ -f ~/docker-cache/${filename}.tar ]; then
+                echo "Loading $image..."
+                docker load -i ~/docker-cache/${filename}.tar || echo "Warning: Failed to load $image from cache" &
+              fi
+            done
+            wait
+            echo "All cached images loaded"
+          else
+            echo "No Docker cache found, pulling images in parallel..."
+            # Pull all images in parallel
+            for image in "${IMAGES[@]}"; do
+              docker pull "$image" &
+            done
+            wait
+            
+            # Only save cache on main branches (not PRs) to avoid cache pollution
+            if [[ "${{ github.ref }}" == "refs/heads/master" ]] || [[ "${{ github.ref }}" == "refs/heads/dev" ]]; then
+              echo "Saving Docker images to cache in parallel..."
+              for image in "${IMAGES[@]}"; do
+                # Convert image name to filename (replace : and / with -)
+                filename=$(echo "$image" | tr ':/' '--')
+                echo "Saving $image..."
+                docker save -o ~/docker-cache/${filename}.tar "$image" || echo "Warning: Failed to save $image" &
+              done
+              wait
+              echo "Docker image cache saved"
+            else
+              echo "Skipping cache save for PR/feature branch"
+            fi
+          fi
+          
+          echo "Docker images ready for use"
+
+      # Phase 2: Build migrate service with GitHub Actions cache
+      - name: Build migrate Docker image with cache
+        working-directory: autogpt_platform
+        run: |
+          # Build the migrate image with buildx for GHA caching
+          docker buildx build \
+            --cache-from type=gha \
+            --cache-to type=gha,mode=max \
+            --target migrate \
+            --tag autogpt_platform-migrate:latest \
+            --load \
+            -f backend/Dockerfile \
+            ..
+
+      # Start services using pre-built images
+      - name: Start Docker services for development
+        working-directory: autogpt_platform
+        run: |
+          # Start essential services (migrate image already built with correct tag)
+          docker compose --profile local up deps --no-build --detach
+          echo "Waiting for services to be ready..."
+          
+          # Wait for database to be ready
+          echo "Checking database readiness..."
+          timeout 30 sh -c 'until docker compose exec -T db pg_isready -U postgres 2>/dev/null; do 
+            echo "  Waiting for database..."
+            sleep 2
+          done' && echo "✅ Database is ready" || echo "⚠️ Database ready check timeout after 30s, continuing..."
+          
+          # Check migrate service status
+          echo "Checking migration status..."
+          docker compose ps migrate || echo "  Migrate service not visible in ps output"
+          
+          # Wait for migrate service to complete
+          echo "Waiting for migrations to complete..."
+          timeout 30 bash -c '
+            ATTEMPTS=0
+            while [ $ATTEMPTS -lt 15 ]; do
+              ATTEMPTS=$((ATTEMPTS + 1))
+              
+              # Check using docker directly (more reliable than docker compose ps)
+              CONTAINER_STATUS=$(docker ps -a --filter "label=com.docker.compose.service=migrate" --format "{{.Status}}" | head -1)
+              
+              if [ -z "$CONTAINER_STATUS" ]; then
+                echo "  Attempt $ATTEMPTS: Migrate container not found yet..."
+              elif echo "$CONTAINER_STATUS" | grep -q "Exited (0)"; then
+                echo "✅ Migrations completed successfully"
+                docker compose logs migrate --tail=5 2>/dev/null || true
+                exit 0
+              elif echo "$CONTAINER_STATUS" | grep -q "Exited ([1-9]"; then
+                EXIT_CODE=$(echo "$CONTAINER_STATUS" | grep -oE "Exited \([0-9]+\)" | grep -oE "[0-9]+")
+                echo "❌ Migrations failed with exit code: $EXIT_CODE"
+                echo "Migration logs:"
+                docker compose logs migrate --tail=20 2>/dev/null || true
+                exit 1
+              elif echo "$CONTAINER_STATUS" | grep -q "Up"; then
+                echo "  Attempt $ATTEMPTS: Migrate container is running... ($CONTAINER_STATUS)"
+              else
+                echo "  Attempt $ATTEMPTS: Migrate container status: $CONTAINER_STATUS"
+              fi
+              
+              sleep 2
+            done
+            
+            echo "⚠️ Timeout: Could not determine migration status after 30 seconds"
+            echo "Final container check:"
+            docker ps -a --filter "label=com.docker.compose.service=migrate" || true
+            echo "Migration logs (if available):"
+            docker compose logs migrate --tail=10 2>/dev/null || echo "  No logs available"
+          ' || echo "⚠️ Migration check completed with warnings, continuing..."
+          
+          # Brief wait for other services to stabilize
+          echo "Waiting 5 seconds for other services to stabilize..."
+          sleep 5
+
+      # Verify installations and provide environment info
+      - name: Verify setup and show environment info
+        run: |
+          echo "=== Python Setup ==="
+          python --version
+          poetry --version
+          
+          echo "=== Node.js Setup ==="
+          node --version
+          pnpm --version
+          
+          echo "=== Additional Tools ==="
+          docker --version
+          docker compose version
+          gh --version || true
+          
+          echo "=== Services Status ==="
+          cd autogpt_platform
+          docker compose ps || true
+          
+          echo "=== Backend Dependencies ==="
+          cd backend
+          poetry show | head -10 || true
+          
+          echo "=== Frontend Dependencies ==="
+          cd ../frontend
+          pnpm list --depth=0 | head -10 || true
+          
+          echo "=== Environment Files ==="
+          ls -la ../.env* || true
+          ls -la .env* || true
+          ls -la ../backend/.env* || true
+          
+          echo "✅ AutoGPT Platform development environment setup complete!"
+          echo "🚀 Ready for development with Docker services running"
+          echo "📝 Backend server: poetry run serve (port 8000)"
+          echo "🌐 Frontend server: pnpm dev (port 3000)"

.github/workflows/platform-backend-ci.yml

@@ -32,7 +32,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.11"]
+        python-version: ["3.11", "3.12", "3.13"]
     runs-on: ubuntu-latest
 
     services:

autogpt_platform/CLAUDE.md

@@ -156,7 +156,7 @@ Key models (defined in `/backend/schema.prisma`):
 5. Register in block registry
 6. Generate the block uuid using `uuid.uuid4()`
 
-Note: when making many new blocks analyze the interfaces for each of these blcoks and picture if they would go well together in a graph based editor or would they struggle to connect productively?
+Note: when making many new blocks analyze the interfaces for each of these blocks and picture if they would go well together in a graph based editor or would they struggle to connect productively?
 ex: do the inputs and outputs tie well together?
 
 **Modifying the API:**

autogpt_platform/autogpt_libs/autogpt_libs/auth/middleware.py

@@ -10,8 +10,8 @@ from starlette.status import HTTP_401_UNAUTHORIZED
 from .config import settings
 from .jwt_utils import parse_jwt_token
 
-security = HTTPBearer()
 logger = logging.getLogger(__name__)
+bearer_auth = HTTPBearer(auto_error=False)
 
 
 async def auth_middleware(request: Request):
@@ -20,11 +20,10 @@ async def auth_middleware(request: Request):
         logger.warning("Auth disabled")
         return {}
 
-    security = HTTPBearer()
-    credentials = await security(request)
+    credentials = await bearer_auth(request)
 
     if not credentials:
-        raise HTTPException(status_code=401, detail="Authorization header is missing")
+        raise HTTPException(status_code=401, detail="Not authenticated")
 
     try:
         payload = parse_jwt_token(credentials.credentials)

autogpt_platform/autogpt_libs/poetry.lock

@@ -1253,30 +1253,31 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.12.3"
+version = "0.12.9"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
 files = [
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+    {file = "ruff-0.12.9.tar.gz", hash = "sha256:fbd94b2e3c623f659962934e52c2bea6fc6da11f667a427a368adaf3af2c866a"},
 ]
 
 [[package]]
@@ -1614,4 +1615,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "f67db13e6f68b1d67a55eee908c1c560bfa44da8509f98f842889a7570a9830f"
+content-hash = "4cc687aabe5865665fb8c4ccc0ea7e0af80b41e401ca37919f57efa6e0b5be00"

autogpt_platform/autogpt_libs/pyproject.toml

@@ -23,7 +23,7 @@ supabase = "^2.16.0"
 uvicorn = "^0.35.0"
 
 [tool.poetry.group.dev.dependencies]
-ruff = "^0.12.3"
+ruff = "^0.12.9"
 
 [build-system]
 requires = ["poetry-core"]

autogpt_platform/backend/.env.default

@@ -106,6 +106,15 @@ TODOIST_CLIENT_SECRET=
 
 NOTION_CLIENT_ID=
 NOTION_CLIENT_SECRET=
+
+# Discord OAuth App credentials
+# 1. Go to https://discord.com/developers/applications
+# 2. Create a new application
+# 3. Go to OAuth2 section and add redirect URI: http://localhost:3000/auth/integrations/oauth_callback
+# 4. Copy Client ID and Client Secret below
+DISCORD_CLIENT_ID=
+DISCORD_CLIENT_SECRET=
+
 REDDIT_CLIENT_ID=
 REDDIT_CLIENT_SECRET=
 

autogpt_platform/backend/Dockerfile

@@ -1,16 +1,21 @@
-FROM python:3.11.10-slim-bookworm AS builder
+FROM debian:13-slim AS builder
 
 # Set environment variables
-ENV PYTHONDONTWRITEBYTECODE 1
-ENV PYTHONUNBUFFERED 1
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
+ENV DEBIAN_FRONTEND=noninteractive
 
 WORKDIR /app
 
 RUN echo 'Acquire::http::Pipeline-Depth 0;\nAcquire::http::No-Cache true;\nAcquire::BrokenProxy true;\n' > /etc/apt/apt.conf.d/99fixbadproxy
 
-# Update package list and install build dependencies in a single layer
+# Update package list and install Python and build dependencies
 RUN apt-get update --allow-releaseinfo-change --fix-missing \
     && apt-get install -y \
+    python3.13 \
+    python3.13-dev \
+    python3.13-venv \
+    python3-pip \
     build-essential \
     libpq5 \
     libz-dev \
@@ -19,13 +24,11 @@ RUN apt-get update --allow-releaseinfo-change --fix-missing \
 
 ENV POETRY_HOME=/opt/poetry
 ENV POETRY_NO_INTERACTION=1
-ENV POETRY_VIRTUALENVS_CREATE=false
+ENV POETRY_VIRTUALENVS_CREATE=true
+ENV POETRY_VIRTUALENVS_IN_PROJECT=true
 ENV PATH=/opt/poetry/bin:$PATH
 
-# Upgrade pip and setuptools to fix security vulnerabilities
-RUN pip3 install --upgrade pip setuptools
-
-RUN pip3 install poetry
+RUN pip3 install poetry --break-system-packages
 
 # Copy and install dependencies
 COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
@@ -37,27 +40,30 @@ RUN poetry install --no-ansi --no-root
 COPY autogpt_platform/backend/schema.prisma ./
 RUN poetry run prisma generate
 
-FROM python:3.11.10-slim-bookworm AS server_dependencies
+FROM debian:13-slim AS server_dependencies
 
 WORKDIR /app
 
 ENV POETRY_HOME=/opt/poetry \
     POETRY_NO_INTERACTION=1 \
-    POETRY_VIRTUALENVS_CREATE=false
+    POETRY_VIRTUALENVS_CREATE=true \
+    POETRY_VIRTUALENVS_IN_PROJECT=true \
+    DEBIAN_FRONTEND=noninteractive
 ENV PATH=/opt/poetry/bin:$PATH
 
-# Upgrade pip and setuptools to fix security vulnerabilities
-RUN pip3 install --upgrade pip setuptools
+# Install Python without upgrading system-managed packages
+RUN apt-get update && apt-get install -y \
+    python3.13 \
+    python3-pip
 
 # Copy only necessary files from builder
 COPY --from=builder /app /app
-COPY --from=builder /usr/local/lib/python3.11 /usr/local/lib/python3.11
-COPY --from=builder /usr/local/bin /usr/local/bin
+COPY --from=builder /usr/local/lib/python3* /usr/local/lib/python3*
+COPY --from=builder /usr/local/bin/poetry /usr/local/bin/poetry
 # Copy Prisma binaries
 COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
 
-
-ENV PATH="/app/.venv/bin:$PATH"
+ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
 
 RUN mkdir -p /app/autogpt_platform/autogpt_libs
 RUN mkdir -p /app/autogpt_platform/backend

autogpt_platform/backend/backend/blocks/agent.py

@@ -25,6 +25,9 @@ class AgentExecutorBlock(Block):
         user_id: str = SchemaField(description="User ID")
         graph_id: str = SchemaField(description="Graph ID")
         graph_version: int = SchemaField(description="Graph Version")
+        agent_name: Optional[str] = SchemaField(
+            default=None, description="Name to display in the Builder UI"
+        )
 
         inputs: BlockInput = SchemaField(description="Input data for the graph")
         input_schema: dict = SchemaField(description="Input schema for the graph")

autogpt_platform/backend/backend/blocks/ai_music_generator.py

@@ -166,7 +166,7 @@ class AIMusicGeneratorBlock(Block):
                     output_format=input_data.output_format,
                     normalization_strategy=input_data.normalization_strategy,
                 )
-                if result and result != "No output received":
+                if result and isinstance(result, str) and result.startswith("http"):
                     yield "result", result
                     return
                 else:

autogpt_platform/backend/backend/blocks/baas/_api.py

@@ -0,0 +1,205 @@
+"""
+Meeting BaaS API client module.
+All API calls centralized for consistency and maintainability.
+"""
+
+from typing import Any, Dict, List, Optional
+
+from backend.sdk import Requests
+
+
+class MeetingBaasAPI:
+    """Client for Meeting BaaS API endpoints."""
+
+    BASE_URL = "https://api.meetingbaas.com"
+
+    def __init__(self, api_key: str):
+        """Initialize API client with authentication key."""
+        self.api_key = api_key
+        self.headers = {"x-meeting-baas-api-key": api_key}
+        self.requests = Requests()
+
+    # Bot Management Endpoints
+
+    async def join_meeting(
+        self,
+        bot_name: str,
+        meeting_url: str,
+        reserved: bool = False,
+        bot_image: Optional[str] = None,
+        entry_message: Optional[str] = None,
+        start_time: Optional[int] = None,
+        speech_to_text: Optional[Dict[str, Any]] = None,
+        webhook_url: Optional[str] = None,
+        automatic_leave: Optional[Dict[str, Any]] = None,
+        extra: Optional[Dict[str, Any]] = None,
+        recording_mode: str = "speaker_view",
+        streaming: Optional[Dict[str, Any]] = None,
+        deduplication_key: Optional[str] = None,
+        zoom_sdk_id: Optional[str] = None,
+        zoom_sdk_pwd: Optional[str] = None,
+    ) -> Dict[str, Any]:
+        """
+        Deploy a bot to join and record a meeting.
+
+        POST /bots
+        """
+        body = {
+            "bot_name": bot_name,
+            "meeting_url": meeting_url,
+            "reserved": reserved,
+            "recording_mode": recording_mode,
+        }
+
+        # Add optional fields if provided
+        if bot_image is not None:
+            body["bot_image"] = bot_image
+        if entry_message is not None:
+            body["entry_message"] = entry_message
+        if start_time is not None:
+            body["start_time"] = start_time
+        if speech_to_text is not None:
+            body["speech_to_text"] = speech_to_text
+        if webhook_url is not None:
+            body["webhook_url"] = webhook_url
+        if automatic_leave is not None:
+            body["automatic_leave"] = automatic_leave
+        if extra is not None:
+            body["extra"] = extra
+        if streaming is not None:
+            body["streaming"] = streaming
+        if deduplication_key is not None:
+            body["deduplication_key"] = deduplication_key
+        if zoom_sdk_id is not None:
+            body["zoom_sdk_id"] = zoom_sdk_id
+        if zoom_sdk_pwd is not None:
+            body["zoom_sdk_pwd"] = zoom_sdk_pwd
+
+        response = await self.requests.post(
+            f"{self.BASE_URL}/bots",
+            headers=self.headers,
+            json=body,
+        )
+        return response.json()
+
+    async def leave_meeting(self, bot_id: str) -> bool:
+        """
+        Remove a bot from an ongoing meeting.
+
+        DELETE /bots/{uuid}
+        """
+        response = await self.requests.delete(
+            f"{self.BASE_URL}/bots/{bot_id}",
+            headers=self.headers,
+        )
+        return response.status in [200, 204]
+
+    async def retranscribe(
+        self,
+        bot_uuid: str,
+        speech_to_text: Optional[Dict[str, Any]] = None,
+        webhook_url: Optional[str] = None,
+    ) -> Dict[str, Any]:
+        """
+        Re-run transcription on a bot's audio.
+
+        POST /bots/retranscribe
+        """
+        body: Dict[str, Any] = {"bot_uuid": bot_uuid}
+
+        if speech_to_text is not None:
+            body["speech_to_text"] = speech_to_text
+        if webhook_url is not None:
+            body["webhook_url"] = webhook_url
+
+        response = await self.requests.post(
+            f"{self.BASE_URL}/bots/retranscribe",
+            headers=self.headers,
+            json=body,
+        )
+
+        if response.status == 202:
+            return {"accepted": True}
+        return response.json()
+
+    # Data Retrieval Endpoints
+
+    async def get_meeting_data(
+        self, bot_id: str, include_transcripts: bool = True
+    ) -> Dict[str, Any]:
+        """
+        Retrieve meeting data including recording and transcripts.
+
+        GET /bots/meeting_data
+        """
+        params = {
+            "bot_id": bot_id,
+            "include_transcripts": str(include_transcripts).lower(),
+        }
+
+        response = await self.requests.get(
+            f"{self.BASE_URL}/bots/meeting_data",
+            headers=self.headers,
+            params=params,
+        )
+        return response.json()
+
+    async def get_screenshots(self, bot_id: str) -> List[Dict[str, Any]]:
+        """
+        Retrieve screenshots captured during a meeting.
+
+        GET /bots/{uuid}/screenshots
+        """
+        response = await self.requests.get(
+            f"{self.BASE_URL}/bots/{bot_id}/screenshots",
+            headers=self.headers,
+        )
+        result = response.json()
+        # Ensure we return a list
+        if isinstance(result, list):
+            return result
+        return []
+
+    async def delete_data(self, bot_id: str) -> bool:
+        """
+        Delete a bot's recorded data.
+
+        POST /bots/{uuid}/delete_data
+        """
+        response = await self.requests.post(
+            f"{self.BASE_URL}/bots/{bot_id}/delete_data",
+            headers=self.headers,
+        )
+        return response.status == 200
+
+    async def list_bots_with_metadata(
+        self,
+        limit: Optional[int] = None,
+        offset: Optional[int] = None,
+        sort_by: Optional[str] = None,
+        sort_order: Optional[str] = None,
+        filter_by: Optional[Dict[str, Any]] = None,
+    ) -> Dict[str, Any]:
+        """
+        List bots with metadata including IDs, names, and meeting details.
+
+        GET /bots/bots_with_metadata
+        """
+        params = {}
+        if limit is not None:
+            params["limit"] = limit
+        if offset is not None:
+            params["offset"] = offset
+        if sort_by is not None:
+            params["sort_by"] = sort_by
+        if sort_order is not None:
+            params["sort_order"] = sort_order
+        if filter_by is not None:
+            params.update(filter_by)
+
+        response = await self.requests.get(
+            f"{self.BASE_URL}/bots/bots_with_metadata",
+            headers=self.headers,
+            params=params,
+        )
+        return response.json()

autogpt_platform/backend/backend/blocks/baas/_config.py

@@ -0,0 +1,13 @@
+"""
+Shared configuration for all Meeting BaaS blocks using the SDK pattern.
+"""
+
+from backend.sdk import BlockCostType, ProviderBuilder
+
+# Configure the Meeting BaaS provider with API key authentication
+baas = (
+    ProviderBuilder("baas")
+    .with_api_key("MEETING_BAAS_API_KEY", "Meeting BaaS API Key")
+    .with_base_cost(5, BlockCostType.RUN)  # Higher cost for meeting recording service
+    .build()
+)

autogpt_platform/backend/backend/blocks/baas/bots.py

@@ -0,0 +1,217 @@
+"""
+Meeting BaaS bot (recording) blocks.
+"""
+
+from typing import Optional
+
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchema,
+    CredentialsMetaInput,
+    SchemaField,
+)
+
+from ._api import MeetingBaasAPI
+from ._config import baas
+
+
+class BaasBotJoinMeetingBlock(Block):
+    """
+    Deploy a bot immediately or at a scheduled start_time to join and record a meeting.
+    """
+
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput = baas.credentials_field(
+            description="Meeting BaaS API credentials"
+        )
+        meeting_url: str = SchemaField(
+            description="The URL of the meeting the bot should join"
+        )
+        bot_name: str = SchemaField(
+            description="Display name for the bot in the meeting"
+        )
+        bot_image: str = SchemaField(
+            description="URL to an image for the bot's avatar (16:9 ratio recommended)",
+            default="",
+        )
+        entry_message: str = SchemaField(
+            description="Chat message the bot will post upon entry", default=""
+        )
+        reserved: bool = SchemaField(
+            description="Use a reserved bot slot (joins 4 min before meeting)",
+            default=False,
+        )
+        start_time: Optional[int] = SchemaField(
+            description="Unix timestamp (ms) when bot should join", default=None
+        )
+        webhook_url: str | None = SchemaField(
+            description="URL to receive webhook events for this bot", default=None
+        )
+        timeouts: dict = SchemaField(
+            description="Automatic leave timeouts configuration", default={}
+        )
+        extra: dict = SchemaField(
+            description="Custom metadata to attach to the bot", default={}
+        )
+
+    class Output(BlockSchema):
+        bot_id: str = SchemaField(description="UUID of the deployed bot")
+        join_response: dict = SchemaField(
+            description="Full response from join operation"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="377d1a6a-a99b-46cf-9af3-1d1b12758e04",
+            description="Deploy a bot to join and record a meeting",
+            categories={BlockCategory.COMMUNICATION},
+            input_schema=self.Input,
+            output_schema=self.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        api_key = credentials.api_key.get_secret_value()
+        api = MeetingBaasAPI(api_key)
+
+        # Call API with all parameters
+        data = await api.join_meeting(
+            bot_name=input_data.bot_name,
+            meeting_url=input_data.meeting_url,
+            reserved=input_data.reserved,
+            bot_image=input_data.bot_image if input_data.bot_image else None,
+            entry_message=(
+                input_data.entry_message if input_data.entry_message else None
+            ),
+            start_time=input_data.start_time,
+            speech_to_text={"provider": "Default"},
+            webhook_url=input_data.webhook_url if input_data.webhook_url else None,
+            automatic_leave=input_data.timeouts if input_data.timeouts else None,
+            extra=input_data.extra if input_data.extra else None,
+        )
+
+        yield "bot_id", data.get("bot_id", "")
+        yield "join_response", data
+
+
+class BaasBotLeaveMeetingBlock(Block):
+    """
+    Force the bot to exit the call.
+    """
+
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput = baas.credentials_field(
+            description="Meeting BaaS API credentials"
+        )
+        bot_id: str = SchemaField(description="UUID of the bot to remove from meeting")
+
+    class Output(BlockSchema):
+        left: bool = SchemaField(description="Whether the bot successfully left")
+
+    def __init__(self):
+        super().__init__(
+            id="bf77d128-8b25-4280-b5c7-2d553ba7e482",
+            description="Remove a bot from an ongoing meeting",
+            categories={BlockCategory.COMMUNICATION},
+            input_schema=self.Input,
+            output_schema=self.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        api_key = credentials.api_key.get_secret_value()
+        api = MeetingBaasAPI(api_key)
+
+        # Leave meeting
+        left = await api.leave_meeting(input_data.bot_id)
+
+        yield "left", left
+
+
+class BaasBotFetchMeetingDataBlock(Block):
+    """
+    Pull MP4 URL, transcript & metadata for a completed meeting.
+    """
+
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput = baas.credentials_field(
+            description="Meeting BaaS API credentials"
+        )
+        bot_id: str = SchemaField(description="UUID of the bot whose data to fetch")
+        include_transcripts: bool = SchemaField(
+            description="Include transcript data in response", default=True
+        )
+
+    class Output(BlockSchema):
+        mp4_url: str = SchemaField(
+            description="URL to download the meeting recording (time-limited)"
+        )
+        transcript: list = SchemaField(description="Meeting transcript data")
+        metadata: dict = SchemaField(description="Meeting metadata and bot information")
+
+    def __init__(self):
+        super().__init__(
+            id="ea7c1309-303c-4da1-893f-89c0e9d64e78",
+            description="Retrieve recorded meeting data",
+            categories={BlockCategory.DATA},
+            input_schema=self.Input,
+            output_schema=self.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        api_key = credentials.api_key.get_secret_value()
+        api = MeetingBaasAPI(api_key)
+
+        # Fetch meeting data
+        data = await api.get_meeting_data(
+            bot_id=input_data.bot_id,
+            include_transcripts=input_data.include_transcripts,
+        )
+
+        yield "mp4_url", data.get("mp4", "")
+        yield "transcript", data.get("bot_data", {}).get("transcripts", [])
+        yield "metadata", data.get("bot_data", {}).get("bot", {})
+
+
+class BaasBotDeleteRecordingBlock(Block):
+    """
+    Purge MP4 + transcript data for privacy or storage management.
+    """
+
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput = baas.credentials_field(
+            description="Meeting BaaS API credentials"
+        )
+        bot_id: str = SchemaField(description="UUID of the bot whose data to delete")
+
+    class Output(BlockSchema):
+        deleted: bool = SchemaField(
+            description="Whether the data was successfully deleted"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="bf8d1aa6-42d8-4944-b6bd-6bac554c0d3b",
+            description="Permanently delete a meeting's recorded data",
+            categories={BlockCategory.DATA},
+            input_schema=self.Input,
+            output_schema=self.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        api_key = credentials.api_key.get_secret_value()
+        api = MeetingBaasAPI(api_key)
+
+        # Delete recording data
+        deleted = await api.delete_data(input_data.bot_id)
+
+        yield "deleted", deleted

autogpt_platform/backend/backend/blocks/dataforseo/_api.py

@@ -0,0 +1,178 @@
+"""
+DataForSEO API client with async support using the SDK patterns.
+"""
+
+import base64
+from typing import Any, Dict, List, Optional
+
+from backend.sdk import Requests, UserPasswordCredentials
+
+
+class DataForSeoClient:
+    """Client for the DataForSEO API using async requests."""
+
+    API_URL = "https://api.dataforseo.com"
+
+    def __init__(self, credentials: UserPasswordCredentials):
+        self.credentials = credentials
+        self.requests = Requests(
+            trusted_origins=["https://api.dataforseo.com"],
+            raise_for_status=False,
+        )
+
+    def _get_headers(self) -> Dict[str, str]:
+        """Generate the authorization header using Basic Auth."""
+        username = self.credentials.username.get_secret_value()
+        password = self.credentials.password.get_secret_value()
+        credentials_str = f"{username}:{password}"
+        encoded = base64.b64encode(credentials_str.encode("ascii")).decode("ascii")
+        return {
+            "Authorization": f"Basic {encoded}",
+            "Content-Type": "application/json",
+        }
+
+    async def keyword_suggestions(
+        self,
+        keyword: str,
+        location_code: Optional[int] = None,
+        language_code: Optional[str] = None,
+        include_seed_keyword: bool = True,
+        include_serp_info: bool = False,
+        include_clickstream_data: bool = False,
+        limit: int = 100,
+    ) -> List[Dict[str, Any]]:
+        """
+        Get keyword suggestions from DataForSEO Labs.
+
+        Args:
+            keyword: Seed keyword
+            location_code: Location code for targeting
+            language_code: Language code (e.g., "en")
+            include_seed_keyword: Include seed keyword in results
+            include_serp_info: Include SERP data
+            include_clickstream_data: Include clickstream metrics
+            limit: Maximum number of results (up to 3000)
+
+        Returns:
+            API response with keyword suggestions
+        """
+        endpoint = f"{self.API_URL}/v3/dataforseo_labs/google/keyword_suggestions/live"
+
+        # Build payload only with non-None values to avoid sending null fields
+        task_data: dict[str, Any] = {
+            "keyword": keyword,
+        }
+
+        if location_code is not None:
+            task_data["location_code"] = location_code
+        if language_code is not None:
+            task_data["language_code"] = language_code
+        if include_seed_keyword is not None:
+            task_data["include_seed_keyword"] = include_seed_keyword
+        if include_serp_info is not None:
+            task_data["include_serp_info"] = include_serp_info
+        if include_clickstream_data is not None:
+            task_data["include_clickstream_data"] = include_clickstream_data
+        if limit is not None:
+            task_data["limit"] = limit
+
+        payload = [task_data]
+
+        response = await self.requests.post(
+            endpoint,
+            headers=self._get_headers(),
+            json=payload,
+        )
+
+        data = response.json()
+
+        # Check for API errors
+        if response.status != 200:
+            error_message = data.get("status_message", "Unknown error")
+            raise Exception(
+                f"DataForSEO API error ({response.status}): {error_message}"
+            )
+
+        # Extract the results from the response
+        if data.get("tasks") and len(data["tasks"]) > 0:
+            task = data["tasks"][0]
+            if task.get("status_code") == 20000:  # Success code
+                return task.get("result", [])
+            else:
+                error_msg = task.get("status_message", "Task failed")
+                raise Exception(f"DataForSEO task error: {error_msg}")
+
+        return []
+
+    async def related_keywords(
+        self,
+        keyword: str,
+        location_code: Optional[int] = None,
+        language_code: Optional[str] = None,
+        include_seed_keyword: bool = True,
+        include_serp_info: bool = False,
+        include_clickstream_data: bool = False,
+        limit: int = 100,
+    ) -> List[Dict[str, Any]]:
+        """
+        Get related keywords from DataForSEO Labs.
+
+        Args:
+            keyword: Seed keyword
+            location_code: Location code for targeting
+            language_code: Language code (e.g., "en")
+            include_seed_keyword: Include seed keyword in results
+            include_serp_info: Include SERP data
+            include_clickstream_data: Include clickstream metrics
+            limit: Maximum number of results (up to 3000)
+
+        Returns:
+            API response with related keywords
+        """
+        endpoint = f"{self.API_URL}/v3/dataforseo_labs/google/related_keywords/live"
+
+        # Build payload only with non-None values to avoid sending null fields
+        task_data: dict[str, Any] = {
+            "keyword": keyword,
+        }
+
+        if location_code is not None:
+            task_data["location_code"] = location_code
+        if language_code is not None:
+            task_data["language_code"] = language_code
+        if include_seed_keyword is not None:
+            task_data["include_seed_keyword"] = include_seed_keyword
+        if include_serp_info is not None:
+            task_data["include_serp_info"] = include_serp_info
+        if include_clickstream_data is not None:
+            task_data["include_clickstream_data"] = include_clickstream_data
+        if limit is not None:
+            task_data["limit"] = limit
+
+        payload = [task_data]
+
+        response = await self.requests.post(
+            endpoint,
+            headers=self._get_headers(),
+            json=payload,
+        )
+
+        data = response.json()
+
+        # Check for API errors
+        if response.status != 200:
+            error_message = data.get("status_message", "Unknown error")
+            raise Exception(
+                f"DataForSEO API error ({response.status}): {error_message}"
+            )
+
+        # Extract the results from the response
+        if data.get("tasks") and len(data["tasks"]) > 0:
+            task = data["tasks"][0]
+            if task.get("status_code") == 20000:  # Success code
+                return task.get("result", [])
+            else:
+                error_msg = task.get("status_message", "Task failed")
+                raise Exception(f"DataForSEO task error: {error_msg}")
+
+        return []

autogpt_platform/backend/backend/blocks/dataforseo/_config.py

@@ -0,0 +1,17 @@
+"""
+Configuration for all DataForSEO blocks using the new SDK pattern.
+"""
+
+from backend.sdk import BlockCostType, ProviderBuilder
+
+# Build the DataForSEO provider with username/password authentication
+dataforseo = (
+    ProviderBuilder("dataforseo")
+    .with_user_password(
+        username_env_var="DATAFORSEO_USERNAME",
+        password_env_var="DATAFORSEO_PASSWORD",
+        title="DataForSEO Credentials",
+    )
+    .with_base_cost(1, BlockCostType.RUN)
+    .build()
+)

autogpt_platform/backend/backend/blocks/dataforseo/keyword_suggestions.py

@@ -0,0 +1,273 @@
+"""
+DataForSEO Google Keyword Suggestions block.
+"""
+
+from typing import Any, Dict, List, Optional
+
+from backend.sdk import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchema,
+    CredentialsMetaInput,
+    SchemaField,
+    UserPasswordCredentials,
+)
+
+from ._api import DataForSeoClient
+from ._config import dataforseo
+
+
+class KeywordSuggestion(BlockSchema):
+    """Schema for a keyword suggestion result."""
+
+    keyword: str = SchemaField(description="The keyword suggestion")
+    search_volume: Optional[int] = SchemaField(
+        description="Monthly search volume", default=None
+    )
+    competition: Optional[float] = SchemaField(
+        description="Competition level (0-1)", default=None
+    )
+    cpc: Optional[float] = SchemaField(
+        description="Cost per click in USD", default=None
+    )
+    keyword_difficulty: Optional[int] = SchemaField(
+        description="Keyword difficulty score", default=None
+    )
+    serp_info: Optional[Dict[str, Any]] = SchemaField(
+        description="data from SERP for each keyword", default=None
+    )
+    clickstream_data: Optional[Dict[str, Any]] = SchemaField(
+        description="Clickstream data metrics", default=None
+    )
+
+
+class DataForSeoKeywordSuggestionsBlock(Block):
+    """Block for getting keyword suggestions from DataForSEO Labs."""
+
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput = dataforseo.credentials_field(
+            description="DataForSEO credentials (username and password)"
+        )
+        keyword: str = SchemaField(description="Seed keyword to get suggestions for")
+        location_code: Optional[int] = SchemaField(
+            description="Location code for targeting (e.g., 2840 for USA)",
+            default=2840,  # USA
+        )
+        language_code: Optional[str] = SchemaField(
+            description="Language code (e.g., 'en' for English)",
+            default="en",
+        )
+        include_seed_keyword: bool = SchemaField(
+            description="Include the seed keyword in results",
+            default=True,
+        )
+        include_serp_info: bool = SchemaField(
+            description="Include SERP information",
+            default=False,
+        )
+        include_clickstream_data: bool = SchemaField(
+            description="Include clickstream metrics",
+            default=False,
+        )
+        limit: int = SchemaField(
+            description="Maximum number of results (up to 3000)",
+            default=100,
+            ge=1,
+            le=3000,
+        )
+
+    class Output(BlockSchema):
+        suggestions: List[KeywordSuggestion] = SchemaField(
+            description="List of keyword suggestions with metrics"
+        )
+        suggestion: KeywordSuggestion = SchemaField(
+            description="A single keyword suggestion with metrics"
+        )
+        total_count: int = SchemaField(
+            description="Total number of suggestions returned"
+        )
+        seed_keyword: str = SchemaField(
+            description="The seed keyword used for the query"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="73c3e7c4-2b3f-4e9f-9e3e-8f7a5c3e2d45",
+            description="Get keyword suggestions from DataForSEO Labs Google API",
+            categories={BlockCategory.SEARCH, BlockCategory.DATA},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "credentials": dataforseo.get_test_credentials().model_dump(),
+                "keyword": "digital marketing",
+                "location_code": 2840,
+                "language_code": "en",
+                "limit": 1,
+            },
+            test_credentials=dataforseo.get_test_credentials(),
+            test_output=[
+                (
+                    "suggestion",
+                    lambda x: hasattr(x, "keyword")
+                    and x.keyword == "digital marketing strategy",
+                ),
+                ("suggestions", lambda x: isinstance(x, list) and len(x) == 1),
+                ("total_count", 1),
+                ("seed_keyword", "digital marketing"),
+            ],
+            test_mock={
+                "_fetch_keyword_suggestions": lambda *args, **kwargs: [
+                    {
+                        "items": [
+                            {
+                                "keyword": "digital marketing strategy",
+                                "keyword_info": {
+                                    "search_volume": 10000,
+                                    "competition": 0.5,
+                                    "cpc": 2.5,
+                                },
+                                "keyword_properties": {
+                                    "keyword_difficulty": 50,
+                                },
+                            }
+                        ]
+                    }
+                ]
+            },
+        )
+
+    async def _fetch_keyword_suggestions(
+        self,
+        client: DataForSeoClient,
+        input_data: Input,
+    ) -> Any:
+        """Private method to fetch keyword suggestions - can be mocked for testing."""
+        return await client.keyword_suggestions(
+            keyword=input_data.keyword,
+            location_code=input_data.location_code,
+            language_code=input_data.language_code,
+            include_seed_keyword=input_data.include_seed_keyword,
+            include_serp_info=input_data.include_serp_info,
+            include_clickstream_data=input_data.include_clickstream_data,
+            limit=input_data.limit,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: UserPasswordCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        """Execute the keyword suggestions query."""
+        client = DataForSeoClient(credentials)
+
+        results = await self._fetch_keyword_suggestions(client, input_data)
+
+        # Process and format the results
+        suggestions = []
+        if results and len(results) > 0:
+            # results is a list, get the first element
+            first_result = results[0] if isinstance(results, list) else results
+            items = (
+                first_result.get("items", []) if isinstance(first_result, dict) else []
+            )
+            for item in items:
+                # Create the KeywordSuggestion object
+                suggestion = KeywordSuggestion(
+                    keyword=item.get("keyword", ""),
+                    search_volume=item.get("keyword_info", {}).get("search_volume"),
+                    competition=item.get("keyword_info", {}).get("competition"),
+                    cpc=item.get("keyword_info", {}).get("cpc"),
+                    keyword_difficulty=item.get("keyword_properties", {}).get(
+                        "keyword_difficulty"
+                    ),
+                    serp_info=(
+                        item.get("serp_info") if input_data.include_serp_info else None
+                    ),
+                    clickstream_data=(
+                        item.get("clickstream_keyword_info")
+                        if input_data.include_clickstream_data
+                        else None
+                    ),
+                )
+                yield "suggestion", suggestion
+                suggestions.append(suggestion)
+
+        yield "suggestions", suggestions
+        yield "total_count", len(suggestions)
+        yield "seed_keyword", input_data.keyword
+
+
+class KeywordSuggestionExtractorBlock(Block):
+    """Extracts individual fields from a KeywordSuggestion object."""
+
+    class Input(BlockSchema):
+        suggestion: KeywordSuggestion = SchemaField(
+            description="The keyword suggestion object to extract fields from"
+        )
+
+    class Output(BlockSchema):
+        keyword: str = SchemaField(description="The keyword suggestion")
+        search_volume: Optional[int] = SchemaField(
+            description="Monthly search volume", default=None
+        )
+        competition: Optional[float] = SchemaField(
+            description="Competition level (0-1)", default=None
+        )
+        cpc: Optional[float] = SchemaField(
+            description="Cost per click in USD", default=None
+        )
+        keyword_difficulty: Optional[int] = SchemaField(
+            description="Keyword difficulty score", default=None
+        )
+        serp_info: Optional[Dict[str, Any]] = SchemaField(
+            description="data from SERP for each keyword", default=None
+        )
+        clickstream_data: Optional[Dict[str, Any]] = SchemaField(
+            description="Clickstream data metrics", default=None
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="4193cb94-677c-48b0-9eec-6ac72fffd0f2",
+            description="Extract individual fields from a KeywordSuggestion object",
+            categories={BlockCategory.DATA},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "suggestion": KeywordSuggestion(
+                    keyword="test keyword",
+                    search_volume=1000,
+                    competition=0.5,
+                    cpc=2.5,
+                    keyword_difficulty=60,
+                ).model_dump()
+            },
+            test_output=[
+                ("keyword", "test keyword"),
+                ("search_volume", 1000),
+                ("competition", 0.5),
+                ("cpc", 2.5),
+                ("keyword_difficulty", 60),
+                ("serp_info", None),
+                ("clickstream_data", None),
+            ],
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        **kwargs,
+    ) -> BlockOutput:
+        """Extract fields from the KeywordSuggestion object."""
+        suggestion = input_data.suggestion
+
+        yield "keyword", suggestion.keyword
+        yield "search_volume", suggestion.search_volume
+        yield "competition", suggestion.competition
+        yield "cpc", suggestion.cpc
+        yield "keyword_difficulty", suggestion.keyword_difficulty
+        yield "serp_info", suggestion.serp_info
+        yield "clickstream_data", suggestion.clickstream_data

autogpt_platform/backend/backend/blocks/dataforseo/related_keywords.py

@@ -0,0 +1,283 @@
+"""
+DataForSEO Google Related Keywords block.
+"""
+
+from typing import Any, Dict, List, Optional
+
+from backend.sdk import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchema,
+    CredentialsMetaInput,
+    SchemaField,
+    UserPasswordCredentials,
+)
+
+from ._api import DataForSeoClient
+from ._config import dataforseo
+
+
+class RelatedKeyword(BlockSchema):
+    """Schema for a related keyword result."""
+
+    keyword: str = SchemaField(description="The related keyword")
+    search_volume: Optional[int] = SchemaField(
+        description="Monthly search volume", default=None
+    )
+    competition: Optional[float] = SchemaField(
+        description="Competition level (0-1)", default=None
+    )
+    cpc: Optional[float] = SchemaField(
+        description="Cost per click in USD", default=None
+    )
+    keyword_difficulty: Optional[int] = SchemaField(
+        description="Keyword difficulty score", default=None
+    )
+    serp_info: Optional[Dict[str, Any]] = SchemaField(
+        description="SERP data for the keyword", default=None
+    )
+    clickstream_data: Optional[Dict[str, Any]] = SchemaField(
+        description="Clickstream data metrics", default=None
+    )
+
+
+class DataForSeoRelatedKeywordsBlock(Block):
+    """Block for getting related keywords from DataForSEO Labs."""
+
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput = dataforseo.credentials_field(
+            description="DataForSEO credentials (username and password)"
+        )
+        keyword: str = SchemaField(
+            description="Seed keyword to find related keywords for"
+        )
+        location_code: Optional[int] = SchemaField(
+            description="Location code for targeting (e.g., 2840 for USA)",
+            default=2840,  # USA
+        )
+        language_code: Optional[str] = SchemaField(
+            description="Language code (e.g., 'en' for English)",
+            default="en",
+        )
+        include_seed_keyword: bool = SchemaField(
+            description="Include the seed keyword in results",
+            default=True,
+        )
+        include_serp_info: bool = SchemaField(
+            description="Include SERP information",
+            default=False,
+        )
+        include_clickstream_data: bool = SchemaField(
+            description="Include clickstream metrics",
+            default=False,
+        )
+        limit: int = SchemaField(
+            description="Maximum number of results (up to 3000)",
+            default=100,
+            ge=1,
+            le=3000,
+        )
+
+    class Output(BlockSchema):
+        related_keywords: List[RelatedKeyword] = SchemaField(
+            description="List of related keywords with metrics"
+        )
+        related_keyword: RelatedKeyword = SchemaField(
+            description="A related keyword with metrics"
+        )
+        total_count: int = SchemaField(
+            description="Total number of related keywords returned"
+        )
+        seed_keyword: str = SchemaField(
+            description="The seed keyword used for the query"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="8f2e4d6a-1b3c-4a5e-9d7f-2c8e6a4b3f1d",
+            description="Get related keywords from DataForSEO Labs Google API",
+            categories={BlockCategory.SEARCH, BlockCategory.DATA},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "credentials": dataforseo.get_test_credentials().model_dump(),
+                "keyword": "content marketing",
+                "location_code": 2840,
+                "language_code": "en",
+                "limit": 1,
+            },
+            test_credentials=dataforseo.get_test_credentials(),
+            test_output=[
+                (
+                    "related_keyword",
+                    lambda x: hasattr(x, "keyword") and x.keyword == "content strategy",
+                ),
+                ("related_keywords", lambda x: isinstance(x, list) and len(x) == 1),
+                ("total_count", 1),
+                ("seed_keyword", "content marketing"),
+            ],
+            test_mock={
+                "_fetch_related_keywords": lambda *args, **kwargs: [
+                    {
+                        "items": [
+                            {
+                                "keyword_data": {
+                                    "keyword": "content strategy",
+                                    "keyword_info": {
+                                        "search_volume": 8000,
+                                        "competition": 0.4,
+                                        "cpc": 3.0,
+                                    },
+                                    "keyword_properties": {
+                                        "keyword_difficulty": 45,
+                                    },
+                                }
+                            }
+                        ]
+                    }
+                ]
+            },
+        )
+
+    async def _fetch_related_keywords(
+        self,
+        client: DataForSeoClient,
+        input_data: Input,
+    ) -> Any:
+        """Private method to fetch related keywords - can be mocked for testing."""
+        return await client.related_keywords(
+            keyword=input_data.keyword,
+            location_code=input_data.location_code,
+            language_code=input_data.language_code,
+            include_seed_keyword=input_data.include_seed_keyword,
+            include_serp_info=input_data.include_serp_info,
+            include_clickstream_data=input_data.include_clickstream_data,
+            limit=input_data.limit,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: UserPasswordCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        """Execute the related keywords query."""
+        client = DataForSeoClient(credentials)
+
+        results = await self._fetch_related_keywords(client, input_data)
+
+        # Process and format the results
+        related_keywords = []
+        if results and len(results) > 0:
+            # results is a list, get the first element
+            first_result = results[0] if isinstance(results, list) else results
+            items = (
+                first_result.get("items", []) if isinstance(first_result, dict) else []
+            )
+            for item in items:
+                # Extract keyword_data from the item
+                keyword_data = item.get("keyword_data", {})
+
+                # Create the RelatedKeyword object
+                keyword = RelatedKeyword(
+                    keyword=keyword_data.get("keyword", ""),
+                    search_volume=keyword_data.get("keyword_info", {}).get(
+                        "search_volume"
+                    ),
+                    competition=keyword_data.get("keyword_info", {}).get("competition"),
+                    cpc=keyword_data.get("keyword_info", {}).get("cpc"),
+                    keyword_difficulty=keyword_data.get("keyword_properties", {}).get(
+                        "keyword_difficulty"
+                    ),
+                    serp_info=(
+                        keyword_data.get("serp_info")
+                        if input_data.include_serp_info
+                        else None
+                    ),
+                    clickstream_data=(
+                        keyword_data.get("clickstream_keyword_info")
+                        if input_data.include_clickstream_data
+                        else None
+                    ),
+                )
+                yield "related_keyword", keyword
+                related_keywords.append(keyword)
+
+        yield "related_keywords", related_keywords
+        yield "total_count", len(related_keywords)
+        yield "seed_keyword", input_data.keyword
+
+
+class RelatedKeywordExtractorBlock(Block):
+    """Extracts individual fields from a RelatedKeyword object."""
+
+    class Input(BlockSchema):
+        related_keyword: RelatedKeyword = SchemaField(
+            description="The related keyword object to extract fields from"
+        )
+
+    class Output(BlockSchema):
+        keyword: str = SchemaField(description="The related keyword")
+        search_volume: Optional[int] = SchemaField(
+            description="Monthly search volume", default=None
+        )
+        competition: Optional[float] = SchemaField(
+            description="Competition level (0-1)", default=None
+        )
+        cpc: Optional[float] = SchemaField(
+            description="Cost per click in USD", default=None
+        )
+        keyword_difficulty: Optional[int] = SchemaField(
+            description="Keyword difficulty score", default=None
+        )
+        serp_info: Optional[Dict[str, Any]] = SchemaField(
+            description="SERP data for the keyword", default=None
+        )
+        clickstream_data: Optional[Dict[str, Any]] = SchemaField(
+            description="Clickstream data metrics", default=None
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="98342061-09d2-4952-bf77-0761fc8cc9a8",
+            description="Extract individual fields from a RelatedKeyword object",
+            categories={BlockCategory.DATA},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "related_keyword": RelatedKeyword(
+                    keyword="test related keyword",
+                    search_volume=800,
+                    competition=0.4,
+                    cpc=3.0,
+                    keyword_difficulty=55,
+                ).model_dump()
+            },
+            test_output=[
+                ("keyword", "test related keyword"),
+                ("search_volume", 800),
+                ("competition", 0.4),
+                ("cpc", 3.0),
+                ("keyword_difficulty", 55),
+                ("serp_info", None),
+                ("clickstream_data", None),
+            ],
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        **kwargs,
+    ) -> BlockOutput:
+        """Extract fields from the RelatedKeyword object."""
+        related_keyword = input_data.related_keyword
+
+        yield "keyword", related_keyword.keyword
+        yield "search_volume", related_keyword.search_volume
+        yield "competition", related_keyword.competition
+        yield "cpc", related_keyword.cpc
+        yield "keyword_difficulty", related_keyword.keyword_difficulty
+        yield "serp_info", related_keyword.serp_info
+        yield "clickstream_data", related_keyword.clickstream_data

autogpt_platform/backend/backend/blocks/discord/_api.py

@@ -0,0 +1,117 @@
+"""
+Discord API helper functions for making authenticated requests.
+"""
+
+import logging
+from typing import Optional
+
+from pydantic import BaseModel
+
+from backend.data.model import OAuth2Credentials
+from backend.util.request import Requests
+
+logger = logging.getLogger(__name__)
+
+
+class DiscordAPIException(Exception):
+    """Exception raised for Discord API errors."""
+
+    def __init__(self, message: str, status_code: int):
+        super().__init__(message)
+        self.status_code = status_code
+
+
+class DiscordOAuthUser(BaseModel):
+    """Model for Discord OAuth user response."""
+
+    user_id: str
+    username: str
+    avatar_url: str
+    banner: Optional[str] = None
+    accent_color: Optional[int] = None
+
+
+def get_api(credentials: OAuth2Credentials) -> Requests:
+    """
+    Create a Requests instance configured for Discord API calls with OAuth2 credentials.
+
+    Args:
+        credentials: The OAuth2 credentials containing the access token.
+
+    Returns:
+        A configured Requests instance for Discord API calls.
+    """
+    return Requests(
+        trusted_origins=[],
+        extra_headers={
+            "Authorization": f"Bearer {credentials.access_token.get_secret_value()}",
+            "Content-Type": "application/json",
+        },
+        raise_for_status=False,
+    )
+
+
+async def get_current_user(credentials: OAuth2Credentials) -> DiscordOAuthUser:
+    """
+    Fetch the current user's information using Discord OAuth2 API.
+
+    Reference: https://discord.com/developers/docs/resources/user#get-current-user
+
+    Args:
+        credentials: The OAuth2 credentials.
+
+    Returns:
+        A model containing user data with avatar URL.
+
+    Raises:
+        DiscordAPIException: If the API request fails.
+    """
+    api = get_api(credentials)
+    response = await api.get("https://discord.com/api/oauth2/@me")
+
+    if not response.ok:
+        error_text = response.text()
+        raise DiscordAPIException(
+            f"Failed to fetch user info: {response.status} - {error_text}",
+            response.status,
+        )
+
+    data = response.json()
+    logger.info(f"Discord OAuth2 API Response: {data}")
+
+    # The /api/oauth2/@me endpoint returns a user object nested in the response
+    user_info = data.get("user", {})
+    logger.info(f"User info extracted: {user_info}")
+
+    # Build avatar URL
+    user_id = user_info.get("id")
+    avatar_hash = user_info.get("avatar")
+    if avatar_hash:
+        # Custom avatar
+        avatar_ext = "gif" if avatar_hash.startswith("a_") else "png"
+        avatar_url = (
+            f"https://cdn.discordapp.com/avatars/{user_id}/{avatar_hash}.{avatar_ext}"
+        )
+    else:
+        # Default avatar based on discriminator or user ID
+        discriminator = user_info.get("discriminator", "0")
+        if discriminator == "0":
+            # New username system - use user ID for default avatar
+            default_avatar_index = (int(user_id) >> 22) % 6
+        else:
+            # Legacy discriminator system
+            default_avatar_index = int(discriminator) % 5
+        avatar_url = (
+            f"https://cdn.discordapp.com/embed/avatars/{default_avatar_index}.png"
+        )
+
+    result = DiscordOAuthUser(
+        user_id=user_id,
+        username=user_info.get("username", ""),
+        avatar_url=avatar_url,
+        banner=user_info.get("banner"),
+        accent_color=user_info.get("accent_color"),
+    )
+
+    logger.info(f"Returning user data: {result.model_dump()}")
+    return result

autogpt_platform/backend/backend/blocks/discord/_auth.py

@@ -0,0 +1,74 @@
+from typing import Literal
+
+from pydantic import SecretStr
+
+from backend.data.model import (
+    APIKeyCredentials,
+    CredentialsField,
+    CredentialsMetaInput,
+    OAuth2Credentials,
+)
+from backend.integrations.providers import ProviderName
+from backend.util.settings import Secrets
+
+secrets = Secrets()
+DISCORD_OAUTH_IS_CONFIGURED = bool(
+    secrets.discord_client_id and secrets.discord_client_secret
+)
+
+# Bot token credentials (existing)
+DiscordBotCredentials = APIKeyCredentials
+DiscordBotCredentialsInput = CredentialsMetaInput[
+    Literal[ProviderName.DISCORD], Literal["api_key"]
+]
+
+# OAuth2 credentials (new)
+DiscordOAuthCredentials = OAuth2Credentials
+DiscordOAuthCredentialsInput = CredentialsMetaInput[
+    Literal[ProviderName.DISCORD], Literal["oauth2"]
+]
+
+
+def DiscordBotCredentialsField() -> DiscordBotCredentialsInput:
+    """Creates a Discord bot token credentials field."""
+    return CredentialsField(description="Discord bot token")
+
+
+def DiscordOAuthCredentialsField(scopes: list[str]) -> DiscordOAuthCredentialsInput:
+    """Creates a Discord OAuth2 credentials field."""
+    return CredentialsField(
+        description="Discord OAuth2 credentials",
+        required_scopes=set(scopes) | {"identify"},  # Basic user info scope
+    )
+
+
+# Test credentials for bot tokens
+TEST_BOT_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="discord",
+    api_key=SecretStr("test_api_key"),
+    title="Mock Discord API key",
+    expires_at=None,
+)
+TEST_BOT_CREDENTIALS_INPUT = {
+    "provider": TEST_BOT_CREDENTIALS.provider,
+    "id": TEST_BOT_CREDENTIALS.id,
+    "type": TEST_BOT_CREDENTIALS.type,
+    "title": TEST_BOT_CREDENTIALS.type,
+}
+
+# Test credentials for OAuth2
+TEST_OAUTH_CREDENTIALS = OAuth2Credentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="discord",
+    access_token=SecretStr("test_access_token"),
+    title="Mock Discord OAuth",
+    scopes=["identify"],
+    username="testuser",
+)
+TEST_OAUTH_CREDENTIALS_INPUT = {
+    "provider": TEST_OAUTH_CREDENTIALS.provider,
+    "id": TEST_OAUTH_CREDENTIALS.id,
+    "type": TEST_OAUTH_CREDENTIALS.type,
+    "title": TEST_OAUTH_CREDENTIALS.type,
+}

autogpt_platform/backend/backend/blocks/discord/bot_blocks.py

@@ -2,45 +2,29 @@ import base64
 import io
 import mimetypes
 from pathlib import Path
-from typing import Any, Literal
+from typing import Any
 
 import aiohttp
 import discord
 from pydantic import SecretStr
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
-from backend.data.model import (
-    APIKeyCredentials,
-    CredentialsField,
-    CredentialsMetaInput,
-    SchemaField,
-)
-from backend.integrations.providers import ProviderName
+from backend.data.model import APIKeyCredentials, SchemaField
 from backend.util.file import store_media_file
 from backend.util.type import MediaFileType
 
-DiscordCredentials = CredentialsMetaInput[
-    Literal[ProviderName.DISCORD], Literal["api_key"]
-]
-
-
-def DiscordCredentialsField() -> DiscordCredentials:
-    return CredentialsField(description="Discord bot token")
-
-
-TEST_CREDENTIALS = APIKeyCredentials(
-    id="01234567-89ab-cdef-0123-456789abcdef",
-    provider="discord",
-    api_key=SecretStr("test_api_key"),
-    title="Mock Discord API key",
-    expires_at=None,
+from ._auth import (
+    TEST_BOT_CREDENTIALS,
+    TEST_BOT_CREDENTIALS_INPUT,
+    DiscordBotCredentialsField,
+    DiscordBotCredentialsInput,
 )
-TEST_CREDENTIALS_INPUT = {
-    "provider": TEST_CREDENTIALS.provider,
-    "id": TEST_CREDENTIALS.id,
-    "type": TEST_CREDENTIALS.type,
-    "title": TEST_CREDENTIALS.type,
-}
+
+# Keep backward compatibility alias
+DiscordCredentials = DiscordBotCredentialsInput
+DiscordCredentialsField = DiscordBotCredentialsField
+TEST_CREDENTIALS = TEST_BOT_CREDENTIALS
+TEST_CREDENTIALS_INPUT = TEST_BOT_CREDENTIALS_INPUT
 
 
 class ReadDiscordMessagesBlock(Block):

autogpt_platform/backend/backend/blocks/discord/oauth_blocks.py

@@ -0,0 +1,99 @@
+"""
+Discord OAuth-based blocks.
+"""
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import OAuth2Credentials, SchemaField
+
+from ._api import DiscordOAuthUser, get_current_user
+from ._auth import (
+    DISCORD_OAUTH_IS_CONFIGURED,
+    TEST_OAUTH_CREDENTIALS,
+    TEST_OAUTH_CREDENTIALS_INPUT,
+    DiscordOAuthCredentialsField,
+    DiscordOAuthCredentialsInput,
+)
+
+
+class DiscordGetCurrentUserBlock(Block):
+    """
+    Gets information about the currently authenticated Discord user using OAuth2.
+    This block requires Discord OAuth2 credentials (not bot tokens).
+    """
+
+    class Input(BlockSchema):
+        credentials: DiscordOAuthCredentialsInput = DiscordOAuthCredentialsField(
+            ["identify"]
+        )
+
+    class Output(BlockSchema):
+        user_id: str = SchemaField(description="The authenticated user's Discord ID")
+        username: str = SchemaField(description="The user's username")
+        avatar_url: str = SchemaField(description="URL to the user's avatar image")
+        banner_url: str = SchemaField(
+            description="URL to the user's banner image (if set)", default=""
+        )
+        accent_color: int = SchemaField(
+            description="The user's accent color as an integer", default=0
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="8c7e39b8-4e9d-4f3a-b4e1-2a8c9d5f6e3b",
+            input_schema=DiscordGetCurrentUserBlock.Input,
+            output_schema=DiscordGetCurrentUserBlock.Output,
+            description="Gets information about the currently authenticated Discord user using OAuth2 credentials.",
+            categories={BlockCategory.SOCIAL},
+            disabled=not DISCORD_OAUTH_IS_CONFIGURED,
+            test_input={
+                "credentials": TEST_OAUTH_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_OAUTH_CREDENTIALS,
+            test_output=[
+                ("user_id", "123456789012345678"),
+                ("username", "testuser"),
+                (
+                    "avatar_url",
+                    "https://cdn.discordapp.com/avatars/123456789012345678/avatar.png",
+                ),
+                ("banner_url", ""),
+                ("accent_color", 0),
+            ],
+            test_mock={
+                "get_user": lambda _: DiscordOAuthUser(
+                    user_id="123456789012345678",
+                    username="testuser",
+                    avatar_url="https://cdn.discordapp.com/avatars/123456789012345678/avatar.png",
+                    banner=None,
+                    accent_color=0,
+                )
+            },
+        )
+
+    @staticmethod
+    async def get_user(credentials: OAuth2Credentials) -> DiscordOAuthUser:
+        user_info = await get_current_user(credentials)
+        return user_info
+
+    async def run(
+        self, input_data: Input, *, credentials: OAuth2Credentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            result = await self.get_user(credentials)
+
+            # Yield each output field
+            yield "user_id", result.user_id
+            yield "username", result.username
+            yield "avatar_url", result.avatar_url
+
+            # Handle banner URL if banner hash exists
+            if result.banner:
+                banner_url = f"https://cdn.discordapp.com/banners/{result.user_id}/{result.banner}.png"
+                yield "banner_url", banner_url
+            else:
+                yield "banner_url", ""
+
+            yield "accent_color", result.accent_color or 0
+
+        except Exception as e:
+            raise ValueError(f"Failed to get Discord user info: {e}")

autogpt_platform/backend/backend/blocks/google/gmail.py

@@ -39,6 +39,18 @@ def serialize_email_recipients(recipients: list[str]) -> str:
     return ", ".join(recipients)
 
 
+def deduplicate_email_addresses(addresses: list[str]) -> list[str]:
+    """Deduplicate email addresses while preserving order.
+
+    Args:
+        addresses: List of email addresses that may contain duplicates or None values
+
+    Returns:
+        List of unique email addresses with None values filtered out
+    """
+    return list(dict.fromkeys(filter(None, addresses)))
+
+
 def _make_mime_text(
     body: str,
     content_type: Optional[Literal["auto", "plain", "html"]] = None,
@@ -1263,11 +1275,8 @@ class GmailReplyBlock(GmailBase):
                 recipients += [
                     addr for _, addr in getaddresses([headers.get("cc", "")])
                 ]
-                dedup: list[str] = []
-                for r in recipients:
-                    if r and r not in dedup:
-                        dedup.append(r)
-                input_data.to = dedup
+                # Deduplicate recipients while preserving order
+                input_data.to = deduplicate_email_addresses(recipients)
             else:
                 sender = parseaddr(headers.get("reply-to", headers.get("from", "")))[1]
                 input_data.to = [sender] if sender else []
@@ -1317,6 +1326,224 @@ class GmailReplyBlock(GmailBase):
         )
 
 
+class GmailCreateDraftReplyBlock(GmailBase):
+    """
+    Creates draft replies to Gmail threads with intelligent content type detection.
+
+    Features:
+    - Automatic HTML detection: Draft replies containing HTML tags are formatted as text/html
+    - No hard-wrap for plain text: Plain text drafts preserve natural line flow
+    - Manual content type override: Use content_type parameter to force specific format
+    - Reply-all functionality: Option to draft reply to all original recipients
+    - Thread preservation: Maintains proper email threading with headers
+    - Full Unicode/emoji support with UTF-8 encoding
+    - Attachment support for multiple files
+    """
+
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            [
+                "https://www.googleapis.com/auth/gmail.modify",
+                "https://www.googleapis.com/auth/gmail.readonly",
+            ]
+        )
+        threadId: str = SchemaField(description="Thread ID to reply in")
+        parentMessageId: str = SchemaField(
+            description="ID of the message being replied to"
+        )
+        to: list[str] = SchemaField(description="To recipients", default_factory=list)
+        cc: list[str] = SchemaField(description="CC recipients", default_factory=list)
+        bcc: list[str] = SchemaField(description="BCC recipients", default_factory=list)
+        replyAll: bool = SchemaField(
+            description="Reply to all original recipients", default=False
+        )
+        subject: str = SchemaField(description="Email subject", default="")
+        body: str = SchemaField(description="Email body (plain text or HTML)")
+        content_type: Optional[Literal["auto", "plain", "html"]] = SchemaField(
+            description="Content type: 'auto' (default - detects HTML), 'plain', or 'html'",
+            default=None,
+            advanced=True,
+        )
+        attachments: list[MediaFileType] = SchemaField(
+            description="Files to attach", default_factory=list, advanced=True
+        )
+
+    class Output(BlockSchema):
+        draftId: str = SchemaField(description="Created draft ID")
+        messageId: str = SchemaField(description="Draft message ID")
+        threadId: str = SchemaField(description="Thread ID")
+        status: str = SchemaField(description="Draft creation status")
+        error: str = SchemaField(description="Error message if any")
+
+    def __init__(self):
+        super().__init__(
+            id="8f2e9d3c-4b1a-4c7e-9a2f-1d3e5f7a9b1c",
+            description="Create draft replies to Gmail threads with automatic HTML detection and proper text formatting. Drafts maintain proper email threading and can be edited before sending.",
+            categories={BlockCategory.COMMUNICATION},
+            input_schema=GmailCreateDraftReplyBlock.Input,
+            output_schema=GmailCreateDraftReplyBlock.Output,
+            disabled=not GOOGLE_OAUTH_IS_CONFIGURED,
+            test_input={
+                "threadId": "t1",
+                "parentMessageId": "m1",
+                "body": "Thanks for your message. I'll draft a response.",
+                "replyAll": False,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("draftId", "draft1"),
+                ("messageId", "msg1"),
+                ("threadId", "t1"),
+                ("status", "draft_reply_created"),
+            ],
+            test_mock={
+                "_create_draft_reply": lambda *args, **kwargs: {
+                    "id": "draft1",
+                    "message": {"id": "msg1", "threadId": "t1"},
+                },
+            },
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GoogleCredentials,
+        graph_exec_id: str,
+        user_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        service = self._build_service(credentials, **kwargs)
+        result = await self._create_draft_reply(
+            service,
+            input_data,
+            graph_exec_id,
+            user_id,
+        )
+        yield "draftId", result["id"]
+        yield "messageId", result["message"]["id"]
+        yield "threadId", result["message"].get("threadId", input_data.threadId)
+        yield "status", "draft_reply_created"
+
+    async def _create_draft_reply(
+        self, service, input_data: Input, graph_exec_id: str, user_id: str
+    ) -> dict:
+        # Fetch parent message metadata
+        parent = await asyncio.to_thread(
+            lambda: service.users()
+            .messages()
+            .get(
+                userId="me",
+                id=input_data.parentMessageId,
+                format="metadata",
+                metadataHeaders=[
+                    "Subject",
+                    "References",
+                    "Message-ID",
+                    "From",
+                    "To",
+                    "Cc",
+                    "Reply-To",
+                ],
+            )
+            .execute()
+        )
+
+        headers = {
+            h["name"].lower(): h["value"]
+            for h in parent.get("payload", {}).get("headers", [])
+        }
+
+        # Auto-populate recipients if not provided
+        if not (input_data.to or input_data.cc or input_data.bcc):
+            if input_data.replyAll:
+                # Reply all - include all original recipients
+                recipients = [parseaddr(headers.get("from", ""))[1]]
+                recipients += [
+                    addr for _, addr in getaddresses([headers.get("to", "")])
+                ]
+                recipients += [
+                    addr for _, addr in getaddresses([headers.get("cc", "")])
+                ]
+                # Deduplicate recipients
+                dedup: list[str] = []
+                for r in recipients:
+                    if r and r not in dedup:
+                        dedup.append(r)
+                input_data.to = dedup
+            else:
+                # Reply to sender only
+                sender = parseaddr(headers.get("reply-to", headers.get("from", "")))[1]
+                input_data.to = [sender] if sender else []
+
+        # Generate subject with Re: prefix if needed
+        subject = input_data.subject or (f"Re: {headers.get('subject', '')}".strip())
+
+        # Build References header chain
+        references = headers.get("references", "").split()
+        if headers.get("message-id"):
+            references.append(headers["message-id"])
+
+        # Create MIME message with threading headers
+        msg = MIMEMultipart()
+        if input_data.to:
+            msg["To"] = ", ".join(input_data.to)
+        if input_data.cc:
+            msg["Cc"] = ", ".join(input_data.cc)
+        if input_data.bcc:
+            msg["Bcc"] = ", ".join(input_data.bcc)
+        msg["Subject"] = subject
+
+        # Set threading headers for proper conversation grouping
+        if headers.get("message-id"):
+            msg["In-Reply-To"] = headers["message-id"]
+        if references:
+            msg["References"] = " ".join(references)
+
+        # Add body with proper content type handling
+        msg.attach(_make_mime_text(input_data.body, input_data.content_type))
+
+        # Handle attachments if any
+        for attach in input_data.attachments:
+            local_path = await store_media_file(
+                user_id=user_id,
+                graph_exec_id=graph_exec_id,
+                file=attach,
+                return_content=False,
+            )
+            abs_path = get_exec_file_path(graph_exec_id, local_path)
+            part = MIMEBase("application", "octet-stream")
+            with open(abs_path, "rb") as f:
+                part.set_payload(f.read())
+            encoders.encode_base64(part)
+            part.add_header(
+                "Content-Disposition", f"attachment; filename={Path(abs_path).name}"
+            )
+            msg.attach(part)
+
+        # Encode message for Gmail API
+        raw = base64.urlsafe_b64encode(msg.as_bytes()).decode("utf-8")
+
+        # Create draft with threadId to ensure it appears as a reply
+        draft = await asyncio.to_thread(
+            lambda: service.users()
+            .drafts()
+            .create(
+                userId="me",
+                body={
+                    "message": {
+                        "threadId": input_data.threadId,
+                        "raw": raw,
+                    }
+                },
+            )
+            .execute()
+        )
+
+        return draft
+
+
 class GmailGetProfileBlock(GmailBase):
     class Input(BlockSchema):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(

autogpt_platform/backend/backend/blocks/system/__init__.py

@@ -0,0 +1 @@
+

autogpt_platform/backend/backend/blocks/system/library_operations.py

@@ -0,0 +1,283 @@
+import logging
+from typing import Any
+
+from pydantic import BaseModel
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+from backend.util.clients import get_database_manager_async_client
+
+logger = logging.getLogger(__name__)
+
+
+# Duplicate pydantic models for store data so we don't accidently change the data shape in the blocks unintentionally when editing the backend
+class LibraryAgent(BaseModel):
+    """Model representing an agent in the user's library."""
+
+    library_agent_id: str = ""
+    agent_id: str = ""
+    agent_version: int = 0
+    agent_name: str = ""
+    description: str = ""
+    creator: str = ""
+    is_archived: bool = False
+    categories: list[str] = []
+
+
+class AddToLibraryFromStoreBlock(Block):
+    """
+    Block that adds an agent from the store to the user's library.
+    This enables users to easily import agents from the marketplace into their personal collection.
+    """
+
+    class Input(BlockSchema):
+        store_listing_version_id: str = SchemaField(
+            description="The ID of the store listing version to add to library"
+        )
+        agent_name: str | None = SchemaField(
+            description="Optional custom name for the agent in your library",
+            default=None,
+        )
+
+    class Output(BlockSchema):
+        success: bool = SchemaField(
+            description="Whether the agent was successfully added to library"
+        )
+        library_agent_id: str = SchemaField(
+            description="The ID of the library agent entry"
+        )
+        agent_id: str = SchemaField(description="The ID of the agent graph")
+        agent_version: int = SchemaField(
+            description="The version number of the agent graph"
+        )
+        agent_name: str = SchemaField(description="The name of the agent")
+        message: str = SchemaField(description="Success or error message")
+
+    def __init__(self):
+        super().__init__(
+            id="2602a7b1-3f4d-4e5f-9c8b-1a2b3c4d5e6f",
+            description="Add an agent from the store to your personal library",
+            categories={BlockCategory.BASIC},
+            input_schema=AddToLibraryFromStoreBlock.Input,
+            output_schema=AddToLibraryFromStoreBlock.Output,
+            test_input={
+                "store_listing_version_id": "test-listing-id",
+                "agent_name": "My Custom Agent",
+            },
+            test_output=[
+                ("success", True),
+                ("library_agent_id", "test-library-id"),
+                ("agent_id", "test-agent-id"),
+                ("agent_version", 1),
+                ("agent_name", "Test Agent"),
+                ("message", "Agent successfully added to library"),
+            ],
+            test_mock={
+                "_add_to_library": lambda *_, **__: LibraryAgent(
+                    library_agent_id="test-library-id",
+                    agent_id="test-agent-id",
+                    agent_version=1,
+                    agent_name="Test Agent",
+                )
+            },
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        user_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        library_agent = await self._add_to_library(
+            user_id=user_id,
+            store_listing_version_id=input_data.store_listing_version_id,
+            custom_name=input_data.agent_name,
+        )
+
+        yield "success", True
+        yield "library_agent_id", library_agent.library_agent_id
+        yield "agent_id", library_agent.agent_id
+        yield "agent_version", library_agent.agent_version
+        yield "agent_name", library_agent.agent_name
+        yield "message", "Agent successfully added to library"
+
+    async def _add_to_library(
+        self,
+        user_id: str,
+        store_listing_version_id: str,
+        custom_name: str | None = None,
+    ) -> LibraryAgent:
+        """
+        Add a store agent to the user's library using the existing library database function.
+        """
+        library_agent = (
+            await get_database_manager_async_client().add_store_agent_to_library(
+                store_listing_version_id=store_listing_version_id, user_id=user_id
+            )
+        )
+
+        # If custom name is provided, we could update the library agent name here
+        # For now, we'll just return the agent info
+        agent_name = custom_name if custom_name else library_agent.name
+
+        return LibraryAgent(
+            library_agent_id=library_agent.id,
+            agent_id=library_agent.graph_id,
+            agent_version=library_agent.graph_version,
+            agent_name=agent_name,
+        )
+
+
+class ListLibraryAgentsBlock(Block):
+    """
+    Block that lists all agents in the user's library.
+    """
+
+    class Input(BlockSchema):
+        search_query: str | None = SchemaField(
+            description="Optional search query to filter agents", default=None
+        )
+        limit: int = SchemaField(
+            description="Maximum number of agents to return", default=50, ge=1, le=100
+        )
+        page: int = SchemaField(
+            description="Page number for pagination", default=1, ge=1
+        )
+
+    class Output(BlockSchema):
+        agents: list[LibraryAgent] = SchemaField(
+            description="List of agents in the library",
+            default_factory=list,
+        )
+        agent: LibraryAgent = SchemaField(
+            description="Individual library agent (yielded for each agent)"
+        )
+        total_count: int = SchemaField(
+            description="Total number of agents in library", default=0
+        )
+        page: int = SchemaField(description="Current page number", default=1)
+        total_pages: int = SchemaField(description="Total number of pages", default=1)
+
+    def __init__(self):
+        super().__init__(
+            id="082602d3-a74d-4600-9e9c-15b3af7eae98",
+            description="List all agents in your personal library",
+            categories={BlockCategory.BASIC, BlockCategory.DATA},
+            input_schema=ListLibraryAgentsBlock.Input,
+            output_schema=ListLibraryAgentsBlock.Output,
+            test_input={
+                "search_query": None,
+                "limit": 10,
+                "page": 1,
+            },
+            test_output=[
+                (
+                    "agents",
+                    [
+                        LibraryAgent(
+                            library_agent_id="test-lib-id",
+                            agent_id="test-agent-id",
+                            agent_version=1,
+                            agent_name="Test Library Agent",
+                            description="A test agent in library",
+                            creator="Test User",
+                        ),
+                    ],
+                ),
+                ("total_count", 1),
+                ("page", 1),
+                ("total_pages", 1),
+                (
+                    "agent",
+                    LibraryAgent(
+                        library_agent_id="test-lib-id",
+                        agent_id="test-agent-id",
+                        agent_version=1,
+                        agent_name="Test Library Agent",
+                        description="A test agent in library",
+                        creator="Test User",
+                    ),
+                ),
+            ],
+            test_mock={
+                "_list_library_agents": lambda *_, **__: {
+                    "agents": [
+                        LibraryAgent(
+                            library_agent_id="test-lib-id",
+                            agent_id="test-agent-id",
+                            agent_version=1,
+                            agent_name="Test Library Agent",
+                            description="A test agent in library",
+                            creator="Test User",
+                        )
+                    ],
+                    "total": 1,
+                    "page": 1,
+                    "total_pages": 1,
+                }
+            },
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        user_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        result = await self._list_library_agents(
+            user_id=user_id,
+            search_query=input_data.search_query,
+            limit=input_data.limit,
+            page=input_data.page,
+        )
+
+        agents = result["agents"]
+
+        yield "agents", agents
+        yield "total_count", result["total"]
+        yield "page", result["page"]
+        yield "total_pages", result["total_pages"]
+
+        # Yield each agent individually for better graph connectivity
+        for agent in agents:
+            yield "agent", agent
+
+    async def _list_library_agents(
+        self,
+        user_id: str,
+        search_query: str | None = None,
+        limit: int = 50,
+        page: int = 1,
+    ) -> dict[str, Any]:
+        """
+        List agents in the user's library using the database client.
+        """
+        result = await get_database_manager_async_client().list_library_agents(
+            user_id=user_id,
+            search_term=search_query,
+            page=page,
+            page_size=limit,
+        )
+
+        agents = [
+            LibraryAgent(
+                library_agent_id=agent.id,
+                agent_id=agent.graph_id,
+                agent_version=agent.graph_version,
+                agent_name=agent.name,
+                description=getattr(agent, "description", ""),
+                creator=getattr(agent, "creator", ""),
+                is_archived=getattr(agent, "is_archived", False),
+                categories=getattr(agent, "categories", []),
+            )
+            for agent in result.agents
+        ]
+
+        return {
+            "agents": agents,
+            "total": result.pagination.total_items,
+            "page": result.pagination.current_page,
+            "total_pages": result.pagination.total_pages,
+        }

autogpt_platform/backend/backend/blocks/system/store_operations.py

@@ -0,0 +1,311 @@
+import logging
+from typing import Literal
+
+from pydantic import BaseModel
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+from backend.util.clients import get_database_manager_async_client
+
+logger = logging.getLogger(__name__)
+
+
+# Duplicate pydantic models for store data so we don't accidently change the data shape in the blocks unintentionally when editing the backend
+class StoreAgent(BaseModel):
+    """Model representing a store agent."""
+
+    slug: str = ""
+    name: str = ""
+    description: str = ""
+    creator: str = ""
+    rating: float = 0.0
+    runs: int = 0
+    categories: list[str] = []
+
+
+class StoreAgentDict(BaseModel):
+    """Dictionary representation of a store agent."""
+
+    slug: str
+    name: str
+    description: str
+    creator: str
+    rating: float
+    runs: int
+
+
+class SearchAgentsResponse(BaseModel):
+    """Response from searching store agents."""
+
+    agents: list[StoreAgentDict]
+    total_count: int
+
+
+class StoreAgentDetails(BaseModel):
+    """Detailed information about a store agent."""
+
+    found: bool
+    store_listing_version_id: str = ""
+    agent_name: str = ""
+    description: str = ""
+    creator: str = ""
+    categories: list[str] = []
+    runs: int = 0
+    rating: float = 0.0
+
+
+class GetStoreAgentDetailsBlock(Block):
+    """
+    Block that retrieves detailed information about an agent from the store.
+    """
+
+    class Input(BlockSchema):
+        creator: str = SchemaField(description="The username of the agent creator")
+        slug: str = SchemaField(description="The name of the agent")
+
+    class Output(BlockSchema):
+        found: bool = SchemaField(
+            description="Whether the agent was found in the store"
+        )
+        store_listing_version_id: str = SchemaField(
+            description="The store listing version ID"
+        )
+        agent_name: str = SchemaField(description="Name of the agent")
+        description: str = SchemaField(description="Description of the agent")
+        creator: str = SchemaField(description="Creator of the agent")
+        categories: list[str] = SchemaField(
+            description="Categories the agent belongs to", default_factory=list
+        )
+        runs: int = SchemaField(
+            description="Number of times the agent has been run", default=0
+        )
+        rating: float = SchemaField(
+            description="Average rating of the agent", default=0.0
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="b604f0ec-6e0d-40a7-bf55-9fd09997cced",
+            description="Get detailed information about an agent from the store",
+            categories={BlockCategory.BASIC, BlockCategory.DATA},
+            input_schema=GetStoreAgentDetailsBlock.Input,
+            output_schema=GetStoreAgentDetailsBlock.Output,
+            test_input={"creator": "test-creator", "slug": "test-agent-slug"},
+            test_output=[
+                ("found", True),
+                ("store_listing_version_id", "test-listing-id"),
+                ("agent_name", "Test Agent"),
+                ("description", "A test agent"),
+                ("creator", "Test Creator"),
+                ("categories", ["productivity", "automation"]),
+                ("runs", 100),
+                ("rating", 4.5),
+            ],
+            test_mock={
+                "_get_agent_details": lambda *_, **__: StoreAgentDetails(
+                    found=True,
+                    store_listing_version_id="test-listing-id",
+                    agent_name="Test Agent",
+                    description="A test agent",
+                    creator="Test Creator",
+                    categories=["productivity", "automation"],
+                    runs=100,
+                    rating=4.5,
+                )
+            },
+            static_output=True,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        **kwargs,
+    ) -> BlockOutput:
+        details = await self._get_agent_details(
+            creator=input_data.creator, slug=input_data.slug
+        )
+        yield "found", details.found
+        yield "store_listing_version_id", details.store_listing_version_id
+        yield "agent_name", details.agent_name
+        yield "description", details.description
+        yield "creator", details.creator
+        yield "categories", details.categories
+        yield "runs", details.runs
+        yield "rating", details.rating
+
+    async def _get_agent_details(self, creator: str, slug: str) -> StoreAgentDetails:
+        """
+        Retrieve detailed information about a store agent.
+        """
+        # Get by specific version ID
+        agent_details = (
+            await get_database_manager_async_client().get_store_agent_details(
+                username=creator, agent_name=slug
+            )
+        )
+
+        return StoreAgentDetails(
+            found=True,
+            store_listing_version_id=agent_details.store_listing_version_id,
+            agent_name=agent_details.agent_name,
+            description=agent_details.description,
+            creator=agent_details.creator,
+            categories=(
+                agent_details.categories if hasattr(agent_details, "categories") else []
+            ),
+            runs=agent_details.runs,
+            rating=agent_details.rating,
+        )
+
+
+class SearchStoreAgentsBlock(Block):
+    """
+    Block that searches for agents in the store based on various criteria.
+    """
+
+    class Input(BlockSchema):
+        query: str | None = SchemaField(
+            description="Search query to find agents", default=None
+        )
+        category: str | None = SchemaField(
+            description="Filter by category", default=None
+        )
+        sort_by: Literal["rating", "runs", "name", "recent"] = SchemaField(
+            description="How to sort the results", default="rating"
+        )
+        limit: int = SchemaField(
+            description="Maximum number of results to return", default=10, ge=1, le=100
+        )
+
+    class Output(BlockSchema):
+        agents: list[StoreAgent] = SchemaField(
+            description="List of agents matching the search criteria",
+            default_factory=list,
+        )
+        agent: StoreAgent = SchemaField(description="Basic information of the agent")
+        total_count: int = SchemaField(
+            description="Total number of agents found", default=0
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="39524701-026c-4328-87cc-1b88c8e2cb4c",
+            description="Search for agents in the store",
+            categories={BlockCategory.BASIC, BlockCategory.DATA},
+            input_schema=SearchStoreAgentsBlock.Input,
+            output_schema=SearchStoreAgentsBlock.Output,
+            test_input={
+                "query": "productivity",
+                "category": None,
+                "sort_by": "rating",
+                "limit": 10,
+            },
+            test_output=[
+                (
+                    "agents",
+                    [
+                        {
+                            "slug": "test-agent",
+                            "name": "Test Agent",
+                            "description": "A test agent",
+                            "creator": "Test Creator",
+                            "rating": 4.5,
+                            "runs": 100,
+                        }
+                    ],
+                ),
+                ("total_count", 1),
+                (
+                    "agent",
+                    {
+                        "slug": "test-agent",
+                        "name": "Test Agent",
+                        "description": "A test agent",
+                        "creator": "Test Creator",
+                        "rating": 4.5,
+                        "runs": 100,
+                    },
+                ),
+            ],
+            test_mock={
+                "_search_agents": lambda *_, **__: SearchAgentsResponse(
+                    agents=[
+                        StoreAgentDict(
+                            slug="test-agent",
+                            name="Test Agent",
+                            description="A test agent",
+                            creator="Test Creator",
+                            rating=4.5,
+                            runs=100,
+                        )
+                    ],
+                    total_count=1,
+                )
+            },
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        **kwargs,
+    ) -> BlockOutput:
+        result = await self._search_agents(
+            query=input_data.query,
+            category=input_data.category,
+            sort_by=input_data.sort_by,
+            limit=input_data.limit,
+        )
+
+        agents = result.agents
+        total_count = result.total_count
+
+        # Convert to dict for output
+        agents_as_dicts = [agent.model_dump() for agent in agents]
+
+        yield "agents", agents_as_dicts
+        yield "total_count", total_count
+
+        for agent_dict in agents_as_dicts:
+            yield "agent", agent_dict
+
+    async def _search_agents(
+        self,
+        query: str | None = None,
+        category: str | None = None,
+        sort_by: str = "rating",
+        limit: int = 10,
+    ) -> SearchAgentsResponse:
+        """
+        Search for agents in the store using the existing store database function.
+        """
+        # Map our sort_by to the store's sorted_by parameter
+        sorted_by_map = {
+            "rating": "most_popular",
+            "runs": "most_runs",
+            "name": "alphabetical",
+            "recent": "recently_updated",
+        }
+
+        result = await get_database_manager_async_client().get_store_agents(
+            featured=False,
+            creators=None,
+            sorted_by=sorted_by_map.get(sort_by, "most_popular"),
+            search_query=query,
+            category=category,
+            page=1,
+            page_size=limit,
+        )
+
+        agents = [
+            StoreAgentDict(
+                slug=agent.slug,
+                name=agent.agent_name,
+                description=agent.description,
+                creator=agent.creator,
+                rating=agent.rating,
+                runs=agent.runs,
+            )
+            for agent in result.agents
+        ]
+
+        return SearchAgentsResponse(agents=agents, total_count=len(agents))

autogpt_platform/backend/backend/blocks/test/test_store_operations.py

@@ -0,0 +1,155 @@
+from unittest.mock import MagicMock
+
+import pytest
+
+from backend.blocks.system.library_operations import (
+    AddToLibraryFromStoreBlock,
+    LibraryAgent,
+)
+from backend.blocks.system.store_operations import (
+    GetStoreAgentDetailsBlock,
+    SearchAgentsResponse,
+    SearchStoreAgentsBlock,
+    StoreAgentDetails,
+    StoreAgentDict,
+)
+
+
+@pytest.mark.asyncio
+async def test_add_to_library_from_store_block_success(mocker):
+    """Test successful addition of agent from store to library."""
+    block = AddToLibraryFromStoreBlock()
+
+    # Mock the library agent response
+    mock_library_agent = MagicMock()
+    mock_library_agent.id = "lib-agent-123"
+    mock_library_agent.graph_id = "graph-456"
+    mock_library_agent.graph_version = 1
+    mock_library_agent.name = "Test Agent"
+
+    mocker.patch.object(
+        block,
+        "_add_to_library",
+        return_value=LibraryAgent(
+            library_agent_id="lib-agent-123",
+            agent_id="graph-456",
+            agent_version=1,
+            agent_name="Test Agent",
+        ),
+    )
+
+    input_data = block.Input(
+        store_listing_version_id="store-listing-v1", agent_name="Custom Agent Name"
+    )
+
+    outputs = {}
+    async for name, value in block.run(input_data, user_id="test-user"):
+        outputs[name] = value
+
+    assert outputs["success"] is True
+    assert outputs["library_agent_id"] == "lib-agent-123"
+    assert outputs["agent_id"] == "graph-456"
+    assert outputs["agent_version"] == 1
+    assert outputs["agent_name"] == "Test Agent"
+    assert outputs["message"] == "Agent successfully added to library"
+
+
+@pytest.mark.asyncio
+async def test_get_store_agent_details_block_success(mocker):
+    """Test successful retrieval of store agent details."""
+    block = GetStoreAgentDetailsBlock()
+
+    mocker.patch.object(
+        block,
+        "_get_agent_details",
+        return_value=StoreAgentDetails(
+            found=True,
+            store_listing_version_id="version-123",
+            agent_name="Test Agent",
+            description="A test agent for testing",
+            creator="Test Creator",
+            categories=["productivity", "automation"],
+            runs=100,
+            rating=4.5,
+        ),
+    )
+
+    input_data = block.Input(creator="Test Creator", slug="test-slug")
+    outputs = {}
+    async for name, value in block.run(input_data):
+        outputs[name] = value
+
+    assert outputs["found"] is True
+    assert outputs["store_listing_version_id"] == "version-123"
+    assert outputs["agent_name"] == "Test Agent"
+    assert outputs["description"] == "A test agent for testing"
+    assert outputs["creator"] == "Test Creator"
+    assert outputs["categories"] == ["productivity", "automation"]
+    assert outputs["runs"] == 100
+    assert outputs["rating"] == 4.5
+
+
+@pytest.mark.asyncio
+async def test_search_store_agents_block(mocker):
+    """Test searching for store agents."""
+    block = SearchStoreAgentsBlock()
+
+    mocker.patch.object(
+        block,
+        "_search_agents",
+        return_value=SearchAgentsResponse(
+            agents=[
+                StoreAgentDict(
+                    slug="creator1/agent1",
+                    name="Agent One",
+                    description="First test agent",
+                    creator="Creator 1",
+                    rating=4.8,
+                    runs=500,
+                ),
+                StoreAgentDict(
+                    slug="creator2/agent2",
+                    name="Agent Two",
+                    description="Second test agent",
+                    creator="Creator 2",
+                    rating=4.2,
+                    runs=200,
+                ),
+            ],
+            total_count=2,
+        ),
+    )
+
+    input_data = block.Input(
+        query="test", category="productivity", sort_by="rating", limit=10
+    )
+
+    outputs = {}
+    async for name, value in block.run(input_data):
+        outputs[name] = value
+
+    assert len(outputs["agents"]) == 2
+    assert outputs["total_count"] == 2
+    assert outputs["agents"][0]["name"] == "Agent One"
+    assert outputs["agents"][0]["rating"] == 4.8
+
+
+@pytest.mark.asyncio
+async def test_search_store_agents_block_empty_results(mocker):
+    """Test searching with no results."""
+    block = SearchStoreAgentsBlock()
+
+    mocker.patch.object(
+        block,
+        "_search_agents",
+        return_value=SearchAgentsResponse(agents=[], total_count=0),
+    )
+
+    input_data = block.Input(query="nonexistent", limit=10)
+
+    outputs = {}
+    async for name, value in block.run(input_data):
+        outputs[name] = value
+
+    assert outputs["agents"] == []
+    assert outputs["total_count"] == 0

autogpt_platform/backend/backend/blocks/time_blocks.py

@@ -1,4 +1,5 @@
 import asyncio
+import logging
 import time
 from datetime import datetime, timedelta
 from typing import Any, Literal, Union
@@ -7,6 +8,7 @@ from zoneinfo import ZoneInfo
 from pydantic import BaseModel
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.execution import UserContext
 from backend.data.model import SchemaField
 
 # Shared timezone literal type for all time/date blocks
@@ -51,16 +53,80 @@ TimezoneLiteral = Literal[
     "Etc/GMT+12",  # UTC-12:00
 ]
 
+logger = logging.getLogger(__name__)
+
+
+def _get_timezone(
+    format_type: Any,  # Any format type with timezone and use_user_timezone attributes
+    user_timezone: str | None,
+) -> ZoneInfo:
+    """
+    Determine which timezone to use based on format settings and user context.
+
+    Args:
+        format_type: The format configuration containing timezone settings
+        user_timezone: The user's timezone from context
+
+    Returns:
+        ZoneInfo object for the determined timezone
+    """
+    if format_type.use_user_timezone and user_timezone:
+        tz = ZoneInfo(user_timezone)
+        logger.debug(f"Using user timezone: {user_timezone}")
+    else:
+        tz = ZoneInfo(format_type.timezone)
+        logger.debug(f"Using specified timezone: {format_type.timezone}")
+    return tz
+
+
+def _format_datetime_iso8601(dt: datetime, include_microseconds: bool = False) -> str:
+    """
+    Format a datetime object to ISO8601 string.
+
+    Args:
+        dt: The datetime object to format
+        include_microseconds: Whether to include microseconds in the output
+
+    Returns:
+        ISO8601 formatted string
+    """
+    if include_microseconds:
+        return dt.isoformat()
+    else:
+        return dt.isoformat(timespec="seconds")
+
+
+# BACKWARDS COMPATIBILITY NOTE:
+# The timezone field is kept at the format level (not block level) for backwards compatibility.
+# Existing graphs have timezone saved within format_type, moving it would break them.
+#
+# The use_user_timezone flag was added to allow using the user's profile timezone.
+# Default is False to maintain backwards compatibility - existing graphs will continue
+# using their specified timezone.
+#
+# KNOWN ISSUE: If a user switches between format types (strftime <-> iso8601),
+# the timezone setting doesn't carry over. This is a UX issue but fixing it would
+# require either:
+#   1. Moving timezone to block level (breaking change, needs migration)
+#   2. Complex state management to sync timezone across format types
+#
+# Future migration path: When we do a major version bump, consider moving timezone
+# to the block Input level for better UX.
+
 
 class TimeStrftimeFormat(BaseModel):
     discriminator: Literal["strftime"]
     format: str = "%H:%M:%S"
     timezone: TimezoneLiteral = "UTC"
+    # When True, overrides timezone with user's profile timezone
+    use_user_timezone: bool = False
 
 
 class TimeISO8601Format(BaseModel):
     discriminator: Literal["iso8601"]
     timezone: TimezoneLiteral = "UTC"
+    # When True, overrides timezone with user's profile timezone
+    use_user_timezone: bool = False
     include_microseconds: bool = False
 
 
@@ -115,25 +181,27 @@ class GetCurrentTimeBlock(Block):
             ],
         )
 
-    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(
+        self, input_data: Input, *, user_context: UserContext, **kwargs
+    ) -> BlockOutput:
+        # Extract timezone from user_context (always present)
+        effective_timezone = user_context.timezone
+
+        # Get the appropriate timezone
+        tz = _get_timezone(input_data.format_type, effective_timezone)
+        dt = datetime.now(tz=tz)
+
         if isinstance(input_data.format_type, TimeISO8601Format):
-            # ISO 8601 format for time only (extract time portion from full ISO datetime)
-            tz = ZoneInfo(input_data.format_type.timezone)
-            dt = datetime.now(tz=tz)
-
             # Get the full ISO format and extract just the time portion with timezone
-            if input_data.format_type.include_microseconds:
-                full_iso = dt.isoformat()
-            else:
-                full_iso = dt.isoformat(timespec="seconds")
-
+            full_iso = _format_datetime_iso8601(
+                dt, input_data.format_type.include_microseconds
+            )
             # Extract time portion (everything after 'T')
             current_time = full_iso.split("T")[1] if "T" in full_iso else full_iso
             current_time = f"T{current_time}"  # Add T prefix for ISO 8601 time format
         else:  # TimeStrftimeFormat
-            tz = ZoneInfo(input_data.format_type.timezone)
-            dt = datetime.now(tz=tz)
             current_time = dt.strftime(input_data.format_type.format)
+
         yield "time", current_time
 
 
@@ -141,11 +209,15 @@ class DateStrftimeFormat(BaseModel):
     discriminator: Literal["strftime"]
     format: str = "%Y-%m-%d"
     timezone: TimezoneLiteral = "UTC"
+    # When True, overrides timezone with user's profile timezone
+    use_user_timezone: bool = False
 
 
 class DateISO8601Format(BaseModel):
     discriminator: Literal["iso8601"]
     timezone: TimezoneLiteral = "UTC"
+    # When True, overrides timezone with user's profile timezone
+    use_user_timezone: bool = False
 
 
 class GetCurrentDateBlock(Block):
@@ -217,20 +289,23 @@ class GetCurrentDateBlock(Block):
         )
 
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        # Extract timezone from user_context (required keyword argument)
+        user_context: UserContext = kwargs["user_context"]
+        effective_timezone = user_context.timezone
+
         try:
             offset = int(input_data.offset)
         except ValueError:
             offset = 0
 
+        # Get the appropriate timezone
+        tz = _get_timezone(input_data.format_type, effective_timezone)
+        current_date = datetime.now(tz=tz) - timedelta(days=offset)
+
         if isinstance(input_data.format_type, DateISO8601Format):
-            # ISO 8601 format for date only (YYYY-MM-DD)
-            tz = ZoneInfo(input_data.format_type.timezone)
-            current_date = datetime.now(tz=tz) - timedelta(days=offset)
             # ISO 8601 date format is YYYY-MM-DD
             date_str = current_date.date().isoformat()
         else:  # DateStrftimeFormat
-            tz = ZoneInfo(input_data.format_type.timezone)
-            current_date = datetime.now(tz=tz) - timedelta(days=offset)
             date_str = current_date.strftime(input_data.format_type.format)
 
         yield "date", date_str
@@ -240,11 +315,15 @@ class StrftimeFormat(BaseModel):
     discriminator: Literal["strftime"]
     format: str = "%Y-%m-%d %H:%M:%S"
     timezone: TimezoneLiteral = "UTC"
+    # When True, overrides timezone with user's profile timezone
+    use_user_timezone: bool = False
 
 
 class ISO8601Format(BaseModel):
     discriminator: Literal["iso8601"]
     timezone: TimezoneLiteral = "UTC"
+    # When True, overrides timezone with user's profile timezone
+    use_user_timezone: bool = False
     include_microseconds: bool = False
 
 
@@ -316,20 +395,22 @@ class GetCurrentDateAndTimeBlock(Block):
         )
 
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        # Extract timezone from user_context (required keyword argument)
+        user_context: UserContext = kwargs["user_context"]
+        effective_timezone = user_context.timezone
+
+        # Get the appropriate timezone
+        tz = _get_timezone(input_data.format_type, effective_timezone)
+        dt = datetime.now(tz=tz)
+
         if isinstance(input_data.format_type, ISO8601Format):
             # ISO 8601 format with specified timezone (also RFC3339-compliant)
-            tz = ZoneInfo(input_data.format_type.timezone)
-            dt = datetime.now(tz=tz)
-
-            # Format with or without microseconds
-            if input_data.format_type.include_microseconds:
-                current_date_time = dt.isoformat()
-            else:
-                current_date_time = dt.isoformat(timespec="seconds")
+            current_date_time = _format_datetime_iso8601(
+                dt, input_data.format_type.include_microseconds
+            )
         else:  # StrftimeFormat
-            tz = ZoneInfo(input_data.format_type.timezone)
-            dt = datetime.now(tz=tz)
             current_date_time = dt.strftime(input_data.format_type.format)
+
         yield "date_time", current_date_time
 
 

autogpt_platform/backend/backend/data/credit.py

@@ -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
 

autogpt_platform/backend/backend/data/credit_test.py

@@ -7,7 +7,7 @@ from prisma.models import CreditTransaction
 from backend.blocks.llm import AITextGeneratorBlock
 from backend.data.block import get_block
 from backend.data.credit import BetaUserCredit, UsageTransactionMetadata
-from backend.data.execution import NodeExecutionEntry
+from backend.data.execution import NodeExecutionEntry, UserContext
 from backend.data.user import DEFAULT_USER_ID
 from backend.executor.utils import block_usage_cost
 from backend.integrations.credentials_store import openai_credentials
@@ -75,6 +75,7 @@ async def test_block_credit_usage(server: SpinTestServer):
                     "type": openai_credentials.type,
                 },
             },
+            user_context=UserContext(timezone="UTC"),
         ),
     )
     assert spending_amount_1 > 0
@@ -88,6 +89,7 @@ async def test_block_credit_usage(server: SpinTestServer):
             node_exec_id="test_node_exec",
             block_id=AITextGeneratorBlock().id,
             inputs={"model": "gpt-4-turbo", "api_key": "owned_api_key"},
+            user_context=UserContext(timezone="UTC"),
         ),
     )
     assert spending_amount_2 == 0

autogpt_platform/backend/backend/data/execution.py

@@ -39,6 +39,7 @@ from pydantic.fields import Field
 from backend.server.v2.store.exceptions import DatabaseError
 from backend.util import type as type_utils
 from backend.util.json import SafeJson
+from backend.util.models import Pagination
 from backend.util.retry import func_retry
 from backend.util.settings import Config
 from backend.util.truncate import truncate
@@ -89,6 +90,7 @@ ExecutionStatus = AgentExecutionStatus
 
 
 class GraphExecutionMeta(BaseDbModel):
+    id: str  # type: ignore # Override base class to make this required
     user_id: str
     graph_id: str
     graph_version: int
@@ -290,13 +292,14 @@ class GraphExecutionWithNodes(GraphExecution):
             node_executions=node_executions,
         )
 
-    def to_graph_execution_entry(self):
+    def to_graph_execution_entry(self, user_context: "UserContext"):
         return GraphExecutionEntry(
             user_id=self.user_id,
             graph_id=self.graph_id,
             graph_version=self.graph_version or 0,
             graph_exec_id=self.id,
             nodes_input_masks={},  # FIXME: store credentials on AgentGraphExecution
+            user_context=user_context,
         )
 
 
@@ -368,7 +371,9 @@ class NodeExecutionResult(BaseModel):
             end_time=_node_exec.endedTime,
         )
 
-    def to_node_execution_entry(self) -> "NodeExecutionEntry":
+    def to_node_execution_entry(
+        self, user_context: "UserContext"
+    ) -> "NodeExecutionEntry":
         return NodeExecutionEntry(
             user_id=self.user_id,
             graph_exec_id=self.graph_exec_id,
@@ -377,6 +382,7 @@ class NodeExecutionResult(BaseModel):
             node_id=self.node_id,
             block_id=self.block_id,
             inputs=self.input_data,
+            user_context=user_context,
         )
 
 
@@ -384,13 +390,13 @@ class NodeExecutionResult(BaseModel):
 
 
 async def get_graph_executions(
-    graph_exec_id: str | None = None,
-    graph_id: str | None = None,
-    user_id: str | None = None,
-    statuses: list[ExecutionStatus] | None = None,
-    created_time_gte: datetime | None = None,
-    created_time_lte: datetime | None = None,
-    limit: int | None = None,
+    graph_exec_id: Optional[str] = None,
+    graph_id: Optional[str] = None,
+    user_id: Optional[str] = None,
+    statuses: Optional[list[ExecutionStatus]] = None,
+    created_time_gte: Optional[datetime] = None,
+    created_time_lte: Optional[datetime] = None,
+    limit: Optional[int] = None,
 ) -> list[GraphExecutionMeta]:
     """⚠️ **Optional `user_id` check**: MUST USE check in user-facing endpoints."""
     where_filter: AgentGraphExecutionWhereInput = {
@@ -418,6 +424,60 @@ async def get_graph_executions(
     return [GraphExecutionMeta.from_db(execution) for execution in executions]
 
 
+class GraphExecutionsPaginated(BaseModel):
+    """Response schema for paginated graph executions."""
+
+    executions: list[GraphExecutionMeta]
+    pagination: Pagination
+
+
+async def get_graph_executions_paginated(
+    user_id: str,
+    graph_id: Optional[str] = None,
+    page: int = 1,
+    page_size: int = 25,
+    statuses: Optional[list[ExecutionStatus]] = None,
+    created_time_gte: Optional[datetime] = None,
+    created_time_lte: Optional[datetime] = None,
+) -> GraphExecutionsPaginated:
+    """Get paginated graph executions for a specific graph."""
+    where_filter: AgentGraphExecutionWhereInput = {
+        "isDeleted": False,
+        "userId": user_id,
+    }
+
+    if graph_id:
+        where_filter["agentGraphId"] = graph_id
+    if created_time_gte or created_time_lte:
+        where_filter["createdAt"] = {
+            "gte": created_time_gte or datetime.min.replace(tzinfo=timezone.utc),
+            "lte": created_time_lte or datetime.max.replace(tzinfo=timezone.utc),
+        }
+    if statuses:
+        where_filter["OR"] = [{"executionStatus": status} for status in statuses]
+
+    total_count = await AgentGraphExecution.prisma().count(where=where_filter)
+    total_pages = (total_count + page_size - 1) // page_size
+
+    offset = (page - 1) * page_size
+    executions = await AgentGraphExecution.prisma().find_many(
+        where=where_filter,
+        order={"createdAt": "desc"},
+        take=page_size,
+        skip=offset,
+    )
+
+    return GraphExecutionsPaginated(
+        executions=[GraphExecutionMeta.from_db(execution) for execution in executions],
+        pagination=Pagination(
+            total_items=total_count,
+            total_pages=total_pages,
+            current_page=page,
+            page_size=page_size,
+        ),
+    )
+
+
 async def get_graph_execution_meta(
     user_id: str, execution_id: str
 ) -> GraphExecutionMeta | None:
@@ -817,12 +877,19 @@ async def get_latest_node_execution(
 # ----------------- Execution Infrastructure ----------------- #
 
 
+class UserContext(BaseModel):
+    """Generic user context for graph execution containing user-specific settings."""
+
+    timezone: str
+
+
 class GraphExecutionEntry(BaseModel):
     user_id: str
     graph_exec_id: str
     graph_id: str
     graph_version: int
     nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None
+    user_context: UserContext
 
 
 class NodeExecutionEntry(BaseModel):
@@ -833,6 +900,7 @@ class NodeExecutionEntry(BaseModel):
     node_id: str
     block_id: str
     inputs: BlockInput
+    user_context: UserContext
 
 
 class ExecutionQueue(Generic[T]):

autogpt_platform/backend/backend/data/model.py

@@ -96,6 +96,12 @@ class User(BaseModel):
         default=True, description="Notify on monthly summary"
     )
 
+    # User timezone for scheduling and time display
+    timezone: str = Field(
+        default="not-set",
+        description="User timezone (IANA timezone identifier or 'not-set')",
+    )
+
     @classmethod
     def from_db(cls, prisma_user: "PrismaUser") -> "User":
         """Convert a database User object to application User model."""
@@ -149,6 +155,7 @@ class User(BaseModel):
             notify_on_daily_summary=prisma_user.notifyOnDailySummary or True,
             notify_on_weekly_summary=prisma_user.notifyOnWeeklySummary or True,
             notify_on_monthly_summary=prisma_user.notifyOnMonthlySummary or True,
+            timezone=prisma_user.timezone or "not-set",
         )
 
 

autogpt_platform/backend/backend/data/notifications.py

@@ -54,19 +54,6 @@ class AgentRunData(BaseNotificationData):
 
 
 class ZeroBalanceData(BaseNotificationData):
-    last_transaction: float
-    last_transaction_time: datetime
-    top_up_link: str
-
-    @field_validator("last_transaction_time")
-    @classmethod
-    def validate_timezone(cls, value: datetime):
-        if value.tzinfo is None:
-            raise ValueError("datetime must have timezone information")
-        return value
-
-
-class LowBalanceData(BaseNotificationData):
     agent_name: str = Field(..., description="Name of the agent")
     current_balance: float = Field(
         ..., description="Current balance in credits (100 = $1)"
@@ -75,6 +62,13 @@ class LowBalanceData(BaseNotificationData):
     shortfall: float = Field(..., description="Amount of credits needed to continue")
 
 
+class LowBalanceData(BaseNotificationData):
+    current_balance: float = Field(
+        ..., description="Current balance in credits (100 = $1)"
+    )
+    billing_page_link: str = Field(..., description="Link to billing page")
+
+
 class BlockExecutionFailedData(BaseNotificationData):
     block_name: str
     block_id: str
@@ -181,6 +175,42 @@ class RefundRequestData(BaseNotificationData):
     balance: int
 
 
+class AgentApprovalData(BaseNotificationData):
+    agent_name: str
+    agent_id: str
+    agent_version: int
+    reviewer_name: str
+    reviewer_email: str
+    comments: str
+    reviewed_at: datetime
+    store_url: str
+
+    @field_validator("reviewed_at")
+    @classmethod
+    def validate_timezone(cls, value: datetime):
+        if value.tzinfo is None:
+            raise ValueError("datetime must have timezone information")
+        return value
+
+
+class AgentRejectionData(BaseNotificationData):
+    agent_name: str
+    agent_id: str
+    agent_version: int
+    reviewer_name: str
+    reviewer_email: str
+    comments: str
+    reviewed_at: datetime
+    resubmit_url: str
+
+    @field_validator("reviewed_at")
+    @classmethod
+    def validate_timezone(cls, value: datetime):
+        if value.tzinfo is None:
+            raise ValueError("datetime must have timezone information")
+        return value
+
+
 NotificationData = Annotated[
     Union[
         AgentRunData,
@@ -240,6 +270,8 @@ def get_notif_data_type(
         NotificationType.MONTHLY_SUMMARY: MonthlySummaryData,
         NotificationType.REFUND_REQUEST: RefundRequestData,
         NotificationType.REFUND_PROCESSED: RefundRequestData,
+        NotificationType.AGENT_APPROVED: AgentApprovalData,
+        NotificationType.AGENT_REJECTED: AgentRejectionData,
     }[notification_type]
 
 
@@ -274,7 +306,7 @@ class NotificationTypeOverride:
             # These are batched by the notification service
             NotificationType.AGENT_RUN: QueueType.BATCH,
             # These are batched by the notification service, but with a backoff strategy
-            NotificationType.ZERO_BALANCE: QueueType.BACKOFF,
+            NotificationType.ZERO_BALANCE: QueueType.IMMEDIATE,
             NotificationType.LOW_BALANCE: QueueType.IMMEDIATE,
             NotificationType.BLOCK_EXECUTION_FAILED: QueueType.BACKOFF,
             NotificationType.CONTINUOUS_AGENT_ERROR: QueueType.BACKOFF,
@@ -283,6 +315,8 @@ class NotificationTypeOverride:
             NotificationType.MONTHLY_SUMMARY: QueueType.SUMMARY,
             NotificationType.REFUND_REQUEST: QueueType.ADMIN,
             NotificationType.REFUND_PROCESSED: QueueType.ADMIN,
+            NotificationType.AGENT_APPROVED: QueueType.IMMEDIATE,
+            NotificationType.AGENT_REJECTED: QueueType.IMMEDIATE,
         }
         return BATCHING_RULES.get(self.notification_type, QueueType.IMMEDIATE)
 
@@ -300,6 +334,8 @@ class NotificationTypeOverride:
             NotificationType.MONTHLY_SUMMARY: "monthly_summary.html",
             NotificationType.REFUND_REQUEST: "refund_request.html",
             NotificationType.REFUND_PROCESSED: "refund_processed.html",
+            NotificationType.AGENT_APPROVED: "agent_approved.html",
+            NotificationType.AGENT_REJECTED: "agent_rejected.html",
         }[self.notification_type]
 
     @property
@@ -315,6 +351,8 @@ class NotificationTypeOverride:
             NotificationType.MONTHLY_SUMMARY: "We did a lot this month!",
             NotificationType.REFUND_REQUEST: "[ACTION REQUIRED] You got a ${{data.amount / 100}} refund request from {{data.user_name}}",
             NotificationType.REFUND_PROCESSED: "Refund for ${{data.amount / 100}} to {{data.user_name}} has been processed",
+            NotificationType.AGENT_APPROVED: "🎉 Your agent '{{data.agent_name}}' has been approved!",
+            NotificationType.AGENT_REJECTED: "Your agent '{{data.agent_name}}' needs some updates",
         }[self.notification_type]
 
 

autogpt_platform/backend/backend/data/notifications_test.py

@@ -0,0 +1,151 @@
+"""Tests for notification data models."""
+
+from datetime import datetime, timezone
+
+import pytest
+from pydantic import ValidationError
+
+from backend.data.notifications import AgentApprovalData, AgentRejectionData
+
+
+class TestAgentApprovalData:
+    """Test cases for AgentApprovalData model."""
+
+    def test_valid_agent_approval_data(self):
+        """Test creating valid AgentApprovalData."""
+        data = AgentApprovalData(
+            agent_name="Test Agent",
+            agent_id="test-agent-123",
+            agent_version=1,
+            reviewer_name="John Doe",
+            reviewer_email="john@example.com",
+            comments="Great agent, approved!",
+            reviewed_at=datetime.now(timezone.utc),
+            store_url="https://app.autogpt.com/store/test-agent-123",
+        )
+
+        assert data.agent_name == "Test Agent"
+        assert data.agent_id == "test-agent-123"
+        assert data.agent_version == 1
+        assert data.reviewer_name == "John Doe"
+        assert data.reviewer_email == "john@example.com"
+        assert data.comments == "Great agent, approved!"
+        assert data.store_url == "https://app.autogpt.com/store/test-agent-123"
+        assert data.reviewed_at.tzinfo is not None
+
+    def test_agent_approval_data_without_timezone_raises_error(self):
+        """Test that AgentApprovalData raises error without timezone."""
+        with pytest.raises(
+            ValidationError, match="datetime must have timezone information"
+        ):
+            AgentApprovalData(
+                agent_name="Test Agent",
+                agent_id="test-agent-123",
+                agent_version=1,
+                reviewer_name="John Doe",
+                reviewer_email="john@example.com",
+                comments="Great agent, approved!",
+                reviewed_at=datetime.now(),  # No timezone
+                store_url="https://app.autogpt.com/store/test-agent-123",
+            )
+
+    def test_agent_approval_data_with_empty_comments(self):
+        """Test AgentApprovalData with empty comments."""
+        data = AgentApprovalData(
+            agent_name="Test Agent",
+            agent_id="test-agent-123",
+            agent_version=1,
+            reviewer_name="John Doe",
+            reviewer_email="john@example.com",
+            comments="",  # Empty comments
+            reviewed_at=datetime.now(timezone.utc),
+            store_url="https://app.autogpt.com/store/test-agent-123",
+        )
+
+        assert data.comments == ""
+
+
+class TestAgentRejectionData:
+    """Test cases for AgentRejectionData model."""
+
+    def test_valid_agent_rejection_data(self):
+        """Test creating valid AgentRejectionData."""
+        data = AgentRejectionData(
+            agent_name="Test Agent",
+            agent_id="test-agent-123",
+            agent_version=1,
+            reviewer_name="Jane Doe",
+            reviewer_email="jane@example.com",
+            comments="Please fix the security issues before resubmitting.",
+            reviewed_at=datetime.now(timezone.utc),
+            resubmit_url="https://app.autogpt.com/build/test-agent-123",
+        )
+
+        assert data.agent_name == "Test Agent"
+        assert data.agent_id == "test-agent-123"
+        assert data.agent_version == 1
+        assert data.reviewer_name == "Jane Doe"
+        assert data.reviewer_email == "jane@example.com"
+        assert data.comments == "Please fix the security issues before resubmitting."
+        assert data.resubmit_url == "https://app.autogpt.com/build/test-agent-123"
+        assert data.reviewed_at.tzinfo is not None
+
+    def test_agent_rejection_data_without_timezone_raises_error(self):
+        """Test that AgentRejectionData raises error without timezone."""
+        with pytest.raises(
+            ValidationError, match="datetime must have timezone information"
+        ):
+            AgentRejectionData(
+                agent_name="Test Agent",
+                agent_id="test-agent-123",
+                agent_version=1,
+                reviewer_name="Jane Doe",
+                reviewer_email="jane@example.com",
+                comments="Please fix the security issues.",
+                reviewed_at=datetime.now(),  # No timezone
+                resubmit_url="https://app.autogpt.com/build/test-agent-123",
+            )
+
+    def test_agent_rejection_data_with_long_comments(self):
+        """Test AgentRejectionData with long comments."""
+        long_comment = "A" * 1000  # Very long comment
+        data = AgentRejectionData(
+            agent_name="Test Agent",
+            agent_id="test-agent-123",
+            agent_version=1,
+            reviewer_name="Jane Doe",
+            reviewer_email="jane@example.com",
+            comments=long_comment,
+            reviewed_at=datetime.now(timezone.utc),
+            resubmit_url="https://app.autogpt.com/build/test-agent-123",
+        )
+
+        assert data.comments == long_comment
+
+    def test_model_serialization(self):
+        """Test that models can be serialized and deserialized."""
+        original_data = AgentRejectionData(
+            agent_name="Test Agent",
+            agent_id="test-agent-123",
+            agent_version=1,
+            reviewer_name="Jane Doe",
+            reviewer_email="jane@example.com",
+            comments="Please fix the issues.",
+            reviewed_at=datetime.now(timezone.utc),
+            resubmit_url="https://app.autogpt.com/build/test-agent-123",
+        )
+
+        # Serialize to dict
+        data_dict = original_data.model_dump()
+
+        # Deserialize back
+        restored_data = AgentRejectionData.model_validate(data_dict)
+
+        assert restored_data.agent_name == original_data.agent_name
+        assert restored_data.agent_id == original_data.agent_id
+        assert restored_data.agent_version == original_data.agent_version
+        assert restored_data.reviewer_name == original_data.reviewer_name
+        assert restored_data.reviewer_email == original_data.reviewer_email
+        assert restored_data.comments == original_data.comments
+        assert restored_data.reviewed_at == original_data.reviewed_at
+        assert restored_data.resubmit_url == original_data.resubmit_url

autogpt_platform/backend/backend/data/user.py

@@ -208,6 +208,8 @@ async def get_user_notification_preference(user_id: str) -> NotificationPreferen
             NotificationType.DAILY_SUMMARY: user.notifyOnDailySummary or False,
             NotificationType.WEEKLY_SUMMARY: user.notifyOnWeeklySummary or False,
             NotificationType.MONTHLY_SUMMARY: user.notifyOnMonthlySummary or False,
+            NotificationType.AGENT_APPROVED: user.notifyOnAgentApproved or False,
+            NotificationType.AGENT_REJECTED: user.notifyOnAgentRejected or False,
         }
         daily_limit = user.maxEmailsPerDay or 3
         notification_preference = NotificationPreference(
@@ -266,6 +268,14 @@ async def update_user_notification_preference(
             update_data["notifyOnMonthlySummary"] = data.preferences[
                 NotificationType.MONTHLY_SUMMARY
             ]
+        if NotificationType.AGENT_APPROVED in data.preferences:
+            update_data["notifyOnAgentApproved"] = data.preferences[
+                NotificationType.AGENT_APPROVED
+            ]
+        if NotificationType.AGENT_REJECTED in data.preferences:
+            update_data["notifyOnAgentRejected"] = data.preferences[
+                NotificationType.AGENT_REJECTED
+            ]
         if data.daily_limit:
             update_data["maxEmailsPerDay"] = data.daily_limit
 
@@ -286,6 +296,8 @@ async def update_user_notification_preference(
             NotificationType.DAILY_SUMMARY: user.notifyOnDailySummary or True,
             NotificationType.WEEKLY_SUMMARY: user.notifyOnWeeklySummary or True,
             NotificationType.MONTHLY_SUMMARY: user.notifyOnMonthlySummary or True,
+            NotificationType.AGENT_APPROVED: user.notifyOnAgentApproved or True,
+            NotificationType.AGENT_REJECTED: user.notifyOnAgentRejected or True,
         }
         notification_preference = NotificationPreference(
             user_id=user.id,
@@ -384,3 +396,17 @@ async def unsubscribe_user_by_token(token: str) -> None:
         )
     except Exception as e:
         raise DatabaseError(f"Failed to unsubscribe user by token {token}: {e}") from e
+
+
+async def update_user_timezone(user_id: str, timezone: str) -> User:
+    """Update a user's timezone setting."""
+    try:
+        user = await PrismaUser.prisma().update(
+            where={"id": user_id},
+            data={"timezone": timezone},
+        )
+        if not user:
+            raise ValueError(f"User not found with ID: {user_id}")
+        return User.from_db(user)
+    except Exception as e:
+        raise DatabaseError(f"Failed to update timezone for user {user_id}: {e}") from e

autogpt_platform/backend/backend/executor/database.py

@@ -42,6 +42,8 @@ from backend.data.user import (
     get_user_notification_preference,
     update_user_integrations,
 )
+from backend.server.v2.library.db import add_store_agent_to_library, list_library_agents
+from backend.server.v2.store.db import get_store_agent_details, get_store_agents
 from backend.util.service import (
     AppService,
     AppServiceClient,
@@ -145,6 +147,14 @@ class DatabaseManager(AppService):
         get_user_notification_oldest_message_in_batch
     )
 
+    # Library
+    list_library_agents = _(list_library_agents)
+    add_store_agent_to_library = _(add_store_agent_to_library)
+
+    # Store
+    get_store_agents = _(get_store_agents)
+    get_store_agent_details = _(get_store_agent_details)
+
     # Summary data - async
     get_user_execution_summary_data = _(get_user_execution_summary_data)
 
@@ -173,12 +183,20 @@ 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)
 
+    # User Emails
+    get_user_email_by_id = _(d.get_user_email_by_id)
+
+    # Library
+    list_library_agents = _(d.list_library_agents)
+    add_store_agent_to_library = _(d.add_store_agent_to_library)
+
+    # Store
+    get_store_agents = _(d.get_store_agents)
+    get_store_agent_details = _(d.get_store_agent_details)
+
 
 class DatabaseManagerAsyncClient(AppServiceClient):
     d = DatabaseManager
@@ -223,5 +241,13 @@ class DatabaseManagerAsyncClient(AppServiceClient):
         d.get_user_notification_oldest_message_in_batch
     )
 
+    # Library
+    list_library_agents = d.list_library_agents
+    add_store_agent_to_library = d.add_store_agent_to_library
+
+    # Store
+    get_store_agents = d.get_store_agents
+    get_store_agent_details = d.get_store_agent_details
+
     # Summary data
     get_user_execution_summary_data = d.get_user_execution_summary_data

autogpt_platform/backend/backend/executor/manager.py

@@ -20,6 +20,7 @@ from backend.data.notifications import (
     LowBalanceData,
     NotificationEventModel,
     NotificationType,
+    ZeroBalanceData,
 )
 from backend.data.rabbitmq import SyncRabbitMQ
 from backend.executor.activity_status_generator import (
@@ -51,6 +52,7 @@ from backend.data.execution import (
     GraphExecutionEntry,
     NodeExecutionEntry,
     NodeExecutionResult,
+    UserContext,
 )
 from backend.data.graph import Link, Node
 from backend.executor.utils import (
@@ -74,6 +76,7 @@ from backend.util.clients import (
     get_database_manager_async_client,
     get_database_manager_client,
     get_execution_event_bus,
+    get_notification_manager_client,
 )
 from backend.util.decorator import (
     async_error_logged,
@@ -83,6 +86,7 @@ from backend.util.decorator import (
 )
 from backend.util.file import clean_exec_files
 from backend.util.logging import TruncatedLogger, configure_logging
+from backend.util.metrics import DiscordChannel
 from backend.util.process import AppProcess, set_service_name
 from backend.util.retry import continuous_retry, func_retry
 from backend.util.settings import Settings
@@ -190,6 +194,9 @@ async def execute_node(
         "user_id": user_id,
     }
 
+    # Add user context from NodeExecutionEntry
+    extra_exec_kwargs["user_context"] = data.user_context
+
     # Last-minute fetch credentials + acquire a system-wide read-write lock to prevent
     # changes during execution. ⚠️ This means a set of credentials can only be used by
     # one (running) block at a time; simultaneous execution of blocks using same
@@ -236,6 +243,7 @@ async def _enqueue_next_nodes(
     graph_id: str,
     log_metadata: LogMetadata,
     nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]],
+    user_context: UserContext,
 ) -> list[NodeExecutionEntry]:
     async def add_enqueued_execution(
         node_exec_id: str, node_id: str, block_id: str, data: BlockInput
@@ -254,6 +262,7 @@ async def _enqueue_next_nodes(
             node_id=node_id,
             block_id=block_id,
             inputs=data,
+            user_context=user_context,
         )
 
     async def register_next_executions(node_link: Link) -> list[NodeExecutionEntry]:
@@ -678,19 +687,20 @@ class ExecutionProcessor:
         self,
         node_exec: NodeExecutionEntry,
         execution_count: int,
-    ) -> int:
+    ) -> tuple[int, int]:
         total_cost = 0
+        remaining_balance = 0
         db_client = get_db_client()
         block = get_block(node_exec.block_id)
         if not block:
             logger.error(f"Block {node_exec.block_id} not found.")
-            return total_cost
+            return total_cost, 0
 
         cost, matching_filter = block_usage_cost(
             block=block, input_data=node_exec.inputs
         )
         if cost > 0:
-            db_client.spend_credits(
+            remaining_balance = db_client.spend_credits(
                 user_id=node_exec.user_id,
                 cost=cost,
                 metadata=UsageTransactionMetadata(
@@ -708,7 +718,7 @@ class ExecutionProcessor:
 
         cost, usage_count = execution_usage_cost(execution_count)
         if cost > 0:
-            db_client.spend_credits(
+            remaining_balance = db_client.spend_credits(
                 user_id=node_exec.user_id,
                 cost=cost,
                 metadata=UsageTransactionMetadata(
@@ -723,7 +733,7 @@ class ExecutionProcessor:
             )
             total_cost += cost
 
-        return total_cost
+        return total_cost, remaining_balance
 
     @time_measured
     def _on_graph_execution(
@@ -787,7 +797,8 @@ class ExecutionProcessor:
                     ExecutionStatus.TERMINATED,
                 ],
             ):
-                execution_queue.add(node_exec.to_node_execution_entry())
+                node_entry = node_exec.to_node_execution_entry(graph_exec.user_context)
+                execution_queue.add(node_entry)
 
             # ------------------------------------------------------------
             # Main dispatch / polling loop -----------------------------
@@ -805,12 +816,19 @@ class ExecutionProcessor:
 
                 # Charge usage (may raise) ------------------------------
                 try:
-                    cost = self._charge_usage(
+                    cost, remaining_balance = self._charge_usage(
                         node_exec=queued_node_exec,
                         execution_count=increment_execution_count(graph_exec.user_id),
                     )
                     with execution_stats_lock:
                         execution_stats.cost += cost
+                    # Check if we crossed the low balance threshold
+                    self._handle_low_balance(
+                        db_client=db_client,
+                        user_id=graph_exec.user_id,
+                        current_balance=remaining_balance,
+                        transaction_cost=cost,
+                    )
                 except InsufficientBalanceError as balance_error:
                     error = balance_error  # Set error to trigger FAILED status
                     node_exec_id = queued_node_exec.node_exec_id
@@ -825,11 +843,10 @@ class ExecutionProcessor:
                         status=ExecutionStatus.FAILED,
                     )
 
-                    self._handle_low_balance_notif(
+                    self._handle_insufficient_funds_notif(
                         db_client,
                         graph_exec.user_id,
                         graph_exec.graph_id,
-                        execution_stats,
                         error,
                     )
                     # Gracefully stop the execution loop
@@ -1052,6 +1069,7 @@ class ExecutionProcessor:
         db_client = get_db_async_client()
 
         log_metadata.debug(f"Enqueue nodes for {node_id}: {output}")
+
         for next_execution in await _enqueue_next_nodes(
             db_client=db_client,
             node=output.node,
@@ -1061,6 +1079,7 @@ class ExecutionProcessor:
             graph_id=graph_exec.graph_id,
             log_metadata=log_metadata,
             nodes_input_masks=nodes_input_masks,
+            user_context=graph_exec.user_context,
         ):
             execution_queue.add(next_execution)
 
@@ -1101,25 +1120,25 @@ class ExecutionProcessor:
             )
         )
 
-    def _handle_low_balance_notif(
+    def _handle_insufficient_funds_notif(
         self,
         db_client: "DatabaseManagerClient",
         user_id: str,
         graph_id: str,
-        exec_stats: GraphExecutionStats,
         e: InsufficientBalanceError,
     ):
-        shortfall = e.balance - e.amount
+        shortfall = abs(e.amount) - e.balance
         metadata = db_client.get_graph_metadata(graph_id)
         base_url = (
             settings.config.frontend_base_url or settings.config.platform_base_url
         )
+
         queue_notification(
             NotificationEventModel(
                 user_id=user_id,
-                type=NotificationType.LOW_BALANCE,
-                data=LowBalanceData(
-                    current_balance=exec_stats.cost,
+                type=NotificationType.ZERO_BALANCE,
+                data=ZeroBalanceData(
+                    current_balance=e.balance,
                     billing_page_link=f"{base_url}/profile/credits",
                     shortfall=shortfall,
                     agent_name=metadata.name if metadata else "Unknown Agent",
@@ -1127,6 +1146,73 @@ class ExecutionProcessor:
             )
         )
 
+        try:
+            user_email = db_client.get_user_email_by_id(user_id)
+
+            alert_message = (
+                f"❌ **Insufficient Funds Alert**\n"
+                f"User: {user_email or user_id}\n"
+                f"Agent: {metadata.name if metadata else 'Unknown Agent'}\n"
+                f"Current balance: ${e.balance/100:.2f}\n"
+                f"Attempted cost: ${abs(e.amount)/100:.2f}\n"
+                f"Shortfall: ${abs(shortfall)/100:.2f}\n"
+                f"[View User Details]({base_url}/admin/spending?search={user_email})"
+            )
+
+            get_notification_manager_client().discord_system_alert(
+                alert_message, DiscordChannel.PRODUCT
+            )
+        except Exception as alert_error:
+            logger.error(
+                f"Failed to send insufficient funds Discord alert: {alert_error}"
+            )
+
+    def _handle_low_balance(
+        self,
+        db_client: "DatabaseManagerClient",
+        user_id: str,
+        current_balance: int,
+        transaction_cost: int,
+    ):
+        """Check and handle low balance scenarios after a transaction"""
+        LOW_BALANCE_THRESHOLD = settings.config.low_balance_threshold
+
+        balance_before = current_balance + transaction_cost
+
+        if (
+            current_balance < LOW_BALANCE_THRESHOLD
+            and balance_before >= LOW_BALANCE_THRESHOLD
+        ):
+            base_url = (
+                settings.config.frontend_base_url or settings.config.platform_base_url
+            )
+            queue_notification(
+                NotificationEventModel(
+                    user_id=user_id,
+                    type=NotificationType.LOW_BALANCE,
+                    data=LowBalanceData(
+                        current_balance=current_balance,
+                        billing_page_link=f"{base_url}/profile/credits",
+                    ),
+                )
+            )
+
+            try:
+                user_email = db_client.get_user_email_by_id(user_id)
+                alert_message = (
+                    f"⚠️ **Low Balance Alert**\n"
+                    f"User: {user_email or user_id}\n"
+                    f"Balance dropped below ${LOW_BALANCE_THRESHOLD/100:.2f}\n"
+                    f"Current balance: ${current_balance/100:.2f}\n"
+                    f"Transaction cost: ${transaction_cost/100:.2f}\n"
+                    f"[View User Details]({base_url}/admin/spending?search={user_email})"
+                )
+                get_notification_manager_client().discord_system_alert(
+                    alert_message, DiscordChannel.PRODUCT
+                )
+            except Exception as e:
+                logger.error(f"Failed to send low balance Discord alert: {e}")
+
 
 class ExecutionManager(AppProcess):
     def __init__(self):

autogpt_platform/backend/backend/executor/manager_low_balance_test.py

@@ -0,0 +1,149 @@
+from unittest.mock import MagicMock, patch
+
+import pytest
+from prisma.enums import NotificationType
+
+from backend.data.notifications import LowBalanceData
+from backend.executor.manager import ExecutionProcessor
+from backend.util.test import SpinTestServer
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_handle_low_balance_threshold_crossing(server: SpinTestServer):
+    """Test that _handle_low_balance triggers notification when crossing threshold."""
+
+    execution_processor = ExecutionProcessor()
+    user_id = "test-user-123"
+    current_balance = 400  # $4 - below $5 threshold
+    transaction_cost = 600  # $6 transaction
+
+    # Mock dependencies
+    with patch(
+        "backend.executor.manager.queue_notification"
+    ) as mock_queue_notif, patch(
+        "backend.executor.manager.get_notification_manager_client"
+    ) as mock_get_client, patch(
+        "backend.executor.manager.settings"
+    ) as mock_settings:
+
+        # Setup mocks
+        mock_client = MagicMock()
+        mock_get_client.return_value = mock_client
+        mock_settings.config.low_balance_threshold = 500  # $5 threshold
+        mock_settings.config.frontend_base_url = "https://test.com"
+
+        # Create mock database client
+        mock_db_client = MagicMock()
+        mock_db_client.get_user_email_by_id.return_value = "test@example.com"
+
+        # Test the low balance handler
+        execution_processor._handle_low_balance(
+            db_client=mock_db_client,
+            user_id=user_id,
+            current_balance=current_balance,
+            transaction_cost=transaction_cost,
+        )
+
+        # Verify notification was queued
+        mock_queue_notif.assert_called_once()
+        notification_call = mock_queue_notif.call_args[0][0]
+
+        # Verify notification details
+        assert notification_call.type == NotificationType.LOW_BALANCE
+        assert notification_call.user_id == user_id
+        assert isinstance(notification_call.data, LowBalanceData)
+        assert notification_call.data.current_balance == current_balance
+
+        # Verify Discord alert was sent
+        mock_client.discord_system_alert.assert_called_once()
+        discord_message = mock_client.discord_system_alert.call_args[0][0]
+        assert "Low Balance Alert" in discord_message
+        assert "test@example.com" in discord_message
+        assert "$4.00" in discord_message
+        assert "$6.00" in discord_message
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_handle_low_balance_no_notification_when_not_crossing(
+    server: SpinTestServer,
+):
+    """Test that no notification is sent when not crossing the threshold."""
+
+    execution_processor = ExecutionProcessor()
+    user_id = "test-user-123"
+    current_balance = 600  # $6 - above $5 threshold
+    transaction_cost = (
+        100  # $1 transaction (balance before was $7, still above threshold)
+    )
+
+    # Mock dependencies
+    with patch(
+        "backend.executor.manager.queue_notification"
+    ) as mock_queue_notif, patch(
+        "backend.executor.manager.get_notification_manager_client"
+    ) as mock_get_client, patch(
+        "backend.executor.manager.settings"
+    ) as mock_settings:
+
+        # Setup mocks
+        mock_client = MagicMock()
+        mock_get_client.return_value = mock_client
+        mock_settings.config.low_balance_threshold = 500  # $5 threshold
+
+        # Create mock database client
+        mock_db_client = MagicMock()
+
+        # Test the low balance handler
+        execution_processor._handle_low_balance(
+            db_client=mock_db_client,
+            user_id=user_id,
+            current_balance=current_balance,
+            transaction_cost=transaction_cost,
+        )
+
+        # Verify no notification was sent
+        mock_queue_notif.assert_not_called()
+        mock_client.discord_system_alert.assert_not_called()
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_handle_low_balance_no_duplicate_when_already_below(
+    server: SpinTestServer,
+):
+    """Test that no notification is sent when already below threshold."""
+
+    execution_processor = ExecutionProcessor()
+    user_id = "test-user-123"
+    current_balance = 300  # $3 - below $5 threshold
+    transaction_cost = (
+        100  # $1 transaction (balance before was $4, also below threshold)
+    )
+
+    # Mock dependencies
+    with patch(
+        "backend.executor.manager.queue_notification"
+    ) as mock_queue_notif, patch(
+        "backend.executor.manager.get_notification_manager_client"
+    ) as mock_get_client, patch(
+        "backend.executor.manager.settings"
+    ) as mock_settings:
+
+        # Setup mocks
+        mock_client = MagicMock()
+        mock_get_client.return_value = mock_client
+        mock_settings.config.low_balance_threshold = 500  # $5 threshold
+
+        # Create mock database client
+        mock_db_client = MagicMock()
+
+        # Test the low balance handler
+        execution_processor._handle_low_balance(
+            db_client=mock_db_client,
+            user_id=user_id,
+            current_balance=current_balance,
+            transaction_cost=transaction_cost,
+        )
+
+        # Verify no notification was sent (user was already below threshold)
+        mock_queue_notif.assert_not_called()
+        mock_client.discord_system_alert.assert_not_called()

autogpt_platform/backend/backend/executor/scheduler.py

@@ -17,6 +17,7 @@ from apscheduler.jobstores.memory import MemoryJobStore
 from apscheduler.jobstores.sqlalchemy import SQLAlchemyJobStore
 from apscheduler.schedulers.background import BackgroundScheduler
 from apscheduler.triggers.cron import CronTrigger
+from apscheduler.util import ZoneInfo
 from dotenv import load_dotenv
 from pydantic import BaseModel, Field, ValidationError
 from sqlalchemy import MetaData, create_engine
@@ -303,6 +304,7 @@ class Scheduler(AppService):
                 Jobstores.WEEKLY_NOTIFICATIONS.value: MemoryJobStore(),
             },
             logger=apscheduler_logger,
+            timezone=ZoneInfo("UTC"),
         )
 
         if self.register_system_tasks:
@@ -406,6 +408,8 @@ class Scheduler(AppService):
             )
         )
 
+        logger.info(f"Scheduling job for user {user_id} in UTC (cron: {cron})")
+
         job_args = GraphExecutionJobArgs(
             user_id=user_id,
             graph_id=graph_id,
@@ -418,12 +422,12 @@ class Scheduler(AppService):
             execute_graph,
             kwargs=job_args.model_dump(),
             name=name,
-            trigger=CronTrigger.from_crontab(cron),
+            trigger=CronTrigger.from_crontab(cron, timezone="UTC"),
             jobstore=Jobstores.EXECUTION.value,
             replace_existing=True,
         )
         logger.info(
-            f"Added job {job.id} with cron schedule '{cron}' input data: {input_data}"
+            f"Added job {job.id} with cron schedule '{cron}' in UTC, input data: {input_data}"
         )
         return GraphExecutionJobInfo.from_db(job_args, job)
 

autogpt_platform/backend/backend/executor/utils.py

@@ -18,10 +18,12 @@ from backend.data.execution import (
     ExecutionStatus,
     GraphExecutionStats,
     GraphExecutionWithNodes,
+    UserContext,
 )
 from backend.data.graph import GraphModel, Node
 from backend.data.model import CredentialsMetaInput
 from backend.data.rabbitmq import Exchange, ExchangeType, Queue, RabbitMQConfig
+from backend.data.user import get_user_by_id
 from backend.util.clients import (
     get_async_execution_event_bus,
     get_async_execution_queue,
@@ -34,6 +36,27 @@ from backend.util.mock import MockObject
 from backend.util.settings import Config
 from backend.util.type import convert
 
+
+async def get_user_context(user_id: str) -> UserContext:
+    """
+    Get UserContext for a user, always returns a valid context with timezone.
+    Defaults to UTC if user has no timezone set.
+    """
+    user_context = UserContext(timezone="UTC")  # Default to UTC
+    try:
+        user = await get_user_by_id(user_id)
+        if user and user.timezone and user.timezone != "not-set":
+            user_context.timezone = user.timezone
+            logger.debug(f"Retrieved user context: timezone={user.timezone}")
+        else:
+            logger.debug("User has no timezone set, using UTC")
+    except Exception as e:
+        logger.warning(f"Could not fetch user timezone: {e}")
+        # Continue with UTC as default
+
+    return user_context
+
+
 config = Config()
 logger = TruncatedLogger(logging.getLogger(__name__), prefix="[GraphExecutorUtil]")
 
@@ -877,8 +900,11 @@ async def add_graph_execution(
             preset_id=preset_id,
         )
 
+        # Fetch user context for the graph execution
+        user_context = await get_user_context(user_id)
+
         queue = await get_async_execution_queue()
-        graph_exec_entry = graph_exec.to_graph_execution_entry()
+        graph_exec_entry = graph_exec.to_graph_execution_entry(user_context)
         if nodes_input_masks:
             graph_exec_entry.nodes_input_masks = nodes_input_masks
 

autogpt_platform/backend/backend/integrations/oauth/__init__.py

@@ -4,6 +4,7 @@ from pydantic import BaseModel
 
 from backend.integrations.oauth.todoist import TodoistOAuthHandler
 
+from .discord import DiscordOAuthHandler
 from .github import GitHubOAuthHandler
 from .google import GoogleOAuthHandler
 from .notion import NotionOAuthHandler
@@ -15,6 +16,7 @@ if TYPE_CHECKING:
 # --8<-- [start:HANDLERS_BY_NAMEExample]
 # Build handlers dict with string keys for compatibility with SDK auto-registration
 _ORIGINAL_HANDLERS = [
+    DiscordOAuthHandler,
     GitHubOAuthHandler,
     GoogleOAuthHandler,
     NotionOAuthHandler,

autogpt_platform/backend/backend/integrations/oauth/discord.py

@@ -0,0 +1,175 @@
+import time
+from typing import Optional
+from urllib.parse import urlencode
+
+from backend.data.model import OAuth2Credentials
+from backend.integrations.providers import ProviderName
+from backend.util.request import Requests
+
+from .base import BaseOAuthHandler
+
+
+class DiscordOAuthHandler(BaseOAuthHandler):
+    """
+    Discord OAuth2 handler implementation.
+
+    Based on the documentation at:
+    - https://discord.com/developers/docs/topics/oauth2
+
+    Discord OAuth2 tokens expire after 7 days by default and include refresh tokens.
+    """
+
+    PROVIDER_NAME = ProviderName.DISCORD
+    DEFAULT_SCOPES = ["identify"]  # Basic user information
+
+    def __init__(self, client_id: str, client_secret: str, redirect_uri: str):
+        self.client_id = client_id
+        self.client_secret = client_secret
+        self.redirect_uri = redirect_uri
+        self.auth_base_url = "https://discord.com/oauth2/authorize"
+        self.token_url = "https://discord.com/api/oauth2/token"
+        self.revoke_url = "https://discord.com/api/oauth2/token/revoke"
+
+    def get_login_url(
+        self, scopes: list[str], state: str, code_challenge: Optional[str]
+    ) -> str:
+        # Handle default scopes
+        scopes = self.handle_default_scopes(scopes)
+
+        params = {
+            "client_id": self.client_id,
+            "redirect_uri": self.redirect_uri,
+            "response_type": "code",
+            "scope": " ".join(scopes),
+            "state": state,
+        }
+
+        # Discord supports PKCE
+        if code_challenge:
+            params["code_challenge"] = code_challenge
+            params["code_challenge_method"] = "S256"
+
+        return f"{self.auth_base_url}?{urlencode(params)}"
+
+    async def exchange_code_for_tokens(
+        self, code: str, scopes: list[str], code_verifier: Optional[str]
+    ) -> OAuth2Credentials:
+        params = {
+            "code": code,
+            "redirect_uri": self.redirect_uri,
+            "grant_type": "authorization_code",
+        }
+
+        # Include PKCE verifier if provided
+        if code_verifier:
+            params["code_verifier"] = code_verifier
+
+        return await self._request_tokens(params)
+
+    async def revoke_tokens(self, credentials: OAuth2Credentials) -> bool:
+        if not credentials.access_token:
+            raise ValueError("No access token to revoke")
+
+        # Discord requires client authentication for token revocation
+        data = {
+            "token": credentials.access_token.get_secret_value(),
+            "token_type_hint": "access_token",
+        }
+
+        headers = {
+            "Content-Type": "application/x-www-form-urlencoded",
+        }
+
+        response = await Requests().post(
+            url=self.revoke_url,
+            data=data,
+            headers=headers,
+            auth=(self.client_id, self.client_secret),
+        )
+
+        # Discord returns 200 OK for successful revocation
+        return response.status == 200
+
+    async def _refresh_tokens(
+        self, credentials: OAuth2Credentials
+    ) -> OAuth2Credentials:
+        if not credentials.refresh_token:
+            return credentials
+
+        return await self._request_tokens(
+            {
+                "refresh_token": credentials.refresh_token.get_secret_value(),
+                "grant_type": "refresh_token",
+            },
+            current_credentials=credentials,
+        )
+
+    async def _request_tokens(
+        self,
+        params: dict[str, str],
+        current_credentials: Optional[OAuth2Credentials] = None,
+    ) -> OAuth2Credentials:
+        request_body = {
+            "client_id": self.client_id,
+            "client_secret": self.client_secret,
+            **params,
+        }
+
+        headers = {
+            "Content-Type": "application/x-www-form-urlencoded",
+        }
+
+        response = await Requests().post(
+            self.token_url, data=request_body, headers=headers
+        )
+        token_data: dict = response.json()
+
+        # Get username if this is a new token request
+        username = None
+        if "access_token" in token_data:
+            username = await self._request_username(token_data["access_token"])
+
+        now = int(time.time())
+        new_credentials = OAuth2Credentials(
+            provider=self.PROVIDER_NAME,
+            title=current_credentials.title if current_credentials else None,
+            username=username,
+            access_token=token_data["access_token"],
+            scopes=token_data.get("scope", "").split()
+            or (current_credentials.scopes if current_credentials else []),
+            refresh_token=token_data.get("refresh_token"),
+            # Discord tokens expire after expires_in seconds (typically 7 days)
+            access_token_expires_at=(
+                now + expires_in
+                if (expires_in := token_data.get("expires_in", None))
+                else None
+            ),
+            # Discord doesn't provide separate refresh token expiration
+            refresh_token_expires_at=None,
+        )
+
+        if current_credentials:
+            new_credentials.id = current_credentials.id
+
+        return new_credentials
+
+    async def _request_username(self, access_token: str) -> str | None:
+        """
+        Fetch the username using the Discord OAuth2 @me endpoint.
+        """
+        url = "https://discord.com/api/oauth2/@me"
+        headers = {
+            "Authorization": f"Bearer {access_token}",
+        }
+
+        response = await Requests().get(url, headers=headers)
+
+        if not response.ok:
+            return None
+
+        # Get user info from the response
+        data = response.json()
+        user_info = data.get("user", {})
+
+        # Return username (without discriminator)
+        return user_info.get("username")

autogpt_platform/backend/backend/notifications/notifications.py

@@ -29,7 +29,7 @@ from backend.data.user import generate_unsubscribe_link
 from backend.notifications.email import EmailSender
 from backend.util.clients import get_database_manager_async_client
 from backend.util.logging import TruncatedLogger
-from backend.util.metrics import discord_send_alert
+from backend.util.metrics import DiscordChannel, discord_send_alert
 from backend.util.retry import continuous_retry
 from backend.util.service import (
     AppService,
@@ -382,8 +382,10 @@ class NotificationManager(AppService):
             }
 
     @expose
-    async def discord_system_alert(self, content: str):
-        await discord_send_alert(content)
+    async def discord_system_alert(
+        self, content: str, channel: DiscordChannel = DiscordChannel.PLATFORM
+    ):
+        await discord_send_alert(content, channel)
 
     async def _queue_scheduled_notification(self, event: SummaryParamsEventModel):
         """Queue a scheduled notification - exposed method for other services to call"""

autogpt_platform/backend/backend/notifications/templates/agent_approved.html.jinja2

@@ -0,0 +1,73 @@
+{# Agent Approved Notification Email Template #}
+{#
+  Template variables:
+  data.agent_name: the name of the approved agent
+  data.agent_id: the ID of the agent
+  data.agent_version: the version of the agent
+  data.reviewer_name: the name of the reviewer who approved it
+  data.reviewer_email: the email of the reviewer
+  data.comments: comments from the reviewer
+  data.reviewed_at: when the agent was reviewed
+  data.store_url: URL to view the agent in the store
+
+  Subject: 🎉 Your agent '{{ data.agent_name }}' has been approved!
+#}
+
+{% block content %}
+<h1 style="color: #28a745; font-size: 32px; font-weight: 700; margin: 0 0 24px 0; text-align: center;">
+  🎉 Congratulations!
+</h1>
+
+<p style="color: #586069; font-size: 18px; text-align: center; margin: 0 0 24px 0;">
+  Your agent <strong>'{{ data.agent_name }}'</strong> has been approved and is now live in the store!
+</p>
+
+<div style="height: 32px; background: transparent;"></div>
+
+{% if data.comments %}
+<div style="background: #d4edda; border: 1px solid #c3e6cb; border-radius: 8px; padding: 20px; margin: 0;">
+  <h3 style="color: #155724; font-size: 16px; font-weight: 600; margin: 0 0 12px 0;">
+    💬 Creator feedback area
+  </h3>
+  <p style="color: #155724; margin: 0; font-size: 16px; line-height: 1.5;">
+    {{ data.comments }}
+  </p>
+</div>
+
+<div style="height: 40px; background: transparent;"></div>
+{% endif %}
+
+<div style="background: #d1ecf1; border: 1px solid #bee5eb; border-radius: 8px; padding: 20px; margin: 0;">
+  <h3 style="color: #0c5460; font-size: 16px; font-weight: 600; margin: 0 0 12px 0;">
+    What's Next?
+  </h3>
+  <ul style="color: #0c5460; margin: 0; padding-left: 18px; font-size: 16px; line-height: 1.6;">
+    <li>Your agent is now live and discoverable in the AutoGPT Store</li>
+    <li>Users can find, install, and run your agent</li>
+    <li>You can update your agent anytime by submitting a new version</li>
+  </ul>
+</div>
+
+<div style="height: 32px; background: transparent;"></div>
+
+<div style="text-align: center; margin: 24px 0;">
+  <a href="{{ data.store_url }}" style="display: inline-block; background: linear-gradient(135deg, #7c3aed 0%, #5b21b6 100%); color: black; text-decoration: none; padding: 14px 28px; border-radius: 6px; font-weight: 600; font-size: 16px;">
+    View Your Agent in Store
+  </a>
+</div>
+
+<div style="height: 32px; background: transparent;"></div>
+
+<div style="background: #fff3cd; border: 1px solid #ffeaa7; border-radius: 6px; padding: 16px; margin: 24px 0; text-align: center;">
+  <p style="margin: 0; color: #856404; font-size: 14px;">
+    <strong>💡 Pro Tip:</strong> Share your agent with the community! Post about it on social media, forums, or your blog to help more users discover and benefit from your creation.
+  </p>
+</div>
+
+<div style="height: 32px; background: transparent;"></div>
+
+<p style="color: #6a737d; font-size: 14px; text-align: center; margin: 24px 0;">
+  Thank you for contributing to the AutoGPT ecosystem! 🚀
+</p>
+
+{% endblock %}

autogpt_platform/backend/backend/notifications/templates/agent_rejected.html.jinja2

@@ -0,0 +1,77 @@
+{# Agent Rejected Notification Email Template #}
+{#
+  Template variables:
+  data.agent_name: the name of the rejected agent
+  data.agent_id: the ID of the agent
+  data.agent_version: the version of the agent
+  data.reviewer_name: the name of the reviewer who rejected it
+  data.reviewer_email: the email of the reviewer
+  data.comments: comments from the reviewer explaining the rejection
+  data.reviewed_at: when the agent was reviewed
+  data.resubmit_url: URL to resubmit the agent
+
+  Subject: Your agent '{{ data.agent_name }}' needs some updates
+#}
+
+
+{% block content %}
+<h1 style="color: #d73a49; font-size: 32px; font-weight: 700; margin: 0 0 24px 0; text-align: center;">
+  📝 Review Complete
+</h1>
+
+<p style="color: #586069; font-size: 18px; text-align: center; margin: 0 0 24px 0;">
+  Your agent <strong>'{{ data.agent_name }}'</strong> needs some updates before approval.
+</p>
+
+<div style="height: 32px; background: transparent;"></div>
+
+<div style="background: #f8d7da; border: 1px solid #f5c6cb; border-radius: 8px; padding: 20px; margin: 0 0 24px 0;">
+  <h3 style="color: #721c24; font-size: 16px; font-weight: 600; margin: 0 0 12px 0;">
+    💬 Creator feedback area
+  </h3>
+  <p style="color: #721c24; margin: 0; font-size: 16px; line-height: 1.5;">
+    {{ data.comments }}
+  </p>
+</div>
+
+<div style="height: 40px; background: transparent;"></div>
+
+<div style="background: #d4edda; border: 1px solid #c3e6cb; border-radius: 8px; padding: 20px; margin: 0 0 24px 0;">
+  <h3 style="color: #155724; font-size: 16px; font-weight: 600; margin: 0 0 12px 0;">
+    ☑ Steps to Resubmit:
+  </h3>
+  <ul style="color: #155724; margin: 0; padding-left: 18px; font-size: 16px; line-height: 1.6;">
+    <li>Review the feedback provided above carefully</li>
+    <li>Make the necessary updates to your agent</li>
+    <li>Test your agent thoroughly to ensure it works as expected</li>
+    <li>Submit your updated agent for review</li>
+  </ul>
+</div>
+
+<div style="height: 32px; background: transparent;"></div>
+
+<div style="background: #fff3cd; border: 1px solid #ffeaa7; border-radius: 6px; padding: 12px; margin: 0 0 24px 0; text-align: center;">
+  <p style="margin: 0; color: #856404; font-size: 14px;">
+    <strong>💡 Tip:</strong> Address all the points mentioned in the feedback to increase your chances of approval in the next review.
+  </p>
+</div>
+
+<div style="text-align: center; margin: 32px 0;">
+  <a href="{{ data.resubmit_url }}" style="display: inline-block; background: linear-gradient(135deg, #7c3aed 0%, #5b21b6 100%); color: black; text-decoration: none; padding: 14px 28px; border-radius: 6px; font-weight: 600; font-size: 16px;">
+    Update & Resubmit Agent
+  </a>
+</div>
+
+<div style="background: #d1ecf1; border: 1px solid #bee5eb; border-radius: 6px; padding: 16px; margin: 24px 0;">
+  <p style="margin: 0; color: #0c5460; font-size: 14px; text-align: center;">
+    <strong>🌟 Don't Give Up!</strong> Many successful agents go through multiple iterations before approval. Our review team is here to help you succeed!
+  </p>
+</div>
+
+<div style="height: 32px; background: transparent;"></div>
+
+<p style="color: #6a737d; font-size: 14px; text-align: center; margin: 32px 0 24px 0;">
+  We're excited to see your improved agent submission! 🚀
+</p>
+
+{% endblock %}

autogpt_platform/backend/backend/notifications/templates/low_balance.html.jinja2

@@ -1,9 +1,7 @@
 {# Low Balance Notification Email Template #}
 {# Template variables:
-data.agent_name: the name of the agent
 data.current_balance: the current balance of the user
 data.billing_page_link: the link to the billing page
-data.shortfall: the shortfall amount
 #}
 
 <p style="
@@ -25,7 +23,7 @@ data.shortfall: the shortfall amount
     margin-top: 0;
     margin-bottom: 20px;
   ">
-  Your agent "<strong>{{ data.agent_name }}</strong>" has been stopped due to low balance.
+  Your account balance has dropped below the recommended threshold.
 </p>
 
 <div style="
@@ -44,15 +42,6 @@ data.shortfall: the shortfall amount
   ">
     <strong>Current Balance:</strong> ${{ "{:.2f}".format((data.current_balance|float)/100) }}
   </p>
-  <p style="
-    font-family: 'Poppins', sans-serif;
-    color: #070629;
-    font-size: 16px;
-    margin-top: 0;
-    margin-bottom: 10px;
-  ">
-    <strong>Shortfall:</strong> ${{ "{:.2f}".format((data.shortfall|float)/100) }}
-  </p>
 </div>
 
 
@@ -79,7 +68,7 @@ data.shortfall: the shortfall amount
     margin-top: 0;
     margin-bottom: 5px;
   ">
-    Your agent "<strong>{{ data.agent_name }}</strong>" requires additional credits to continue running. The current operation has been canceled until your balance is replenished.
+    Your account requires additional credits to continue running agents. Please add credits to your account to avoid service interruption.
   </p>
 </div>
 
@@ -110,5 +99,5 @@ data.shortfall: the shortfall amount
     margin-bottom: 10px;
     font-style: italic;
   ">
-  This is an automated notification. Your agent is stopped and will need manually restarted unless set to trigger automatically.
+  This is an automated low balance notification. Consider adding credits soon to avoid service interruption.
 </p>

autogpt_platform/backend/backend/notifications/templates/zero_balance.html.jinja2

@@ -0,0 +1,114 @@
+{# Low Balance Notification Email Template #}
+{# Template variables:
+data.agent_name: the name of the agent
+data.current_balance: the current balance of the user
+data.billing_page_link: the link to the billing page
+data.shortfall: the shortfall amount
+#}
+
+<p style="
+    font-family: 'Poppins', sans-serif;
+    color: #070629;
+    font-size: 16px;
+    line-height: 165%;
+    margin-top: 0;
+    margin-bottom: 10px;
+  ">
+  <strong>Zero Balance Warning</strong>
+</p>
+
+<p style="
+    font-family: 'Poppins', sans-serif;
+    color: #070629;
+    font-size: 16px;
+    line-height: 165%;
+    margin-top: 0;
+    margin-bottom: 20px;
+  ">
+  Your agent "<strong>{{ data.agent_name }}</strong>" has been stopped due to low balance.
+</p>
+
+<div style="
+    margin-left: 15px;
+    margin-bottom: 20px;
+    padding: 15px;
+    border-left: 4px solid #5D23BB;
+    background-color: #f8f8ff;
+  ">
+  <p style="
+    font-family: 'Poppins', sans-serif;
+    color: #070629;
+    font-size: 16px;
+    margin-top: 0;
+    margin-bottom: 10px;
+  ">
+    <strong>Current Balance:</strong> ${{ "{:.2f}".format((data.current_balance|float)/100) }}
+  </p>
+  <p style="
+    font-family: 'Poppins', sans-serif;
+    color: #070629;
+    font-size: 16px;
+    margin-top: 0;
+    margin-bottom: 10px;
+  ">
+    <strong>Shortfall:</strong> ${{ "{:.2f}".format((data.shortfall|float)/100) }}
+  </p>
+</div>
+
+
+<div style="
+    margin-left: 15px;
+    margin-bottom: 20px;
+    padding: 15px;
+    border-left: 4px solid #FF6B6B;
+    background-color: #FFF0F0;
+  ">
+  <p style="
+    font-family: 'Poppins', sans-serif;
+    color: #070629;
+    font-size: 16px;
+    margin-top: 0;
+    margin-bottom: 10px;
+  ">
+    <strong>Low Balance:</strong>
+  </p>
+  <p style="
+    font-family: 'Poppins', sans-serif;
+    color: #070629;
+    font-size: 16px;
+    margin-top: 0;
+    margin-bottom: 5px;
+  ">
+    Your agent "<strong>{{ data.agent_name }}</strong>" requires additional credits to continue running. The current operation has been canceled until your balance is replenished.
+  </p>
+</div>
+
+<div style="
+    text-align: center;
+    margin: 30px 0;
+  ">
+  <a href="{{ data.billing_page_link }}" style="
+    font-family: 'Poppins', sans-serif;
+    background-color: #5D23BB;
+    color: white;
+    padding: 12px 24px;
+    text-decoration: none;
+    border-radius: 4px;
+    font-weight: 500;
+    display: inline-block;
+  ">
+    Manage Billing
+  </a>
+</div>
+
+<p style="
+    font-family: 'Poppins', sans-serif;
+    color: #070629;
+    font-size: 16px;
+    line-height: 150%;
+    margin-top: 30px;
+    margin-bottom: 10px;
+    font-style: italic;
+  ">
+  This is an automated notification. Your agent is stopped and will need manually restarted unless set to trigger automatically.
+</p>

autogpt_platform/backend/backend/sdk/provider.py

@@ -14,6 +14,8 @@ from backend.data.model import (
     CredentialsField,
     CredentialsMetaInput,
     CredentialsType,
+    OAuth2Credentials,
+    UserPasswordCredentials,
 )
 from backend.integrations.oauth.base import BaseOAuthHandler
 from backend.integrations.webhooks._base import BaseWebhooksManager
@@ -104,14 +106,39 @@ class Provider:
         )
 
     def get_test_credentials(self) -> Credentials:
-        """Get test credentials for the provider."""
-        return APIKeyCredentials(
-            id=str(self.test_credentials_uuid),
-            provider=self.name,
-            api_key=SecretStr("mock-api-key"),
-            title=f"Mock {self.name.title()} API key",
-            expires_at=None,
-        )
+        """Get test credentials for the provider based on supported auth types."""
+        test_id = str(self.test_credentials_uuid)
+
+        # Return credentials based on the first supported auth type
+        if "user_password" in self.supported_auth_types:
+            return UserPasswordCredentials(
+                id=test_id,
+                provider=self.name,
+                username=SecretStr(f"mock-{self.name}-username"),
+                password=SecretStr(f"mock-{self.name}-password"),
+                title=f"Mock {self.name.title()} credentials",
+            )
+        elif "oauth2" in self.supported_auth_types:
+            return OAuth2Credentials(
+                id=test_id,
+                provider=self.name,
+                username=f"mock-{self.name}-username",
+                access_token=SecretStr(f"mock-{self.name}-access-token"),
+                access_token_expires_at=None,
+                refresh_token=SecretStr(f"mock-{self.name}-refresh-token"),
+                refresh_token_expires_at=None,
+                scopes=[f"mock-{self.name}-scope"],
+                title=f"Mock {self.name.title()} OAuth credentials",
+            )
+        else:
+            # Default to API key credentials
+            return APIKeyCredentials(
+                id=test_id,
+                provider=self.name,
+                api_key=SecretStr(f"mock-{self.name}-api-key"),
+                title=f"Mock {self.name.title()} API key",
+                expires_at=None,
+            )
 
     def get_api(self, credentials: Credentials) -> Any:
         """Get API client instance for the given credentials."""

autogpt_platform/backend/backend/server/model.py

@@ -5,6 +5,7 @@ import pydantic
 
 from backend.data.api_key import APIKeyPermission, APIKeyWithoutHash
 from backend.data.graph import Graph
+from backend.util.timezone_name import TimeZoneName
 
 
 class WSMethod(enum.Enum):
@@ -60,21 +61,6 @@ 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
 
@@ -85,3 +71,12 @@ class UploadFileResponse(pydantic.BaseModel):
     size: int
     content_type: str
     expires_in_hours: int
+
+
+class TimezoneResponse(pydantic.BaseModel):
+    # Allow "not-set" as a special value, or any valid IANA timezone
+    timezone: TimeZoneName | str
+
+
+class UpdateTimezoneRequest(pydantic.BaseModel):
+    timezone: TimeZoneName

autogpt_platform/backend/backend/server/rest_api.py

@@ -20,6 +20,8 @@ import backend.server.routers.postmark.postmark
 import backend.server.routers.v1
 import backend.server.v2.admin.credit_admin_routes
 import backend.server.v2.admin.store_admin_routes
+import backend.server.v2.builder
+import backend.server.v2.builder.routes
 import backend.server.v2.library.db
 import backend.server.v2.library.model
 import backend.server.v2.library.routes
@@ -195,6 +197,9 @@ app.include_router(backend.server.routers.v1.v1_router, tags=["v1"], prefix="/ap
 app.include_router(
     backend.server.v2.store.routes.router, tags=["v2"], prefix="/api/store"
 )
+app.include_router(
+    backend.server.v2.builder.routes.router, tags=["v2"], prefix="/api/builder"
+)
 app.include_router(
     backend.server.v2.admin.store_admin_routes.router,
     tags=["v2", "admin"],

autogpt_platform/backend/backend/server/routers/v1.py

@@ -15,6 +15,7 @@ from fastapi import (
     File,
     HTTPException,
     Path,
+    Query,
     Request,
     Response,
     UploadFile,
@@ -60,9 +61,11 @@ from backend.data.onboarding import (
 )
 from backend.data.user import (
     get_or_create_user,
+    get_user_by_id,
     get_user_notification_preference,
     update_user_email,
     update_user_notification_preference,
+    update_user_timezone,
 )
 from backend.executor import scheduler
 from backend.executor import utils as execution_utils
@@ -77,15 +80,21 @@ from backend.server.model import (
     ExecuteGraphResponse,
     RequestTopUp,
     SetGraphActiveVersion,
+    TimezoneResponse,
     UpdatePermissionsRequest,
+    UpdateTimezoneRequest,
     UploadFileResponse,
 )
 from backend.server.utils import get_user_id
 from backend.util.clients import get_scheduler_client
 from backend.util.cloud_storage import get_cloud_storage_handler
 from backend.util.exceptions import GraphValidationError, NotFoundError
-from backend.util.feature_flag import feature_flag
 from backend.util.settings import Settings
+from backend.util.timezone_utils import (
+    convert_cron_to_utc,
+    convert_utc_time_to_user_timezone,
+    get_user_timezone_or_utc,
+)
 from backend.util.virus_scanner import scan_content_safe
 
 
@@ -149,6 +158,35 @@ async def update_user_email_route(
     return {"email": email}
 
 
+@v1_router.get(
+    "/auth/user/timezone",
+    summary="Get user timezone",
+    tags=["auth"],
+    dependencies=[Depends(auth_middleware)],
+)
+async def get_user_timezone_route(
+    user_data: dict = Depends(auth_middleware),
+) -> TimezoneResponse:
+    """Get user timezone setting."""
+    user = await get_or_create_user(user_data)
+    return TimezoneResponse(timezone=user.timezone)
+
+
+@v1_router.post(
+    "/auth/user/timezone",
+    summary="Update user timezone",
+    tags=["auth"],
+    dependencies=[Depends(auth_middleware)],
+    response_model=TimezoneResponse,
+)
+async def update_user_timezone_route(
+    user_id: Annotated[str, Depends(get_user_id)], request: UpdateTimezoneRequest
+) -> TimezoneResponse:
+    """Update user timezone. The timezone should be a valid IANA timezone identifier."""
+    user = await update_user_timezone(user_id, str(request.timezone))
+    return TimezoneResponse(timezone=user.timezone)
+
+
 @v1_router.get(
     "/auth/user/preferences",
     summary="Get notification preferences",
@@ -820,11 +858,11 @@ async def _stop_graph_run(
 
 @v1_router.get(
     path="/executions",
-    summary="Get all executions",
+    summary="List all executions",
     tags=["graphs"],
     dependencies=[Depends(auth_middleware)],
 )
-async def get_graphs_executions(
+async def list_graphs_executions(
     user_id: Annotated[str, Depends(get_user_id)],
 ) -> list[execution_db.GraphExecutionMeta]:
     return await execution_db.get_graph_executions(user_id=user_id)
@@ -832,15 +870,24 @@ async def get_graphs_executions(
 
 @v1_router.get(
     path="/graphs/{graph_id}/executions",
-    summary="Get graph executions",
+    summary="List graph executions",
     tags=["graphs"],
     dependencies=[Depends(auth_middleware)],
 )
-async def get_graph_executions(
+async def list_graph_executions(
     graph_id: str,
     user_id: Annotated[str, Depends(get_user_id)],
-) -> list[execution_db.GraphExecutionMeta]:
-    return await execution_db.get_graph_executions(graph_id=graph_id, user_id=user_id)
+    page: int = Query(1, ge=1, description="Page number (1-indexed)"),
+    page_size: int = Query(
+        25, ge=1, le=100, description="Number of executions per page"
+    ),
+) -> execution_db.GraphExecutionsPaginated:
+    return await execution_db.get_graph_executions_paginated(
+        graph_id=graph_id,
+        user_id=user_id,
+        page=page,
+        page_size=page_size,
+    )
 
 
 @v1_router.get(
@@ -924,16 +971,36 @@ async def create_graph_execution_schedule(
             detail=f"Graph #{graph_id} v{schedule_params.graph_version} not found.",
         )
 
-    return await get_scheduler_client().add_execution_schedule(
+    user = await get_user_by_id(user_id)
+    user_timezone = get_user_timezone_or_utc(user.timezone if user else None)
+
+    # Convert cron expression from user timezone to UTC
+    try:
+        utc_cron = convert_cron_to_utc(schedule_params.cron, user_timezone)
+    except ValueError as e:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Invalid cron expression for timezone {user_timezone}: {e}",
+        )
+
+    result = await get_scheduler_client().add_execution_schedule(
         user_id=user_id,
         graph_id=graph_id,
         graph_version=graph.version,
         name=schedule_params.name,
-        cron=schedule_params.cron,
+        cron=utc_cron,  # Send UTC cron to scheduler
         input_data=schedule_params.inputs,
         input_credentials=schedule_params.credentials,
     )
 
+    # Convert the next_run_time back to user timezone for display
+    if result.next_run_time:
+        result.next_run_time = convert_utc_time_to_user_timezone(
+            result.next_run_time, user_timezone
+        )
+
+    return result
+
 
 @v1_router.get(
     path="/graphs/{graph_id}/schedules",
@@ -945,11 +1012,24 @@ async def list_graph_execution_schedules(
     user_id: Annotated[str, Depends(get_user_id)],
     graph_id: str = Path(),
 ) -> list[scheduler.GraphExecutionJobInfo]:
-    return await get_scheduler_client().get_execution_schedules(
+    schedules = await get_scheduler_client().get_execution_schedules(
         user_id=user_id,
         graph_id=graph_id,
     )
 
+    # Get user timezone for conversion
+    user = await get_user_by_id(user_id)
+    user_timezone = get_user_timezone_or_utc(user.timezone if user else None)
+
+    # Convert next_run_time to user timezone for display
+    for schedule in schedules:
+        if schedule.next_run_time:
+            schedule.next_run_time = convert_utc_time_to_user_timezone(
+                schedule.next_run_time, user_timezone
+            )
+
+    return schedules
+
 
 @v1_router.get(
     path="/schedules",
@@ -960,7 +1040,20 @@ async def list_graph_execution_schedules(
 async def list_all_graphs_execution_schedules(
     user_id: Annotated[str, Depends(get_user_id)],
 ) -> list[scheduler.GraphExecutionJobInfo]:
-    return await get_scheduler_client().get_execution_schedules(user_id=user_id)
+    schedules = await get_scheduler_client().get_execution_schedules(user_id=user_id)
+
+    # Get user timezone for conversion
+    user = await get_user_by_id(user_id)
+    user_timezone = get_user_timezone_or_utc(user.timezone if user else None)
+
+    # Convert UTC next_run_time to user timezone for display
+    for schedule in schedules:
+        if schedule.next_run_time:
+            schedule.next_run_time = convert_utc_time_to_user_timezone(
+                schedule.next_run_time, user_timezone
+            )
+
+    return schedules
 
 
 @v1_router.delete(
@@ -1071,7 +1164,6 @@ 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]:
@@ -1100,7 +1192,6 @@ 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]:
@@ -1126,7 +1217,6 @@ 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,

autogpt_platform/backend/backend/server/v2/AutoMod/manager.py

@@ -83,7 +83,7 @@ class AutoModManager:
             f"Moderating inputs for graph execution {graph_exec.graph_exec_id}"
         )
         try:
-            moderation_passed = await self._moderate_content(
+            moderation_passed, content_id = await self._moderate_content(
                 content,
                 {
                     "user_id": graph_exec.user_id,
@@ -99,7 +99,7 @@ class AutoModManager:
                 )
                 # Update node statuses for frontend display before raising error
                 await self._update_failed_nodes_for_moderation(
-                    db_client, graph_exec.graph_exec_id, "input"
+                    db_client, graph_exec.graph_exec_id, "input", content_id
                 )
 
                 return ModerationError(
@@ -107,6 +107,7 @@ class AutoModManager:
                     user_id=graph_exec.user_id,
                     graph_exec_id=graph_exec.graph_exec_id,
                     moderation_type="input",
+                    content_id=content_id,
                 )
 
             return None
@@ -167,7 +168,7 @@ class AutoModManager:
         # Run moderation
         logger.warning(f"Moderating outputs for graph execution {graph_exec_id}")
         try:
-            moderation_passed = await self._moderate_content(
+            moderation_passed, content_id = await self._moderate_content(
                 content,
                 {
                     "user_id": user_id,
@@ -181,7 +182,7 @@ class AutoModManager:
                 logger.warning(f"Moderation failed for graph execution {graph_exec_id}")
                 # Update node statuses for frontend display before raising error
                 await self._update_failed_nodes_for_moderation(
-                    db_client, graph_exec_id, "output"
+                    db_client, graph_exec_id, "output", content_id
                 )
 
                 return ModerationError(
@@ -189,6 +190,7 @@ class AutoModManager:
                     user_id=user_id,
                     graph_exec_id=graph_exec_id,
                     moderation_type="output",
+                    content_id=content_id,
                 )
 
             return None
@@ -212,6 +214,7 @@ class AutoModManager:
         db_client: "DatabaseManagerAsyncClient",
         graph_exec_id: str,
         moderation_type: Literal["input", "output"],
+        content_id: str | None = None,
     ):
         """Update node execution statuses for frontend display when moderation fails"""
         # Import here to avoid circular imports
@@ -236,6 +239,11 @@ class AutoModManager:
         if not executions_to_update:
             return
 
+        # Create error message with content_id if available
+        error_message = "Failed due to content moderation"
+        if content_id:
+            error_message += f" (Moderation ID: {content_id})"
+
         # Prepare database update tasks
         exec_updates = []
         for exec_entry in executions_to_update:
@@ -245,11 +253,11 @@ class AutoModManager:
 
             if exec_entry.input_data:
                 for name in exec_entry.input_data.keys():
-                    cleared_inputs[name] = ["Failed due to content moderation"]
+                    cleared_inputs[name] = [error_message]
 
             if exec_entry.output_data:
                 for name in exec_entry.output_data.keys():
-                    cleared_outputs[name] = ["Failed due to content moderation"]
+                    cleared_outputs[name] = [error_message]
 
             # Add update task to list
             exec_updates.append(
@@ -257,7 +265,7 @@ class AutoModManager:
                     exec_entry.node_exec_id,
                     status=ExecutionStatus.FAILED,
                     stats={
-                        "error": "Failed due to content moderation",
+                        "error": error_message,
                         "cleared_inputs": cleared_inputs,
                         "cleared_outputs": cleared_outputs,
                     },
@@ -275,12 +283,15 @@ class AutoModManager:
             ]
         )
 
-    async def _moderate_content(self, content: str, metadata: dict[str, Any]) -> bool:
+    async def _moderate_content(
+        self, content: str, metadata: dict[str, Any]
+    ) -> tuple[bool, str | None]:
         """Moderate content using AutoMod API
 
         Returns:
-            True: Content approved or timeout occurred
-            False: Content rejected by moderation
+            Tuple of (approval_status, content_id)
+            - approval_status: True if approved or timeout occurred, False if rejected
+            - content_id: Reference ID from moderation API, or None if not available
 
         Raises:
             asyncio.TimeoutError: When moderation times out (should be bypassed)
@@ -298,12 +309,12 @@ class AutoModManager:
                 logger.debug(
                     f"Content approved for {metadata.get('graph_exec_id', 'unknown')}"
                 )
-                return True
+                return True, response.content_id
             else:
                 reasons = [r.reason for r in response.moderation_results if r.reason]
                 error_msg = f"Content rejected by AutoMod: {'; '.join(reasons)}"
                 logger.warning(f"Content rejected: {error_msg}")
-                return False
+                return False, response.content_id
 
         except asyncio.TimeoutError:
             # Re-raise timeout to be handled by calling methods
@@ -313,7 +324,7 @@ class AutoModManager:
             raise
         except Exception as e:
             logger.error(f"AutoMod moderation error: {e}")
-            return self.config.fail_open
+            return self.config.fail_open, None
 
     async def _make_request(self, request_data: AutoModRequest) -> AutoModResponse:
         """Make HTTP request to AutoMod API using the standard request utility"""

autogpt_platform/backend/backend/server/v2/AutoMod/models.py

@@ -26,6 +26,9 @@ class AutoModResponse(BaseModel):
     """Response model for AutoMod API"""
 
     success: bool = Field(..., description="Whether the request was successful")
+    content_id: str = Field(
+        ..., description="Unique reference ID for this moderation request"
+    )
     status: str = Field(
         ..., description="Overall status: 'approved', 'rejected', 'flagged', 'pending'"
     )

autogpt_platform/backend/backend/server/v2/admin/credit_admin_routes_test.py

@@ -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)

autogpt_platform/backend/backend/server/v2/admin/model.py

@@ -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):

autogpt_platform/backend/backend/server/v2/builder/db.py

@@ -0,0 +1,376 @@
+import functools
+import logging
+from datetime import datetime, timedelta, timezone
+
+import prisma
+
+import backend.data.block
+from backend.blocks import load_all_blocks
+from backend.blocks.llm import LlmModel
+from backend.data.block import Block, BlockCategory, BlockSchema
+from backend.data.credit import get_block_costs
+from backend.integrations.providers import ProviderName
+from backend.server.v2.builder.model import (
+    BlockCategoryResponse,
+    BlockData,
+    BlockResponse,
+    BlockType,
+    CountResponse,
+    Provider,
+    ProviderResponse,
+    SearchBlocksResponse,
+)
+from backend.util.models import Pagination
+
+logger = logging.getLogger(__name__)
+llm_models = [name.name.lower().replace("_", " ") for name in LlmModel]
+_static_counts_cache: dict | None = None
+_suggested_blocks: list[BlockData] | None = None
+
+
+def get_block_categories(category_blocks: int = 3) -> list[BlockCategoryResponse]:
+    categories: dict[BlockCategory, BlockCategoryResponse] = {}
+
+    for block_type in load_all_blocks().values():
+        block: Block[BlockSchema, BlockSchema] = block_type()
+        # Skip disabled blocks
+        if block.disabled:
+            continue
+        # Skip blocks that don't have categories (all should have at least one)
+        if not block.categories:
+            continue
+
+        # Add block to the categories
+        for category in block.categories:
+            if category not in categories:
+                categories[category] = BlockCategoryResponse(
+                    name=category.name.lower(),
+                    total_blocks=0,
+                    blocks=[],
+                )
+
+            categories[category].total_blocks += 1
+
+            # Append if the category has less than the specified number of blocks
+            if len(categories[category].blocks) < category_blocks:
+                categories[category].blocks.append(block.to_dict())
+
+    # Sort categories by name
+    return sorted(categories.values(), key=lambda x: x.name)
+
+
+def get_blocks(
+    *,
+    category: str | None = None,
+    type: BlockType | None = None,
+    provider: ProviderName | None = None,
+    page: int = 1,
+    page_size: int = 50,
+) -> BlockResponse:
+    """
+    Get blocks based on either category, type or provider.
+    Providing nothing fetches all block types.
+    """
+    # Only one of category, type, or provider can be specified
+    if (category and type) or (category and provider) or (type and provider):
+        raise ValueError("Only one of category, type, or provider can be specified")
+
+    blocks: list[Block[BlockSchema, BlockSchema]] = []
+    skip = (page - 1) * page_size
+    take = page_size
+    total = 0
+
+    for block_type in load_all_blocks().values():
+        block: Block[BlockSchema, BlockSchema] = block_type()
+        # Skip disabled blocks
+        if block.disabled:
+            continue
+        # Skip blocks that don't match the category
+        if category and category not in {c.name.lower() for c in block.categories}:
+            continue
+        # Skip blocks that don't match the type
+        if (
+            (type == "input" and block.block_type.value != "Input")
+            or (type == "output" and block.block_type.value != "Output")
+            or (type == "action" and block.block_type.value in ("Input", "Output"))
+        ):
+            continue
+        # Skip blocks that don't match the provider
+        if provider:
+            credentials_info = block.input_schema.get_credentials_fields_info().values()
+            if not any(provider in info.provider for info in credentials_info):
+                continue
+
+        total += 1
+        if skip > 0:
+            skip -= 1
+            continue
+        if take > 0:
+            take -= 1
+            blocks.append(block)
+
+    costs = get_block_costs()
+
+    return BlockResponse(
+        blocks=[{**b.to_dict(), "costs": costs.get(b.id, [])} for b in blocks],
+        pagination=Pagination(
+            total_items=total,
+            total_pages=(total + page_size - 1) // page_size,
+            current_page=page,
+            page_size=page_size,
+        ),
+    )
+
+
+def search_blocks(
+    include_blocks: bool = True,
+    include_integrations: bool = True,
+    query: str = "",
+    page: int = 1,
+    page_size: int = 50,
+) -> SearchBlocksResponse:
+    """
+    Get blocks based on the filter and query.
+    `providers` only applies for `integrations` filter.
+    """
+    blocks: list[Block[BlockSchema, BlockSchema]] = []
+    query = query.lower()
+
+    total = 0
+    skip = (page - 1) * page_size
+    take = page_size
+    block_count = 0
+    integration_count = 0
+
+    for block_type in load_all_blocks().values():
+        block: Block[BlockSchema, BlockSchema] = block_type()
+        # Skip disabled blocks
+        if block.disabled:
+            continue
+        # Skip blocks that don't match the query
+        if (
+            query not in block.name.lower()
+            and query not in block.description.lower()
+            and not _matches_llm_model(block.input_schema, query)
+        ):
+            continue
+        keep = False
+        credentials = list(block.input_schema.get_credentials_fields().values())
+        if include_integrations and len(credentials) > 0:
+            keep = True
+            integration_count += 1
+        if include_blocks and len(credentials) == 0:
+            keep = True
+            block_count += 1
+
+        if not keep:
+            continue
+
+        total += 1
+        if skip > 0:
+            skip -= 1
+            continue
+        if take > 0:
+            take -= 1
+            blocks.append(block)
+
+    costs = get_block_costs()
+
+    return SearchBlocksResponse(
+        blocks=BlockResponse(
+            blocks=[{**b.to_dict(), "costs": costs.get(b.id, [])} for b in blocks],
+            pagination=Pagination(
+                total_items=total,
+                total_pages=(total + page_size - 1) // page_size,
+                current_page=page,
+                page_size=page_size,
+            ),
+        ),
+        total_block_count=block_count,
+        total_integration_count=integration_count,
+    )
+
+
+def get_providers(
+    query: str = "",
+    page: int = 1,
+    page_size: int = 50,
+) -> ProviderResponse:
+    providers = []
+    query = query.lower()
+
+    skip = (page - 1) * page_size
+    take = page_size
+
+    all_providers = _get_all_providers()
+
+    for provider in all_providers.values():
+        if (
+            query not in provider.name.value.lower()
+            and query not in provider.description.lower()
+        ):
+            continue
+        if skip > 0:
+            skip -= 1
+            continue
+        if take > 0:
+            take -= 1
+            providers.append(provider)
+
+    total = len(all_providers)
+
+    return ProviderResponse(
+        providers=providers,
+        pagination=Pagination(
+            total_items=total,
+            total_pages=(total + page_size - 1) // page_size,
+            current_page=page,
+            page_size=page_size,
+        ),
+    )
+
+
+async def get_counts(user_id: str) -> CountResponse:
+    my_agents = await prisma.models.LibraryAgent.prisma().count(
+        where={
+            "userId": user_id,
+            "isDeleted": False,
+            "isArchived": False,
+        }
+    )
+    counts = await _get_static_counts()
+    return CountResponse(
+        my_agents=my_agents,
+        **counts,
+    )
+
+
+async def _get_static_counts():
+    """
+    Get counts of blocks, integrations, and marketplace agents.
+    This is cached to avoid unnecessary database queries and calculations.
+    Can't use functools.cache here because the function is async.
+    """
+    global _static_counts_cache
+    if _static_counts_cache is not None:
+        return _static_counts_cache
+
+    all_blocks = 0
+    input_blocks = 0
+    action_blocks = 0
+    output_blocks = 0
+    integrations = 0
+
+    for block_type in load_all_blocks().values():
+        block: Block[BlockSchema, BlockSchema] = block_type()
+        if block.disabled:
+            continue
+
+        all_blocks += 1
+
+        if block.block_type.value == "Input":
+            input_blocks += 1
+        elif block.block_type.value == "Output":
+            output_blocks += 1
+        else:
+            action_blocks += 1
+
+        credentials = list(block.input_schema.get_credentials_fields().values())
+        if len(credentials) > 0:
+            integrations += 1
+
+    marketplace_agents = await prisma.models.StoreAgent.prisma().count()
+
+    _static_counts_cache = {
+        "all_blocks": all_blocks,
+        "input_blocks": input_blocks,
+        "action_blocks": action_blocks,
+        "output_blocks": output_blocks,
+        "integrations": integrations,
+        "marketplace_agents": marketplace_agents,
+    }
+
+    return _static_counts_cache
+
+
+def _matches_llm_model(schema_cls: type[BlockSchema], query: str) -> bool:
+    for field in schema_cls.model_fields.values():
+        if field.annotation == LlmModel:
+            # Check if query matches any value in llm_models
+            if any(query in name for name in llm_models):
+                return True
+    return False
+
+
+@functools.cache
+def _get_all_providers() -> dict[ProviderName, Provider]:
+    providers: dict[ProviderName, Provider] = {}
+
+    for block_type in load_all_blocks().values():
+        block: Block[BlockSchema, BlockSchema] = block_type()
+        if block.disabled:
+            continue
+
+        credentials_info = block.input_schema.get_credentials_fields_info().values()
+        for info in credentials_info:
+            for provider in info.provider:  # provider is a ProviderName enum member
+                if provider in providers:
+                    providers[provider].integration_count += 1
+                else:
+                    providers[provider] = Provider(
+                        name=provider, description="", integration_count=1
+                    )
+    return providers
+
+
+async def get_suggested_blocks(count: int = 5) -> list[BlockData]:
+    global _suggested_blocks
+
+    if _suggested_blocks is not None and len(_suggested_blocks) >= count:
+        return _suggested_blocks[:count]
+
+    _suggested_blocks = []
+    # Sum the number of executions for each block type
+    # Prisma cannot group by nested relations, so we do a raw query
+    # Calculate the cutoff timestamp
+    timestamp_threshold = datetime.now(timezone.utc) - timedelta(days=30)
+
+    results = await prisma.get_client().query_raw(
+        """
+        SELECT
+            agent_node."agentBlockId" AS block_id,
+            COUNT(execution.id) AS execution_count
+        FROM "AgentNodeExecution" execution
+        JOIN "AgentNode" agent_node ON execution."agentNodeId" = agent_node.id
+        WHERE execution."endedTime" >= $1::timestamp
+        GROUP BY agent_node."agentBlockId"
+        ORDER BY execution_count DESC;
+        """,
+        timestamp_threshold,
+    )
+
+    # Get the top blocks based on execution count
+    # But ignore Input and Output blocks
+    blocks: list[tuple[BlockData, int]] = []
+
+    for block_type in load_all_blocks().values():
+        block: Block[BlockSchema, BlockSchema] = block_type()
+        if block.disabled or block.block_type in (
+            backend.data.block.BlockType.INPUT,
+            backend.data.block.BlockType.OUTPUT,
+            backend.data.block.BlockType.AGENT,
+        ):
+            continue
+        # Find the execution count for this block
+        execution_count = next(
+            (row["execution_count"] for row in results if row["block_id"] == block.id),
+            0,
+        )
+        blocks.append((block.to_dict(), execution_count))
+    # Sort blocks by execution count
+    blocks.sort(key=lambda x: x[1], reverse=True)
+
+    _suggested_blocks = [block[0] for block in blocks]
+
+    # Return the top blocks
+    return _suggested_blocks[:count]

autogpt_platform/backend/backend/server/v2/builder/model.py

@@ -0,0 +1,87 @@
+from typing import Any, Literal
+
+from pydantic import BaseModel
+
+import backend.server.v2.library.model as library_model
+import backend.server.v2.store.model as store_model
+from backend.integrations.providers import ProviderName
+from backend.util.models import Pagination
+
+FilterType = Literal[
+    "blocks",
+    "integrations",
+    "marketplace_agents",
+    "my_agents",
+]
+
+BlockType = Literal["all", "input", "action", "output"]
+
+BlockData = dict[str, Any]
+
+
+# Suggestions
+class SuggestionsResponse(BaseModel):
+    otto_suggestions: list[str]
+    recent_searches: list[str]
+    providers: list[ProviderName]
+    top_blocks: list[BlockData]
+
+
+# All blocks
+class BlockCategoryResponse(BaseModel):
+    name: str
+    total_blocks: int
+    blocks: list[BlockData]
+
+    model_config = {"use_enum_values": False}  # <== use enum names like "AI"
+
+
+# Input/Action/Output and see all for block categories
+class BlockResponse(BaseModel):
+    blocks: list[BlockData]
+    pagination: Pagination
+
+
+# Providers
+class Provider(BaseModel):
+    name: ProviderName
+    description: str
+    integration_count: int
+
+
+class ProviderResponse(BaseModel):
+    providers: list[Provider]
+    pagination: Pagination
+
+
+# Search
+class SearchRequest(BaseModel):
+    search_query: str | None = None
+    filter: list[FilterType] | None = None
+    by_creator: list[str] | None = None
+    search_id: str | None = None
+    page: int | None = None
+    page_size: int | None = None
+
+
+class SearchBlocksResponse(BaseModel):
+    blocks: BlockResponse
+    total_block_count: int
+    total_integration_count: int
+
+
+class SearchResponse(BaseModel):
+    items: list[BlockData | library_model.LibraryAgent | store_model.StoreAgent]
+    total_items: dict[FilterType, int]
+    page: int
+    more_pages: bool
+
+
+class CountResponse(BaseModel):
+    all_blocks: int
+    input_blocks: int
+    action_blocks: int
+    output_blocks: int
+    integrations: int
+    marketplace_agents: int
+    my_agents: int

autogpt_platform/backend/backend/server/v2/builder/routes.py

@@ -0,0 +1,239 @@
+import logging
+from typing import Annotated, Sequence
+
+import fastapi
+from autogpt_libs.auth.depends import auth_middleware, get_user_id
+
+import backend.server.v2.builder.db as builder_db
+import backend.server.v2.builder.model as builder_model
+import backend.server.v2.library.db as library_db
+import backend.server.v2.library.model as library_model
+import backend.server.v2.store.db as store_db
+import backend.server.v2.store.model as store_model
+from backend.integrations.providers import ProviderName
+from backend.util.models import Pagination
+
+logger = logging.getLogger(__name__)
+
+router = fastapi.APIRouter()
+
+
+# Taken from backend/server/v2/store/db.py
+def sanitize_query(query: str | None) -> str | None:
+    if query is None:
+        return query
+    query = query.strip()[:100]
+    return (
+        query.replace("\\", "\\\\")
+        .replace("%", "\\%")
+        .replace("_", "\\_")
+        .replace("[", "\\[")
+        .replace("]", "\\]")
+        .replace("'", "\\'")
+        .replace('"', '\\"')
+        .replace(";", "\\;")
+        .replace("--", "\\--")
+        .replace("/*", "\\/*")
+        .replace("*/", "\\*/")
+    )
+
+
+@router.get(
+    "/suggestions",
+    summary="Get Builder suggestions",
+    dependencies=[fastapi.Depends(auth_middleware)],
+    response_model=builder_model.SuggestionsResponse,
+)
+async def get_suggestions(
+    user_id: Annotated[str, fastapi.Depends(get_user_id)],
+) -> builder_model.SuggestionsResponse:
+    """
+    Get all suggestions for the Blocks Menu.
+    """
+    return builder_model.SuggestionsResponse(
+        otto_suggestions=[
+            "What blocks do I need to get started?",
+            "Help me create a list",
+            "Help me feed my data to Google Maps",
+        ],
+        recent_searches=[
+            "image generation",
+            "deepfake",
+            "competitor analysis",
+        ],
+        providers=[
+            ProviderName.TWITTER,
+            ProviderName.GITHUB,
+            ProviderName.NOTION,
+            ProviderName.GOOGLE,
+            ProviderName.DISCORD,
+            ProviderName.GOOGLE_MAPS,
+        ],
+        top_blocks=await builder_db.get_suggested_blocks(),
+    )
+
+
+@router.get(
+    "/categories",
+    summary="Get Builder block categories",
+    dependencies=[fastapi.Depends(auth_middleware)],
+    response_model=Sequence[builder_model.BlockCategoryResponse],
+)
+async def get_block_categories(
+    blocks_per_category: Annotated[int, fastapi.Query()] = 3,
+) -> Sequence[builder_model.BlockCategoryResponse]:
+    """
+    Get all block categories with a specified number of blocks per category.
+    """
+    return builder_db.get_block_categories(blocks_per_category)
+
+
+@router.get(
+    "/blocks",
+    summary="Get Builder blocks",
+    dependencies=[fastapi.Depends(auth_middleware)],
+    response_model=builder_model.BlockResponse,
+)
+async def get_blocks(
+    category: Annotated[str | None, fastapi.Query()] = None,
+    type: Annotated[builder_model.BlockType | None, fastapi.Query()] = None,
+    provider: Annotated[ProviderName | None, fastapi.Query()] = None,
+    page: Annotated[int, fastapi.Query()] = 1,
+    page_size: Annotated[int, fastapi.Query()] = 50,
+) -> builder_model.BlockResponse:
+    """
+    Get blocks based on either category, type, or provider.
+    """
+    return builder_db.get_blocks(
+        category=category,
+        type=type,
+        provider=provider,
+        page=page,
+        page_size=page_size,
+    )
+
+
+@router.get(
+    "/providers",
+    summary="Get Builder integration providers",
+    dependencies=[fastapi.Depends(auth_middleware)],
+    response_model=builder_model.ProviderResponse,
+)
+async def get_providers(
+    page: Annotated[int, fastapi.Query()] = 1,
+    page_size: Annotated[int, fastapi.Query()] = 50,
+) -> builder_model.ProviderResponse:
+    """
+    Get all integration providers with their block counts.
+    """
+    return builder_db.get_providers(
+        page=page,
+        page_size=page_size,
+    )
+
+
+@router.post(
+    "/search",
+    summary="Builder search",
+    tags=["store", "private"],
+    dependencies=[fastapi.Depends(auth_middleware)],
+    response_model=builder_model.SearchResponse,
+)
+async def search(
+    options: builder_model.SearchRequest,
+    user_id: Annotated[str, fastapi.Depends(get_user_id)],
+) -> builder_model.SearchResponse:
+    """
+    Search for blocks (including integrations), marketplace agents, and user library agents.
+    """
+    # If no filters are provided, then we will return all types
+    if not options.filter:
+        options.filter = [
+            "blocks",
+            "integrations",
+            "marketplace_agents",
+            "my_agents",
+        ]
+    options.search_query = sanitize_query(options.search_query)
+    options.page = options.page or 1
+    options.page_size = options.page_size or 50
+
+    # Blocks&Integrations
+    blocks = builder_model.SearchBlocksResponse(
+        blocks=builder_model.BlockResponse(
+            blocks=[],
+            pagination=Pagination.empty(),
+        ),
+        total_block_count=0,
+        total_integration_count=0,
+    )
+    if "blocks" in options.filter or "integrations" in options.filter:
+        blocks = builder_db.search_blocks(
+            include_blocks="blocks" in options.filter,
+            include_integrations="integrations" in options.filter,
+            query=options.search_query or "",
+            page=options.page,
+            page_size=options.page_size,
+        )
+
+    # Library Agents
+    my_agents = library_model.LibraryAgentResponse(
+        agents=[],
+        pagination=Pagination.empty(),
+    )
+    if "my_agents" in options.filter:
+        my_agents = await library_db.list_library_agents(
+            user_id=user_id,
+            search_term=options.search_query,
+            page=options.page,
+            page_size=options.page_size,
+        )
+
+    # Marketplace Agents
+    marketplace_agents = store_model.StoreAgentsResponse(
+        agents=[],
+        pagination=Pagination.empty(),
+    )
+    if "marketplace_agents" in options.filter:
+        marketplace_agents = await store_db.get_store_agents(
+            creators=options.by_creator,
+            search_query=options.search_query,
+            page=options.page,
+            page_size=options.page_size,
+        )
+
+    more_pages = False
+    if (
+        blocks.blocks.pagination.current_page < blocks.blocks.pagination.total_pages
+        or my_agents.pagination.current_page < my_agents.pagination.total_pages
+        or marketplace_agents.pagination.current_page
+        < marketplace_agents.pagination.total_pages
+    ):
+        more_pages = True
+
+    return builder_model.SearchResponse(
+        items=blocks.blocks.blocks + my_agents.agents + marketplace_agents.agents,
+        total_items={
+            "blocks": blocks.total_block_count,
+            "integrations": blocks.total_integration_count,
+            "marketplace_agents": marketplace_agents.pagination.total_items,
+            "my_agents": my_agents.pagination.total_items,
+        },
+        page=options.page,
+        more_pages=more_pages,
+    )
+
+
+@router.get(
+    "/counts",
+    summary="Get Builder item counts",
+    dependencies=[fastapi.Depends(auth_middleware)],
+    response_model=builder_model.CountResponse,
+)
+async def get_counts(
+    user_id: Annotated[str, fastapi.Depends(get_user_id)],
+) -> builder_model.CountResponse:
+    """
+    Get item counts for the menu categories in the Blocks Menu.
+    """
+    return await builder_db.get_counts(user_id)

autogpt_platform/backend/backend/server/v2/library/db.py

@@ -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,

autogpt_platform/backend/backend/server/v2/library/model.py

@@ -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):
@@ -51,6 +51,7 @@ class LibraryAgent(pydantic.BaseModel):
     description: str
 
     input_schema: dict[str, Any]  # Should be BlockIOObjectSubSchema in frontend
+    output_schema: dict[str, Any]
     credentials_input_schema: dict[str, Any] | None = pydantic.Field(
         description="Input schema for credentials required by the agent",
     )
@@ -126,6 +127,7 @@ class LibraryAgent(pydantic.BaseModel):
             name=graph.name,
             description=graph.description,
             input_schema=graph.input_schema,
+            output_schema=graph.output_schema,
             credentials_input_schema=(
                 graph.credentials_input_schema if sub_graphs is not None else None
             ),
@@ -213,7 +215,7 @@ 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 +319,7 @@ 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):

autogpt_platform/backend/backend/server/v2/library/routes_test.py

@@ -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)
@@ -50,6 +50,7 @@ async def test_get_library_agents_success(
                 creator_name="Test Creator",
                 creator_image_url="",
                 input_schema={"type": "object", "properties": {}},
+                output_schema={"type": "object", "properties": {}},
                 credentials_input_schema={"type": "object", "properties": {}},
                 has_external_trigger=False,
                 status=library_model.LibraryAgentStatus.COMPLETED,
@@ -68,6 +69,7 @@ async def test_get_library_agents_success(
                 creator_name="Test Creator",
                 creator_image_url="",
                 input_schema={"type": "object", "properties": {}},
+                output_schema={"type": "object", "properties": {}},
                 credentials_input_schema={"type": "object", "properties": {}},
                 has_external_trigger=False,
                 status=library_model.LibraryAgentStatus.COMPLETED,
@@ -77,7 +79,7 @@ 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
         ),
     )
@@ -132,6 +134,7 @@ def test_add_agent_to_library_success(mocker: pytest_mock.MockFixture):
         creator_name="Test Creator",
         creator_image_url="",
         input_schema={"type": "object", "properties": {}},
+        output_schema={"type": "object", "properties": {}},
         credentials_input_schema={"type": "object", "properties": {}},
         has_external_trigger=False,
         status=library_model.LibraryAgentStatus.COMPLETED,

autogpt_platform/backend/backend/server/v2/store/db.py

@@ -17,8 +17,21 @@ from backend.data.graph import (
     get_sub_graphs,
 )
 from backend.data.includes import AGENT_GRAPH_INCLUDE
+from backend.data.notifications import (
+    AgentApprovalData,
+    AgentRejectionData,
+    NotificationEventModel,
+)
+from backend.notifications.notifications import queue_notification_async
+from backend.util.settings import Settings
 
 logger = logging.getLogger(__name__)
+settings = Settings()
+
+
+# Constants for default admin values
+DEFAULT_ADMIN_NAME = "AutoGPT Admin"
+DEFAULT_ADMIN_EMAIL = "admin@autogpt.co"
 
 
 def sanitize_query(query: str | None) -> str | None:
@@ -42,7 +55,7 @@ def sanitize_query(query: str | None) -> str | None:
 
 async def get_store_agents(
     featured: bool = False,
-    creator: str | None = None,
+    creators: list[str] | None = None,
     sorted_by: str | None = None,
     search_query: str | None = None,
     category: str | None = None,
@@ -53,15 +66,15 @@ async def get_store_agents(
     Get PUBLIC store agents from the StoreAgent view
     """
     logger.debug(
-        f"Getting store agents. featured={featured}, creator={creator}, sorted_by={sorted_by}, search={search_query}, category={category}, page={page}"
+        f"Getting store agents. featured={featured}, creators={creators}, sorted_by={sorted_by}, search={search_query}, category={category}, page={page}"
     )
     sanitized_query = sanitize_query(search_query)
 
     where_clause = {}
     if featured:
         where_clause["featured"] = featured
-    if creator:
-        where_clause["creator_username"] = creator
+    if creators:
+        where_clause["creator_username"] = {"in": creators}
     if category:
         where_clause["categories"] = {"has": category}
 
@@ -466,6 +479,8 @@ 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 +561,7 @@ 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 +700,160 @@ 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 +865,7 @@ 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
@@ -1085,7 +1254,8 @@ async def review_store_submission(
                 where={"id": store_listing_version_id},
                 include={
                     "StoreListing": True,
-                    "AgentGraph": {"include": AGENT_GRAPH_INCLUDE},
+                    "AgentGraph": {"include": {**AGENT_GRAPH_INCLUDE, "User": True}},
+                    "Reviewer": True,
                 },
             )
         )
@@ -1096,6 +1266,13 @@ async def review_store_submission(
                 detail=f"Store listing version {store_listing_version_id} not found",
             )
 
+        # Check if we're rejecting an already approved agent
+        is_rejecting_approved = (
+            not is_approved
+            and store_listing_version.submissionStatus
+            == prisma.enums.SubmissionStatus.APPROVED
+        )
+
         # If approving, update the listing to indicate it has an approved version
         if is_approved and store_listing_version.AgentGraph:
             heading = f"Sub-graph of {store_listing_version.name}v{store_listing_version.agentGraphVersion}"
@@ -1126,6 +1303,37 @@ async def review_store_submission(
                 },
             )
 
+        # If rejecting an approved agent, update the StoreListing accordingly
+        if is_rejecting_approved:
+            # Check if there are other approved versions
+            other_approved = (
+                await prisma.models.StoreListingVersion.prisma().find_first(
+                    where={
+                        "storeListingId": store_listing_version.StoreListing.id,
+                        "id": {"not": store_listing_version_id},
+                        "submissionStatus": prisma.enums.SubmissionStatus.APPROVED,
+                    }
+                )
+            )
+
+            if not other_approved:
+                # No other approved versions, update hasApprovedVersion to False
+                await prisma.models.StoreListing.prisma().update(
+                    where={"id": store_listing_version.StoreListing.id},
+                    data={
+                        "hasApprovedVersion": False,
+                        "ActiveVersion": {"disconnect": True},
+                    },
+                )
+            else:
+                # Set the most recent other approved version as active
+                await prisma.models.StoreListing.prisma().update(
+                    where={"id": store_listing_version.StoreListing.id},
+                    data={
+                        "ActiveVersion": {"connect": {"id": other_approved.id}},
+                    },
+                )
+
         submission_status = (
             prisma.enums.SubmissionStatus.APPROVED
             if is_approved
@@ -1154,6 +1362,89 @@ async def review_store_submission(
                 f"Failed to update store listing version {store_listing_version_id}"
             )
 
+        # Send email notification to the agent creator
+        if store_listing_version.AgentGraph and store_listing_version.AgentGraph.User:
+            agent_creator = store_listing_version.AgentGraph.User
+            reviewer = (
+                store_listing_version.Reviewer
+                if store_listing_version.Reviewer
+                else None
+            )
+
+            try:
+                base_url = (
+                    settings.config.frontend_base_url
+                    or settings.config.platform_base_url
+                )
+
+                if is_approved:
+                    store_agent = (
+                        await prisma.models.StoreAgent.prisma().find_first_or_raise(
+                            where={"storeListingVersionId": submission.id}
+                        )
+                    )
+
+                    # Send approval notification
+                    notification_data = AgentApprovalData(
+                        agent_name=submission.name,
+                        agent_id=submission.agentGraphId,
+                        agent_version=submission.agentGraphVersion,
+                        reviewer_name=(
+                            reviewer.name
+                            if reviewer and reviewer.name
+                            else DEFAULT_ADMIN_NAME
+                        ),
+                        reviewer_email=(
+                            reviewer.email if reviewer else DEFAULT_ADMIN_EMAIL
+                        ),
+                        comments=external_comments,
+                        reviewed_at=submission.reviewedAt
+                        or datetime.now(tz=timezone.utc),
+                        store_url=f"{base_url}/marketplace/agent/{store_agent.creator_username}/{store_agent.slug}",
+                    )
+
+                    notification_event = NotificationEventModel[AgentApprovalData](
+                        user_id=agent_creator.id,
+                        type=prisma.enums.NotificationType.AGENT_APPROVED,
+                        data=notification_data,
+                    )
+                else:
+                    # Send rejection notification
+                    notification_data = AgentRejectionData(
+                        agent_name=submission.name,
+                        agent_id=submission.agentGraphId,
+                        agent_version=submission.agentGraphVersion,
+                        reviewer_name=(
+                            reviewer.name
+                            if reviewer and reviewer.name
+                            else DEFAULT_ADMIN_NAME
+                        ),
+                        reviewer_email=(
+                            reviewer.email if reviewer else DEFAULT_ADMIN_EMAIL
+                        ),
+                        comments=external_comments,
+                        reviewed_at=submission.reviewedAt
+                        or datetime.now(tz=timezone.utc),
+                        resubmit_url=f"{base_url}/build?flowID={submission.agentGraphId}",
+                    )
+
+                    notification_event = NotificationEventModel[AgentRejectionData](
+                        user_id=agent_creator.id,
+                        type=prisma.enums.NotificationType.AGENT_REJECTED,
+                        data=notification_data,
+                    )
+
+                # Queue the notification for immediate sending
+                await queue_notification_async(notification_event)
+                logger.info(
+                    f"Queued {'approval' if is_approved else 'rejection'} notification for user {agent_creator.id} and agent {submission.name}"
+                )
+
+            except Exception as e:
+                logger.error(f"Failed to send email notification for agent review: {e}")
+                # Don't fail the review process if email sending fails
+                pass
+
         # Convert to Pydantic model for consistency
         return backend.server.v2.store.model.StoreSubmission(
             agent_id=submission.agentGraphId,

autogpt_platform/backend/backend/server/v2/store/exceptions.py

@@ -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

autogpt_platform/backend/backend/server/v2/store/model.py

@@ -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

autogpt_platform/backend/backend/server/v2/store/routes.py

@@ -162,7 +162,7 @@ async def get_agents(
     try:
         agents = await backend.server.v2.store.db.get_store_agents(
             featured=featured,
-            creator=creator,
+            creators=[creator] if creator else None,
             sorted_by=sorted_by,
             search_query=search_query,
             category=category,
@@ -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",

autogpt_platform/backend/backend/server/v2/store/routes_test.py

@@ -66,7 +66,7 @@ def test_get_agents_defaults(
     snapshot.assert_match(json.dumps(response.json(), indent=2), "def_agts")
     mock_db_call.assert_called_once_with(
         featured=False,
-        creator=None,
+        creators=None,
         sorted_by=None,
         search_query=None,
         category=None,
@@ -113,7 +113,7 @@ def test_get_agents_featured(
     snapshot.assert_match(json.dumps(response.json(), indent=2), "feat_agts")
     mock_db_call.assert_called_once_with(
         featured=True,
-        creator=None,
+        creators=None,
         sorted_by=None,
         search_query=None,
         category=None,
@@ -160,7 +160,7 @@ def test_get_agents_by_creator(
     snapshot.assert_match(json.dumps(response.json(), indent=2), "agts_by_creator")
     mock_db_call.assert_called_once_with(
         featured=False,
-        creator="specific-creator",
+        creators=["specific-creator"],
         sorted_by=None,
         search_query=None,
         category=None,
@@ -207,7 +207,7 @@ def test_get_agents_sorted(
     snapshot.assert_match(json.dumps(response.json(), indent=2), "agts_sorted")
     mock_db_call.assert_called_once_with(
         featured=False,
-        creator=None,
+        creators=None,
         sorted_by="runs",
         search_query=None,
         category=None,
@@ -254,7 +254,7 @@ def test_get_agents_search(
     snapshot.assert_match(json.dumps(response.json(), indent=2), "agts_search")
     mock_db_call.assert_called_once_with(
         featured=False,
-        creator=None,
+        creators=None,
         sorted_by=None,
         search_query="specific",
         category=None,
@@ -300,7 +300,7 @@ def test_get_agents_category(
     snapshot.assert_match(json.dumps(response.json(), indent=2), "agts_category")
     mock_db_call.assert_called_once_with(
         featured=False,
-        creator=None,
+        creators=None,
         sorted_by=None,
         search_query=None,
         category="test-category",
@@ -349,7 +349,7 @@ def test_get_agents_pagination(
     snapshot.assert_match(json.dumps(response.json(), indent=2), "agts_pagination")
     mock_db_call.assert_called_once_with(
         featured=False,
-        creator=None,
+        creators=None,
         sorted_by=None,
         search_query=None,
         category=None,
@@ -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(

autogpt_platform/backend/backend/util/exceptions.py

@@ -40,6 +40,7 @@ class ModerationError(ValueError):
     message: str
     graph_exec_id: str
     moderation_type: str
+    content_id: str | None
 
     def __init__(
         self,
@@ -47,16 +48,20 @@ class ModerationError(ValueError):
         user_id: str,
         graph_exec_id: str,
         moderation_type: str = "content",
+        content_id: str | None = None,
     ):
         super().__init__(message)
-        self.args = (message, user_id, graph_exec_id, moderation_type)
+        self.args = (message, user_id, graph_exec_id, moderation_type, content_id)
         self.message = message
         self.user_id = user_id
         self.graph_exec_id = graph_exec_id
         self.moderation_type = moderation_type
+        self.content_id = content_id
 
     def __str__(self):
         """Used to display the error message in the frontend, because we str() the error when sending the execution update"""
+        if self.content_id:
+            return f"{self.message} (Moderation ID: {self.content_id})"
         return self.message
 
 

autogpt_platform/backend/backend/util/metrics.py

@@ -1,4 +1,5 @@
 import logging
+from enum import Enum
 
 import sentry_sdk
 from pydantic import SecretStr
@@ -10,6 +11,11 @@ from backend.util.settings import Settings
 settings = Settings()
 
 
+class DiscordChannel(str, Enum):
+    PLATFORM = "platform"  # For platform/system alerts
+    PRODUCT = "product"  # For product alerts (low balance, zero balance, etc.)
+
+
 def sentry_init():
     sentry_dsn = settings.secrets.sentry_dsn
     sentry_sdk.init(
@@ -32,8 +38,10 @@ def sentry_capture_error(error: Exception):
     sentry_sdk.flush()
 
 
-async def discord_send_alert(content: str):
-    from backend.blocks.discord import SendDiscordMessageBlock
+async def discord_send_alert(
+    content: str, channel: DiscordChannel = DiscordChannel.PLATFORM
+):
+    from backend.blocks.discord.bot_blocks import SendDiscordMessageBlock
     from backend.data.model import APIKeyCredentials, CredentialsMetaInput, ProviderName
 
     creds = APIKeyCredentials(
@@ -43,6 +51,14 @@ async def discord_send_alert(content: str):
         expires_at=None,
     )
 
+    # Select channel based on enum
+    if channel == DiscordChannel.PLATFORM:
+        channel_name = settings.config.platform_alert_discord_channel
+    elif channel == DiscordChannel.PRODUCT:
+        channel_name = settings.config.product_alert_discord_channel
+    else:
+        channel_name = settings.config.platform_alert_discord_channel
+
     return await SendDiscordMessageBlock().run_once(
         SendDiscordMessageBlock.Input(
             credentials=CredentialsMetaInput(
@@ -52,7 +68,7 @@ async def discord_send_alert(content: str):
                 provider=ProviderName.DISCORD,
             ),
             message_content=content,
-            channel_name=settings.config.platform_alert_discord_channel,
+            channel_name=channel_name,
         ),
         "status",
         credentials=creds,

autogpt_platform/backend/backend/util/models.py

@@ -0,0 +1,29 @@
+"""
+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]
+    )
+
+    @staticmethod
+    def empty() -> "Pagination":
+        return Pagination(
+            total_items=0,
+            total_pages=0,
+            current_page=0,
+            page_size=0,
+        )

autogpt_platform/backend/backend/util/process.py

@@ -48,10 +48,9 @@ class AppProcess(ABC):
         """
         pass
 
-    @classmethod
     @property
-    def service_name(cls) -> str:
-        return cls.__name__
+    def service_name(self) -> str:
+        return self.__class__.__name__
 
     @abstractmethod
     def cleanup(self):

autogpt_platform/backend/backend/util/service.py

@@ -97,11 +97,11 @@ class BaseAppService(AppProcess, ABC):
     @classmethod
     def get_host(cls) -> str:
         source_host = os.environ.get(f"{get_service_name().upper()}_HOST", api_host)
-        target_host = os.environ.get(f"{cls.service_name.upper()}_HOST", api_host)
+        target_host = os.environ.get(f"{cls.__name__.upper()}_HOST", api_host)
 
         if source_host == target_host and source_host != api_host:
             logger.warning(
-                f"Service {cls.service_name} is the same host as the source service."
+                f"Service {cls.__name__} is the same host as the source service."
                 f"Use the localhost of {api_host} instead."
             )
             return api_host

autogpt_platform/backend/backend/util/settings.py

@@ -95,6 +95,10 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         default=500,
         description="Maximum number of credits above the balance to be auto-approved.",
     )
+    low_balance_threshold: int = Field(
+        default=500,
+        description="Credit threshold for low balance notifications (100 = $1, default 500 = $5)",
+    )
     refund_notification_email: str = Field(
         default="refund@agpt.co",
         description="Email address to send refund notifications to.",
@@ -250,6 +254,10 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         default="local-alerts",
         description="The Discord channel for the platform",
     )
+    product_alert_discord_channel: str = Field(
+        default="product-alerts",
+        description="The Discord channel for product alerts (low balance, zero balance, etc.)",
+    )
 
     clamav_service_host: str = Field(
         default="localhost",
@@ -465,6 +473,10 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
     twitter_client_secret: str = Field(
         default="", description="Twitter/X OAuth client secret"
     )
+    discord_client_id: str = Field(default="", description="Discord OAuth client ID")
+    discord_client_secret: str = Field(
+        default="", description="Discord OAuth client secret"
+    )
 
     openai_api_key: str = Field(default="", description="OpenAI API key")
     aiml_api_key: str = Field(default="", description="'AI/ML API' key")

autogpt_platform/backend/backend/util/test.py

@@ -9,6 +9,7 @@ from backend.data.block import Block, BlockSchema, initialize_blocks
 from backend.data.execution import (
     ExecutionStatus,
     NodeExecutionResult,
+    UserContext,
     get_graph_execution,
 )
 from backend.data.model import _BaseCredentials
@@ -138,6 +139,7 @@ async def execute_block_test(block: Block):
         "graph_exec_id": str(uuid.uuid4()),
         "node_exec_id": str(uuid.uuid4()),
         "user_id": str(uuid.uuid4()),
+        "user_context": UserContext(timezone="UTC"),  # Default for tests
     }
     input_model = cast(type[BlockSchema], block.input_schema)
     credentials_input_fields = input_model.get_credentials_fields()

autogpt_platform/backend/backend/util/timezone_name.py

@@ -0,0 +1,115 @@
+"""
+Time zone name validation and serialization.
+
+This file is adapted from pydantic-extra-types:
+https://github.com/pydantic/pydantic-extra-types/blob/main/pydantic_extra_types/timezone_name.py
+
+The MIT License (MIT)
+
+Copyright (c) 2023 Samuel Colvin and other contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+
+Modifications:
+- Modified to always use pytz for timezone data to ensure consistency across environments
+- Removed zoneinfo support to prevent environment-specific timezone lists
+"""
+
+from __future__ import annotations
+
+from typing import Any, Callable, cast
+
+import pytz
+from pydantic import GetCoreSchemaHandler, GetJsonSchemaHandler
+from pydantic_core import PydanticCustomError, core_schema
+
+# Cache the timezones at module level to avoid repeated computation
+ALL_TIMEZONES: set[str] = set(pytz.all_timezones)
+
+
+def get_timezones() -> set[str]:
+    """Get timezones from pytz for consistency across all environments."""
+    # Return cached timezone set
+    return ALL_TIMEZONES
+
+
+class TimeZoneNameSettings(type):
+    def __new__(
+        cls, name: str, bases: tuple[type, ...], dct: dict[str, Any], **kwargs: Any
+    ) -> type[TimeZoneName]:
+        dct["strict"] = kwargs.pop("strict", True)
+        return cast("type[TimeZoneName]", super().__new__(cls, name, bases, dct))
+
+    def __init__(
+        cls, name: str, bases: tuple[type, ...], dct: dict[str, Any], **kwargs: Any
+    ) -> None:
+        super().__init__(name, bases, dct)
+        cls.strict = kwargs.get("strict", True)
+
+
+def timezone_name_settings(
+    **kwargs: Any,
+) -> Callable[[type[TimeZoneName]], type[TimeZoneName]]:
+    def wrapper(cls: type[TimeZoneName]) -> type[TimeZoneName]:
+        cls.strict = kwargs.get("strict", True)
+        return cls
+
+    return wrapper
+
+
+@timezone_name_settings(strict=True)
+class TimeZoneName(str):
+    """TimeZoneName is a custom string subclass for validating and serializing timezone names."""
+
+    __slots__: list[str] = []
+    allowed_values: set[str] = set(get_timezones())
+    allowed_values_list: list[str] = sorted(allowed_values)
+    allowed_values_upper_to_correct: dict[str, str] = {
+        val.upper(): val for val in allowed_values
+    }
+    strict: bool
+
+    @classmethod
+    def _validate(
+        cls, __input_value: str, _: core_schema.ValidationInfo
+    ) -> TimeZoneName:
+        if __input_value not in cls.allowed_values:
+            if not cls.strict:
+                upper_value = __input_value.strip().upper()
+                if upper_value in cls.allowed_values_upper_to_correct:
+                    return cls(cls.allowed_values_upper_to_correct[upper_value])
+            raise PydanticCustomError("TimeZoneName", "Invalid timezone name.")
+        return cls(__input_value)
+
+    @classmethod
+    def __get_pydantic_core_schema__(
+        cls, _: type[Any], __: GetCoreSchemaHandler
+    ) -> core_schema.AfterValidatorFunctionSchema:
+        return core_schema.with_info_after_validator_function(
+            cls._validate,
+            core_schema.str_schema(min_length=1),
+        )
+
+    @classmethod
+    def __get_pydantic_json_schema__(
+        cls, schema: core_schema.CoreSchema, handler: GetJsonSchemaHandler
+    ) -> dict[str, Any]:
+        json_schema = handler(schema)
+        json_schema.update({"enum": cls.allowed_values_list})
+        return json_schema

autogpt_platform/backend/backend/util/timezone_utils.py

@@ -0,0 +1,148 @@
+"""
+Timezone conversion utilities for API endpoints.
+Handles conversion between user timezones and UTC for scheduler operations.
+"""
+
+import logging
+from datetime import datetime
+from typing import Optional
+from zoneinfo import ZoneInfo
+
+from croniter import croniter
+
+logger = logging.getLogger(__name__)
+
+
+def convert_cron_to_utc(cron_expr: str, user_timezone: str) -> str:
+    """
+    Convert a cron expression from user timezone to UTC.
+
+    NOTE: This is a simplified conversion that only adjusts minute and hour fields.
+    Complex cron expressions with specific day/month/weekday patterns may not
+    convert accurately due to timezone offset variations throughout the year.
+
+    Args:
+        cron_expr: Cron expression in user timezone
+        user_timezone: User's IANA timezone identifier
+
+    Returns:
+        Cron expression adjusted for UTC execution
+
+    Raises:
+        ValueError: If timezone or cron expression is invalid
+    """
+    try:
+        user_tz = ZoneInfo(user_timezone)
+        utc_tz = ZoneInfo("UTC")
+
+        # Split the cron expression into its five fields
+        cron_fields = cron_expr.strip().split()
+        if len(cron_fields) != 5:
+            raise ValueError(
+                "Cron expression must have 5 fields (minute hour day month weekday)"
+            )
+
+        # Get the current time in the user's timezone
+        now_user = datetime.now(user_tz)
+
+        # Get the next scheduled time in user timezone
+        cron = croniter(cron_expr, now_user)
+        next_user_time = cron.get_next(datetime)
+
+        # Convert to UTC
+        next_utc_time = next_user_time.astimezone(utc_tz)
+
+        # Adjust minute and hour fields for UTC, keep day/month/weekday as in original
+        utc_cron_parts = [
+            str(next_utc_time.minute),
+            str(next_utc_time.hour),
+            cron_fields[2],  # day of month
+            cron_fields[3],  # month
+            cron_fields[4],  # day of week
+        ]
+
+        utc_cron = " ".join(utc_cron_parts)
+
+        logger.debug(
+            f"Converted cron '{cron_expr}' from {user_timezone} to UTC: '{utc_cron}'"
+        )
+        return utc_cron
+
+    except Exception as e:
+        logger.error(
+            f"Failed to convert cron expression '{cron_expr}' from {user_timezone} to UTC: {e}"
+        )
+        raise ValueError(f"Invalid cron expression or timezone: {e}")
+
+
+def convert_utc_time_to_user_timezone(utc_time_str: str, user_timezone: str) -> str:
+    """
+    Convert a UTC datetime string to user timezone.
+
+    Args:
+        utc_time_str: ISO format datetime string in UTC
+        user_timezone: User's IANA timezone identifier
+
+    Returns:
+        ISO format datetime string in user timezone
+    """
+    try:
+        # Parse the time string
+        parsed_time = datetime.fromisoformat(utc_time_str.replace("Z", "+00:00"))
+
+        user_tz = ZoneInfo(user_timezone)
+
+        # If the time already has timezone info, convert it to user timezone
+        if parsed_time.tzinfo is not None:
+            # Convert to user timezone regardless of source timezone
+            user_time = parsed_time.astimezone(user_tz)
+            return user_time.isoformat()
+
+        # If no timezone info, treat as UTC and convert to user timezone
+        parsed_time = parsed_time.replace(tzinfo=ZoneInfo("UTC"))
+        user_time = parsed_time.astimezone(user_tz)
+        return user_time.isoformat()
+
+    except Exception as e:
+        logger.error(
+            f"Failed to convert UTC time '{utc_time_str}' to {user_timezone}: {e}"
+        )
+        # Return original time if conversion fails
+        return utc_time_str
+
+
+def validate_timezone(timezone: str) -> bool:
+    """
+    Validate if a timezone string is a valid IANA timezone identifier.
+
+    Args:
+        timezone: Timezone string to validate
+
+    Returns:
+        True if valid, False otherwise
+    """
+    try:
+        ZoneInfo(timezone)
+        return True
+    except Exception:
+        return False
+
+
+def get_user_timezone_or_utc(user_timezone: Optional[str]) -> str:
+    """
+    Get user timezone or default to UTC if invalid/missing.
+
+    Args:
+        user_timezone: User's timezone preference
+
+    Returns:
+        Valid timezone string (user's preference or UTC fallback)
+    """
+    if not user_timezone or user_timezone == "not-set":
+        return "UTC"
+
+    if validate_timezone(user_timezone):
+        return user_timezone
+
+    logger.warning(f"Invalid user timezone '{user_timezone}', falling back to UTC")
+    return "UTC"

autogpt_platform/backend/migrations/20250805111135_add_video_url_and_categories_to_store_submission_view/migration.sql

@@ -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; 

autogpt_platform/backend/migrations/20250819163527_add_user_timezone/migration.sql

@@ -0,0 +1,3 @@
+-- AlterTable
+ALTER TABLE "User" ADD COLUMN     "timezone" TEXT NOT NULL DEFAULT 'not-set' 
+    CHECK (timezone = 'not-set' OR now() AT TIME ZONE timezone IS NOT NULL);

autogpt_platform/backend/migrations/20250824000317_add_notifications_for_approved_and_denied_agents/migration.sql

@@ -0,0 +1,14 @@
+-- AlterEnum
+-- This migration adds more than one value to an enum.
+-- With PostgreSQL versions 11 and earlier, this is not possible
+-- in a single migration. This can be worked around by creating
+-- multiple migrations, each migration adding only one value to
+-- the enum.
+
+
+ALTER TYPE "NotificationType" ADD VALUE 'AGENT_APPROVED';
+ALTER TYPE "NotificationType" ADD VALUE 'AGENT_REJECTED';
+
+-- AlterTable
+ALTER TABLE "User" ADD COLUMN     "notifyOnAgentApproved" BOOLEAN NOT NULL DEFAULT true,
+ADD COLUMN     "notifyOnAgentRejected" BOOLEAN NOT NULL DEFAULT true;

autogpt_platform/backend/poetry.lock

@@ -331,6 +331,66 @@ docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphi
 tests = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
 tests-mypy = ["mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\""]
 
+[[package]]
+name = "audioop-lts"
+version = "0.2.2"
+description = "LTS Port of Python audioop"
+optional = false
+python-versions = ">=3.13"
+groups = ["main"]
+markers = "python_version >= \"3.13\""
+files = [
+    {file = "audioop_lts-0.2.2-cp313-abi3-macosx_10_13_universal2.whl", hash = "sha256:fd3d4602dc64914d462924a08c1a9816435a2155d74f325853c1f1ac3b2d9800"},
+    {file = "audioop_lts-0.2.2-cp313-abi3-macosx_10_13_x86_64.whl", hash = "sha256:550c114a8df0aafe9a05442a1162dfc8fec37e9af1d625ae6060fed6e756f303"},
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+    {file = "audioop_lts-0.2.2-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:5b00be98ccd0fc123dcfad31d50030d25fcf31488cde9e61692029cd7394733b"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:a6d2e0f9f7a69403e388894d4ca5ada5c47230716a03f2847cfc7bd1ecb589d6"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f9b0b8a03ef474f56d1a842af1a2e01398b8f7654009823c6d9e0ecff4d5cfbf"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2b267b70747d82125f1a021506565bdc5609a2b24bcb4773c16d79d2bb260bbd"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0337d658f9b81f4cd0fdb1f47635070cc084871a3d4646d9de74fdf4e7c3d24a"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:167d3b62586faef8b6b2275c3218796b12621a60e43f7e9d5845d627b9c9b80e"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:0d9385e96f9f6da847f4d571ce3cb15b5091140edf3db97276872647ce37efd7"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:48159d96962674eccdca9a3df280e864e8ac75e40a577cc97c5c42667ffabfc5"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:8fefe5868cd082db1186f2837d64cfbfa78b548ea0d0543e9b28935ccce81ce9"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:58cf54380c3884fb49fdd37dfb7a772632b6701d28edd3e2904743c5e1773602"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:088327f00488cdeed296edd9215ca159f3a5a5034741465789cad403fcf4bec0"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-win32.whl", hash = "sha256:068aa17a38b4e0e7de771c62c60bbca2455924b67a8814f3b0dee92b5820c0b3"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-win_amd64.whl", hash = "sha256:a5bf613e96f49712073de86f20dbdd4014ca18efd4d34ed18c75bd808337851b"},
+    {file = "audioop_lts-0.2.2-cp314-cp314t-win_arm64.whl", hash = "sha256:b492c3b040153e68b9fdaff5913305aaaba5bb433d8a7f73d5cf6a64ed3cc1dd"},
+    {file = "audioop_lts-0.2.2.tar.gz", hash = "sha256:64d0c62d88e67b98a1a5e71987b7aa7b5bcffc7dcee65b635823dbdd0a8dbbd0"},
+]
+
 [[package]]
 name = "autogpt-libs"
 version = "0.2.0"
@@ -802,6 +862,22 @@ files = [
     {file = "crashtest-0.4.1.tar.gz", hash = "sha256:80d7b1f316ebfbd429f648076d6275c877ba30ba48979de4191714a75266f0ce"},
 ]
 
+[[package]]
+name = "croniter"
+version = "6.0.0"
+description = "croniter provides iteration for datetime object with cron like format"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.6"
+groups = ["main"]
+files = [
+    {file = "croniter-6.0.0-py2.py3-none-any.whl", hash = "sha256:2f878c3856f17896979b2a4379ba1f09c83e374931ea15cc835c5dd2eee9b368"},
+    {file = "croniter-6.0.0.tar.gz", hash = "sha256:37c504b313956114a983ece2c2b07790b1f1094fe9d81cc94739214748255577"},
+]
+
+[package.dependencies]
+python-dateutil = "*"
+pytz = ">2021.1"
+
 [[package]]
 name = "cryptography"
 version = "43.0.3"
@@ -905,6 +981,7 @@ files = [
 
 [package.dependencies]
 aiohttp = ">=3.7.4,<4"
+audioop-lts = {version = "*", markers = "python_version >= \"3.13\""}
 
 [package.extras]
 dev = ["black (==22.6)", "typing_extensions (>=4.3,<5)"]
@@ -1442,7 +1519,10 @@ grpcio-status = [
     {version = ">=1.33.2,<2.0.0", optional = true, markers = "extra == \"grpc\""},
     {version = ">=1.49.1,<2.0.0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
 ]
-proto-plus = ">=1.22.3,<2.0.0"
+proto-plus = [
+    {version = ">=1.22.3,<2.0.0"},
+    {version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
+]
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 requests = ">=2.18.0,<3.0.0"
 
@@ -1548,7 +1628,10 @@ files = [
 [package.dependencies]
 google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.11.dev0,<3.0.0", extras = ["grpc"]}
 google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0"
-proto-plus = ">=1.22.3,<2.0.0"
+proto-plus = [
+    {version = ">=1.22.3,<2.0.0"},
+    {version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
+]
 protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 
 [[package]]
@@ -1609,6 +1692,7 @@ opentelemetry-api = ">=1.9.0"
 proto-plus = [
     {version = ">=1.22.0,<2.0.0"},
     {version = ">=1.22.2,<2.0.0", markers = "python_version >= \"3.11\""},
+    {version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
 ]
 protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 
@@ -4769,6 +4853,7 @@ grpcio = ">=1.41.0"
 httpx = {version = ">=0.20.0", extras = ["http2"]}
 numpy = [
     {version = ">=1.21", markers = "python_version >= \"3.10\" and python_version < \"3.12\""},
+    {version = ">=2.1.0", markers = "python_version >= \"3.13\""},
     {version = ">=1.26", markers = "python_version == \"3.12\""},
 ]
 portalocker = ">=2.7.0,<3.0.0"
@@ -6736,5 +6821,5 @@ cffi = ["cffi (>=1.11)"]
 
 [metadata]
 lock-version = "2.1"
-python-versions = ">=3.10,<3.13"
-content-hash = "795414d7ce8f288ea6c65893268b5c29a7c9a60ad75cde28ac7bcdb65f426dfe"
+python-versions = ">=3.10,<3.14"
+content-hash = "e780199a6b02f5fef3f930a4f1d69443af1977b591172c3a18a299166345c37a"

autogpt_platform/backend/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "autogpt-platform-backend"
-version = "0.4.9"
+version = "0.6.22"
 description = "A platform for building AI-powered agentic workflows"
 authors = ["AutoGPT <info@agpt.co>"]
 readme = "README.md"
@@ -8,7 +8,7 @@ packages = [{ include = "backend", format = "sdist" }]
 
 
 [tool.poetry.dependencies]
-python = ">=3.10,<3.13"
+python = ">=3.10,<3.14"
 aio-pika = "^9.5.5"
 aiohttp = "^3.10.0"
 aiodns = "^3.5.0"
@@ -77,6 +77,7 @@ gcloud-aio-storage = "^9.5.0"
 pandas = "^2.3.1"
 firecrawl-py = "^2.16.3"
 exa-py = "^1.14.20"
+croniter = "^6.0.0"
 
 [tool.poetry.group.dev.dependencies]
 aiohappyeyeballs = "^2.6.1"

autogpt_platform/backend/schema.prisma

@@ -33,6 +33,10 @@ model User {
   notifyOnDailySummary         Boolean @default(true)
   notifyOnWeeklySummary        Boolean @default(true)
   notifyOnMonthlySummary       Boolean @default(true)
+  notifyOnAgentApproved        Boolean @default(true)
+  notifyOnAgentRejected        Boolean @default(true)
+
+  timezone                     String  @default("not-set")
 
   // Relations
 
@@ -187,6 +191,8 @@ enum NotificationType {
   MONTHLY_SUMMARY
   REFUND_REQUEST
   REFUND_PROCESSED
+  AGENT_APPROVED
+  AGENT_REJECTED
 }
 
 model NotificationEvent {
@@ -659,6 +665,8 @@ view StoreSubmission {
   internal_comments        String?
   reviewed_at              DateTime?
   changes_summary          String?
+  video_url                String?
+  categories               String[]
 
   // Index or unique are not applied to views
 }

autogpt_platform/backend/snapshots/lib_agts_search

@@ -15,6 +15,10 @@
         "type": "object",
         "properties": {}
       },
+      "output_schema": {
+        "type": "object",
+        "properties": {}
+      },
       "credentials_input_schema": {
         "type": "object",
         "properties": {}
@@ -40,6 +44,10 @@
         "type": "object",
         "properties": {}
       },
+      "output_schema": {
+        "type": "object",
+        "properties": {}
+      },
       "credentials_input_schema": {
         "type": "object",
         "properties": {}

autogpt_platform/backend/snapshots/sub_success

@@ -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": {

autogpt_platform/backend/test/e2e_test_data.py

@@ -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:

autogpt_platform/frontend/orval.config.ts

@@ -27,6 +27,7 @@ export default defineConfig({
           usePrefetch: true,
           // Will add more as their use cases arise
         },
+        useDates: true,
         operations: {
           "getV2List library agents": {
             query: {
@@ -34,6 +35,12 @@ export default defineConfig({
               useInfiniteQueryParam: "page",
             },
           },
+          "getV1List graph executions": {
+            query: {
+              useInfinite: true,
+              useInfiniteQueryParam: "page",
+            },
+          },
         },
       },
     },

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/OldAgentLibraryView.tsx

@@ -41,6 +41,7 @@ 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 { useAgentRunsInfinite } from "../use-agent-runs";
 import { AgentRunsSelectorList } from "./components/agent-runs-selector-list";
 import { AgentScheduleDetailsView } from "./components/agent-schedule-details-view";
 
@@ -55,7 +56,8 @@ export function OldAgentLibraryView() {
 
   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 agentRunsQuery = useAgentRunsInfinite(graph?.id); // only runs once graph.id is known
+  const agentRuns = agentRunsQuery.agentRuns;
   const [agentPresets, setAgentPresets] = useState<LibraryAgentPreset[]>([]);
   const [schedules, setSchedules] = useState<Schedule[]>([]);
   const [selectedView, selectView] = useState<
@@ -156,19 +158,22 @@ export function OldAgentLibraryView() {
           (graph && graph.version == _graph.version) || setGraph(_graph),
       );
       Promise.all([
-        api.getGraphExecutions(agent.graph_id),
+        agentRunsQuery.refetchRuns(),
         api.listLibraryAgentPresets({
           graph_id: agent.graph_id,
           page_size: 100,
         }),
-      ]).then(([runs, presets]) => {
-        setAgentRuns(runs);
+      ]).then(([runsQueryResult, presets]) => {
         setAgentPresets(presets.presets);
 
+        const newestAgentRunsResponse = runsQueryResult.data?.pages[0];
+        if (!newestAgentRunsResponse || newestAgentRunsResponse.status != 200)
+          return;
+        const newestAgentRuns = newestAgentRunsResponse.data.executions;
         // 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),
-        );
+        new Set(
+          newestAgentRuns.slice(0, 10).map((run) => run.graph_version),
+        ).forEach((version) => getGraphVersion(agent.graph_id, version));
       });
     });
   }, [api, agentID, getGraphVersion, graph]);
@@ -187,7 +192,7 @@ export function OldAgentLibraryView() {
         else if (!latest.started_at) return latest;
         return latest.started_at > current.started_at ? latest : current;
       }, agentRuns[0]);
-      selectRun(latestRun.id);
+      selectRun(latestRun.id as GraphExecutionID);
     } else {
       // select top preset
       const latestPreset = agentPresets.toSorted(
@@ -277,18 +282,7 @@ export function OldAgentLibraryView() {
           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 }));
-        }
+        agentRunsQuery.upsertAgentRun(data);
       },
     );
 
@@ -344,7 +338,7 @@ export function OldAgentLibraryView() {
       if (selectedView.type == "run" && selectedView.id == run.id) {
         openRunDraftView();
       }
-      setAgentRuns((runs) => runs.filter((r) => r.id !== run.id));
+      agentRunsQuery.removeAgentRun(run.id);
     },
     [api, selectedView, openRunDraftView],
   );
@@ -481,9 +475,9 @@ export function OldAgentLibraryView() {
       {/* 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"
+        className="agpt-div w-full border-b pb-2 lg:w-auto lg:border-b-0 lg:border-r lg:pb-0"
         agent={agent}
-        agentRuns={agentRuns}
+        agentRunsQuery={agentRunsQuery}
         agentPresets={agentPresets}
         schedules={schedules}
         selectedView={selectedView}

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

@@ -14,16 +14,19 @@ import {
 import { cn } from "@/lib/utils";
 
 import { Badge } from "@/components/ui/badge";
-import { ScrollArea } from "@/components/ui/scroll-area";
+import { Button } from "@/components/atoms/Button/Button";
+import LoadingBox from "@/components/ui/loading";
+import { InfiniteScroll } from "@/components/contextual/InfiniteScroll/InfiniteScroll";
 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 "../../../../../../../../components/atoms/Button/Button";
+import { AgentRunsQuery } from "../../use-agent-runs";
+import { ScrollArea } from "@/components/ui/scroll-area";
 
 interface AgentRunsSelectorListProps {
   agent: LibraryAgent;
-  agentRuns: GraphExecutionMeta[];
+  agentRunsQuery: AgentRunsQuery;
   agentPresets: LibraryAgentPreset[];
   schedules: Schedule[];
   selectedView: { type: "run" | "preset" | "schedule"; id?: string };
@@ -40,7 +43,13 @@ interface AgentRunsSelectorListProps {
 
 export function AgentRunsSelectorList({
   agent,
-  agentRuns,
+  agentRunsQuery: {
+    agentRuns,
+    agentRunsLoading,
+    hasMoreRuns,
+    fetchMoreRuns,
+    isFetchingMoreRuns,
+  },
   agentPresets,
   schedules,
   selectedView,
@@ -66,7 +75,7 @@ export function AgentRunsSelectorList({
     }
   }, [selectedView]);
 
-  const listItemClasses = "h-28 w-72 lg:h-32 xl:w-80";
+  const listItemClasses = "h-28 w-72 lg:w-full lg:h-32";
 
   return (
     <aside className={cn("flex flex-col gap-4", className)}>
@@ -101,84 +110,99 @@ export function AgentRunsSelectorList({
       </div>
 
       {/* Runs / Schedules list */}
-      <ScrollArea className="lg:h-[calc(100vh-200px)]">
-        <div className="flex gap-2 lg:flex-col">
-          {/* New Run button - only in small layouts */}
-          {allowDraftNewRun && (
-            <Button
-              size="large"
-              className={
-                "flex h-28 w-40 items-center gap-2 py-6 lg:hidden " +
-                (selectedView.type == "run" && !selectedView.id
-                  ? "agpt-card-selected text-accent"
-                  : "")
-              }
-              onClick={onSelectDraftNewRun}
-              leftIcon={<Plus className="h-6 w-6" />}
-            >
-              New {agent.has_external_trigger ? "trigger" : "run"}
-            </Button>
-          )}
+      {agentRunsLoading && activeListTab === "runs" ? (
+        <LoadingBox className="h-28 w-full lg:h-[calc(100vh-300px)] lg:w-72 xl:w-80" />
+      ) : (
+        <ScrollArea
+          className="w-full lg:h-[calc(100vh-300px)] lg:w-72 xl:w-80"
+          orientation={window.innerWidth >= 1024 ? "vertical" : "horizontal"}
+        >
+          <InfiniteScroll
+            direction={window.innerWidth >= 1024 ? "vertical" : "horizontal"}
+            hasNextPage={hasMoreRuns}
+            fetchNextPage={fetchMoreRuns}
+            isFetchingNextPage={isFetchingMoreRuns}
+          >
+            <div className="flex items-center gap-2 lg:flex-col">
+              {/* New Run button - only in small layouts */}
+              {allowDraftNewRun && (
+                <Button
+                  size="large"
+                  className={
+                    "flex h-12 w-40 items-center gap-2 py-6 lg:hidden " +
+                    (selectedView.type == "run" && !selectedView.id
+                      ? "agpt-card-selected text-accent"
+                      : "")
+                  }
+                  onClick={onSelectDraftNewRun}
+                  leftIcon={<Plus className="h-6 w-6" />}
+                >
+                  New {agent.has_external_trigger ? "trigger" : "run"}
+                </Button>
+              )}
 
-          {activeListTab === "runs" ? (
-            <>
-              {agentPresets
-                .toSorted(
-                  (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
-                )
-                .map((preset) => (
-                  <AgentRunSummaryCard
-                    className={cn(listItemClasses, "lg:h-auto")}
-                    key={preset.id}
-                    type="preset"
-                    status={preset.is_active ? "active" : "inactive"}
-                    title={preset.name}
-                    // timestamp={preset.last_run_time} // TODO: implement this
-                    selected={selectedView.id === preset.id}
-                    onClick={() => onSelectPreset(preset.id)}
-                    onDelete={() => doDeletePreset(preset.id)}
-                  />
-                ))}
-              {agentPresets.length > 0 && <Separator className="my-1" />}
-              {agentRuns
-                .toSorted(
-                  (a, b) => b.started_at.getTime() - a.started_at.getTime(),
-                )
-                .map((run) => (
+              {activeListTab === "runs" ? (
+                <>
+                  {agentPresets
+                    .toSorted(
+                      (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
+                    )
+                    .map((preset) => (
+                      <AgentRunSummaryCard
+                        className={cn(listItemClasses, "lg:h-auto")}
+                        key={preset.id}
+                        type="preset"
+                        status={preset.is_active ? "active" : "inactive"}
+                        title={preset.name}
+                        // timestamp={preset.last_run_time} // TODO: implement this
+                        selected={selectedView.id === preset.id}
+                        onClick={() => onSelectPreset(preset.id)}
+                        onDelete={() => doDeletePreset(preset.id)}
+                      />
+                    ))}
+                  {agentPresets.length > 0 && <Separator className="my-1" />}
+                  {agentRuns
+                    .toSorted(
+                      (a, b) => b.started_at.getTime() - a.started_at.getTime(),
+                    )
+                    .map((run) => (
+                      <AgentRunSummaryCard
+                        className={listItemClasses}
+                        key={run.id}
+                        type="run"
+                        status={agentRunStatusMap[run.status]}
+                        title={
+                          (run.preset_id
+                            ? agentPresets.find((p) => p.id == run.preset_id)
+                                ?.name
+                            : null) ?? agent.name
+                        }
+                        timestamp={run.started_at}
+                        selected={selectedView.id === run.id}
+                        onClick={() => onSelectRun(run.id)}
+                        onDelete={() => doDeleteRun(run)}
+                      />
+                    ))}
+                </>
+              ) : (
+                schedules.map((schedule) => (
                   <AgentRunSummaryCard
                     className={listItemClasses}
-                    key={run.id}
-                    type="run"
-                    status={agentRunStatusMap[run.status]}
-                    title={
-                      (run.preset_id
-                        ? agentPresets.find((p) => p.id == run.preset_id)?.name
-                        : null) ?? agent.name
-                    }
-                    timestamp={run.started_at}
-                    selected={selectedView.id === run.id}
-                    onClick={() => onSelectRun(run.id)}
-                    onDelete={() => doDeleteRun(run)}
+                    key={schedule.id}
+                    type="schedule"
+                    status="scheduled" // TODO: implement active/inactive status for schedules
+                    title={schedule.name}
+                    timestamp={schedule.next_run_time}
+                    selected={selectedView.id === schedule.id}
+                    onClick={() => onSelectSchedule(schedule.id)}
+                    onDelete={() => doDeleteSchedule(schedule.id)}
                   />
-                ))}
-            </>
-          ) : (
-            schedules.map((schedule) => (
-              <AgentRunSummaryCard
-                className={listItemClasses}
-                key={schedule.id}
-                type="schedule"
-                status="scheduled" // TODO: implement active/inactive status for schedules
-                title={schedule.name}
-                timestamp={schedule.next_run_time}
-                selected={selectedView.id === schedule.id}
-                onClick={() => onSelectSchedule(schedule.id)}
-                onDelete={() => doDeleteSchedule(schedule.id)}
-              />
-            ))
-          )}
-        </div>
-      </ScrollArea>
+                ))
+              )}
+            </div>
+          </InfiniteScroll>
+        </ScrollArea>
+      )}
     </aside>
   );
 }

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

@@ -18,6 +18,8 @@ import { Input } from "@/components/ui/input";
 import LoadingBox from "@/components/ui/loading";
 import { useToastOnFail } from "@/components/molecules/Toast/use-toast";
 import { humanizeCronExpression } from "@/lib/cron-expression-utils";
+import { formatScheduleTime } from "@/lib/timezone-utils";
+import { useGetV1GetUserTimezone } from "@/app/api/__generated__/endpoints/auth/auth";
 import { PlayIcon } from "lucide-react";
 
 export function AgentScheduleDetailsView({
@@ -39,6 +41,10 @@ export function AgentScheduleDetailsView({
 
   const toastOnFail = useToastOnFail();
 
+  // Get user's timezone for displaying schedule times
+  const { data: timezoneData } = useGetV1GetUserTimezone();
+  const userTimezone = timezoneData?.data?.timezone || "UTC";
+
   const infoStats: { label: string; value: React.ReactNode }[] = useMemo(() => {
     return [
       {
@@ -49,14 +55,14 @@ export function AgentScheduleDetailsView({
       },
       {
         label: "Schedule",
-        value: humanizeCronExpression(schedule.cron),
+        value: humanizeCronExpression(schedule.cron, userTimezone),
       },
       {
         label: "Next run",
-        value: schedule.next_run_time.toLocaleString(),
+        value: formatScheduleTime(schedule.next_run_time, userTimezone),
       },
     ];
-  }, [schedule, selectedRunStatus]);
+  }, [schedule, selectedRunStatus, userTimezone]);
 
   const agentRunInputs: Record<
     string,

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/use-agent-runs.ts

@@ -0,0 +1,201 @@
+import {
+  getV1ListGraphExecutionsResponse,
+  useGetV1ListGraphExecutionsInfinite,
+} from "@/app/api/__generated__/endpoints/graphs/graphs";
+import { GraphExecutionsPaginated } from "@/app/api/__generated__/models/graphExecutionsPaginated";
+import { getQueryClient } from "@/lib/react-query/queryClient";
+import {
+  GraphExecutionMeta as LegacyGraphExecutionMeta,
+  GraphID,
+  GraphExecutionID,
+} from "@/lib/autogpt-server-api";
+import { GraphExecutionMeta as RawGraphExecutionMeta } from "@/app/api/__generated__/models/graphExecutionMeta";
+
+export type GraphExecutionMeta = Omit<
+  RawGraphExecutionMeta,
+  "id" | "user_id" | "graph_id" | "preset_id" | "stats"
+> &
+  Pick<
+    LegacyGraphExecutionMeta,
+    "id" | "user_id" | "graph_id" | "preset_id" | "stats"
+  >;
+
+/** Hook to fetch runs for a specific graph, with support for infinite scroll.
+ *
+ * @param graphID - The ID of the graph to fetch agent runs for. This parameter is
+ *                  optional in the sense that the hook doesn't run unless it is passed.
+ *                  This way, it can be used in components where the graph ID is not
+ *                  immediately available.
+ */
+export const useAgentRunsInfinite = (graphID?: GraphID) => {
+  const queryClient = getQueryClient();
+  const {
+    data: queryResults,
+    refetch: refetchRuns,
+    isPending: agentRunsLoading,
+    isRefetching: agentRunsReloading,
+    hasNextPage: hasMoreRuns,
+    fetchNextPage: fetchMoreRuns,
+    isFetchingNextPage: isFetchingMoreRuns,
+    queryKey,
+  } = useGetV1ListGraphExecutionsInfinite(
+    graphID!,
+    { page: 1, page_size: 20 },
+    {
+      query: {
+        getNextPageParam: (lastPage) => {
+          const pagination = (lastPage.data as GraphExecutionsPaginated)
+            .pagination;
+          const hasMore =
+            pagination.current_page * pagination.page_size <
+            pagination.total_items;
+
+          return hasMore ? pagination.current_page + 1 : undefined;
+        },
+
+        // Prevent query from running if graphID is not available (yet)
+        ...(!graphID
+          ? {
+              enabled: false,
+              queryFn: () =>
+                // Fake empty response if graphID is not available (yet)
+                Promise.resolve({
+                  status: 200,
+                  data: {
+                    executions: [],
+                    pagination: {
+                      current_page: 1,
+                      page_size: 20,
+                      total_items: 0,
+                      total_pages: 0,
+                    },
+                  },
+                  headers: new Headers(),
+                } satisfies getV1ListGraphExecutionsResponse),
+            }
+          : {}),
+      },
+    },
+    queryClient,
+  );
+
+  const agentRuns =
+    queryResults?.pages.flatMap((page) => {
+      const response = page.data as GraphExecutionsPaginated;
+      return response.executions;
+    }) ?? [];
+
+  const agentRunCount = queryResults?.pages[-1]
+    ? (queryResults.pages[-1].data as GraphExecutionsPaginated).pagination
+        .total_items
+    : 0;
+
+  const upsertAgentRun = (newAgentRun: GraphExecutionMeta) => {
+    queryClient.setQueryData(
+      [queryKey, { page: 1, page_size: 20 }],
+      (currentQueryData: typeof queryResults) => {
+        if (!currentQueryData?.pages) return currentQueryData;
+
+        const exists = currentQueryData.pages.some((page) => {
+          const response = page.data as GraphExecutionsPaginated;
+          return response.executions.some((run) => run.id === newAgentRun.id);
+        });
+        if (exists) {
+          // If the run already exists, we update it
+          return {
+            ...currentQueryData,
+            pages: currentQueryData.pages.map((page) => {
+              const response = page.data as GraphExecutionsPaginated;
+              const executions = response.executions;
+
+              const index = executions.findIndex(
+                (run) => run.id === newAgentRun.id,
+              );
+              if (index === -1) return page;
+
+              const newExecutions = [...executions];
+              newExecutions[index] = newAgentRun;
+
+              return {
+                ...page,
+                data: {
+                  ...response,
+                  executions: newExecutions,
+                },
+              };
+            }),
+          };
+        }
+
+        // If the run does not exist, we add it to the first page
+        const page = currentQueryData.pages[0];
+        const updatedExecutions = [
+          newAgentRun,
+          ...(page.data as GraphExecutionsPaginated).executions,
+        ];
+        const updatedPage = {
+          ...page,
+          data: {
+            ...page.data,
+            executions: updatedExecutions,
+          },
+        };
+        const updatedPages = [updatedPage, ...currentQueryData.pages.slice(1)];
+        return {
+          ...currentQueryData,
+          pages: updatedPages,
+        };
+      },
+    );
+  };
+
+  const removeAgentRun = (runID: GraphExecutionID) => {
+    queryClient.setQueryData(
+      [queryKey, { page: 1, page_size: 20 }],
+      (currentQueryData: typeof queryResults) => {
+        if (!currentQueryData?.pages) return currentQueryData;
+
+        let found = false;
+        return {
+          ...currentQueryData,
+          pages: currentQueryData.pages.map((page) => {
+            const response = page.data as GraphExecutionsPaginated;
+            const filteredExecutions = response.executions.filter(
+              (run) => run.id !== runID,
+            );
+            if (filteredExecutions.length < response.executions.length) {
+              found = true;
+            }
+
+            return {
+              ...page,
+              data: {
+                ...response,
+                executions: filteredExecutions,
+                pagination: {
+                  ...response.pagination,
+                  total_items:
+                    response.pagination.total_items - (found ? 1 : 0),
+                },
+              },
+            };
+          }),
+        };
+      },
+    );
+  };
+
+  return {
+    agentRuns: agentRuns as GraphExecutionMeta[],
+    refetchRuns,
+    agentRunCount,
+    agentRunsLoading: agentRunsLoading || agentRunsReloading,
+    hasMoreRuns,
+    fetchMoreRuns,
+    isFetchingMoreRuns,
+    upsertAgentRun,
+    removeAgentRun,
+  };
+};
+
+export type AgentRunsQuery = ReturnType<typeof useAgentRunsInfinite>;

autogpt_platform/frontend/src/app/(platform)/library/components/LibraryAgentList/LibraryAgentList.tsx

@@ -28,7 +28,6 @@ export default function LibraryAgentList() {
           </div>
         ) : (
           <InfiniteScroll
-            dataLength={agents.length}
             isFetchingNextPage={isFetchingNextPage}
             fetchNextPage={fetchNextPage}
             hasNextPage={hasNextPage}

autogpt_platform/frontend/src/app/(platform)/library/components/LibraryUploadAgentDialog/LibraryUploadAgentDialog.tsx

@@ -45,6 +45,7 @@ export default function LibraryUploadAgentDialog(): React.ReactNode {
     form,
     setisDroped,
     agentObject,
+    clearAgentFile,
   } = useLibraryUploadAgentDialog();
   return (
     <Dialog open={isOpen} onOpenChange={setIsOpen}>
@@ -105,9 +106,7 @@ export default function LibraryUploadAgentDialog(): React.ReactNode {
                       <div className="relative flex rounded-[10px] border p-2 font-sans text-sm font-medium text-[#525252] outline-none">
                         <span className="line-clamp-1">{field.value.name}</span>
                         <Button
-                          onClick={() =>
-                            form.setValue("agentFile", undefined as any)
-                          }
+                          onClick={clearAgentFile}
                           className="absolute left-[-10px] top-[-16px] mt-2 h-fit border-none bg-red-200 p-1"
                         >
                           <X

autogpt_platform/frontend/src/app/(platform)/library/components/LibraryUploadAgentDialog/useLibraryUploadAgentDialog.ts

@@ -102,6 +102,22 @@ export const useLibraryUploadAgentDialog = () => {
     setisDroped(false);
   };
 
+  const clearAgentFile = () => {
+    const currentName = form.getValues("agentName");
+    const currentDescription = form.getValues("agentDescription");
+    const prevAgent = agentObject;
+
+    form.setValue("agentFile", undefined as any);
+    if (prevAgent && currentName === prevAgent.name) {
+      form.setValue("agentName", "");
+    }
+    if (prevAgent && currentDescription === prevAgent.description) {
+      form.setValue("agentDescription", "");
+    }
+
+    setAgentObject(null);
+  };
+
   return {
     onSubmit,
     isUploading,
@@ -112,5 +128,6 @@ export const useLibraryUploadAgentDialog = () => {
     isDroped,
     handleChange,
     setisDroped,
+    clearAgentFile,
   };
 };

autogpt_platform/frontend/src/app/(platform)/library/page.tsx

@@ -1,11 +1,4 @@
 "use client";
-import Link from "next/link";
-
-import { Alert, AlertDescription } from "@/components/ui/alert";
-import {
-  ArrowBottomRightIcon,
-  QuestionMarkCircledIcon,
-} from "@radix-ui/react-icons";
 
 import LibraryActionHeader from "./components/LibraryActionHeader/LibraryActionHeader";
 import LibraryAgentList from "./components/LibraryAgentList/LibraryAgentList";
@@ -22,21 +15,6 @@ export default function LibraryPage() {
         <LibraryActionHeader />
         <LibraryAgentList />
       </LibraryPageStateProvider>
-
-      <Alert
-        variant="default"
-        className="fixed bottom-2 left-1/2 hidden max-w-4xl -translate-x-1/2 md:block"
-      >
-        <AlertDescription className="text-center">
-          Prefer the old experience? Click{" "}
-          <Link href="/monitoring" className="underline">
-            here
-          </Link>{" "}
-          to go to it. Please do let us know why by clicking the{" "}
-          <QuestionMarkCircledIcon className="inline-block size-6 rounded-full bg-[rgba(65,65,64,1)] p-1 align-bottom text-neutral-50" />{" "}
-          in the bottom right corner <ArrowBottomRightIcon className="inline" />
-        </AlertDescription>
-      </Alert>
     </main>
   );
 }

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

@@ -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>

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

@@ -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

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

@@ -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;
@@ -13,8 +13,8 @@ export interface AgentTableCardProps {
   sub_heading: string;
   description: string;
   imageSrc: string[];
-  dateSubmitted: string;
-  status: StatusType;
+  dateSubmitted: Date;
+  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,
     });
@@ -81,7 +80,7 @@ export const AgentTableCard = ({
       <div className="mt-4 flex flex-wrap gap-4">
         <Status status={status} />
         <div className="text-sm text-neutral-600 dark:text-neutral-400">
-          {dateSubmitted}
+          {dateSubmitted.toLocaleDateString()}
         </div>
         <div className="text-sm text-neutral-600 dark:text-neutral-400">
           {runs.toLocaleString()} runs

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

@@ -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;
@@ -22,14 +25,22 @@ export interface AgentTableRowProps {
   sub_heading: string;
   description: string;
   imageSrc: string[];
-  date_submitted: string;
-  status: StatusType;
+  dateSubmitted: Date;
+  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 +55,18 @@ 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,
@@ -58,16 +74,23 @@ 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-id={agent_id}
-      data-agent-name={agentName}
+      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">
@@ -106,7 +129,7 @@ export const AgentTableRow = ({
 
         {/* Date column */}
         <div className="text-sm text-neutral-600 dark:text-neutral-400">
-          {dateSubmitted}
+          {dateSubmitted.toLocaleDateString()}
         </div>
 
         {/* Status column */}
@@ -140,13 +163,23 @@ 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}

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

@@ -1,25 +1,36 @@
 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;
   sub_heading: string;
   description: string;
   imageSrc: string[];
-  dateSubmitted: string;
-  status: string;
+  dateSubmitted: Date;
+  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 };
 };