style: Format code after orjson integration

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

.github/copilot-instructions.md

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+# 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/claude-ci-failure-auto-fix.yml

@@ -0,0 +1,97 @@
+name: Auto Fix CI Failures
+
+on:
+  workflow_run:
+    workflows: ["CI"]
+    types:
+      - completed
+
+permissions:
+  contents: write
+  pull-requests: write
+  actions: read
+  issues: write
+  id-token: write # Required for OIDC token exchange
+
+jobs:
+  auto-fix:
+    if: |
+      github.event.workflow_run.conclusion == 'failure' &&
+      github.event.workflow_run.pull_requests[0] &&
+      !startsWith(github.event.workflow_run.head_branch, 'claude-auto-fix-ci-')
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          ref: ${{ github.event.workflow_run.head_branch }}
+          fetch-depth: 0
+          token: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Setup git identity
+        run: |
+          git config --global user.email "claude[bot]@users.noreply.github.com"
+          git config --global user.name "claude[bot]"
+
+      - name: Create fix branch
+        id: branch
+        run: |
+          BRANCH_NAME="claude-auto-fix-ci-${{ github.event.workflow_run.head_branch }}-${{ github.run_id }}"
+          git checkout -b "$BRANCH_NAME"
+          echo "branch_name=$BRANCH_NAME" >> $GITHUB_OUTPUT
+
+      - name: Get CI failure details
+        id: failure_details
+        uses: actions/github-script@v7
+        with:
+          script: |
+            const run = await github.rest.actions.getWorkflowRun({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              run_id: ${{ github.event.workflow_run.id }}
+            });
+
+            const jobs = await github.rest.actions.listJobsForWorkflowRun({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              run_id: ${{ github.event.workflow_run.id }}
+            });
+
+            const failedJobs = jobs.data.jobs.filter(job => job.conclusion === 'failure');
+
+            let errorLogs = [];
+            for (const job of failedJobs) {
+              const logs = await github.rest.actions.downloadJobLogsForWorkflowRun({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                job_id: job.id
+              });
+              errorLogs.push({
+                jobName: job.name,
+                logs: logs.data
+              });
+            }
+
+            return {
+              runUrl: run.data.html_url,
+              failedJobs: failedJobs.map(j => j.name),
+              errorLogs: errorLogs
+            };
+
+      - name: Fix CI failures with Claude
+        id: claude
+        uses: anthropics/claude-code-action@v1
+        with:
+          prompt: |
+            /fix-ci 
+            Failed CI Run: ${{ fromJSON(steps.failure_details.outputs.result).runUrl }}
+            Failed Jobs: ${{ join(fromJSON(steps.failure_details.outputs.result).failedJobs, ', ') }}
+            PR Number: ${{ github.event.workflow_run.pull_requests[0].number }}
+            Branch Name: ${{ steps.branch.outputs.branch_name }}
+            Base Branch: ${{ github.event.workflow_run.head_branch }}
+            Repository: ${{ github.repository }}
+
+            Error logs:
+            ${{ toJSON(fromJSON(steps.failure_details.outputs.result).errorLogs) }}
+          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
+          claude_args: "--allowedTools 'Edit,MultiEdit,Write,Read,Glob,Grep,LS,Bash(git:*),Bash(bun:*),Bash(npm:*),Bash(npx:*),Bash(gh:*)'"

.github/workflows/claude-dependabot.yml

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+# Claude Dependabot PR Review Workflow
+# 
+# This workflow automatically runs Claude analysis on Dependabot PRs to:
+# - Identify dependency changes and their versions
+# - Look up changelogs for updated packages  
+# - Assess breaking changes and security impacts
+# - Provide actionable recommendations for the development team
+#
+# Triggered on: Dependabot PRs (opened, synchronize)
+# Requirements: ANTHROPIC_API_KEY secret must be configured
+
+name: Claude Dependabot PR Review
+
+on:
+  pull_request:
+    types: [opened, synchronize]
+
+jobs:
+  dependabot-review:
+    # Only run on Dependabot PRs
+    if: github.actor == 'dependabot[bot]'
+    runs-on: ubuntu-latest
+    timeout-minutes: 30
+
+    permissions:
+      contents: write
+      pull-requests: read
+      issues: read
+      id-token: write
+      actions: read # Required for CI access
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
+
+      # 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)"
+
+
+      - name: Run Claude Dependabot Analysis
+        id: claude_review
+        uses: anthropics/claude-code-action@v1
+        with:
+          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
+          claude_args: |
+            --allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*)"
+          prompt: |
+            You are Claude, an AI assistant specialized in reviewing Dependabot dependency update PRs. 
+            
+            Your primary tasks are:
+            1. **Analyze the dependency changes** in this Dependabot PR
+            2. **Look up changelogs** for all updated dependencies to understand what changed
+            3. **Identify breaking changes** and assess potential impact on the AutoGPT codebase
+            4. **Provide actionable recommendations** for the development team
+            
+            ## Analysis Process:
+            
+            1. **Identify Changed Dependencies**: 
+               - Use git diff to see what dependencies were updated
+               - Parse package.json, poetry.lock, requirements files, etc.
+               - List all package versions: old → new
+            
+            2. **Changelog Research**:
+               - For each updated dependency, look up its changelog/release notes
+               - Use WebFetch to access GitHub releases, NPM package pages, PyPI project pages. The pr should also have some details
+               - Focus on versions between the old and new versions
+               - Identify: breaking changes, deprecations, security fixes, new features
+            
+            3. **Breaking Change Assessment**:
+               - Categorize changes: BREAKING, MAJOR, MINOR, PATCH, SECURITY
+               - Assess impact on AutoGPT's usage patterns
+               - Check if AutoGPT uses affected APIs/features
+               - Look for migration guides or upgrade instructions
+            
+            4. **Codebase Impact Analysis**:
+               - Search the AutoGPT codebase for usage of changed APIs
+               - Identify files that might be affected by breaking changes
+               - Check test files for deprecated usage patterns
+               - Look for configuration changes needed
+            
+            ## Output Format:
+            
+            Provide a comprehensive review comment with:
+            
+            ### 🔍 Dependency Analysis Summary
+            - List of updated packages with version changes
+            - Overall risk assessment (LOW/MEDIUM/HIGH)
+            
+            ### 📋 Detailed Changelog Review
+            For each updated dependency:
+            - **Package**: name (old_version → new_version)
+            - **Changes**: Summary of key changes
+            - **Breaking Changes**: List any breaking changes
+            - **Security Fixes**: Note security improvements
+            - **Migration Notes**: Any upgrade steps needed
+            
+            ### ⚠️ Impact Assessment
+            - **Breaking Changes Found**: Yes/No with details
+            - **Affected Files**: List AutoGPT files that may need updates
+            - **Test Impact**: Any tests that may need updating
+            - **Configuration Changes**: Required config updates
+            
+            ### 🛠️ Recommendations
+            - **Action Required**: What the team should do
+            - **Testing Focus**: Areas to test thoroughly
+            - **Follow-up Tasks**: Any additional work needed
+            - **Merge Recommendation**: APPROVE/REVIEW_NEEDED/HOLD
+            
+            ### 📚 Useful Links
+            - Links to relevant changelogs, migration guides, documentation
+            
+            Be thorough but concise. Focus on actionable insights that help the development team make informed decisions about the dependency updates.

.github/workflows/claude.yml

@@ -30,18 +30,296 @@ jobs:
         github.event.issue.author_association == 'COLLABORATOR'
       )
     runs-on: ubuntu-latest
+    timeout-minutes: 45
+
     permissions:
-      contents: read
+      contents: write
       pull-requests: read
       issues: read
       id-token: write
+      actions: read # Required for CI access
     steps:
-      - name: Checkout repository
+      - name: Checkout code
         uses: actions/checkout@v4
         with:
           fetch-depth: 1
+
+      # 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)"
+
       - name: Run Claude Code
         id: claude
-        uses: anthropics/claude-code-action@beta
+        uses: anthropics/claude-code-action@v1
         with:
           anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
+          claude_args: |
+            --allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*), Bash(gh pr edit:*)"
+            --model opus
+          additional_permissions: |
+            actions: read

.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-autogpt-deploy-dev.yaml

@@ -5,6 +5,13 @@ on:
     branches: [ dev ]
     paths:
       - 'autogpt_platform/**'
+  workflow_dispatch:
+    inputs:
+      git_ref:
+        description: 'Git ref (branch/tag) of AutoGPT to deploy'
+        required: true
+        default: 'master'
+        type: string
 
 permissions:
   contents: 'read'
@@ -19,6 +26,8 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          ref: ${{ github.event.inputs.git_ref || github.ref_name }}
 
       - name: Set up Python
         uses: actions/setup-python@v5
@@ -48,4 +57,4 @@ jobs:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
           event-type: build_deploy_dev
-          client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}", "repository": "${{ github.repository }}"}'
+          client-payload: '{"ref": "${{ github.event.inputs.git_ref || github.ref }}", "repository": "${{ github.repository }}"}'

.github/workflows/platform-autogpt-deploy-prod.yml

@@ -3,6 +3,7 @@ name: AutoGPT Platform - Deploy Prod Environment
 on:
   release:
     types: [published]
+  workflow_dispatch:
 
 permissions:
   contents: 'read'
@@ -17,6 +18,8 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          ref: ${{ github.ref_name || 'master' }}
 
       - name: Set up Python
         uses: actions/setup-python@v5
@@ -36,7 +39,7 @@ jobs:
           DATABASE_URL: ${{ secrets.BACKEND_DATABASE_URL }}
           DIRECT_URL: ${{ secrets.BACKEND_DATABASE_URL }}
 
-          
+
   trigger:
     needs: migrate
     runs-on: ubuntu-latest
@@ -47,4 +50,5 @@ jobs:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
           event-type: build_deploy_prod
-          client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}", "repository": "${{ github.repository }}"}'
+          client-payload: |
+            {"ref": "${{ github.ref_name || 'master' }}", "repository": "${{ github.repository }}"}

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

@@ -32,14 +32,12 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.11"]
+        python-version: ["3.11", "3.12", "3.13"]
     runs-on: ubuntu-latest
 
     services:
       redis:
-        image: bitnami/redis:6.2
-        env:
-          REDIS_PASSWORD: testpassword
+        image: redis:latest
         ports:
           - 6379:6379
       rabbitmq:
@@ -201,10 +199,9 @@ jobs:
           DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
           SUPABASE_URL: ${{ steps.supabase.outputs.API_URL }}
           SUPABASE_SERVICE_ROLE_KEY: ${{ steps.supabase.outputs.SERVICE_ROLE_KEY }}
-          SUPABASE_JWT_SECRET: ${{ steps.supabase.outputs.JWT_SECRET }}
+          JWT_VERIFY_KEY: ${{ steps.supabase.outputs.JWT_SECRET }}
           REDIS_HOST: "localhost"
           REDIS_PORT: "6379"
-          REDIS_PASSWORD: "testpassword"
           ENCRYPTION_KEY: "dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=" # DO NOT USE IN PRODUCTION!!
 
     env:

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

@@ -160,7 +160,7 @@ jobs:
 
       - name: Run docker compose
         run: |
-          docker compose -f ../docker-compose.yml up -d
+          NEXT_PUBLIC_PW_TEST=true docker compose -f ../docker-compose.yml up -d
         env:
           DOCKER_BUILDKIT: 1
           BUILDX_CACHE_FROM: type=local,src=/tmp/.buildx-cache

autogpt_platform/CLAUDE.md

@@ -61,24 +61,27 @@ poetry run pytest path/to/test.py --snapshot-update
 
 ```bash
 # Install dependencies
-cd frontend && npm install
+cd frontend && pnpm i
 
 # Start development server
-npm run dev
+pnpm dev
 
 # Run E2E tests
-npm run test
+pnpm test
 
 # Run Storybook for component development
-npm run storybook
+pnpm storybook
 
 # Build production
-npm run build
+pnpm build
 
 # Type checking
-npm run types
+pnpm types
 ```
 
+We have a components library in autogpt_platform/frontend/src/components/atoms that should be used when adding new pages and components. 
+
+
 ## Architecture Overview
 
 ### Backend Architecture
@@ -149,14 +152,23 @@ Key models (defined in `/backend/schema.prisma`):
 
 **Adding a new block:**
 
-1. Create new file in `/backend/backend/blocks/`
-2. Inherit from `Block` base class
-3. Define input/output schemas
-4. Implement `run` method
-5. Register in block registry
-6. Generate the block uuid using `uuid.uuid4()`
+Follow the comprehensive [Block SDK Guide](../../../docs/content/platform/block-sdk-guide.md) which covers:
+- Provider configuration with `ProviderBuilder`
+- Block schema definition
+- Authentication (API keys, OAuth, webhooks)
+- Testing and validation
+- File organization
 
-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?
+Quick steps:
+1. Create new file in `/backend/backend/blocks/`
+2. Configure provider using `ProviderBuilder` in `_config.py`
+3. Inherit from `Block` base class
+4. Define input/output schemas using `BlockSchema`
+5. Implement async `run` method
+6. Generate unique block ID using `uuid.uuid4()`
+7. Test with `poetry run pytest backend/blocks/test/test_block.py`
+
+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/api_key/key_manager.py

@@ -1,35 +0,0 @@
-import hashlib
-import secrets
-from typing import NamedTuple
-
-
-class APIKeyContainer(NamedTuple):
-    """Container for API key parts."""
-
-    raw: str
-    prefix: str
-    postfix: str
-    hash: str
-
-
-class APIKeyManager:
-    PREFIX: str = "agpt_"
-    PREFIX_LENGTH: int = 8
-    POSTFIX_LENGTH: int = 8
-
-    def generate_api_key(self) -> APIKeyContainer:
-        """Generate a new API key with all its parts."""
-        raw_key = f"{self.PREFIX}{secrets.token_urlsafe(32)}"
-        return APIKeyContainer(
-            raw=raw_key,
-            prefix=raw_key[: self.PREFIX_LENGTH],
-            postfix=raw_key[-self.POSTFIX_LENGTH :],
-            hash=hashlib.sha256(raw_key.encode()).hexdigest(),
-        )
-
-    def verify_api_key(self, provided_key: str, stored_hash: str) -> bool:
-        """Verify if a provided API key matches the stored hash."""
-        if not provided_key.startswith(self.PREFIX):
-            return False
-        provided_hash = hashlib.sha256(provided_key.encode()).hexdigest()
-        return secrets.compare_digest(provided_hash, stored_hash)

autogpt_platform/autogpt_libs/autogpt_libs/api_key/keysmith.py

@@ -0,0 +1,78 @@
+import hashlib
+import secrets
+from typing import NamedTuple
+
+from cryptography.hazmat.primitives.kdf.scrypt import Scrypt
+
+
+class APIKeyContainer(NamedTuple):
+    """Container for API key parts."""
+
+    key: str
+    head: str
+    tail: str
+    hash: str
+    salt: str
+
+
+class APIKeySmith:
+    PREFIX: str = "agpt_"
+    HEAD_LENGTH: int = 8
+    TAIL_LENGTH: int = 8
+
+    def generate_key(self) -> APIKeyContainer:
+        """Generate a new API key with secure hashing."""
+        raw_key = f"{self.PREFIX}{secrets.token_urlsafe(32)}"
+        hash, salt = self.hash_key(raw_key)
+
+        return APIKeyContainer(
+            key=raw_key,
+            head=raw_key[: self.HEAD_LENGTH],
+            tail=raw_key[-self.TAIL_LENGTH :],
+            hash=hash,
+            salt=salt,
+        )
+
+    def verify_key(
+        self, provided_key: str, known_hash: str, known_salt: str | None = None
+    ) -> bool:
+        """
+        Verify an API key against a known hash (+ salt).
+        Supports verifying both legacy SHA256 and secure Scrypt hashes.
+        """
+        if not provided_key.startswith(self.PREFIX):
+            return False
+
+        # Handle legacy SHA256 hashes (migration support)
+        if known_salt is None:
+            legacy_hash = hashlib.sha256(provided_key.encode()).hexdigest()
+            return secrets.compare_digest(legacy_hash, known_hash)
+
+        try:
+            salt_bytes = bytes.fromhex(known_salt)
+            provided_hash = self._hash_key_with_salt(provided_key, salt_bytes)
+            return secrets.compare_digest(provided_hash, known_hash)
+        except (ValueError, TypeError):
+            return False
+
+    def hash_key(self, raw_key: str) -> tuple[str, str]:
+        """Migrate a legacy hash to secure hash format."""
+        salt = self._generate_salt()
+        hash = self._hash_key_with_salt(raw_key, salt)
+        return hash, salt.hex()
+
+    def _generate_salt(self) -> bytes:
+        """Generate a random salt for hashing."""
+        return secrets.token_bytes(32)
+
+    def _hash_key_with_salt(self, raw_key: str, salt: bytes) -> str:
+        """Hash API key using Scrypt with salt."""
+        kdf = Scrypt(
+            length=32,
+            salt=salt,
+            n=2**14,  # CPU/memory cost parameter
+            r=8,  # Block size parameter
+            p=1,  # Parallelization parameter
+        )
+        key_hash = kdf.derive(raw_key.encode())
+        return key_hash.hex()

autogpt_platform/autogpt_libs/autogpt_libs/api_key/test_keysmith.py

@@ -0,0 +1,79 @@
+import hashlib
+
+from autogpt_libs.api_key.keysmith import APIKeySmith
+
+
+def test_generate_api_key():
+    keysmith = APIKeySmith()
+    key = keysmith.generate_key()
+
+    assert key.key.startswith(keysmith.PREFIX)
+    assert key.head == key.key[: keysmith.HEAD_LENGTH]
+    assert key.tail == key.key[-keysmith.TAIL_LENGTH :]
+    assert len(key.hash) == 64  # 32 bytes hex encoded
+    assert len(key.salt) == 64  # 32 bytes hex encoded
+
+
+def test_verify_new_secure_key():
+    keysmith = APIKeySmith()
+    key = keysmith.generate_key()
+
+    # Test correct key validates
+    assert keysmith.verify_key(key.key, key.hash, key.salt) is True
+
+    # Test wrong key fails
+    wrong_key = f"{keysmith.PREFIX}wrongkey123"
+    assert keysmith.verify_key(wrong_key, key.hash, key.salt) is False
+
+
+def test_verify_legacy_key():
+    keysmith = APIKeySmith()
+    legacy_key = f"{keysmith.PREFIX}legacykey123"
+    legacy_hash = hashlib.sha256(legacy_key.encode()).hexdigest()
+
+    # Test legacy key validates without salt
+    assert keysmith.verify_key(legacy_key, legacy_hash) is True
+
+    # Test wrong legacy key fails
+    wrong_key = f"{keysmith.PREFIX}wronglegacy"
+    assert keysmith.verify_key(wrong_key, legacy_hash) is False
+
+
+def test_rehash_existing_key():
+    keysmith = APIKeySmith()
+    legacy_key = f"{keysmith.PREFIX}migratekey123"
+
+    # Migrate the legacy key
+    new_hash, new_salt = keysmith.hash_key(legacy_key)
+
+    # Verify migrated key works
+    assert keysmith.verify_key(legacy_key, new_hash, new_salt) is True
+
+    # Verify different key fails with migrated hash
+    wrong_key = f"{keysmith.PREFIX}wrongkey"
+    assert keysmith.verify_key(wrong_key, new_hash, new_salt) is False
+
+
+def test_invalid_key_prefix():
+    keysmith = APIKeySmith()
+    key = keysmith.generate_key()
+
+    # Test key without proper prefix fails
+    invalid_key = "invalid_prefix_key"
+    assert keysmith.verify_key(invalid_key, key.hash, key.salt) is False
+
+
+def test_secure_hash_requires_salt():
+    keysmith = APIKeySmith()
+    key = keysmith.generate_key()
+
+    # Secure hash without salt should fail
+    assert keysmith.verify_key(key.key, key.hash) is False
+
+
+def test_invalid_salt_format():
+    keysmith = APIKeySmith()
+    key = keysmith.generate_key()
+
+    # Invalid salt format should fail gracefully
+    assert keysmith.verify_key(key.key, key.hash, "invalid_hex") is False

autogpt_platform/autogpt_libs/autogpt_libs/auth/__init__.py

@@ -1,13 +1,13 @@
-from .depends import requires_admin_user, requires_user
-from .jwt_utils import parse_jwt_token
-from .middleware import APIKeyValidator, auth_middleware
+from .config import verify_settings
+from .dependencies import get_user_id, requires_admin_user, requires_user
+from .helpers import add_auth_responses_to_openapi
 from .models import User
 
 __all__ = [
-    "parse_jwt_token",
-    "requires_user",
+    "verify_settings",
+    "get_user_id",
     "requires_admin_user",
-    "APIKeyValidator",
-    "auth_middleware",
+    "requires_user",
+    "add_auth_responses_to_openapi",
     "User",
 ]

autogpt_platform/autogpt_libs/autogpt_libs/auth/config.py

@@ -1,11 +1,90 @@
+import logging
 import os
 
+from jwt.algorithms import get_default_algorithms, has_crypto
+
+logger = logging.getLogger(__name__)
+
+
+class AuthConfigError(ValueError):
+    """Raised when authentication configuration is invalid."""
+
+    pass
+
+
+ALGO_RECOMMENDATION = (
+    "We highly recommend using an asymmetric algorithm such as ES256, "
+    "because when leaked, a shared secret would allow anyone to "
+    "forge valid tokens and impersonate users. "
+    "More info: https://supabase.com/docs/guides/auth/signing-keys#choosing-the-right-signing-algorithm"  # noqa
+)
+
 
 class Settings:
     def __init__(self):
-        self.JWT_SECRET_KEY: str = os.getenv("SUPABASE_JWT_SECRET", "")
-        self.ENABLE_AUTH: bool = os.getenv("ENABLE_AUTH", "false").lower() == "true"
-        self.JWT_ALGORITHM: str = "HS256"
+        self.JWT_VERIFY_KEY: str = os.getenv(
+            "JWT_VERIFY_KEY", os.getenv("SUPABASE_JWT_SECRET", "")
+        ).strip()
+        self.JWT_ALGORITHM: str = os.getenv("JWT_SIGN_ALGORITHM", "HS256").strip()
+
+        self.validate()
+
+    def validate(self):
+        if not self.JWT_VERIFY_KEY:
+            raise AuthConfigError(
+                "JWT_VERIFY_KEY must be set. "
+                "An empty JWT secret would allow anyone to forge valid tokens."
+            )
+
+        if len(self.JWT_VERIFY_KEY) < 32:
+            logger.warning(
+                "⚠️ JWT_VERIFY_KEY appears weak (less than 32 characters). "
+                "Consider using a longer, cryptographically secure secret."
+            )
+
+        supported_algorithms = get_default_algorithms().keys()
+
+        if not has_crypto:
+            logger.warning(
+                "⚠️ Asymmetric JWT verification is not available "
+                "because the 'cryptography' package is not installed. "
+                + ALGO_RECOMMENDATION
+            )
+
+        if (
+            self.JWT_ALGORITHM not in supported_algorithms
+            or self.JWT_ALGORITHM == "none"
+        ):
+            raise AuthConfigError(
+                f"Invalid JWT_SIGN_ALGORITHM: '{self.JWT_ALGORITHM}'. "
+                "Supported algorithms are listed on "
+                "https://pyjwt.readthedocs.io/en/stable/algorithms.html"
+            )
+
+        if self.JWT_ALGORITHM.startswith("HS"):
+            logger.warning(
+                f"⚠️ JWT_SIGN_ALGORITHM is set to '{self.JWT_ALGORITHM}', "
+                "a symmetric shared-key signature algorithm. " + ALGO_RECOMMENDATION
+            )
 
 
-settings = Settings()
+_settings: Settings = None  # type: ignore
+
+
+def get_settings() -> Settings:
+    global _settings
+
+    if not _settings:
+        _settings = Settings()
+
+    return _settings
+
+
+def verify_settings() -> None:
+    global _settings
+
+    if not _settings:
+        _settings = Settings()  # calls validation indirectly
+        return
+
+    _settings.validate()

autogpt_platform/autogpt_libs/autogpt_libs/auth/config_test.py

@@ -0,0 +1,306 @@
+"""
+Comprehensive tests for auth configuration to ensure 100% line and branch coverage.
+These tests verify critical security checks preventing JWT token forgery.
+"""
+
+import logging
+import os
+
+import pytest
+from pytest_mock import MockerFixture
+
+from autogpt_libs.auth.config import AuthConfigError, Settings
+
+
+def test_environment_variable_precedence(mocker: MockerFixture):
+    """Test that environment variables take precedence over defaults."""
+    secret = "environment-secret-key-with-proper-length-123456"
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == secret
+
+
+def test_environment_variable_backwards_compatible(mocker: MockerFixture):
+    """Test that SUPABASE_JWT_SECRET is read if JWT_VERIFY_KEY is not set."""
+    secret = "environment-secret-key-with-proper-length-123456"
+    mocker.patch.dict(os.environ, {"SUPABASE_JWT_SECRET": secret}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == secret
+
+
+def test_auth_config_error_inheritance():
+    """Test that AuthConfigError is properly defined as an Exception."""
+    assert issubclass(AuthConfigError, Exception)
+    error = AuthConfigError("test message")
+    assert str(error) == "test message"
+
+
+def test_settings_static_after_creation(mocker: MockerFixture):
+    """Test that settings maintain their values after creation."""
+    secret = "immutable-secret-key-with-proper-length-12345"
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret}, clear=True)
+
+    settings = Settings()
+    original_secret = settings.JWT_VERIFY_KEY
+
+    # Changing environment after creation shouldn't affect settings
+    os.environ["JWT_VERIFY_KEY"] = "different-secret"
+
+    assert settings.JWT_VERIFY_KEY == original_secret
+
+
+def test_settings_load_with_valid_secret(mocker: MockerFixture):
+    """Test auth enabled with a valid JWT secret."""
+    valid_secret = "a" * 32  # 32 character secret
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": valid_secret}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == valid_secret
+
+
+def test_settings_load_with_strong_secret(mocker: MockerFixture):
+    """Test auth enabled with a cryptographically strong secret."""
+    strong_secret = "super-secret-jwt-token-with-at-least-32-characters-long"
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": strong_secret}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == strong_secret
+    assert len(settings.JWT_VERIFY_KEY) >= 32
+
+
+def test_secret_empty_raises_error(mocker: MockerFixture):
+    """Test that auth enabled with empty secret raises AuthConfigError."""
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": ""}, clear=True)
+
+    with pytest.raises(Exception) as exc_info:
+        Settings()
+    assert "JWT_VERIFY_KEY" in str(exc_info.value)
+
+
+def test_secret_missing_raises_error(mocker: MockerFixture):
+    """Test that auth enabled without secret env var raises AuthConfigError."""
+    mocker.patch.dict(os.environ, {}, clear=True)
+
+    with pytest.raises(Exception) as exc_info:
+        Settings()
+    assert "JWT_VERIFY_KEY" in str(exc_info.value)
+
+
+@pytest.mark.parametrize("secret", [" ", "  ", "\t", "\n", " \t\n "])
+def test_secret_only_whitespace_raises_error(mocker: MockerFixture, secret: str):
+    """Test that auth enabled with whitespace-only secret raises error."""
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret}, clear=True)
+
+    with pytest.raises(ValueError):
+        Settings()
+
+
+def test_secret_weak_logs_warning(
+    mocker: MockerFixture, caplog: pytest.LogCaptureFixture
+):
+    """Test that weak JWT secret triggers warning log."""
+    weak_secret = "short"  # Less than 32 characters
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": weak_secret}, clear=True)
+
+    with caplog.at_level(logging.WARNING):
+        settings = Settings()
+        assert settings.JWT_VERIFY_KEY == weak_secret
+        assert "key appears weak" in caplog.text.lower()
+        assert "less than 32 characters" in caplog.text
+
+
+def test_secret_31_char_logs_warning(
+    mocker: MockerFixture, caplog: pytest.LogCaptureFixture
+):
+    """Test that 31-character secret triggers warning (boundary test)."""
+    secret_31 = "a" * 31  # Exactly 31 characters
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret_31}, clear=True)
+
+    with caplog.at_level(logging.WARNING):
+        settings = Settings()
+        assert len(settings.JWT_VERIFY_KEY) == 31
+        assert "key appears weak" in caplog.text.lower()
+
+
+def test_secret_32_char_no_warning(
+    mocker: MockerFixture, caplog: pytest.LogCaptureFixture
+):
+    """Test that 32-character secret does not trigger warning (boundary test)."""
+    secret_32 = "a" * 32  # Exactly 32 characters
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret_32}, clear=True)
+
+    with caplog.at_level(logging.WARNING):
+        settings = Settings()
+        assert len(settings.JWT_VERIFY_KEY) == 32
+        assert "JWT secret appears weak" not in caplog.text
+
+
+def test_secret_whitespace_stripped(mocker: MockerFixture):
+    """Test that JWT secret whitespace is stripped."""
+    secret = "a" * 32
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": f"  {secret}  "}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == secret
+
+
+def test_secret_with_special_characters(mocker: MockerFixture):
+    """Test JWT secret with special characters."""
+    special_secret = "!@#$%^&*()_+-=[]{}|;:,.<>?`~" + "a" * 10  # 40 chars total
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": special_secret}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == special_secret
+
+
+def test_secret_with_unicode(mocker: MockerFixture):
+    """Test JWT secret with unicode characters."""
+    unicode_secret = "秘密🔐キー" + "a" * 25  # Ensure >32 bytes
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": unicode_secret}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == unicode_secret
+
+
+def test_secret_very_long(mocker: MockerFixture):
+    """Test JWT secret with excessive length."""
+    long_secret = "a" * 1000  # 1000 character secret
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": long_secret}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == long_secret
+    assert len(settings.JWT_VERIFY_KEY) == 1000
+
+
+def test_secret_with_newline(mocker: MockerFixture):
+    """Test JWT secret containing newlines."""
+    multiline_secret = "secret\nwith\nnewlines" + "a" * 20
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": multiline_secret}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == multiline_secret
+
+
+def test_secret_base64_encoded(mocker: MockerFixture):
+    """Test JWT secret that looks like base64."""
+    base64_secret = "dGhpc19pc19hX3NlY3JldF9rZXlfd2l0aF9wcm9wZXJfbGVuZ3Ro"
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": base64_secret}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == base64_secret
+
+
+def test_secret_numeric_only(mocker: MockerFixture):
+    """Test JWT secret with only numbers."""
+    numeric_secret = "1234567890" * 4  # 40 character numeric secret
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": numeric_secret}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_VERIFY_KEY == numeric_secret
+
+
+def test_algorithm_default_hs256(mocker: MockerFixture):
+    """Test that JWT algorithm defaults to HS256."""
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": "a" * 32}, clear=True)
+
+    settings = Settings()
+    assert settings.JWT_ALGORITHM == "HS256"
+
+
+def test_algorithm_whitespace_stripped(mocker: MockerFixture):
+    """Test that JWT algorithm whitespace is stripped."""
+    secret = "a" * 32
+    mocker.patch.dict(
+        os.environ,
+        {"JWT_VERIFY_KEY": secret, "JWT_SIGN_ALGORITHM": "  HS256  "},
+        clear=True,
+    )
+
+    settings = Settings()
+    assert settings.JWT_ALGORITHM == "HS256"
+
+
+def test_no_crypto_warning(mocker: MockerFixture, caplog: pytest.LogCaptureFixture):
+    """Test warning when crypto package is not available."""
+    secret = "a" * 32
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret}, clear=True)
+
+    # Mock has_crypto to return False
+    mocker.patch("autogpt_libs.auth.config.has_crypto", False)
+
+    with caplog.at_level(logging.WARNING):
+        Settings()
+        assert "Asymmetric JWT verification is not available" in caplog.text
+        assert "cryptography" in caplog.text
+
+
+def test_algorithm_invalid_raises_error(mocker: MockerFixture):
+    """Test that invalid JWT algorithm raises AuthConfigError."""
+    secret = "a" * 32
+    mocker.patch.dict(
+        os.environ,
+        {"JWT_VERIFY_KEY": secret, "JWT_SIGN_ALGORITHM": "INVALID_ALG"},
+        clear=True,
+    )
+
+    with pytest.raises(AuthConfigError) as exc_info:
+        Settings()
+    assert "Invalid JWT_SIGN_ALGORITHM" in str(exc_info.value)
+    assert "INVALID_ALG" in str(exc_info.value)
+
+
+def test_algorithm_none_raises_error(mocker: MockerFixture):
+    """Test that 'none' algorithm raises AuthConfigError."""
+    secret = "a" * 32
+    mocker.patch.dict(
+        os.environ,
+        {"JWT_VERIFY_KEY": secret, "JWT_SIGN_ALGORITHM": "none"},
+        clear=True,
+    )
+
+    with pytest.raises(AuthConfigError) as exc_info:
+        Settings()
+    assert "Invalid JWT_SIGN_ALGORITHM" in str(exc_info.value)
+
+
+@pytest.mark.parametrize("algorithm", ["HS256", "HS384", "HS512"])
+def test_algorithm_symmetric_warning(
+    mocker: MockerFixture, caplog: pytest.LogCaptureFixture, algorithm: str
+):
+    """Test warning for symmetric algorithms (HS256, HS384, HS512)."""
+    secret = "a" * 32
+    mocker.patch.dict(
+        os.environ,
+        {"JWT_VERIFY_KEY": secret, "JWT_SIGN_ALGORITHM": algorithm},
+        clear=True,
+    )
+
+    with caplog.at_level(logging.WARNING):
+        settings = Settings()
+        assert algorithm in caplog.text
+        assert "symmetric shared-key signature algorithm" in caplog.text
+        assert settings.JWT_ALGORITHM == algorithm
+
+
+@pytest.mark.parametrize(
+    "algorithm",
+    ["ES256", "ES384", "ES512", "RS256", "RS384", "RS512", "PS256", "PS384", "PS512"],
+)
+def test_algorithm_asymmetric_no_warning(
+    mocker: MockerFixture, caplog: pytest.LogCaptureFixture, algorithm: str
+):
+    """Test that asymmetric algorithms do not trigger warning."""
+    secret = "a" * 32
+    mocker.patch.dict(
+        os.environ,
+        {"JWT_VERIFY_KEY": secret, "JWT_SIGN_ALGORITHM": algorithm},
+        clear=True,
+    )
+
+    with caplog.at_level(logging.WARNING):
+        settings = Settings()
+        # Should not contain the symmetric algorithm warning
+        assert "symmetric shared-key signature algorithm" not in caplog.text
+        assert settings.JWT_ALGORITHM == algorithm

autogpt_platform/autogpt_libs/autogpt_libs/auth/dependencies.py

@@ -0,0 +1,45 @@
+"""
+FastAPI dependency functions for JWT-based authentication and authorization.
+
+These are the high-level dependency functions used in route definitions.
+"""
+
+import fastapi
+
+from .jwt_utils import get_jwt_payload, verify_user
+from .models import User
+
+
+def requires_user(jwt_payload: dict = fastapi.Security(get_jwt_payload)) -> User:
+    """
+    FastAPI dependency that requires a valid authenticated user.
+
+    Raises:
+        HTTPException: 401 for authentication failures
+    """
+    return verify_user(jwt_payload, admin_only=False)
+
+
+def requires_admin_user(jwt_payload: dict = fastapi.Security(get_jwt_payload)) -> User:
+    """
+    FastAPI dependency that requires a valid admin user.
+
+    Raises:
+        HTTPException: 401 for authentication failures, 403 for insufficient permissions
+    """
+    return verify_user(jwt_payload, admin_only=True)
+
+
+def get_user_id(jwt_payload: dict = fastapi.Security(get_jwt_payload)) -> str:
+    """
+    FastAPI dependency that returns the ID of the authenticated user.
+
+    Raises:
+        HTTPException: 401 for authentication failures or missing user ID
+    """
+    user_id = jwt_payload.get("sub")
+    if not user_id:
+        raise fastapi.HTTPException(
+            status_code=401, detail="User ID not found in token"
+        )
+    return user_id

autogpt_platform/autogpt_libs/autogpt_libs/auth/dependencies_test.py

@@ -0,0 +1,335 @@
+"""
+Comprehensive integration tests for authentication dependencies.
+Tests the full authentication flow from HTTP requests to user validation.
+"""
+
+import os
+
+import pytest
+from fastapi import FastAPI, HTTPException, Security
+from fastapi.testclient import TestClient
+from pytest_mock import MockerFixture
+
+from autogpt_libs.auth.dependencies import (
+    get_user_id,
+    requires_admin_user,
+    requires_user,
+)
+from autogpt_libs.auth.models import User
+
+
+class TestAuthDependencies:
+    """Test suite for authentication dependency functions."""
+
+    @pytest.fixture
+    def app(self):
+        """Create a test FastAPI application."""
+        app = FastAPI()
+
+        @app.get("/user")
+        def get_user_endpoint(user: User = Security(requires_user)):
+            return {"user_id": user.user_id, "role": user.role}
+
+        @app.get("/admin")
+        def get_admin_endpoint(user: User = Security(requires_admin_user)):
+            return {"user_id": user.user_id, "role": user.role}
+
+        @app.get("/user-id")
+        def get_user_id_endpoint(user_id: str = Security(get_user_id)):
+            return {"user_id": user_id}
+
+        return app
+
+    @pytest.fixture
+    def client(self, app):
+        """Create a test client."""
+        return TestClient(app)
+
+    def test_requires_user_with_valid_jwt_payload(self, mocker: MockerFixture):
+        """Test requires_user with valid JWT payload."""
+        jwt_payload = {"sub": "user-123", "role": "user", "email": "user@example.com"}
+
+        # Mock get_jwt_payload to return our test payload
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+        user = requires_user(jwt_payload)
+        assert isinstance(user, User)
+        assert user.user_id == "user-123"
+        assert user.role == "user"
+
+    def test_requires_user_with_admin_jwt_payload(self, mocker: MockerFixture):
+        """Test requires_user accepts admin users."""
+        jwt_payload = {
+            "sub": "admin-456",
+            "role": "admin",
+            "email": "admin@example.com",
+        }
+
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+        user = requires_user(jwt_payload)
+        assert user.user_id == "admin-456"
+        assert user.role == "admin"
+
+    def test_requires_user_missing_sub(self):
+        """Test requires_user with missing user ID."""
+        jwt_payload = {"role": "user", "email": "user@example.com"}
+
+        with pytest.raises(HTTPException) as exc_info:
+            requires_user(jwt_payload)
+        assert exc_info.value.status_code == 401
+        assert "User ID not found" in exc_info.value.detail
+
+    def test_requires_user_empty_sub(self):
+        """Test requires_user with empty user ID."""
+        jwt_payload = {"sub": "", "role": "user"}
+
+        with pytest.raises(HTTPException) as exc_info:
+            requires_user(jwt_payload)
+        assert exc_info.value.status_code == 401
+
+    def test_requires_admin_user_with_admin(self, mocker: MockerFixture):
+        """Test requires_admin_user with admin role."""
+        jwt_payload = {
+            "sub": "admin-789",
+            "role": "admin",
+            "email": "admin@example.com",
+        }
+
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+        user = requires_admin_user(jwt_payload)
+        assert user.user_id == "admin-789"
+        assert user.role == "admin"
+
+    def test_requires_admin_user_with_regular_user(self):
+        """Test requires_admin_user rejects regular users."""
+        jwt_payload = {"sub": "user-123", "role": "user", "email": "user@example.com"}
+
+        with pytest.raises(HTTPException) as exc_info:
+            requires_admin_user(jwt_payload)
+        assert exc_info.value.status_code == 403
+        assert "Admin access required" in exc_info.value.detail
+
+    def test_requires_admin_user_missing_role(self):
+        """Test requires_admin_user with missing role."""
+        jwt_payload = {"sub": "user-123", "email": "user@example.com"}
+
+        with pytest.raises(KeyError):
+            requires_admin_user(jwt_payload)
+
+    def test_get_user_id_with_valid_payload(self, mocker: MockerFixture):
+        """Test get_user_id extracts user ID correctly."""
+        jwt_payload = {"sub": "user-id-xyz", "role": "user"}
+
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+        user_id = get_user_id(jwt_payload)
+        assert user_id == "user-id-xyz"
+
+    def test_get_user_id_missing_sub(self):
+        """Test get_user_id with missing user ID."""
+        jwt_payload = {"role": "user"}
+
+        with pytest.raises(HTTPException) as exc_info:
+            get_user_id(jwt_payload)
+        assert exc_info.value.status_code == 401
+        assert "User ID not found" in exc_info.value.detail
+
+    def test_get_user_id_none_sub(self):
+        """Test get_user_id with None user ID."""
+        jwt_payload = {"sub": None, "role": "user"}
+
+        with pytest.raises(HTTPException) as exc_info:
+            get_user_id(jwt_payload)
+        assert exc_info.value.status_code == 401
+
+
+class TestAuthDependenciesIntegration:
+    """Integration tests for auth dependencies with FastAPI."""
+
+    acceptable_jwt_secret = "test-secret-with-proper-length-123456"
+
+    @pytest.fixture
+    def create_token(self, mocker: MockerFixture):
+        """Helper to create JWT tokens."""
+        import jwt
+
+        mocker.patch.dict(
+            os.environ,
+            {"JWT_VERIFY_KEY": self.acceptable_jwt_secret},
+            clear=True,
+        )
+
+        def _create_token(payload, secret=self.acceptable_jwt_secret):
+            return jwt.encode(payload, secret, algorithm="HS256")
+
+        return _create_token
+
+    def test_endpoint_auth_enabled_no_token(self):
+        """Test endpoints require token when auth is enabled."""
+        app = FastAPI()
+
+        @app.get("/test")
+        def test_endpoint(user: User = Security(requires_user)):
+            return {"user_id": user.user_id}
+
+        client = TestClient(app)
+
+        # Should fail without auth header
+        response = client.get("/test")
+        assert response.status_code == 401
+
+    def test_endpoint_with_valid_token(self, create_token):
+        """Test endpoint with valid JWT token."""
+        app = FastAPI()
+
+        @app.get("/test")
+        def test_endpoint(user: User = Security(requires_user)):
+            return {"user_id": user.user_id, "role": user.role}
+
+        client = TestClient(app)
+
+        token = create_token(
+            {"sub": "test-user", "role": "user", "aud": "authenticated"},
+            secret=self.acceptable_jwt_secret,
+        )
+
+        response = client.get("/test", headers={"Authorization": f"Bearer {token}"})
+        assert response.status_code == 200
+        assert response.json()["user_id"] == "test-user"
+
+    def test_admin_endpoint_requires_admin_role(self, create_token):
+        """Test admin endpoint rejects non-admin users."""
+        app = FastAPI()
+
+        @app.get("/admin")
+        def admin_endpoint(user: User = Security(requires_admin_user)):
+            return {"user_id": user.user_id}
+
+        client = TestClient(app)
+
+        # Regular user token
+        user_token = create_token(
+            {"sub": "regular-user", "role": "user", "aud": "authenticated"},
+            secret=self.acceptable_jwt_secret,
+        )
+
+        response = client.get(
+            "/admin", headers={"Authorization": f"Bearer {user_token}"}
+        )
+        assert response.status_code == 403
+
+        # Admin token
+        admin_token = create_token(
+            {"sub": "admin-user", "role": "admin", "aud": "authenticated"},
+            secret=self.acceptable_jwt_secret,
+        )
+
+        response = client.get(
+            "/admin", headers={"Authorization": f"Bearer {admin_token}"}
+        )
+        assert response.status_code == 200
+        assert response.json()["user_id"] == "admin-user"
+
+
+class TestAuthDependenciesEdgeCases:
+    """Edge case tests for authentication dependencies."""
+
+    def test_dependency_with_complex_payload(self):
+        """Test dependencies handle complex JWT payloads."""
+        complex_payload = {
+            "sub": "user-123",
+            "role": "admin",
+            "email": "test@example.com",
+            "app_metadata": {"provider": "email", "providers": ["email"]},
+            "user_metadata": {
+                "full_name": "Test User",
+                "avatar_url": "https://example.com/avatar.jpg",
+            },
+            "aud": "authenticated",
+            "iat": 1234567890,
+            "exp": 9999999999,
+        }
+
+        user = requires_user(complex_payload)
+        assert user.user_id == "user-123"
+        assert user.email == "test@example.com"
+
+        admin = requires_admin_user(complex_payload)
+        assert admin.role == "admin"
+
+    def test_dependency_with_unicode_in_payload(self):
+        """Test dependencies handle unicode in JWT payloads."""
+        unicode_payload = {
+            "sub": "user-😀-123",
+            "role": "user",
+            "email": "测试@example.com",
+            "name": "日本語",
+        }
+
+        user = requires_user(unicode_payload)
+        assert "😀" in user.user_id
+        assert user.email == "测试@example.com"
+
+    def test_dependency_with_null_values(self):
+        """Test dependencies handle null values in payload."""
+        null_payload = {
+            "sub": "user-123",
+            "role": "user",
+            "email": None,
+            "phone": None,
+            "metadata": None,
+        }
+
+        user = requires_user(null_payload)
+        assert user.user_id == "user-123"
+        assert user.email is None
+
+    def test_concurrent_requests_isolation(self):
+        """Test that concurrent requests don't interfere with each other."""
+        payload1 = {"sub": "user-1", "role": "user"}
+        payload2 = {"sub": "user-2", "role": "admin"}
+
+        # Simulate concurrent processing
+        user1 = requires_user(payload1)
+        user2 = requires_admin_user(payload2)
+
+        assert user1.user_id == "user-1"
+        assert user2.user_id == "user-2"
+        assert user1.role == "user"
+        assert user2.role == "admin"
+
+    @pytest.mark.parametrize(
+        "payload,expected_error,admin_only",
+        [
+            (None, "Authorization header is missing", False),
+            ({}, "User ID not found", False),
+            ({"sub": ""}, "User ID not found", False),
+            ({"role": "user"}, "User ID not found", False),
+            ({"sub": "user", "role": "user"}, "Admin access required", True),
+        ],
+    )
+    def test_dependency_error_cases(
+        self, payload, expected_error: str, admin_only: bool
+    ):
+        """Test that errors propagate correctly through dependencies."""
+        # Import verify_user to test it directly since dependencies use FastAPI Security
+        from autogpt_libs.auth.jwt_utils import verify_user
+
+        with pytest.raises(HTTPException) as exc_info:
+            verify_user(payload, admin_only=admin_only)
+        assert expected_error in exc_info.value.detail
+
+    def test_dependency_valid_user(self):
+        """Test valid user case for dependency."""
+        # Import verify_user to test it directly since dependencies use FastAPI Security
+        from autogpt_libs.auth.jwt_utils import verify_user
+
+        # Valid case
+        user = verify_user({"sub": "user", "role": "user"}, admin_only=False)
+        assert user.user_id == "user"

autogpt_platform/autogpt_libs/autogpt_libs/auth/depends.py

@@ -1,46 +0,0 @@
-import fastapi
-
-from .config import settings
-from .middleware import auth_middleware
-from .models import DEFAULT_USER_ID, User
-
-
-def requires_user(payload: dict = fastapi.Depends(auth_middleware)) -> User:
-    return verify_user(payload, admin_only=False)
-
-
-def requires_admin_user(
-    payload: dict = fastapi.Depends(auth_middleware),
-) -> User:
-    return verify_user(payload, admin_only=True)
-
-
-def verify_user(payload: dict | None, admin_only: bool) -> User:
-    if not payload:
-        if settings.ENABLE_AUTH:
-            raise fastapi.HTTPException(
-                status_code=401, detail="Authorization header is missing"
-            )
-        # This handles the case when authentication is disabled
-        payload = {"sub": DEFAULT_USER_ID, "role": "admin"}
-
-    user_id = payload.get("sub")
-
-    if not user_id:
-        raise fastapi.HTTPException(
-            status_code=401, detail="User ID not found in token"
-        )
-
-    if admin_only and payload["role"] != "admin":
-        raise fastapi.HTTPException(status_code=403, detail="Admin access required")
-
-    return User.from_payload(payload)
-
-
-def get_user_id(payload: dict = fastapi.Depends(auth_middleware)) -> str:
-    user_id = payload.get("sub")
-    if not user_id:
-        raise fastapi.HTTPException(
-            status_code=401, detail="User ID not found in token"
-        )
-    return user_id

autogpt_platform/autogpt_libs/autogpt_libs/auth/depends_tests.py

@@ -1,68 +0,0 @@
-import pytest
-
-from .depends import requires_admin_user, requires_user, verify_user
-
-
-def test_verify_user_no_payload():
-    user = verify_user(None, admin_only=False)
-    assert user.user_id == "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
-    assert user.role == "admin"
-
-
-def test_verify_user_no_user_id():
-    with pytest.raises(Exception):
-        verify_user({"role": "admin"}, admin_only=False)
-
-
-def test_verify_user_not_admin():
-    with pytest.raises(Exception):
-        verify_user(
-            {"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "user"},
-            admin_only=True,
-        )
-
-
-def test_verify_user_with_admin_role():
-    user = verify_user(
-        {"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "admin"},
-        admin_only=True,
-    )
-    assert user.user_id == "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
-    assert user.role == "admin"
-
-
-def test_verify_user_with_user_role():
-    user = verify_user(
-        {"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "user"},
-        admin_only=False,
-    )
-    assert user.user_id == "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
-    assert user.role == "user"
-
-
-def test_requires_user():
-    user = requires_user(
-        {"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "user"}
-    )
-    assert user.user_id == "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
-    assert user.role == "user"
-
-
-def test_requires_user_no_user_id():
-    with pytest.raises(Exception):
-        requires_user({"role": "user"})
-
-
-def test_requires_admin_user():
-    user = requires_admin_user(
-        {"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "admin"}
-    )
-    assert user.user_id == "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
-    assert user.role == "admin"
-
-
-def test_requires_admin_user_not_admin():
-    with pytest.raises(Exception):
-        requires_admin_user(
-            {"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "user"}
-        )

autogpt_platform/autogpt_libs/autogpt_libs/auth/helpers.py

@@ -0,0 +1,68 @@
+from fastapi import FastAPI
+from fastapi.openapi.utils import get_openapi
+
+from .jwt_utils import bearer_jwt_auth
+
+
+def add_auth_responses_to_openapi(app: FastAPI) -> None:
+    """
+    Set up custom OpenAPI schema generation that adds 401 responses
+    to all authenticated endpoints.
+
+    This is needed when using HTTPBearer with auto_error=False to get proper
+    401 responses instead of 403, but FastAPI only automatically adds security
+    responses when auto_error=True.
+    """
+
+    def custom_openapi():
+        if app.openapi_schema:
+            return app.openapi_schema
+
+        openapi_schema = get_openapi(
+            title=app.title,
+            version=app.version,
+            description=app.description,
+            routes=app.routes,
+        )
+
+        # Add 401 response to all endpoints that have security requirements
+        for path, methods in openapi_schema["paths"].items():
+            for method, details in methods.items():
+                security_schemas = [
+                    schema
+                    for auth_option in details.get("security", [])
+                    for schema in auth_option.keys()
+                ]
+                if bearer_jwt_auth.scheme_name not in security_schemas:
+                    continue
+
+                if "responses" not in details:
+                    details["responses"] = {}
+
+                details["responses"]["401"] = {
+                    "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+                }
+
+        # Ensure #/components/responses exists
+        if "components" not in openapi_schema:
+            openapi_schema["components"] = {}
+        if "responses" not in openapi_schema["components"]:
+            openapi_schema["components"]["responses"] = {}
+
+        # Define 401 response
+        openapi_schema["components"]["responses"]["HTTP401NotAuthenticatedError"] = {
+            "description": "Authentication required",
+            "content": {
+                "application/json": {
+                    "schema": {
+                        "type": "object",
+                        "properties": {"detail": {"type": "string"}},
+                    }
+                }
+            },
+        }
+
+        app.openapi_schema = openapi_schema
+        return app.openapi_schema
+
+    app.openapi = custom_openapi

autogpt_platform/autogpt_libs/autogpt_libs/auth/helpers_test.py

@@ -0,0 +1,435 @@
+"""
+Comprehensive tests for auth helpers module to achieve 100% coverage.
+Tests OpenAPI schema generation and authentication response handling.
+"""
+
+from unittest import mock
+
+from fastapi import FastAPI
+from fastapi.openapi.utils import get_openapi
+
+from autogpt_libs.auth.helpers import add_auth_responses_to_openapi
+from autogpt_libs.auth.jwt_utils import bearer_jwt_auth
+
+
+def test_add_auth_responses_to_openapi_basic():
+    """Test adding 401 responses to OpenAPI schema."""
+    app = FastAPI(title="Test App", version="1.0.0")
+
+    # Add some test endpoints with authentication
+    from fastapi import Depends
+
+    from autogpt_libs.auth.dependencies import requires_user
+
+    @app.get("/protected", dependencies=[Depends(requires_user)])
+    def protected_endpoint():
+        return {"message": "Protected"}
+
+    @app.get("/public")
+    def public_endpoint():
+        return {"message": "Public"}
+
+    # Apply the OpenAPI customization
+    add_auth_responses_to_openapi(app)
+
+    # Get the OpenAPI schema
+    schema = app.openapi()
+
+    # Verify basic schema properties
+    assert schema["info"]["title"] == "Test App"
+    assert schema["info"]["version"] == "1.0.0"
+
+    # Verify 401 response component is added
+    assert "components" in schema
+    assert "responses" in schema["components"]
+    assert "HTTP401NotAuthenticatedError" in schema["components"]["responses"]
+
+    # Verify 401 response structure
+    error_response = schema["components"]["responses"]["HTTP401NotAuthenticatedError"]
+    assert error_response["description"] == "Authentication required"
+    assert "application/json" in error_response["content"]
+    assert "schema" in error_response["content"]["application/json"]
+
+    # Verify schema properties
+    response_schema = error_response["content"]["application/json"]["schema"]
+    assert response_schema["type"] == "object"
+    assert "detail" in response_schema["properties"]
+    assert response_schema["properties"]["detail"]["type"] == "string"
+
+
+def test_add_auth_responses_to_openapi_with_security():
+    """Test that 401 responses are added only to secured endpoints."""
+    app = FastAPI()
+
+    # Mock endpoint with security
+    from fastapi import Security
+
+    from autogpt_libs.auth.dependencies import get_user_id
+
+    @app.get("/secured")
+    def secured_endpoint(user_id: str = Security(get_user_id)):
+        return {"user_id": user_id}
+
+    @app.post("/also-secured")
+    def another_secured(user_id: str = Security(get_user_id)):
+        return {"status": "ok"}
+
+    @app.get("/unsecured")
+    def unsecured_endpoint():
+        return {"public": True}
+
+    # Apply OpenAPI customization
+    add_auth_responses_to_openapi(app)
+
+    # Get schema
+    schema = app.openapi()
+
+    # Check that secured endpoints have 401 responses
+    if "/secured" in schema["paths"]:
+        if "get" in schema["paths"]["/secured"]:
+            secured_get = schema["paths"]["/secured"]["get"]
+            if "responses" in secured_get:
+                assert "401" in secured_get["responses"]
+                assert (
+                    secured_get["responses"]["401"]["$ref"]
+                    == "#/components/responses/HTTP401NotAuthenticatedError"
+                )
+
+    if "/also-secured" in schema["paths"]:
+        if "post" in schema["paths"]["/also-secured"]:
+            secured_post = schema["paths"]["/also-secured"]["post"]
+            if "responses" in secured_post:
+                assert "401" in secured_post["responses"]
+
+    # Check that unsecured endpoint does not have 401 response
+    if "/unsecured" in schema["paths"]:
+        if "get" in schema["paths"]["/unsecured"]:
+            unsecured_get = schema["paths"]["/unsecured"]["get"]
+            if "responses" in unsecured_get:
+                assert "401" not in unsecured_get.get("responses", {})
+
+
+def test_add_auth_responses_to_openapi_cached_schema():
+    """Test that OpenAPI schema is cached after first generation."""
+    app = FastAPI()
+
+    # Apply customization
+    add_auth_responses_to_openapi(app)
+
+    # Get schema twice
+    schema1 = app.openapi()
+    schema2 = app.openapi()
+
+    # Should return the same cached object
+    assert schema1 is schema2
+
+
+def test_add_auth_responses_to_openapi_existing_responses():
+    """Test handling endpoints that already have responses defined."""
+    app = FastAPI()
+
+    from fastapi import Security
+
+    from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+    @app.get(
+        "/with-responses",
+        responses={
+            200: {"description": "Success"},
+            404: {"description": "Not found"},
+        },
+    )
+    def endpoint_with_responses(jwt: dict = Security(get_jwt_payload)):
+        return {"data": "test"}
+
+    # Apply customization
+    add_auth_responses_to_openapi(app)
+
+    schema = app.openapi()
+
+    # Check that existing responses are preserved and 401 is added
+    if "/with-responses" in schema["paths"]:
+        if "get" in schema["paths"]["/with-responses"]:
+            responses = schema["paths"]["/with-responses"]["get"].get("responses", {})
+            # Original responses should be preserved
+            if "200" in responses:
+                assert responses["200"]["description"] == "Success"
+            if "404" in responses:
+                assert responses["404"]["description"] == "Not found"
+            # 401 should be added
+            if "401" in responses:
+                assert (
+                    responses["401"]["$ref"]
+                    == "#/components/responses/HTTP401NotAuthenticatedError"
+                )
+
+
+def test_add_auth_responses_to_openapi_no_security_endpoints():
+    """Test with app that has no secured endpoints."""
+    app = FastAPI()
+
+    @app.get("/public1")
+    def public1():
+        return {"message": "public1"}
+
+    @app.post("/public2")
+    def public2():
+        return {"message": "public2"}
+
+    # Apply customization
+    add_auth_responses_to_openapi(app)
+
+    schema = app.openapi()
+
+    # Component should still be added for consistency
+    assert "HTTP401NotAuthenticatedError" in schema["components"]["responses"]
+
+    # But no endpoints should have 401 responses
+    for path in schema["paths"].values():
+        for method in path.values():
+            if isinstance(method, dict) and "responses" in method:
+                assert "401" not in method["responses"]
+
+
+def test_add_auth_responses_to_openapi_multiple_security_schemes():
+    """Test endpoints with multiple security requirements."""
+    app = FastAPI()
+
+    from fastapi import Security
+
+    from autogpt_libs.auth.dependencies import requires_admin_user, requires_user
+    from autogpt_libs.auth.models import User
+
+    @app.get("/multi-auth")
+    def multi_auth(
+        user: User = Security(requires_user),
+        admin: User = Security(requires_admin_user),
+    ):
+        return {"status": "super secure"}
+
+    # Apply customization
+    add_auth_responses_to_openapi(app)
+
+    schema = app.openapi()
+
+    # Should have 401 response
+    if "/multi-auth" in schema["paths"]:
+        if "get" in schema["paths"]["/multi-auth"]:
+            responses = schema["paths"]["/multi-auth"]["get"].get("responses", {})
+            if "401" in responses:
+                assert (
+                    responses["401"]["$ref"]
+                    == "#/components/responses/HTTP401NotAuthenticatedError"
+                )
+
+
+def test_add_auth_responses_to_openapi_empty_components():
+    """Test when OpenAPI schema has no components section initially."""
+    app = FastAPI()
+
+    # Mock get_openapi to return schema without components
+    original_get_openapi = get_openapi
+
+    def mock_get_openapi(*args, **kwargs):
+        schema = original_get_openapi(*args, **kwargs)
+        # Remove components if it exists
+        if "components" in schema:
+            del schema["components"]
+        return schema
+
+    with mock.patch("autogpt_libs.auth.helpers.get_openapi", mock_get_openapi):
+        # Apply customization
+        add_auth_responses_to_openapi(app)
+
+        schema = app.openapi()
+
+        # Components should be created
+        assert "components" in schema
+        assert "responses" in schema["components"]
+        assert "HTTP401NotAuthenticatedError" in schema["components"]["responses"]
+
+
+def test_add_auth_responses_to_openapi_all_http_methods():
+    """Test that all HTTP methods are handled correctly."""
+    app = FastAPI()
+
+    from fastapi import Security
+
+    from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+    @app.get("/resource")
+    def get_resource(jwt: dict = Security(get_jwt_payload)):
+        return {"method": "GET"}
+
+    @app.post("/resource")
+    def post_resource(jwt: dict = Security(get_jwt_payload)):
+        return {"method": "POST"}
+
+    @app.put("/resource")
+    def put_resource(jwt: dict = Security(get_jwt_payload)):
+        return {"method": "PUT"}
+
+    @app.patch("/resource")
+    def patch_resource(jwt: dict = Security(get_jwt_payload)):
+        return {"method": "PATCH"}
+
+    @app.delete("/resource")
+    def delete_resource(jwt: dict = Security(get_jwt_payload)):
+        return {"method": "DELETE"}
+
+    # Apply customization
+    add_auth_responses_to_openapi(app)
+
+    schema = app.openapi()
+
+    # All methods should have 401 response
+    if "/resource" in schema["paths"]:
+        for method in ["get", "post", "put", "patch", "delete"]:
+            if method in schema["paths"]["/resource"]:
+                method_spec = schema["paths"]["/resource"][method]
+                if "responses" in method_spec:
+                    assert "401" in method_spec["responses"]
+
+
+def test_bearer_jwt_auth_scheme_config():
+    """Test that bearer_jwt_auth is configured correctly."""
+    assert bearer_jwt_auth.scheme_name == "HTTPBearerJWT"
+    assert bearer_jwt_auth.auto_error is False
+
+
+def test_add_auth_responses_with_no_routes():
+    """Test OpenAPI generation with app that has no routes."""
+    app = FastAPI(title="Empty App")
+
+    # Apply customization to empty app
+    add_auth_responses_to_openapi(app)
+
+    schema = app.openapi()
+
+    # Should still have basic structure
+    assert schema["info"]["title"] == "Empty App"
+    assert "components" in schema
+    assert "responses" in schema["components"]
+    assert "HTTP401NotAuthenticatedError" in schema["components"]["responses"]
+
+
+def test_custom_openapi_function_replacement():
+    """Test that the custom openapi function properly replaces the default."""
+    app = FastAPI()
+
+    # Store original function
+    original_openapi = app.openapi
+
+    # Apply customization
+    add_auth_responses_to_openapi(app)
+
+    # Function should be replaced
+    assert app.openapi != original_openapi
+    assert callable(app.openapi)
+
+
+def test_endpoint_without_responses_section():
+    """Test endpoint that has security but no responses section initially."""
+    app = FastAPI()
+
+    from fastapi import Security
+    from fastapi.openapi.utils import get_openapi as original_get_openapi
+
+    from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+    # Create endpoint
+    @app.get("/no-responses")
+    def endpoint_without_responses(jwt: dict = Security(get_jwt_payload)):
+        return {"data": "test"}
+
+    # Mock get_openapi to remove responses from the endpoint
+    def mock_get_openapi(*args, **kwargs):
+        schema = original_get_openapi(*args, **kwargs)
+        # Remove responses from our endpoint to trigger line 40
+        if "/no-responses" in schema.get("paths", {}):
+            if "get" in schema["paths"]["/no-responses"]:
+                # Delete responses to force the code to create it
+                if "responses" in schema["paths"]["/no-responses"]["get"]:
+                    del schema["paths"]["/no-responses"]["get"]["responses"]
+        return schema
+
+    with mock.patch("autogpt_libs.auth.helpers.get_openapi", mock_get_openapi):
+        # Apply customization
+        add_auth_responses_to_openapi(app)
+
+        # Get schema and verify 401 was added
+        schema = app.openapi()
+
+        # The endpoint should now have 401 response
+        if "/no-responses" in schema["paths"]:
+            if "get" in schema["paths"]["/no-responses"]:
+                responses = schema["paths"]["/no-responses"]["get"].get("responses", {})
+                assert "401" in responses
+                assert (
+                    responses["401"]["$ref"]
+                    == "#/components/responses/HTTP401NotAuthenticatedError"
+                )
+
+
+def test_components_with_existing_responses():
+    """Test when components already has a responses section."""
+    app = FastAPI()
+
+    # Mock get_openapi to return schema with existing components/responses
+    from fastapi.openapi.utils import get_openapi as original_get_openapi
+
+    def mock_get_openapi(*args, **kwargs):
+        schema = original_get_openapi(*args, **kwargs)
+        # Add existing components/responses
+        if "components" not in schema:
+            schema["components"] = {}
+        schema["components"]["responses"] = {
+            "ExistingResponse": {"description": "An existing response"}
+        }
+        return schema
+
+    with mock.patch("autogpt_libs.auth.helpers.get_openapi", mock_get_openapi):
+        # Apply customization
+        add_auth_responses_to_openapi(app)
+
+        schema = app.openapi()
+
+        # Both responses should exist
+        assert "ExistingResponse" in schema["components"]["responses"]
+        assert "HTTP401NotAuthenticatedError" in schema["components"]["responses"]
+
+        # Verify our 401 response structure
+        error_response = schema["components"]["responses"][
+            "HTTP401NotAuthenticatedError"
+        ]
+        assert error_response["description"] == "Authentication required"
+
+
+def test_openapi_schema_persistence():
+    """Test that modifications to OpenAPI schema persist correctly."""
+    app = FastAPI()
+
+    from fastapi import Security
+
+    from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+    @app.get("/test")
+    def test_endpoint(jwt: dict = Security(get_jwt_payload)):
+        return {"test": True}
+
+    # Apply customization
+    add_auth_responses_to_openapi(app)
+
+    # Get schema multiple times
+    schema1 = app.openapi()
+
+    # Modify the cached schema (shouldn't affect future calls)
+    schema1["info"]["title"] = "Modified Title"
+
+    # Clear cache and get again
+    app.openapi_schema = None
+    schema2 = app.openapi()
+
+    # Should regenerate with original title
+    assert schema2["info"]["title"] == app.title
+    assert schema2["info"]["title"] != "Modified Title"

autogpt_platform/autogpt_libs/autogpt_libs/auth/jwt_utils.py

@@ -1,11 +1,48 @@
-from typing import Any, Dict
+import logging
+from typing import Any
 
 import jwt
+from fastapi import HTTPException, Security
+from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
 
-from .config import settings
+from .config import get_settings
+from .models import User
+
+logger = logging.getLogger(__name__)
+
+# Bearer token authentication scheme
+bearer_jwt_auth = HTTPBearer(
+    bearerFormat="jwt", scheme_name="HTTPBearerJWT", auto_error=False
+)
 
 
-def parse_jwt_token(token: str) -> Dict[str, Any]:
+def get_jwt_payload(
+    credentials: HTTPAuthorizationCredentials | None = Security(bearer_jwt_auth),
+) -> dict[str, Any]:
+    """
+    Extract and validate JWT payload from HTTP Authorization header.
+
+    This is the core authentication function that handles:
+    - Reading the `Authorization` header to obtain the JWT token
+    - Verifying the JWT token's signature
+    - Decoding the JWT token's payload
+
+    :param credentials: HTTP Authorization credentials from bearer token
+    :return: JWT payload dictionary
+    :raises HTTPException: 401 if authentication fails
+    """
+    if not credentials:
+        raise HTTPException(status_code=401, detail="Authorization header is missing")
+
+    try:
+        payload = parse_jwt_token(credentials.credentials)
+        logger.debug("Token decoded successfully")
+        return payload
+    except ValueError as e:
+        raise HTTPException(status_code=401, detail=str(e))
+
+
+def parse_jwt_token(token: str) -> dict[str, Any]:
     """
     Parse and validate a JWT token.
 
@@ -13,10 +50,11 @@ def parse_jwt_token(token: str) -> Dict[str, Any]:
     :return: The decoded payload
     :raises ValueError: If the token is invalid or expired
     """
+    settings = get_settings()
     try:
         payload = jwt.decode(
             token,
-            settings.JWT_SECRET_KEY,
+            settings.JWT_VERIFY_KEY,
             algorithms=[settings.JWT_ALGORITHM],
             audience="authenticated",
         )
@@ -25,3 +63,18 @@ def parse_jwt_token(token: str) -> Dict[str, Any]:
         raise ValueError("Token has expired")
     except jwt.InvalidTokenError as e:
         raise ValueError(f"Invalid token: {str(e)}")
+
+
+def verify_user(jwt_payload: dict | None, admin_only: bool) -> User:
+    if jwt_payload is None:
+        raise HTTPException(status_code=401, detail="Authorization header is missing")
+
+    user_id = jwt_payload.get("sub")
+
+    if not user_id:
+        raise HTTPException(status_code=401, detail="User ID not found in token")
+
+    if admin_only and jwt_payload["role"] != "admin":
+        raise HTTPException(status_code=403, detail="Admin access required")
+
+    return User.from_payload(jwt_payload)

autogpt_platform/autogpt_libs/autogpt_libs/auth/jwt_utils_test.py

@@ -0,0 +1,308 @@
+"""
+Comprehensive tests for JWT token parsing and validation.
+Ensures 100% line and branch coverage for JWT security functions.
+"""
+
+import os
+from datetime import datetime, timedelta, timezone
+
+import jwt
+import pytest
+from fastapi import HTTPException
+from fastapi.security import HTTPAuthorizationCredentials
+from pytest_mock import MockerFixture
+
+from autogpt_libs.auth import config, jwt_utils
+from autogpt_libs.auth.config import Settings
+from autogpt_libs.auth.models import User
+
+MOCK_JWT_SECRET = "test-secret-key-with-at-least-32-characters"
+TEST_USER_PAYLOAD = {
+    "sub": "test-user-id",
+    "role": "user",
+    "aud": "authenticated",
+    "email": "test@example.com",
+}
+TEST_ADMIN_PAYLOAD = {
+    "sub": "admin-user-id",
+    "role": "admin",
+    "aud": "authenticated",
+    "email": "admin@example.com",
+}
+
+
+@pytest.fixture(autouse=True)
+def mock_config(mocker: MockerFixture):
+    mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": MOCK_JWT_SECRET}, clear=True)
+    mocker.patch.object(config, "_settings", Settings())
+    yield
+
+
+def create_token(payload, secret=None, algorithm="HS256"):
+    """Helper to create JWT tokens."""
+    if secret is None:
+        secret = MOCK_JWT_SECRET
+    return jwt.encode(payload, secret, algorithm=algorithm)
+
+
+def test_parse_jwt_token_valid():
+    """Test parsing a valid JWT token."""
+    token = create_token(TEST_USER_PAYLOAD)
+    result = jwt_utils.parse_jwt_token(token)
+
+    assert result["sub"] == "test-user-id"
+    assert result["role"] == "user"
+    assert result["aud"] == "authenticated"
+
+
+def test_parse_jwt_token_expired():
+    """Test parsing an expired JWT token."""
+    expired_payload = {
+        **TEST_USER_PAYLOAD,
+        "exp": datetime.now(timezone.utc) - timedelta(hours=1),
+    }
+    token = create_token(expired_payload)
+
+    with pytest.raises(ValueError) as exc_info:
+        jwt_utils.parse_jwt_token(token)
+    assert "Token has expired" in str(exc_info.value)
+
+
+def test_parse_jwt_token_invalid_signature():
+    """Test parsing a token with invalid signature."""
+    # Create token with different secret
+    token = create_token(TEST_USER_PAYLOAD, secret="wrong-secret")
+
+    with pytest.raises(ValueError) as exc_info:
+        jwt_utils.parse_jwt_token(token)
+    assert "Invalid token" in str(exc_info.value)
+
+
+def test_parse_jwt_token_malformed():
+    """Test parsing a malformed token."""
+    malformed_tokens = [
+        "not.a.token",
+        "invalid",
+        "",
+        # Header only
+        "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9",
+        # No signature
+        "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJ0ZXN0In0",
+    ]
+
+    for token in malformed_tokens:
+        with pytest.raises(ValueError) as exc_info:
+            jwt_utils.parse_jwt_token(token)
+        assert "Invalid token" in str(exc_info.value)
+
+
+def test_parse_jwt_token_wrong_audience():
+    """Test parsing a token with wrong audience."""
+    wrong_aud_payload = {**TEST_USER_PAYLOAD, "aud": "wrong-audience"}
+    token = create_token(wrong_aud_payload)
+
+    with pytest.raises(ValueError) as exc_info:
+        jwt_utils.parse_jwt_token(token)
+    assert "Invalid token" in str(exc_info.value)
+
+
+def test_parse_jwt_token_missing_audience():
+    """Test parsing a token without audience claim."""
+    no_aud_payload = {k: v for k, v in TEST_USER_PAYLOAD.items() if k != "aud"}
+    token = create_token(no_aud_payload)
+
+    with pytest.raises(ValueError) as exc_info:
+        jwt_utils.parse_jwt_token(token)
+    assert "Invalid token" in str(exc_info.value)
+
+
+def test_get_jwt_payload_with_valid_token():
+    """Test extracting JWT payload with valid bearer token."""
+    token = create_token(TEST_USER_PAYLOAD)
+    credentials = HTTPAuthorizationCredentials(scheme="Bearer", credentials=token)
+
+    result = jwt_utils.get_jwt_payload(credentials)
+    assert result["sub"] == "test-user-id"
+    assert result["role"] == "user"
+
+
+def test_get_jwt_payload_no_credentials():
+    """Test JWT payload when no credentials provided."""
+    with pytest.raises(HTTPException) as exc_info:
+        jwt_utils.get_jwt_payload(None)
+    assert exc_info.value.status_code == 401
+    assert "Authorization header is missing" in exc_info.value.detail
+
+
+def test_get_jwt_payload_invalid_token():
+    """Test JWT payload extraction with invalid token."""
+    credentials = HTTPAuthorizationCredentials(
+        scheme="Bearer", credentials="invalid.token.here"
+    )
+
+    with pytest.raises(HTTPException) as exc_info:
+        jwt_utils.get_jwt_payload(credentials)
+    assert exc_info.value.status_code == 401
+    assert "Invalid token" in exc_info.value.detail
+
+
+def test_verify_user_with_valid_user():
+    """Test verifying a valid user."""
+    user = jwt_utils.verify_user(TEST_USER_PAYLOAD, admin_only=False)
+    assert isinstance(user, User)
+    assert user.user_id == "test-user-id"
+    assert user.role == "user"
+    assert user.email == "test@example.com"
+
+
+def test_verify_user_with_admin():
+    """Test verifying an admin user."""
+    user = jwt_utils.verify_user(TEST_ADMIN_PAYLOAD, admin_only=True)
+    assert isinstance(user, User)
+    assert user.user_id == "admin-user-id"
+    assert user.role == "admin"
+
+
+def test_verify_user_admin_only_with_regular_user():
+    """Test verifying regular user when admin is required."""
+    with pytest.raises(HTTPException) as exc_info:
+        jwt_utils.verify_user(TEST_USER_PAYLOAD, admin_only=True)
+    assert exc_info.value.status_code == 403
+    assert "Admin access required" in exc_info.value.detail
+
+
+def test_verify_user_no_payload():
+    """Test verifying user with no payload."""
+    with pytest.raises(HTTPException) as exc_info:
+        jwt_utils.verify_user(None, admin_only=False)
+    assert exc_info.value.status_code == 401
+    assert "Authorization header is missing" in exc_info.value.detail
+
+
+def test_verify_user_missing_sub():
+    """Test verifying user with payload missing 'sub' field."""
+    invalid_payload = {"role": "user", "email": "test@example.com"}
+    with pytest.raises(HTTPException) as exc_info:
+        jwt_utils.verify_user(invalid_payload, admin_only=False)
+    assert exc_info.value.status_code == 401
+    assert "User ID not found in token" in exc_info.value.detail
+
+
+def test_verify_user_empty_sub():
+    """Test verifying user with empty 'sub' field."""
+    invalid_payload = {"sub": "", "role": "user"}
+    with pytest.raises(HTTPException) as exc_info:
+        jwt_utils.verify_user(invalid_payload, admin_only=False)
+    assert exc_info.value.status_code == 401
+    assert "User ID not found in token" in exc_info.value.detail
+
+
+def test_verify_user_none_sub():
+    """Test verifying user with None 'sub' field."""
+    invalid_payload = {"sub": None, "role": "user"}
+    with pytest.raises(HTTPException) as exc_info:
+        jwt_utils.verify_user(invalid_payload, admin_only=False)
+    assert exc_info.value.status_code == 401
+    assert "User ID not found in token" in exc_info.value.detail
+
+
+def test_verify_user_missing_role_admin_check():
+    """Test verifying admin when role field is missing."""
+    no_role_payload = {"sub": "user-id"}
+    with pytest.raises(KeyError):
+        # This will raise KeyError when checking payload["role"]
+        jwt_utils.verify_user(no_role_payload, admin_only=True)
+
+
+# ======================== EDGE CASES ======================== #
+
+
+def test_jwt_with_additional_claims():
+    """Test JWT token with additional custom claims."""
+    extra_claims_payload = {
+        "sub": "user-id",
+        "role": "user",
+        "aud": "authenticated",
+        "custom_claim": "custom_value",
+        "permissions": ["read", "write"],
+        "metadata": {"key": "value"},
+    }
+    token = create_token(extra_claims_payload)
+
+    result = jwt_utils.parse_jwt_token(token)
+    assert result["sub"] == "user-id"
+    assert result["custom_claim"] == "custom_value"
+    assert result["permissions"] == ["read", "write"]
+
+
+def test_jwt_with_numeric_sub():
+    """Test JWT token with numeric user ID."""
+    payload = {
+        "sub": 12345,  # Numeric ID
+        "role": "user",
+        "aud": "authenticated",
+    }
+    # Should convert to string internally
+    user = jwt_utils.verify_user(payload, admin_only=False)
+    assert user.user_id == 12345
+
+
+def test_jwt_with_very_long_sub():
+    """Test JWT token with very long user ID."""
+    long_id = "a" * 1000
+    payload = {
+        "sub": long_id,
+        "role": "user",
+        "aud": "authenticated",
+    }
+    user = jwt_utils.verify_user(payload, admin_only=False)
+    assert user.user_id == long_id
+
+
+def test_jwt_with_special_characters_in_claims():
+    """Test JWT token with special characters in claims."""
+    payload = {
+        "sub": "user@example.com/special-chars!@#$%",
+        "role": "admin",
+        "aud": "authenticated",
+        "email": "test+special@example.com",
+    }
+    user = jwt_utils.verify_user(payload, admin_only=True)
+    assert "special-chars!@#$%" in user.user_id
+
+
+def test_jwt_with_future_iat():
+    """Test JWT token with issued-at time in future."""
+    future_payload = {
+        "sub": "user-id",
+        "role": "user",
+        "aud": "authenticated",
+        "iat": datetime.now(timezone.utc) + timedelta(hours=1),
+    }
+    token = create_token(future_payload)
+
+    # PyJWT validates iat claim and should reject future tokens
+    with pytest.raises(ValueError, match="not yet valid"):
+        jwt_utils.parse_jwt_token(token)
+
+
+def test_jwt_with_different_algorithms():
+    """Test that only HS256 algorithm is accepted."""
+    payload = {
+        "sub": "user-id",
+        "role": "user",
+        "aud": "authenticated",
+    }
+
+    # Try different algorithms
+    algorithms = ["HS384", "HS512", "none"]
+    for algo in algorithms:
+        if algo == "none":
+            # Special case for 'none' algorithm (security vulnerability if accepted)
+            token = create_token(payload, "", algorithm="none")
+        else:
+            token = create_token(payload, algorithm=algo)
+
+        with pytest.raises(ValueError) as exc_info:
+            jwt_utils.parse_jwt_token(token)
+        assert "Invalid token" in str(exc_info.value)

autogpt_platform/autogpt_libs/autogpt_libs/auth/middleware.py

@@ -1,140 +0,0 @@
-import inspect
-import logging
-import secrets
-from typing import Any, Callable, Optional
-
-from fastapi import HTTPException, Request, Security
-from fastapi.security import APIKeyHeader, HTTPBearer
-from starlette.status import HTTP_401_UNAUTHORIZED
-
-from .config import settings
-from .jwt_utils import parse_jwt_token
-
-security = HTTPBearer()
-logger = logging.getLogger(__name__)
-
-
-async def auth_middleware(request: Request):
-    if not settings.ENABLE_AUTH:
-        # If authentication is disabled, allow the request to proceed
-        logger.warning("Auth disabled")
-        return {}
-
-    security = HTTPBearer()
-    credentials = await security(request)
-
-    if not credentials:
-        raise HTTPException(status_code=401, detail="Authorization header is missing")
-
-    try:
-        payload = parse_jwt_token(credentials.credentials)
-        request.state.user = payload
-        logger.debug("Token decoded successfully")
-    except ValueError as e:
-        raise HTTPException(status_code=401, detail=str(e))
-    return payload
-
-
-class APIKeyValidator:
-    """
-    Configurable API key validator that supports custom validation functions
-    for FastAPI applications.
-
-    This class provides a flexible way to implement API key authentication with optional
-    custom validation logic. It can be used for simple token matching
-    or more complex validation scenarios like database lookups.
-
-    Examples:
-        Simple token validation:
-        ```python
-        validator = APIKeyValidator(
-            header_name="X-API-Key",
-            expected_token="your-secret-token"
-        )
-
-        @app.get("/protected", dependencies=[Depends(validator.get_dependency())])
-        def protected_endpoint():
-            return {"message": "Access granted"}
-        ```
-
-        Custom validation with database lookup:
-        ```python
-        async def validate_with_db(api_key: str):
-            api_key_obj = await db.get_api_key(api_key)
-            return api_key_obj if api_key_obj and api_key_obj.is_active else None
-
-        validator = APIKeyValidator(
-            header_name="X-API-Key",
-            validate_fn=validate_with_db
-        )
-        ```
-
-    Args:
-        header_name (str): The name of the header containing the API key
-        expected_token (Optional[str]): The expected API key value for simple token matching
-        validate_fn (Optional[Callable]): Custom validation function that takes an API key
-            string and returns a boolean or object. Can be async.
-        error_status (int): HTTP status code to use for validation errors
-        error_message (str): Error message to return when validation fails
-    """
-
-    def __init__(
-        self,
-        header_name: str,
-        expected_token: Optional[str] = None,
-        validate_fn: Optional[Callable[[str], bool]] = None,
-        error_status: int = HTTP_401_UNAUTHORIZED,
-        error_message: str = "Invalid API key",
-    ):
-        # Create the APIKeyHeader as a class property
-        self.security_scheme = APIKeyHeader(name=header_name)
-        self.expected_token = expected_token
-        self.custom_validate_fn = validate_fn
-        self.error_status = error_status
-        self.error_message = error_message
-
-    async def default_validator(self, api_key: str) -> bool:
-        if not self.expected_token:
-            raise ValueError(
-                "Expected Token Required to be set when uisng API Key Validator default validation"
-            )
-        return secrets.compare_digest(api_key, self.expected_token)
-
-    async def __call__(
-        self, request: Request, api_key: str = Security(APIKeyHeader)
-    ) -> Any:
-        if api_key is None:
-            raise HTTPException(status_code=self.error_status, detail="Missing API key")
-
-        # Use custom validation if provided, otherwise use default equality check
-        validator = self.custom_validate_fn or self.default_validator
-        result = (
-            await validator(api_key)
-            if inspect.iscoroutinefunction(validator)
-            else validator(api_key)
-        )
-
-        if not result:
-            raise HTTPException(
-                status_code=self.error_status, detail=self.error_message
-            )
-
-        # Store validation result in request state if it's not just a boolean
-        if result is not True:
-            request.state.api_key = result
-
-        return result
-
-    def get_dependency(self):
-        """
-        Returns a callable dependency that FastAPI will recognize as a security scheme
-        """
-
-        async def validate_api_key(
-            request: Request, api_key: str = Security(self.security_scheme)
-        ) -> Any:
-            return await self(request, api_key)
-
-        # This helps FastAPI recognize it as a security dependency
-        validate_api_key.__name__ = f"validate_{self.security_scheme.model.name}"
-        return validate_api_key

autogpt_platform/autogpt_libs/autogpt_libs/rate_limit/config.py

@@ -1,3 +1,5 @@
+from typing import Optional
+
 from pydantic import Field
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
@@ -13,8 +15,8 @@ class RateLimitSettings(BaseSettings):
         default="6379", description="Redis port", validation_alias="REDIS_PORT"
     )
 
-    redis_password: str = Field(
-        default="password",
+    redis_password: Optional[str] = Field(
+        default=None,
         description="Redis password",
         validation_alias="REDIS_PASSWORD",
     )

autogpt_platform/autogpt_libs/autogpt_libs/rate_limit/limiter.py

@@ -11,7 +11,7 @@ class RateLimiter:
         self,
         redis_host: str = RATE_LIMIT_SETTINGS.redis_host,
         redis_port: str = RATE_LIMIT_SETTINGS.redis_port,
-        redis_password: str = RATE_LIMIT_SETTINGS.redis_password,
+        redis_password: str | None = RATE_LIMIT_SETTINGS.redis_password,
         requests_per_minute: int = RATE_LIMIT_SETTINGS.requests_per_minute,
     ):
         self.redis = Redis(

autogpt_platform/autogpt_libs/autogpt_libs/utils/cache.py

@@ -1,90 +1,68 @@
+import asyncio
 import inspect
 import logging
 import threading
 import time
 from functools import wraps
 from typing import (
-    Awaitable,
+    Any,
     Callable,
     ParamSpec,
     Protocol,
-    Tuple,
     TypeVar,
     cast,
-    overload,
     runtime_checkable,
 )
 
 P = ParamSpec("P")
 R = TypeVar("R")
+R_co = TypeVar("R_co", covariant=True)
 
 logger = logging.getLogger(__name__)
 
 
-@overload
-def thread_cached(func: Callable[P, Awaitable[R]]) -> Callable[P, Awaitable[R]]:
-    pass
+def _make_hashable_key(
+    args: tuple[Any, ...], kwargs: dict[str, Any]
+) -> tuple[Any, ...]:
+    """
+    Convert args and kwargs into a hashable cache key.
 
+    Handles unhashable types like dict, list, set by converting them to
+    their sorted string representations.
+    """
 
-@overload
-def thread_cached(func: Callable[P, R]) -> Callable[P, R]:
-    pass
+    def make_hashable(obj: Any) -> Any:
+        """Recursively convert an object to a hashable representation."""
+        if isinstance(obj, dict):
+            # Sort dict items to ensure consistent ordering
+            return (
+                "__dict__",
+                tuple(sorted((k, make_hashable(v)) for k, v in obj.items())),
+            )
+        elif isinstance(obj, (list, tuple)):
+            return ("__list__", tuple(make_hashable(item) for item in obj))
+        elif isinstance(obj, set):
+            return ("__set__", tuple(sorted(make_hashable(item) for item in obj)))
+        elif hasattr(obj, "__dict__"):
+            # Handle objects with __dict__ attribute
+            return ("__obj__", obj.__class__.__name__, make_hashable(obj.__dict__))
+        else:
+            # For basic hashable types (str, int, bool, None, etc.)
+            try:
+                hash(obj)
+                return obj
+            except TypeError:
+                # Fallback: convert to string representation
+                return ("__str__", str(obj))
 
-
-def thread_cached(
-    func: Callable[P, R] | Callable[P, Awaitable[R]],
-) -> Callable[P, R] | Callable[P, Awaitable[R]]:
-    thread_local = threading.local()
-
-    def _clear():
-        if hasattr(thread_local, "cache"):
-            del thread_local.cache
-
-    if inspect.iscoroutinefunction(func):
-
-        async def async_wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
-            cache = getattr(thread_local, "cache", None)
-            if cache is None:
-                cache = thread_local.cache = {}
-            key = (args, tuple(sorted(kwargs.items())))
-            if key not in cache:
-                cache[key] = await cast(Callable[P, Awaitable[R]], func)(
-                    *args, **kwargs
-                )
-            return cache[key]
-
-        setattr(async_wrapper, "clear_cache", _clear)
-        return async_wrapper
-
-    else:
-
-        def sync_wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
-            cache = getattr(thread_local, "cache", None)
-            if cache is None:
-                cache = thread_local.cache = {}
-            key = (args, tuple(sorted(kwargs.items())))
-            if key not in cache:
-                cache[key] = func(*args, **kwargs)
-            return cache[key]
-
-        setattr(sync_wrapper, "clear_cache", _clear)
-        return sync_wrapper
-
-
-def clear_thread_cache(func: Callable) -> None:
-    if clear := getattr(func, "clear_cache", None):
-        clear()
-
-
-FuncT = TypeVar("FuncT")
-
-
-R_co = TypeVar("R_co", covariant=True)
+    hashable_args = tuple(make_hashable(arg) for arg in args)
+    hashable_kwargs = tuple(sorted((k, make_hashable(v)) for k, v in kwargs.items()))
+    return (hashable_args, hashable_kwargs)
 
 
 @runtime_checkable
-class AsyncCachedFunction(Protocol[P, R_co]):
-    """Protocol for async functions with cache management methods."""
+class CachedFunction(Protocol[P, R_co]):
+    """Protocol for cached functions with cache management methods."""
 
     def cache_clear(self) -> None:
         """Clear all cached entries."""
@@ -94,101 +72,169 @@ class AsyncCachedFunction(Protocol[P, R_co]):
         """Get cache statistics."""
         return {}
 
-    async def __call__(self, *args: P.args, **kwargs: P.kwargs) -> R_co:
+    def cache_delete(self, *args: P.args, **kwargs: P.kwargs) -> bool:
+        """Delete a specific cache entry by its arguments. Returns True if entry existed."""
+        return False
+
+    def __call__(self, *args: P.args, **kwargs: P.kwargs) -> R_co:
         """Call the cached function."""
         return None  # type: ignore
 
 
-def async_ttl_cache(
-    maxsize: int = 128, ttl_seconds: int | None = None
-) -> Callable[[Callable[P, Awaitable[R]]], AsyncCachedFunction[P, R]]:
+def cached(
+    *,
+    maxsize: int = 128,
+    ttl_seconds: int | None = None,
+) -> Callable[[Callable], CachedFunction]:
     """
-    TTL (Time To Live) cache decorator for async functions.
+    Thundering herd safe cache decorator for both sync and async functions.
 
-    Similar to functools.lru_cache but works with async functions and includes optional TTL.
+    Uses double-checked locking to prevent multiple threads/coroutines from
+    executing the expensive operation simultaneously during cache misses.
 
     Args:
+        func: The function to cache (when used without parentheses)
         maxsize: Maximum number of cached entries
-        ttl_seconds: Time to live in seconds. If None, entries never expire (like lru_cache)
+        ttl_seconds: Time to live in seconds. If None, entries never expire
 
     Returns:
-        Decorator function
+        Decorated function or decorator
 
     Example:
-        # With TTL
-        @async_ttl_cache(maxsize=1000, ttl_seconds=300)
-        async def api_call(param: str) -> dict:
+        @cache()  # Default: maxsize=128, no TTL
+        def expensive_sync_operation(param: str) -> dict:
             return {"result": param}
 
-        # Without TTL (permanent cache like lru_cache)
-        @async_ttl_cache(maxsize=1000)
-        async def expensive_computation(param: str) -> dict:
+        @cache()  # Works with async too
+        async def expensive_async_operation(param: str) -> dict:
+            return {"result": param}
+
+        @cache(maxsize=1000, ttl_seconds=300)  # Custom maxsize and TTL
+        def another_operation(param: str) -> dict:
             return {"result": param}
     """
 
-    def decorator(
-        async_func: Callable[P, Awaitable[R]],
-    ) -> AsyncCachedFunction[P, R]:
-        # Cache storage - use union type to handle both cases
-        cache_storage: dict[tuple, R | Tuple[R, float]] = {}
+    def decorator(target_func):
+        # Cache storage and locks
+        cache_storage = {}
 
-        @wraps(async_func)
-        async def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
-            # Create cache key from arguments
-            key = (args, tuple(sorted(kwargs.items())))
-            current_time = time.time()
+        if inspect.iscoroutinefunction(target_func):
+            # Async function with asyncio.Lock
+            cache_lock = asyncio.Lock()
 
-            # Check if we have a valid cached entry
-            if key in cache_storage:
-                if ttl_seconds is None:
-                    # No TTL - return cached result directly
-                    logger.debug(
-                        f"Cache hit for {async_func.__name__} with key: {str(key)[:50]}"
-                    )
-                    return cast(R, cache_storage[key])
-                else:
-                    # With TTL - check expiration
-                    cached_data = cache_storage[key]
-                    if isinstance(cached_data, tuple):
-                        result, timestamp = cached_data
-                        if current_time - timestamp < ttl_seconds:
-                            logger.debug(
-                                f"Cache hit for {async_func.__name__} with key: {str(key)[:50]}"
-                            )
-                            return cast(R, result)
+            @wraps(target_func)
+            async def async_wrapper(*args: P.args, **kwargs: P.kwargs):
+                key = _make_hashable_key(args, kwargs)
+                current_time = time.time()
+
+                # Fast path: check cache without lock
+                if key in cache_storage:
+                    if ttl_seconds is None:
+                        logger.debug(f"Cache hit for {target_func.__name__}")
+                        return cache_storage[key]
+                    else:
+                        cached_data = cache_storage[key]
+                        if isinstance(cached_data, tuple):
+                            result, timestamp = cached_data
+                            if current_time - timestamp < ttl_seconds:
+                                logger.debug(f"Cache hit for {target_func.__name__}")
+                                return result
+
+                # Slow path: acquire lock for cache miss/expiry
+                async with cache_lock:
+                    # Double-check: another coroutine might have populated cache
+                    if key in cache_storage:
+                        if ttl_seconds is None:
+                            return cache_storage[key]
                         else:
-                            # Expired entry
-                            del cache_storage[key]
-                            logger.debug(
-                                f"Cache entry expired for {async_func.__name__}"
-                            )
+                            cached_data = cache_storage[key]
+                            if isinstance(cached_data, tuple):
+                                result, timestamp = cached_data
+                                if current_time - timestamp < ttl_seconds:
+                                    return result
 
-            # Cache miss or expired - fetch fresh data
-            logger.debug(
-                f"Cache miss for {async_func.__name__} with key: {str(key)[:50]}"
-            )
-            result = await async_func(*args, **kwargs)
+                    # Cache miss - execute function
+                    logger.debug(f"Cache miss for {target_func.__name__}")
+                    result = await target_func(*args, **kwargs)
 
-            # Store in cache
-            if ttl_seconds is None:
-                cache_storage[key] = result
-            else:
-                cache_storage[key] = (result, current_time)
+                    # Store result
+                    if ttl_seconds is None:
+                        cache_storage[key] = result
+                    else:
+                        cache_storage[key] = (result, current_time)
 
-            # Simple cleanup when cache gets too large
-            if len(cache_storage) > maxsize:
-                # Remove oldest entries (simple FIFO cleanup)
-                cutoff = maxsize // 2
-                oldest_keys = list(cache_storage.keys())[:-cutoff] if cutoff > 0 else []
-                for old_key in oldest_keys:
-                    cache_storage.pop(old_key, None)
-                logger.debug(
-                    f"Cache cleanup: removed {len(oldest_keys)} entries for {async_func.__name__}"
-                )
+                    # Cleanup if needed
+                    if len(cache_storage) > maxsize:
+                        cutoff = maxsize // 2
+                        oldest_keys = (
+                            list(cache_storage.keys())[:-cutoff] if cutoff > 0 else []
+                        )
+                        for old_key in oldest_keys:
+                            cache_storage.pop(old_key, None)
 
-            return result
+                    return result
 
-        # Add cache management methods (similar to functools.lru_cache)
+            wrapper = async_wrapper
+
+        else:
+            # Sync function with threading.Lock
+            cache_lock = threading.Lock()
+
+            @wraps(target_func)
+            def sync_wrapper(*args: P.args, **kwargs: P.kwargs):
+                key = _make_hashable_key(args, kwargs)
+                current_time = time.time()
+
+                # Fast path: check cache without lock
+                if key in cache_storage:
+                    if ttl_seconds is None:
+                        logger.debug(f"Cache hit for {target_func.__name__}")
+                        return cache_storage[key]
+                    else:
+                        cached_data = cache_storage[key]
+                        if isinstance(cached_data, tuple):
+                            result, timestamp = cached_data
+                            if current_time - timestamp < ttl_seconds:
+                                logger.debug(f"Cache hit for {target_func.__name__}")
+                                return result
+
+                # Slow path: acquire lock for cache miss/expiry
+                with cache_lock:
+                    # Double-check: another thread might have populated cache
+                    if key in cache_storage:
+                        if ttl_seconds is None:
+                            return cache_storage[key]
+                        else:
+                            cached_data = cache_storage[key]
+                            if isinstance(cached_data, tuple):
+                                result, timestamp = cached_data
+                                if current_time - timestamp < ttl_seconds:
+                                    return result
+
+                    # Cache miss - execute function
+                    logger.debug(f"Cache miss for {target_func.__name__}")
+                    result = target_func(*args, **kwargs)
+
+                    # Store result
+                    if ttl_seconds is None:
+                        cache_storage[key] = result
+                    else:
+                        cache_storage[key] = (result, current_time)
+
+                    # Cleanup if needed
+                    if len(cache_storage) > maxsize:
+                        cutoff = maxsize // 2
+                        oldest_keys = (
+                            list(cache_storage.keys())[:-cutoff] if cutoff > 0 else []
+                        )
+                        for old_key in oldest_keys:
+                            cache_storage.pop(old_key, None)
+
+                    return result
+
+            wrapper = sync_wrapper
+
+        # Add cache management methods
         def cache_clear() -> None:
             cache_storage.clear()
 
@@ -199,68 +245,84 @@ def async_ttl_cache(
                 "ttl_seconds": ttl_seconds,
             }
 
-        # Attach methods to wrapper
+        def cache_delete(*args, **kwargs) -> bool:
+            """Delete a specific cache entry. Returns True if entry existed."""
+            key = _make_hashable_key(args, kwargs)
+            if key in cache_storage:
+                del cache_storage[key]
+                return True
+            return False
+
         setattr(wrapper, "cache_clear", cache_clear)
         setattr(wrapper, "cache_info", cache_info)
+        setattr(wrapper, "cache_delete", cache_delete)
 
-        return cast(AsyncCachedFunction[P, R], wrapper)
+        return cast(CachedFunction, wrapper)
 
     return decorator
 
 
-@overload
-def async_cache(
-    func: Callable[P, Awaitable[R]],
-) -> AsyncCachedFunction[P, R]:
-    pass
-
-
-@overload
-def async_cache(
-    func: None = None,
-    *,
-    maxsize: int = 128,
-) -> Callable[[Callable[P, Awaitable[R]]], AsyncCachedFunction[P, R]]:
-    pass
-
-
-def async_cache(
-    func: Callable[P, Awaitable[R]] | None = None,
-    *,
-    maxsize: int = 128,
-) -> (
-    AsyncCachedFunction[P, R]
-    | Callable[[Callable[P, Awaitable[R]]], AsyncCachedFunction[P, R]]
-):
+def thread_cached(func):
     """
-    Process-level cache decorator for async functions (no TTL).
+    Thread-local cache decorator for both sync and async functions.
 
-    Similar to functools.lru_cache but works with async functions.
-    This is a convenience wrapper around async_ttl_cache with ttl_seconds=None.
+    Each thread gets its own cache, which is useful for request-scoped caching
+    in web applications where you want to cache within a single request but
+    not across requests.
 
     Args:
-        func: The async function to cache (when used without parentheses)
-        maxsize: Maximum number of cached entries
+        func: The function to cache
 
     Returns:
-        Decorated function or decorator
+        Decorated function with thread-local caching
 
     Example:
-        # Without parentheses (uses default maxsize=128)
-        @async_cache
-        async def get_data(param: str) -> dict:
+        @thread_cached
+        def expensive_operation(param: str) -> dict:
             return {"result": param}
 
-        # With parentheses and custom maxsize
-        @async_cache(maxsize=1000)
-        async def expensive_computation(param: str) -> dict:
-            # Expensive computation here
+        @thread_cached  # Works with async too
+        async def expensive_async_operation(param: str) -> dict:
             return {"result": param}
     """
-    if func is None:
-        # Called with parentheses @async_cache() or @async_cache(maxsize=...)
-        return async_ttl_cache(maxsize=maxsize, ttl_seconds=None)
+    thread_local = threading.local()
+
+    def _clear():
+        if hasattr(thread_local, "cache"):
+            del thread_local.cache
+
+    if inspect.iscoroutinefunction(func):
+
+        @wraps(func)
+        async def async_wrapper(*args, **kwargs):
+            cache = getattr(thread_local, "cache", None)
+            if cache is None:
+                cache = thread_local.cache = {}
+            key = _make_hashable_key(args, kwargs)
+            if key not in cache:
+                cache[key] = await func(*args, **kwargs)
+            return cache[key]
+
+        setattr(async_wrapper, "clear_cache", _clear)
+        return async_wrapper
+
     else:
-        # Called without parentheses @async_cache
-        decorator = async_ttl_cache(maxsize=maxsize, ttl_seconds=None)
-        return decorator(func)
+
+        @wraps(func)
+        def sync_wrapper(*args, **kwargs):
+            cache = getattr(thread_local, "cache", None)
+            if cache is None:
+                cache = thread_local.cache = {}
+            key = _make_hashable_key(args, kwargs)
+            if key not in cache:
+                cache[key] = func(*args, **kwargs)
+            return cache[key]
+
+        setattr(sync_wrapper, "clear_cache", _clear)
+        return sync_wrapper
+
+
+def clear_thread_cache(func: Callable) -> None:
+    """Clear thread-local cache for a function."""
+    if clear := getattr(func, "clear_cache", None):
+        clear()

autogpt_platform/autogpt_libs/autogpt_libs/utils/cache_test.py

@@ -16,12 +16,7 @@ from unittest.mock import Mock
 
 import pytest
 
-from autogpt_libs.utils.cache import (
-    async_cache,
-    async_ttl_cache,
-    clear_thread_cache,
-    thread_cached,
-)
+from autogpt_libs.utils.cache import cached, clear_thread_cache, thread_cached
 
 
 class TestThreadCached:
@@ -330,102 +325,202 @@ class TestThreadCached:
         assert mock.call_count == 2
 
 
-class TestAsyncTTLCache:
-    """Tests for the @async_ttl_cache decorator."""
+class TestCache:
+    """Tests for the unified @cache decorator (works for both sync and async)."""
 
-    @pytest.mark.asyncio
-    async def test_basic_caching(self):
-        """Test basic caching functionality."""
+    def test_basic_sync_caching(self):
+        """Test basic sync caching functionality."""
         call_count = 0
 
-        @async_ttl_cache(maxsize=10, ttl_seconds=60)
-        async def cached_function(x: int, y: int = 0) -> int:
+        @cached()
+        def expensive_sync_function(x: int, y: int = 0) -> int:
+            nonlocal call_count
+            call_count += 1
+            return x + y
+
+        # First call
+        result1 = expensive_sync_function(1, 2)
+        assert result1 == 3
+        assert call_count == 1
+
+        # Second call with same args - should use cache
+        result2 = expensive_sync_function(1, 2)
+        assert result2 == 3
+        assert call_count == 1
+
+        # Different args - should call function again
+        result3 = expensive_sync_function(2, 3)
+        assert result3 == 5
+        assert call_count == 2
+
+    @pytest.mark.asyncio
+    async def test_basic_async_caching(self):
+        """Test basic async caching functionality."""
+        call_count = 0
+
+        @cached()
+        async def expensive_async_function(x: int, y: int = 0) -> int:
             nonlocal call_count
             call_count += 1
             await asyncio.sleep(0.01)  # Simulate async work
             return x + y
 
         # First call
-        result1 = await cached_function(1, 2)
+        result1 = await expensive_async_function(1, 2)
         assert result1 == 3
         assert call_count == 1
 
         # Second call with same args - should use cache
-        result2 = await cached_function(1, 2)
+        result2 = await expensive_async_function(1, 2)
         assert result2 == 3
-        assert call_count == 1  # No additional call
+        assert call_count == 1
 
         # Different args - should call function again
-        result3 = await cached_function(2, 3)
+        result3 = await expensive_async_function(2, 3)
         assert result3 == 5
         assert call_count == 2
 
-    @pytest.mark.asyncio
-    async def test_ttl_expiration(self):
-        """Test that cache entries expire after TTL."""
+    def test_sync_thundering_herd_protection(self):
+        """Test that concurrent sync calls don't cause thundering herd."""
         call_count = 0
+        results = []
 
-        @async_ttl_cache(maxsize=10, ttl_seconds=1)  # Short TTL
-        async def short_lived_cache(x: int) -> int:
+        @cached()
+        def slow_function(x: int) -> int:
             nonlocal call_count
             call_count += 1
-            return x * 2
+            time.sleep(0.1)  # Simulate expensive operation
+            return x * x
+
+        def worker():
+            result = slow_function(5)
+            results.append(result)
+
+        # Launch multiple concurrent threads
+        with ThreadPoolExecutor(max_workers=5) as executor:
+            futures = [executor.submit(worker) for _ in range(5)]
+            for future in futures:
+                future.result()
+
+        # All results should be the same
+        assert all(result == 25 for result in results)
+        # Only one thread should have executed the expensive operation
+        assert call_count == 1
+
+    @pytest.mark.asyncio
+    async def test_async_thundering_herd_protection(self):
+        """Test that concurrent async calls don't cause thundering herd."""
+        call_count = 0
+
+        @cached()
+        async def slow_async_function(x: int) -> int:
+            nonlocal call_count
+            call_count += 1
+            await asyncio.sleep(0.1)  # Simulate expensive operation
+            return x * x
+
+        # Launch concurrent coroutines
+        tasks = [slow_async_function(7) for _ in range(5)]
+        results = await asyncio.gather(*tasks)
+
+        # All results should be the same
+        assert all(result == 49 for result in results)
+        # Only one coroutine should have executed the expensive operation
+        assert call_count == 1
+
+    def test_ttl_functionality(self):
+        """Test TTL functionality with sync function."""
+        call_count = 0
+
+        @cached(maxsize=10, ttl_seconds=1)  # Short TTL
+        def ttl_function(x: int) -> int:
+            nonlocal call_count
+            call_count += 1
+            return x * 3
 
         # First call
-        result1 = await short_lived_cache(5)
-        assert result1 == 10
+        result1 = ttl_function(3)
+        assert result1 == 9
         assert call_count == 1
 
         # Second call immediately - should use cache
-        result2 = await short_lived_cache(5)
-        assert result2 == 10
+        result2 = ttl_function(3)
+        assert result2 == 9
+        assert call_count == 1
+
+        # Wait for TTL to expire
+        time.sleep(1.1)
+
+        # Third call after expiration - should call function again
+        result3 = ttl_function(3)
+        assert result3 == 9
+        assert call_count == 2
+
+    @pytest.mark.asyncio
+    async def test_async_ttl_functionality(self):
+        """Test TTL functionality with async function."""
+        call_count = 0
+
+        @cached(maxsize=10, ttl_seconds=1)  # Short TTL
+        async def async_ttl_function(x: int) -> int:
+            nonlocal call_count
+            call_count += 1
+            await asyncio.sleep(0.01)
+            return x * 4
+
+        # First call
+        result1 = await async_ttl_function(3)
+        assert result1 == 12
+        assert call_count == 1
+
+        # Second call immediately - should use cache
+        result2 = await async_ttl_function(3)
+        assert result2 == 12
         assert call_count == 1
 
         # Wait for TTL to expire
         await asyncio.sleep(1.1)
 
         # Third call after expiration - should call function again
-        result3 = await short_lived_cache(5)
-        assert result3 == 10
+        result3 = await async_ttl_function(3)
+        assert result3 == 12
         assert call_count == 2
 
-    @pytest.mark.asyncio
-    async def test_cache_info(self):
+    def test_cache_info(self):
         """Test cache info functionality."""
 
-        @async_ttl_cache(maxsize=5, ttl_seconds=300)
-        async def info_test_function(x: int) -> int:
+        @cached(maxsize=10, ttl_seconds=60)
+        def info_test_function(x: int) -> int:
             return x * 3
 
         # Check initial cache info
         info = info_test_function.cache_info()
         assert info["size"] == 0
-        assert info["maxsize"] == 5
-        assert info["ttl_seconds"] == 300
+        assert info["maxsize"] == 10
+        assert info["ttl_seconds"] == 60
 
         # Add an entry
-        await info_test_function(1)
+        info_test_function(1)
         info = info_test_function.cache_info()
         assert info["size"] == 1
 
-    @pytest.mark.asyncio
-    async def test_cache_clear(self):
+    def test_cache_clear(self):
         """Test cache clearing functionality."""
         call_count = 0
 
-        @async_ttl_cache(maxsize=10, ttl_seconds=60)
-        async def clearable_function(x: int) -> int:
+        @cached()
+        def clearable_function(x: int) -> int:
             nonlocal call_count
             call_count += 1
             return x * 4
 
         # First call
-        result1 = await clearable_function(2)
+        result1 = clearable_function(2)
         assert result1 == 8
         assert call_count == 1
 
         # Second call - should use cache
-        result2 = await clearable_function(2)
+        result2 = clearable_function(2)
         assert result2 == 8
         assert call_count == 1
 
@@ -433,273 +528,149 @@ class TestAsyncTTLCache:
         clearable_function.cache_clear()
 
         # Third call after clear - should call function again
-        result3 = await clearable_function(2)
+        result3 = clearable_function(2)
         assert result3 == 8
         assert call_count == 2
 
     @pytest.mark.asyncio
-    async def test_maxsize_cleanup(self):
-        """Test that cache cleans up when maxsize is exceeded."""
+    async def test_async_cache_clear(self):
+        """Test cache clearing functionality with async function."""
         call_count = 0
 
-        @async_ttl_cache(maxsize=3, ttl_seconds=60)
-        async def size_limited_function(x: int) -> int:
+        @cached()
+        async def async_clearable_function(x: int) -> int:
             nonlocal call_count
             call_count += 1
-            return x**2
+            await asyncio.sleep(0.01)
+            return x * 5
 
-        # Fill cache to maxsize
-        await size_limited_function(1)  # call_count: 1
-        await size_limited_function(2)  # call_count: 2
-        await size_limited_function(3)  # call_count: 3
-
-        info = size_limited_function.cache_info()
-        assert info["size"] == 3
-
-        # Add one more entry - should trigger cleanup
-        await size_limited_function(4)  # call_count: 4
-
-        # Cache size should be reduced (cleanup removes oldest entries)
-        info = size_limited_function.cache_info()
-        assert info["size"] is not None and info["size"] <= 3  # Should be cleaned up
-
-    @pytest.mark.asyncio
-    async def test_argument_variations(self):
-        """Test caching with different argument patterns."""
-        call_count = 0
-
-        @async_ttl_cache(maxsize=10, ttl_seconds=60)
-        async def arg_test_function(a: int, b: str = "default", *, c: int = 100) -> str:
-            nonlocal call_count
-            call_count += 1
-            return f"{a}-{b}-{c}"
-
-        # Different ways to call with same logical arguments
-        result1 = await arg_test_function(1, "test", c=200)
-        assert call_count == 1
-
-        # Same arguments, same order - should use cache
-        result2 = await arg_test_function(1, "test", c=200)
-        assert call_count == 1
-        assert result1 == result2
-
-        # Different arguments - should call function
-        result3 = await arg_test_function(2, "test", c=200)
-        assert call_count == 2
-        assert result1 != result3
-
-    @pytest.mark.asyncio
-    async def test_exception_handling(self):
-        """Test that exceptions are not cached."""
-        call_count = 0
-
-        @async_ttl_cache(maxsize=10, ttl_seconds=60)
-        async def exception_function(x: int) -> int:
-            nonlocal call_count
-            call_count += 1
-            if x < 0:
-                raise ValueError("Negative value not allowed")
-            return x * 2
-
-        # Successful call - should be cached
-        result1 = await exception_function(5)
+        # First call
+        result1 = await async_clearable_function(2)
         assert result1 == 10
         assert call_count == 1
 
-        # Same successful call - should use cache
-        result2 = await exception_function(5)
+        # Second call - should use cache
+        result2 = await async_clearable_function(2)
         assert result2 == 10
         assert call_count == 1
 
-        # Exception call - should not be cached
-        with pytest.raises(ValueError):
-            await exception_function(-1)
+        # Clear cache
+        async_clearable_function.cache_clear()
+
+        # Third call after clear - should call function again
+        result3 = await async_clearable_function(2)
+        assert result3 == 10
         assert call_count == 2
 
-        # Same exception call - should call again (not cached)
-        with pytest.raises(ValueError):
-            await exception_function(-1)
+    @pytest.mark.asyncio
+    async def test_async_function_returns_results_not_coroutines(self):
+        """Test that cached async functions return actual results, not coroutines."""
+        call_count = 0
+
+        @cached()
+        async def async_result_function(x: int) -> str:
+            nonlocal call_count
+            call_count += 1
+            await asyncio.sleep(0.01)
+            return f"result_{x}"
+
+        # First call
+        result1 = await async_result_function(1)
+        assert result1 == "result_1"
+        assert isinstance(result1, str)  # Should be string, not coroutine
+        assert call_count == 1
+
+        # Second call - should return cached result (string), not coroutine
+        result2 = await async_result_function(1)
+        assert result2 == "result_1"
+        assert isinstance(result2, str)  # Should be string, not coroutine
+        assert call_count == 1  # Function should not be called again
+
+        # Verify results are identical
+        assert result1 is result2  # Should be same cached object
+
+    def test_cache_delete(self):
+        """Test selective cache deletion functionality."""
+        call_count = 0
+
+        @cached()
+        def deletable_function(x: int) -> int:
+            nonlocal call_count
+            call_count += 1
+            return x * 6
+
+        # First call for x=1
+        result1 = deletable_function(1)
+        assert result1 == 6
+        assert call_count == 1
+
+        # First call for x=2
+        result2 = deletable_function(2)
+        assert result2 == 12
+        assert call_count == 2
+
+        # Second calls - should use cache
+        assert deletable_function(1) == 6
+        assert deletable_function(2) == 12
+        assert call_count == 2
+
+        # Delete specific entry for x=1
+        was_deleted = deletable_function.cache_delete(1)
+        assert was_deleted is True
+
+        # Call with x=1 should execute function again
+        result3 = deletable_function(1)
+        assert result3 == 6
         assert call_count == 3
 
-    @pytest.mark.asyncio
-    async def test_concurrent_calls(self):
-        """Test caching behavior with concurrent calls."""
-        call_count = 0
+        # Call with x=2 should still use cache
+        assert deletable_function(2) == 12
+        assert call_count == 3
 
-        @async_ttl_cache(maxsize=10, ttl_seconds=60)
-        async def concurrent_function(x: int) -> int:
-            nonlocal call_count
-            call_count += 1
-            await asyncio.sleep(0.05)  # Simulate work
-            return x * x
-
-        # Launch concurrent calls with same arguments
-        tasks = [concurrent_function(3) for _ in range(5)]
-        results = await asyncio.gather(*tasks)
-
-        # All results should be the same
-        assert all(result == 9 for result in results)
-
-        # Note: Due to race conditions, call_count might be up to 5 for concurrent calls
-        # This tests that the cache doesn't break under concurrent access
-        assert 1 <= call_count <= 5
-
-
-class TestAsyncCache:
-    """Tests for the @async_cache decorator (no TTL)."""
+        # Try to delete non-existent entry
+        was_deleted = deletable_function.cache_delete(99)
+        assert was_deleted is False
 
     @pytest.mark.asyncio
-    async def test_basic_caching_no_ttl(self):
-        """Test basic caching functionality without TTL."""
+    async def test_async_cache_delete(self):
+        """Test selective cache deletion functionality with async function."""
         call_count = 0
 
-        @async_cache(maxsize=10)
-        async def cached_function(x: int, y: int = 0) -> int:
+        @cached()
+        async def async_deletable_function(x: int) -> int:
             nonlocal call_count
             call_count += 1
-            await asyncio.sleep(0.01)  # Simulate async work
-            return x + y
+            await asyncio.sleep(0.01)
+            return x * 7
 
-        # First call
-        result1 = await cached_function(1, 2)
-        assert result1 == 3
+        # First call for x=1
+        result1 = await async_deletable_function(1)
+        assert result1 == 7
         assert call_count == 1
 
-        # Second call with same args - should use cache
-        result2 = await cached_function(1, 2)
-        assert result2 == 3
-        assert call_count == 1  # No additional call
-
-        # Third call after some time - should still use cache (no TTL)
-        await asyncio.sleep(0.05)
-        result3 = await cached_function(1, 2)
-        assert result3 == 3
-        assert call_count == 1  # Still no additional call
-
-        # Different args - should call function again
-        result4 = await cached_function(2, 3)
-        assert result4 == 5
+        # First call for x=2
+        result2 = await async_deletable_function(2)
+        assert result2 == 14
         assert call_count == 2
 
-    @pytest.mark.asyncio
-    async def test_no_ttl_vs_ttl_behavior(self):
-        """Test the difference between TTL and no-TTL caching."""
-        ttl_call_count = 0
-        no_ttl_call_count = 0
+        # Second calls - should use cache
+        assert await async_deletable_function(1) == 7
+        assert await async_deletable_function(2) == 14
+        assert call_count == 2
 
-        @async_ttl_cache(maxsize=10, ttl_seconds=1)  # Short TTL
-        async def ttl_function(x: int) -> int:
-            nonlocal ttl_call_count
-            ttl_call_count += 1
-            return x * 2
+        # Delete specific entry for x=1
+        was_deleted = async_deletable_function.cache_delete(1)
+        assert was_deleted is True
 
-        @async_cache(maxsize=10)  # No TTL
-        async def no_ttl_function(x: int) -> int:
-            nonlocal no_ttl_call_count
-            no_ttl_call_count += 1
-            return x * 2
+        # Call with x=1 should execute function again
+        result3 = await async_deletable_function(1)
+        assert result3 == 7
+        assert call_count == 3
 
-        # First calls
-        await ttl_function(5)
-        await no_ttl_function(5)
-        assert ttl_call_count == 1
-        assert no_ttl_call_count == 1
+        # Call with x=2 should still use cache
+        assert await async_deletable_function(2) == 14
+        assert call_count == 3
 
-        # Wait for TTL to expire
-        await asyncio.sleep(1.1)
-
-        # Second calls after TTL expiry
-        await ttl_function(5)  # Should call function again (TTL expired)
-        await no_ttl_function(5)  # Should use cache (no TTL)
-        assert ttl_call_count == 2  # TTL function called again
-        assert no_ttl_call_count == 1  # No-TTL function still cached
-
-    @pytest.mark.asyncio
-    async def test_async_cache_info(self):
-        """Test cache info for no-TTL cache."""
-
-        @async_cache(maxsize=5)
-        async def info_test_function(x: int) -> int:
-            return x * 3
-
-        # Check initial cache info
-        info = info_test_function.cache_info()
-        assert info["size"] == 0
-        assert info["maxsize"] == 5
-        assert info["ttl_seconds"] is None  # No TTL
-
-        # Add an entry
-        await info_test_function(1)
-        info = info_test_function.cache_info()
-        assert info["size"] == 1
-
-
-class TestTTLOptional:
-    """Tests for optional TTL functionality."""
-
-    @pytest.mark.asyncio
-    async def test_ttl_none_behavior(self):
-        """Test that ttl_seconds=None works like no TTL."""
-        call_count = 0
-
-        @async_ttl_cache(maxsize=10, ttl_seconds=None)
-        async def no_ttl_via_none(x: int) -> int:
-            nonlocal call_count
-            call_count += 1
-            return x**2
-
-        # First call
-        result1 = await no_ttl_via_none(3)
-        assert result1 == 9
-        assert call_count == 1
-
-        # Wait (would expire if there was TTL)
-        await asyncio.sleep(0.1)
-
-        # Second call - should still use cache
-        result2 = await no_ttl_via_none(3)
-        assert result2 == 9
-        assert call_count == 1  # No additional call
-
-        # Check cache info
-        info = no_ttl_via_none.cache_info()
-        assert info["ttl_seconds"] is None
-
-    @pytest.mark.asyncio
-    async def test_cache_options_comparison(self):
-        """Test different cache options work as expected."""
-        ttl_calls = 0
-        no_ttl_calls = 0
-
-        @async_ttl_cache(maxsize=10, ttl_seconds=1)  # With TTL
-        async def ttl_function(x: int) -> int:
-            nonlocal ttl_calls
-            ttl_calls += 1
-            return x * 10
-
-        @async_cache(maxsize=10)  # Process-level cache (no TTL)
-        async def process_function(x: int) -> int:
-            nonlocal no_ttl_calls
-            no_ttl_calls += 1
-            return x * 10
-
-        # Both should cache initially
-        await ttl_function(3)
-        await process_function(3)
-        assert ttl_calls == 1
-        assert no_ttl_calls == 1
-
-        # Immediate second calls - both should use cache
-        await ttl_function(3)
-        await process_function(3)
-        assert ttl_calls == 1
-        assert no_ttl_calls == 1
-
-        # Wait for TTL to expire
-        await asyncio.sleep(1.1)
-
-        # After TTL expiry
-        await ttl_function(3)  # Should call function again
-        await process_function(3)  # Should still use cache
-        assert ttl_calls == 2  # TTL cache expired, called again
-        assert no_ttl_calls == 1  # Process cache never expires
+        # Try to delete non-existent entry
+        was_deleted = async_deletable_function.cache_delete(99)
+        assert was_deleted is False

autogpt_platform/autogpt_libs/poetry.lock

@@ -54,7 +54,7 @@ version = "1.2.0"
 description = "Backport of asyncio.Runner, a context manager that controls event loop life cycle."
 optional = false
 python-versions = "<3.11,>=3.8"
-groups = ["main"]
+groups = ["dev"]
 markers = "python_version < \"3.11\""
 files = [
     {file = "backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5"},
@@ -85,6 +85,87 @@ files = [
     {file = "certifi-2025.7.14.tar.gz", hash = "sha256:8ea99dbdfaaf2ba2f9bac77b9249ef62ec5218e7c2b2e903378ed5fccf765995"},
 ]
 
+[[package]]
+name = "cffi"
+version = "1.17.1"
+description = "Foreign Function Interface for Python calling C code."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+markers = "platform_python_implementation != \"PyPy\""
+files = [
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+    {file = "cffi-1.17.1.tar.gz", hash = "sha256:1c39c6016c32bc48dd54561950ebd6836e1670f2ae46128f67cf49e789c52824"},
+]
+
+[package.dependencies]
+pycparser = "*"
+
 [[package]]
 name = "charset-normalizer"
 version = "3.4.2"
@@ -208,12 +289,176 @@ version = "0.4.6"
 description = "Cross-platform colored terminal text."
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
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 ]
 
+[[package]]
+name = "coverage"
+version = "7.10.5"
+description = "Code coverage measurement for Python"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
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+]
+
+[package.dependencies]
+cffi = {version = ">=1.14", markers = "platform_python_implementation != \"PyPy\""}
+
+[package.extras]
+docs = ["sphinx (>=5.3.0)", "sphinx-inline-tabs ; python_full_version >= \"3.8.0\"", "sphinx-rtd-theme (>=3.0.0) ; python_full_version >= \"3.8.0\""]
+docstest = ["pyenchant (>=3)", "readme-renderer (>=30.0)", "sphinxcontrib-spelling (>=7.3.1)"]
+nox = ["nox (>=2024.4.15)", "nox[uv] (>=2024.3.2) ; python_full_version >= \"3.8.0\""]
+pep8test = ["check-sdist ; python_full_version >= \"3.8.0\"", "click (>=8.0.1)", "mypy (>=1.4)", "ruff (>=0.3.6)"]
+sdist = ["build (>=1.0.0)"]
+ssh = ["bcrypt (>=3.1.5)"]
+test = ["certifi (>=2024)", "cryptography-vectors (==45.0.6)", "pretend (>=0.7)", "pytest (>=7.4.0)", "pytest-benchmark (>=4.0)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=3.5.0)"]
+test-randomorder = ["pytest-randomly"]
+
 [[package]]
 name = "deprecation"
 version = "2.1.0"
@@ -235,7 +480,7 @@ version = "1.3.0"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
-groups = ["main"]
+groups = ["main", "dev"]
 markers = "python_version < \"3.11\""
 files = [
     {file = "exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10"},
@@ -710,7 +955,7 @@ version = "2.1.0"
 description = "brain-dead simple config-ini parsing"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["dev"]
 files = [
     {file = "iniconfig-2.1.0-py3-none-any.whl", hash = "sha256:9deba5723312380e77435581c6bf4935c94cbfab9b1ed33ef8d238ea168eb760"},
     {file = "iniconfig-2.1.0.tar.gz", hash = "sha256:3abbd2e30b36733fee78f9c7f7308f2d0050e88f0087fd25c2645f63c773e1c7"},
@@ -757,6 +1002,18 @@ dynamodb = ["boto3 (>=1.9.71)"]
 redis = ["redis (>=2.10.5)"]
 test-filesource = ["pyyaml (>=5.3.1)", "watchdog (>=3.0.0)"]
 
+[[package]]
+name = "nodeenv"
+version = "1.9.1"
+description = "Node.js virtual environment builder"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
+groups = ["dev"]
+files = [
+    {file = "nodeenv-1.9.1-py2.py3-none-any.whl", hash = "sha256:ba11c9782d29c27c70ffbdda2d7415098754709be8a7056d79a737cd901155c9"},
+    {file = "nodeenv-1.9.1.tar.gz", hash = "sha256:6ec12890a2dab7946721edbfbcd91f3319c6ccc9aec47be7c7e6b7011ee6645f"},
+]
+
 [[package]]
 name = "opentelemetry-api"
 version = "1.35.0"
@@ -779,7 +1036,7 @@ version = "25.0"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "packaging-25.0-py3-none-any.whl", hash = "sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484"},
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@@ -791,7 +1048,7 @@ version = "1.6.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
 python-versions = ">=3.9"
-groups = ["main"]
+groups = ["dev"]
 files = [
     {file = "pluggy-1.6.0-py3-none-any.whl", hash = "sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746"},
     {file = "pluggy-1.6.0.tar.gz", hash = "sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3"},
@@ -883,6 +1140,19 @@ files = [
 [package.dependencies]
 pyasn1 = ">=0.6.1,<0.7.0"
 
+[[package]]
+name = "pycparser"
+version = "2.22"
+description = "C parser in Python"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+markers = "platform_python_implementation != \"PyPy\""
+files = [
+    {file = "pycparser-2.22-py3-none-any.whl", hash = "sha256:c3702b6d3dd8c7abc1afa565d7e63d53a1d0bd86cdc24edd75470f4de499cfcc"},
+    {file = "pycparser-2.22.tar.gz", hash = "sha256:491c8be9c040f5390f5bf44a5b07752bd07f56edf992381b05c701439eec10f6"},
+]
+
 [[package]]
 name = "pydantic"
 version = "2.11.7"
@@ -1047,7 +1317,7 @@ version = "2.19.2"
 description = "Pygments is a syntax highlighting package written in Python."
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["dev"]
 files = [
     {file = "pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b"},
     {file = "pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887"},
@@ -1068,6 +1338,9 @@ files = [
     {file = "pyjwt-2.10.1.tar.gz", hash = "sha256:3cc5772eb20009233caf06e9d8a0577824723b44e6648ee0a2aedb6cf9381953"},
 ]
 
+[package.dependencies]
+cryptography = {version = ">=3.4.0", optional = true, markers = "extra == \"crypto\""}
+
 [package.extras]
 crypto = ["cryptography (>=3.4.0)"]
 dev = ["coverage[toml] (==5.0.4)", "cryptography (>=3.4.0)", "pre-commit", "pytest (>=6.0.0,<7.0.0)", "sphinx", "sphinx-rtd-theme", "zope.interface"]
@@ -1086,13 +1359,34 @@ files = [
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 ]
 
+[[package]]
+name = "pyright"
+version = "1.1.404"
+description = "Command line wrapper for pyright"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
+    {file = "pyright-1.1.404-py3-none-any.whl", hash = "sha256:c7b7ff1fdb7219c643079e4c3e7d4125f0dafcc19d253b47e898d130ea426419"},
+    {file = "pyright-1.1.404.tar.gz", hash = "sha256:455e881a558ca6be9ecca0b30ce08aa78343ecc031d37a198ffa9a7a1abeb63e"},
+]
+
+[package.dependencies]
+nodeenv = ">=1.6.0"
+typing-extensions = ">=4.1"
+
+[package.extras]
+all = ["nodejs-wheel-binaries", "twine (>=3.4.1)"]
+dev = ["twine (>=3.4.1)"]
+nodejs = ["nodejs-wheel-binaries"]
+
 [[package]]
 name = "pytest"
 version = "8.4.1"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.9"
-groups = ["main"]
+groups = ["dev"]
 files = [
     {file = "pytest-8.4.1-py3-none-any.whl", hash = "sha256:539c70ba6fcead8e78eebbf1115e8b589e7565830d7d006a8723f19ac8a0afb7"},
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@@ -1116,7 +1410,7 @@ version = "1.1.0"
 description = "Pytest support for asyncio"
 optional = false
 python-versions = ">=3.9"
-groups = ["main"]
+groups = ["dev"]
 files = [
     {file = "pytest_asyncio-1.1.0-py3-none-any.whl", hash = "sha256:5fe2d69607b0bd75c656d1211f969cadba035030156745ee09e7d71740e58ecf"},
     {file = "pytest_asyncio-1.1.0.tar.gz", hash = "sha256:796aa822981e01b68c12e4827b8697108f7205020f24b5793b3c41555dab68ea"},
@@ -1130,13 +1424,33 @@ pytest = ">=8.2,<9"
 docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1)"]
 testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
+[[package]]
+name = "pytest-cov"
+version = "6.2.1"
+description = "Pytest plugin for measuring coverage."
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "pytest_cov-6.2.1-py3-none-any.whl", hash = "sha256:f5bc4c23f42f1cdd23c70b1dab1bbaef4fc505ba950d53e0081d0730dd7e86d5"},
+    {file = "pytest_cov-6.2.1.tar.gz", hash = "sha256:25cc6cc0a5358204b8108ecedc51a9b57b34cc6b8c967cc2c01a4e00d8a67da2"},
+]
+
+[package.dependencies]
+coverage = {version = ">=7.5", extras = ["toml"]}
+pluggy = ">=1.2"
+pytest = ">=6.2.5"
+
+[package.extras]
+testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
+
 [[package]]
 name = "pytest-mock"
 version = "3.14.1"
 description = "Thin-wrapper around the mock package for easier use with pytest"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["dev"]
 files = [
     {file = "pytest_mock-3.14.1-py3-none-any.whl", hash = "sha256:178aefcd11307d874b4cd3100344e7e2d888d9791a6a1d9bfe90fbc1b74fd1d0"},
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@@ -1253,30 +1567,31 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.12.3"
+version = "0.12.11"
 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-0.12.3-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:e1417051edb436230023575b149e8ff843a324557fe0a265863b7602df86722f"},
-    {file = "ruff-0.12.3-py3-none-win32.whl", hash = "sha256:dfd45e6e926deb6409d0616078a666ebce93e55e07f0fb0228d4b2608b2c248d"},
-    {file = "ruff-0.12.3-py3-none-win_amd64.whl", hash = "sha256:a946cf1e7ba3209bdef039eb97647f1c77f6f540e5845ec9c114d3af8df873e7"},
-    {file = "ruff-0.12.3-py3-none-win_arm64.whl", hash = "sha256:5f9c7c9c8f84c2d7f27e93674d27136fbf489720251544c4da7fb3d742e011b1"},
-    {file = "ruff-0.12.3.tar.gz", hash = "sha256:f1b5a4b6668fd7b7ea3697d8d98857390b40c1320a63a178eee6be0899ea2d77"},
+    {file = "ruff-0.12.11-py3-none-linux_armv6l.whl", hash = "sha256:93fce71e1cac3a8bf9200e63a38ac5c078f3b6baebffb74ba5274fb2ab276065"},
+    {file = "ruff-0.12.11-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:b8e33ac7b28c772440afa80cebb972ffd823621ded90404f29e5ab6d1e2d4b93"},
+    {file = "ruff-0.12.11-py3-none-macosx_11_0_arm64.whl", hash = "sha256:d69fb9d4937aa19adb2e9f058bc4fbfe986c2040acb1a4a9747734834eaa0bfd"},
+    {file = "ruff-0.12.11-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:411954eca8464595077a93e580e2918d0a01a19317af0a72132283e28ae21bee"},
+    {file = "ruff-0.12.11-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6a2c0a2e1a450f387bf2c6237c727dd22191ae8c00e448e0672d624b2bbd7fb0"},
+    {file = "ruff-0.12.11-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8ca4c3a7f937725fd2413c0e884b5248a19369ab9bdd850b5781348ba283f644"},
+    {file = "ruff-0.12.11-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:4d1df0098124006f6a66ecf3581a7f7e754c4df7644b2e6704cd7ca80ff95211"},
+    {file = "ruff-0.12.11-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5a8dd5f230efc99a24ace3b77e3555d3fbc0343aeed3fc84c8d89e75ab2ff793"},
+    {file = "ruff-0.12.11-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4dc75533039d0ed04cd33fb8ca9ac9620b99672fe7ff1533b6402206901c34ee"},
+    {file = "ruff-0.12.11-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4fc58f9266d62c6eccc75261a665f26b4ef64840887fc6cbc552ce5b29f96cc8"},
+    {file = "ruff-0.12.11-py3-none-manylinux_2_31_riscv64.whl", hash = "sha256:5a0113bd6eafd545146440225fe60b4e9489f59eb5f5f107acd715ba5f0b3d2f"},
+    {file = "ruff-0.12.11-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:0d737b4059d66295c3ea5720e6efc152623bb83fde5444209b69cd33a53e2000"},
+    {file = "ruff-0.12.11-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:916fc5defee32dbc1fc1650b576a8fed68f5e8256e2180d4d9855aea43d6aab2"},
+    {file = "ruff-0.12.11-py3-none-musllinux_1_2_i686.whl", hash = "sha256:c984f07d7adb42d3ded5be894fb4007f30f82c87559438b4879fe7aa08c62b39"},
+    {file = "ruff-0.12.11-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:e07fbb89f2e9249f219d88331c833860489b49cdf4b032b8e4432e9b13e8a4b9"},
+    {file = "ruff-0.12.11-py3-none-win32.whl", hash = "sha256:c792e8f597c9c756e9bcd4d87cf407a00b60af77078c96f7b6366ea2ce9ba9d3"},
+    {file = "ruff-0.12.11-py3-none-win_amd64.whl", hash = "sha256:a3283325960307915b6deb3576b96919ee89432ebd9c48771ca12ee8afe4a0fd"},
+    {file = "ruff-0.12.11-py3-none-win_arm64.whl", hash = "sha256:bae4d6e6a2676f8fb0f98b74594a048bae1b944aab17e9f5d504062303c6dbea"},
+    {file = "ruff-0.12.11.tar.gz", hash = "sha256:c6b09ae8426a65bbee5425b9d0b82796dbb07cb1af045743c79bfb163001165d"},
 ]
 
 [[package]]
@@ -1410,7 +1725,7 @@ version = "2.2.1"
 description = "A lil' TOML parser"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["dev"]
 markers = "python_version < \"3.11\""
 files = [
     {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
@@ -1453,7 +1768,7 @@ version = "4.14.1"
 description = "Backported and Experimental Type Hints for Python 3.9+"
 optional = false
 python-versions = ">=3.9"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "typing_extensions-4.14.1-py3-none-any.whl", hash = "sha256:d1e1e3b58374dc93031d6eda2420a48ea44a36c2b4766a4fdeb3710755731d76"},
     {file = "typing_extensions-4.14.1.tar.gz", hash = "sha256:38b39f4aeeab64884ce9f74c94263ef78f3c22467c8724005483154c26648d36"},
@@ -1614,4 +1929,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "f67db13e6f68b1d67a55eee908c1c560bfa44da8509f98f842889a7570a9830f"
+content-hash = "0c40b63c3c921846cf05ccfb4e685d4959854b29c2c302245f9832e20aac6954"

autogpt_platform/autogpt_libs/pyproject.toml

@@ -9,21 +9,25 @@ packages = [{ include = "autogpt_libs" }]
 [tool.poetry.dependencies]
 python = ">=3.10,<4.0"
 colorama = "^0.4.6"
+cryptography = "^45.0"
 expiringdict = "^1.2.2"
 fastapi = "^0.116.1"
 google-cloud-logging = "^3.12.1"
 launchdarkly-server-sdk = "^9.12.0"
 pydantic = "^2.11.7"
 pydantic-settings = "^2.10.1"
-pyjwt = "^2.10.1"
-pytest-asyncio = "^1.1.0"
-pytest-mock = "^3.14.1"
+pyjwt = { version = "^2.10.1", extras = ["crypto"] }
 redis = "^6.2.0"
 supabase = "^2.16.0"
 uvicorn = "^0.35.0"
 
 [tool.poetry.group.dev.dependencies]
-ruff = "^0.12.3"
+pyright = "^1.1.404"
+pytest = "^8.4.1"
+pytest-asyncio = "^1.1.0"
+pytest-mock = "^3.14.1"
+pytest-cov = "^6.2.1"
+ruff = "^0.12.11"
 
 [build-system]
 requires = ["poetry-core"]

autogpt_platform/backend/.env.default

@@ -16,13 +16,12 @@ DB_SCHEMA=platform
 DATABASE_URL="postgresql://${DB_USER}:${DB_PASS}@${DB_HOST}:${DB_PORT}/${DB_NAME}?schema=${DB_SCHEMA}&connect_timeout=${DB_CONNECT_TIMEOUT}"
 DIRECT_URL="postgresql://${DB_USER}:${DB_PASS}@${DB_HOST}:${DB_PORT}/${DB_NAME}?schema=${DB_SCHEMA}&connect_timeout=${DB_CONNECT_TIMEOUT}"
 PRISMA_SCHEMA="postgres/schema.prisma"
-ENABLE_AUTH=true
 
 ## ===== REQUIRED SERVICE CREDENTIALS ===== ##
 # Redis Configuration
 REDIS_HOST=localhost
 REDIS_PORT=6379
-REDIS_PASSWORD=password
+# REDIS_PASSWORD=
 
 # RabbitMQ Credentials
 RABBITMQ_DEFAULT_USER=rabbitmq_user_default
@@ -31,7 +30,7 @@ RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
 # Supabase Authentication
 SUPABASE_URL=http://localhost:8000
 SUPABASE_SERVICE_ROLE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
-SUPABASE_JWT_SECRET=your-super-secret-jwt-token-with-at-least-32-characters-long
+JWT_VERIFY_KEY=your-super-secret-jwt-token-with-at-least-32-characters-long
 
 ## ===== REQUIRED SECURITY KEYS ===== ##
 # Generate using: from cryptography.fernet import Fernet;Fernet.generate_key().decode()
@@ -67,6 +66,11 @@ NVIDIA_API_KEY=
 GITHUB_CLIENT_ID=
 GITHUB_CLIENT_SECRET=
 
+# Notion OAuth App server credentials - https://developers.notion.com/docs/authorization
+# Configure a public integration
+NOTION_CLIENT_ID=
+NOTION_CLIENT_SECRET=
+
 # Google OAuth App server credentials - https://console.cloud.google.com/apis/credentials, and enable gmail api and set scopes
 # https://console.cloud.google.com/apis/credentials/consent ?project=<your_project_id>
 # You'll need to add/enable the following scopes (minimum):
@@ -106,6 +110,15 @@ 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=
 
@@ -166,4 +179,4 @@ SMARTLEAD_API_KEY=
 ZEROBOUNCE_API_KEY=
 
 # Other Services
-AUTOMOD_API_KEY=
+AUTOMOD_API_KEY=

autogpt_platform/backend/.gitignore

@@ -9,4 +9,12 @@ secrets/*
 !secrets/.gitkeep
 
 *.ignore.*
-*.ign.*
+*.ign.*
+
+# Load test results and reports
+load-tests/*_RESULTS.md
+load-tests/*_REPORT.md
+load-tests/results/
+load-tests/*.json
+load-tests/*.log
+load-tests/node_modules/*

autogpt_platform/backend/Dockerfile

@@ -1,31 +1,43 @@
-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
+# Install Node.js repository key and setup
 RUN apt-get update --allow-releaseinfo-change --fix-missing \
+    && apt-get install -y curl ca-certificates gnupg \
+    && mkdir -p /etc/apt/keyrings \
+    && curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg \
+    && echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_20.x nodistro main" | tee /etc/apt/sources.list.d/nodesource.list
+
+# Update package list and install Python, Node.js, and build dependencies
+RUN apt-get update \
     && apt-get install -y \
+    python3.13 \
+    python3.13-dev \
+    python3.13-venv \
+    python3-pip \
     build-essential \
     libpq5 \
     libz-dev \
     libssl-dev \
-    postgresql-client
+    postgresql-client \
+    nodejs \
+    && rm -rf /var/lib/apt/lists/*
 
 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 +49,35 @@ 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 \
+    && rm -rf /var/lib/apt/lists/*
 
 # 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 Prisma binaries
+COPY --from=builder /usr/local/lib/python3* /usr/local/lib/python3*
+COPY --from=builder /usr/local/bin/poetry /usr/local/bin/poetry
+# Copy Node.js installation for Prisma
+COPY --from=builder /usr/bin/node /usr/bin/node
+COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
+COPY --from=builder /usr/bin/npm /usr/bin/npm
+COPY --from=builder /usr/bin/npx /usr/bin/npx
 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/TESTING.md

@@ -132,17 +132,58 @@ def test_endpoint_success(snapshot: Snapshot):
 
 ### Testing with Authentication
 
+For the main API routes that use JWT authentication, auth is provided by the `autogpt_libs.auth` module. If the test actually uses the `user_id`, the recommended approach for testing is to mock the `get_jwt_payload` function, which underpins all higher-level auth functions used in the API (`requires_user`, `requires_admin_user`, `get_user_id`).
+
+If the test doesn't need the `user_id` specifically, mocking is not necessary as during tests auth is disabled anyway (see `conftest.py`).
+
+#### Using Global Auth Fixtures
+
+Two global auth fixtures are provided by `backend/server/conftest.py`:
+
+- `mock_jwt_user` - Regular user with `test_user_id` ("test-user-id")
+- `mock_jwt_admin` - Admin user with `admin_user_id` ("admin-user-id")
+
+These provide the easiest way to set up authentication mocking in test modules:
+
 ```python
-def override_auth_middleware():
-    return {"sub": "test-user-id"}
+import fastapi
+import fastapi.testclient
+import pytest
+from backend.server.v2.myroute import router
 
-def override_get_user_id():
-    return "test-user-id"
+app = fastapi.FastAPI()
+app.include_router(router)
+client = fastapi.testclient.TestClient(app)
 
-app.dependency_overrides[auth_middleware] = override_auth_middleware
-app.dependency_overrides[get_user_id] = override_get_user_id
+@pytest.fixture(autouse=True)
+def setup_app_auth(mock_jwt_user):
+    """Setup auth overrides for all tests in this module"""
+    from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+    app.dependency_overrides[get_jwt_payload] = mock_jwt_user['get_jwt_payload']
+    yield
+    app.dependency_overrides.clear()
 ```
 
+For admin-only endpoints, use `mock_jwt_admin` instead:
+
+```python
+@pytest.fixture(autouse=True)
+def setup_app_auth(mock_jwt_admin):
+    """Setup auth overrides for admin tests"""
+    from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+    app.dependency_overrides[get_jwt_payload] = mock_jwt_admin['get_jwt_payload']
+    yield
+    app.dependency_overrides.clear()
+```
+
+The IDs are also available separately as fixtures:
+
+- `test_user_id`
+- `admin_user_id`
+- `target_user_id` (for admin <-> user operations)
+
 ### Mocking External Services
 
 ```python
@@ -153,10 +194,10 @@ def test_external_api_call(mocker, snapshot):
         "backend.services.external_api.call",
         return_value=mock_response
     )
-    
+
     response = client.post("/api/process")
     assert response.status_code == 200
-    
+
     snapshot.snapshot_dir = "snapshots"
     snapshot.assert_match(
         json.dumps(response.json(), indent=2, sort_keys=True),
@@ -187,6 +228,17 @@ def test_external_api_call(mocker, snapshot):
 - Use `async def` with `@pytest.mark.asyncio` for testing async functions directly
 
 ### 5. Fixtures
+
+#### Global Fixtures (conftest.py)
+
+Authentication fixtures are available globally from `conftest.py`:
+
+- `mock_jwt_user` - Standard user authentication
+- `mock_jwt_admin` - Admin user authentication
+- `configured_snapshot` - Pre-configured snapshot fixture
+
+#### Custom Fixtures
+
 Create reusable fixtures for common test data:
 
 ```python
@@ -202,9 +254,18 @@ def test_create_user(sample_user, snapshot):
     # ... test implementation
 ```
 
+#### Test Isolation
+
+All tests must use fixtures that ensure proper isolation:
+
+- Authentication overrides are automatically cleaned up after each test
+- Database connections are properly managed with cleanup
+- Mock objects are reset between tests
+
 ## CI/CD Integration
 
 The GitHub Actions workflow automatically runs tests on:
+
 - Pull requests
 - Pushes to main branch
 
@@ -216,16 +277,19 @@ Snapshot tests work in CI by:
 ## Troubleshooting
 
 ### Snapshot Mismatches
+
 - Review the diff carefully
 - If changes are expected: `poetry run pytest --snapshot-update`
 - If changes are unexpected: Fix the code causing the difference
 
 ### Async Test Issues
+
 - Ensure async functions use `@pytest.mark.asyncio`
 - Use `AsyncMock` for mocking async functions
 - FastAPI TestClient handles async automatically
 
 ### Import Errors
+
 - Check that all dependencies are in `pyproject.toml`
 - Run `poetry install` to ensure dependencies are installed
 - Verify import paths are correct
@@ -234,4 +298,4 @@ Snapshot tests work in CI by:
 
 Snapshot testing provides a powerful way to ensure API responses remain consistent. Combined with traditional assertions, it creates a robust test suite that catches regressions while remaining maintainable.
 
-Remember: Good tests are as important as good code!
+Remember: Good tests are as important as good code!

autogpt_platform/backend/backend/blocks/__init__.py

@@ -1,4 +1,3 @@
-import functools
 import importlib
 import logging
 import os
@@ -6,6 +5,8 @@ import re
 from pathlib import Path
 from typing import TYPE_CHECKING, TypeVar
 
+from autogpt_libs.utils.cache import cached
+
 logger = logging.getLogger(__name__)
 
 
@@ -15,7 +16,7 @@ if TYPE_CHECKING:
 T = TypeVar("T")
 
 
-@functools.cache
+@cached()
 def load_all_blocks() -> dict[str, type["Block"]]:
     from backend.data.block import Block
     from backend.util.settings import Config

autogpt_platform/backend/backend/blocks/agent.py

@@ -1,8 +1,6 @@
 import logging
 from typing import Any, Optional
 
-from pydantic import JsonValue
-
 from backend.data.block import (
     Block,
     BlockCategory,
@@ -12,7 +10,7 @@ from backend.data.block import (
     BlockType,
     get_block,
 )
-from backend.data.execution import ExecutionStatus
+from backend.data.execution import ExecutionStatus, NodesInputMasks
 from backend.data.model import NodeExecutionStats, SchemaField
 from backend.util.json import validate_with_jsonschema
 from backend.util.retry import func_retry
@@ -25,12 +23,15 @@ 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")
         output_schema: dict = SchemaField(description="Output schema for the graph")
 
-        nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = SchemaField(
+        nodes_input_masks: Optional[NodesInputMasks] = SchemaField(
             default=None, hidden=True
         )
 

autogpt_platform/backend/backend/blocks/ai_image_customizer.py

@@ -0,0 +1,154 @@
+from enum import Enum
+from typing import Literal
+
+from pydantic import SecretStr
+from replicate.client import Client as ReplicateClient
+from replicate.helpers import FileOutput
+
+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.util.file import MediaFileType
+
+
+class GeminiImageModel(str, Enum):
+    NANO_BANANA = "google/nano-banana"
+
+
+class OutputFormat(str, Enum):
+    JPG = "jpg"
+    PNG = "png"
+
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="replicate",
+    api_key=SecretStr("mock-replicate-api-key"),
+    title="Mock Replicate API key",
+    expires_at=None,
+)
+
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}
+
+
+class AIImageCustomizerBlock(Block):
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.REPLICATE], Literal["api_key"]
+        ] = CredentialsField(
+            description="Replicate API key with permissions for Google Gemini image models",
+        )
+        prompt: str = SchemaField(
+            description="A text description of the image you want to generate",
+            title="Prompt",
+        )
+        model: GeminiImageModel = SchemaField(
+            description="The AI model to use for image generation and editing",
+            default=GeminiImageModel.NANO_BANANA,
+            title="Model",
+        )
+        images: list[MediaFileType] = SchemaField(
+            description="Optional list of input images to reference or modify",
+            default=[],
+            title="Input Images",
+        )
+        output_format: OutputFormat = SchemaField(
+            description="Format of the output image",
+            default=OutputFormat.PNG,
+            title="Output Format",
+        )
+
+    class Output(BlockSchema):
+        image_url: MediaFileType = SchemaField(description="URL of the generated image")
+        error: str = SchemaField(description="Error message if generation failed")
+
+    def __init__(self):
+        super().__init__(
+            id="d76bbe4c-930e-4894-8469-b66775511f71",
+            description=(
+                "Generate and edit custom images using Google's Nano-Banana model from Gemini 2.5. "
+                "Provide a prompt and optional reference images to create or modify images."
+            ),
+            categories={BlockCategory.AI, BlockCategory.MULTIMEDIA},
+            input_schema=AIImageCustomizerBlock.Input,
+            output_schema=AIImageCustomizerBlock.Output,
+            test_input={
+                "prompt": "Make the scene more vibrant and colorful",
+                "model": GeminiImageModel.NANO_BANANA,
+                "images": [],
+                "output_format": OutputFormat.JPG,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[
+                ("image_url", "https://replicate.delivery/generated-image.jpg"),
+            ],
+            test_mock={
+                "run_model": lambda *args, **kwargs: MediaFileType(
+                    "https://replicate.delivery/generated-image.jpg"
+                ),
+            },
+            test_credentials=TEST_CREDENTIALS,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        graph_exec_id: str,
+        user_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            result = await self.run_model(
+                api_key=credentials.api_key,
+                model_name=input_data.model.value,
+                prompt=input_data.prompt,
+                images=input_data.images,
+                output_format=input_data.output_format.value,
+            )
+            yield "image_url", result
+        except Exception as e:
+            yield "error", str(e)
+
+    async def run_model(
+        self,
+        api_key: SecretStr,
+        model_name: str,
+        prompt: str,
+        images: list[MediaFileType],
+        output_format: str,
+    ) -> MediaFileType:
+        client = ReplicateClient(api_token=api_key.get_secret_value())
+
+        input_params: dict = {
+            "prompt": prompt,
+            "output_format": output_format,
+        }
+
+        # Add images to input if provided (API expects "image_input" parameter)
+        if images:
+            input_params["image_input"] = [str(img) for img in images]
+
+        output: FileOutput | str = await client.async_run(  # type: ignore
+            model_name,
+            input=input_params,
+            wait=False,
+        )
+
+        if isinstance(output, FileOutput):
+            return MediaFileType(output.url)
+        if isinstance(output, str):
+            return MediaFileType(output)
+
+        raise ValueError("No output received from the model")

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/airtable/_api.py

@@ -661,6 +661,167 @@ async def update_field(
 #################################################################
 
 
+async def get_table_schema(
+    credentials: Credentials,
+    base_id: str,
+    table_id_or_name: str,
+) -> dict:
+    """
+    Get the schema for a specific table, including all field definitions.
+
+    Args:
+        credentials: Airtable API credentials
+        base_id: The base ID
+        table_id_or_name: The table ID or name
+
+    Returns:
+        Dict containing table schema with fields information
+    """
+    # First get all tables to find the right one
+    response = await Requests().get(
+        f"https://api.airtable.com/v0/meta/bases/{base_id}/tables",
+        headers={"Authorization": credentials.auth_header()},
+    )
+
+    data = response.json()
+    tables = data.get("tables", [])
+
+    # Find the matching table
+    for table in tables:
+        if table.get("id") == table_id_or_name or table.get("name") == table_id_or_name:
+            return table
+
+    raise ValueError(f"Table '{table_id_or_name}' not found in base '{base_id}'")
+
+
+def get_empty_value_for_field(field_type: str) -> Any:
+    """
+    Return the appropriate empty value for a given Airtable field type.
+
+    Args:
+        field_type: The Airtable field type
+
+    Returns:
+        The appropriate empty value for that field type
+    """
+    # Fields that should be false when empty
+    if field_type == "checkbox":
+        return False
+
+    # Fields that should be empty arrays
+    if field_type in [
+        "multipleSelects",
+        "multipleRecordLinks",
+        "multipleAttachments",
+        "multipleLookupValues",
+        "multipleCollaborators",
+    ]:
+        return []
+
+    # Fields that should be 0 when empty (numeric types)
+    if field_type in [
+        "number",
+        "percent",
+        "currency",
+        "rating",
+        "duration",
+        "count",
+        "autoNumber",
+    ]:
+        return 0
+
+    # Fields that should be empty strings
+    if field_type in [
+        "singleLineText",
+        "multilineText",
+        "email",
+        "url",
+        "phoneNumber",
+        "richText",
+        "barcode",
+    ]:
+        return ""
+
+    # Everything else gets null (dates, single selects, formulas, etc.)
+    return None
+
+
+async def normalize_records(
+    records: list[dict],
+    table_schema: dict,
+    include_field_metadata: bool = False,
+) -> dict:
+    """
+    Normalize Airtable records to include all fields with proper empty values.
+
+    Args:
+        records: List of record objects from Airtable API
+        table_schema: Table schema containing field definitions
+        include_field_metadata: Whether to include field metadata in response
+
+    Returns:
+        Dict with normalized records and optionally field metadata
+    """
+    fields = table_schema.get("fields", [])
+
+    # Normalize each record
+    normalized_records = []
+    for record in records:
+        normalized = {
+            "id": record.get("id"),
+            "createdTime": record.get("createdTime"),
+            "fields": {},
+        }
+
+        # Add existing fields
+        existing_fields = record.get("fields", {})
+
+        # Add all fields from schema, using empty values for missing ones
+        for field in fields:
+            field_name = field["name"]
+            field_type = field["type"]
+
+            if field_name in existing_fields:
+                # Field exists, use its value
+                normalized["fields"][field_name] = existing_fields[field_name]
+            else:
+                # Field is missing, add appropriate empty value
+                normalized["fields"][field_name] = get_empty_value_for_field(field_type)
+
+        normalized_records.append(normalized)
+
+    # Build result dictionary
+    if include_field_metadata:
+        field_metadata = {}
+        for field in fields:
+            metadata = {"type": field["type"], "id": field["id"]}
+
+            # Add type-specific metadata
+            options = field.get("options", {})
+            if field["type"] == "currency" and "symbol" in options:
+                metadata["symbol"] = options["symbol"]
+                metadata["precision"] = options.get("precision", 2)
+            elif field["type"] == "duration" and "durationFormat" in options:
+                metadata["format"] = options["durationFormat"]
+            elif field["type"] == "percent" and "precision" in options:
+                metadata["precision"] = options["precision"]
+            elif (
+                field["type"] in ["singleSelect", "multipleSelects"]
+                and "choices" in options
+            ):
+                metadata["choices"] = [choice["name"] for choice in options["choices"]]
+            elif field["type"] == "rating" and "max" in options:
+                metadata["max"] = options["max"]
+                metadata["icon"] = options.get("icon", "star")
+                metadata["color"] = options.get("color", "yellowBright")
+
+            field_metadata[field["name"]] = metadata
+
+        return {"records": normalized_records, "field_metadata": field_metadata}
+    else:
+        return {"records": normalized_records}
+
+
 async def list_records(
     credentials: Credentials,
     base_id: str,
@@ -1249,3 +1410,26 @@ async def list_bases(
     )
 
     return response.json()
+
+
+async def get_base_tables(
+    credentials: Credentials,
+    base_id: str,
+) -> list[dict]:
+    """
+    Get all tables for a specific base.
+
+    Args:
+        credentials: Airtable API credentials
+        base_id: The ID of the base
+
+    Returns:
+        list[dict]: List of table objects with their schemas
+    """
+    response = await Requests().get(
+        f"https://api.airtable.com/v0/meta/bases/{base_id}/tables",
+        headers={"Authorization": credentials.auth_header()},
+    )
+
+    data = response.json()
+    return data.get("tables", [])

autogpt_platform/backend/backend/blocks/airtable/bases.py

@@ -14,13 +14,13 @@ from backend.sdk import (
     SchemaField,
 )
 
-from ._api import create_base, list_bases
+from ._api import create_base, get_base_tables, list_bases
 from ._config import airtable
 
 
 class AirtableCreateBaseBlock(Block):
     """
-    Creates a new base in an Airtable workspace.
+    Creates a new base in an Airtable workspace, or returns existing base if one with the same name exists.
     """
 
     class Input(BlockSchema):
@@ -31,6 +31,10 @@ class AirtableCreateBaseBlock(Block):
             description="The workspace ID where the base will be created"
         )
         name: str = SchemaField(description="The name of the new base")
+        find_existing: bool = SchemaField(
+            description="If true, return existing base with same name instead of creating duplicate",
+            default=True,
+        )
         tables: list[dict] = SchemaField(
             description="At least one table and field must be specified. Array of table objects to create in the base. Each table should have 'name' and 'fields' properties",
             default=[
@@ -50,14 +54,18 @@ class AirtableCreateBaseBlock(Block):
         )
 
     class Output(BlockSchema):
-        base_id: str = SchemaField(description="The ID of the created base")
+        base_id: str = SchemaField(description="The ID of the created or found base")
         tables: list[dict] = SchemaField(description="Array of table objects")
         table: dict = SchemaField(description="A single table object")
+        was_created: bool = SchemaField(
+            description="True if a new base was created, False if existing was found",
+            default=True,
+        )
 
     def __init__(self):
         super().__init__(
             id="f59b88a8-54ce-4676-a508-fd614b4e8dce",
-            description="Create a new base in Airtable",
+            description="Create or find a base in Airtable",
             categories={BlockCategory.DATA},
             input_schema=self.Input,
             output_schema=self.Output,
@@ -66,6 +74,31 @@ class AirtableCreateBaseBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
+        # If find_existing is true, check if a base with this name already exists
+        if input_data.find_existing:
+            # List all bases to check for existing one with same name
+            # Note: Airtable API doesn't have a direct search, so we need to list and filter
+            existing_bases = await list_bases(credentials)
+
+            for base in existing_bases.get("bases", []):
+                if base.get("name") == input_data.name:
+                    # Base already exists, return it
+                    base_id = base.get("id")
+                    yield "base_id", base_id
+                    yield "was_created", False
+
+                    # Get the tables for this base
+                    try:
+                        tables = await get_base_tables(credentials, base_id)
+                        yield "tables", tables
+                        for table in tables:
+                            yield "table", table
+                    except Exception:
+                        # If we can't get tables, return empty list
+                        yield "tables", []
+                    return
+
+        # No existing base found or find_existing is false, create new one
         data = await create_base(
             credentials,
             input_data.workspace_id,
@@ -74,6 +107,7 @@ class AirtableCreateBaseBlock(Block):
         )
 
         yield "base_id", data.get("id", None)
+        yield "was_created", True
         yield "tables", data.get("tables", [])
         for table in data.get("tables", []):
             yield "table", table

autogpt_platform/backend/backend/blocks/airtable/records.py

@@ -2,7 +2,7 @@
 Airtable record operation blocks.
 """
 
-from typing import Optional
+from typing import Optional, cast
 
 from backend.sdk import (
     APIKeyCredentials,
@@ -18,7 +18,9 @@ from ._api import (
     create_record,
     delete_multiple_records,
     get_record,
+    get_table_schema,
     list_records,
+    normalize_records,
     update_multiple_records,
 )
 from ._config import airtable
@@ -54,12 +56,24 @@ class AirtableListRecordsBlock(Block):
         return_fields: list[str] = SchemaField(
             description="Specific fields to return (comma-separated)", default=[]
         )
+        normalize_output: bool = SchemaField(
+            description="Normalize output to include all fields with proper empty values (disable to skip schema fetch and get raw Airtable response)",
+            default=True,
+        )
+        include_field_metadata: bool = SchemaField(
+            description="Include field type and configuration metadata (requires normalize_output=true)",
+            default=False,
+        )
 
     class Output(BlockSchema):
         records: list[dict] = SchemaField(description="Array of record objects")
         offset: Optional[str] = SchemaField(
             description="Offset for next page (null if no more records)", default=None
         )
+        field_metadata: Optional[dict] = SchemaField(
+            description="Field type and configuration metadata (only when include_field_metadata=true)",
+            default=None,
+        )
 
     def __init__(self):
         super().__init__(
@@ -73,6 +87,7 @@ class AirtableListRecordsBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
+
         data = await list_records(
             credentials,
             input_data.base_id,
@@ -88,8 +103,33 @@ class AirtableListRecordsBlock(Block):
             fields=input_data.return_fields if input_data.return_fields else None,
         )
 
-        yield "records", data.get("records", [])
-        yield "offset", data.get("offset", None)
+        records = data.get("records", [])
+
+        # Normalize output if requested
+        if input_data.normalize_output:
+            # Fetch table schema
+            table_schema = await get_table_schema(
+                credentials, input_data.base_id, input_data.table_id_or_name
+            )
+
+            # Normalize the records
+            normalized_data = await normalize_records(
+                records,
+                table_schema,
+                include_field_metadata=input_data.include_field_metadata,
+            )
+
+            yield "records", normalized_data["records"]
+            yield "offset", data.get("offset", None)
+
+            if (
+                input_data.include_field_metadata
+                and "field_metadata" in normalized_data
+            ):
+                yield "field_metadata", normalized_data["field_metadata"]
+        else:
+            yield "records", records
+            yield "offset", data.get("offset", None)
 
 
 class AirtableGetRecordBlock(Block):
@@ -104,11 +144,23 @@ class AirtableGetRecordBlock(Block):
         base_id: str = SchemaField(description="The Airtable base ID")
         table_id_or_name: str = SchemaField(description="Table ID or name")
         record_id: str = SchemaField(description="The record ID to retrieve")
+        normalize_output: bool = SchemaField(
+            description="Normalize output to include all fields with proper empty values (disable to skip schema fetch and get raw Airtable response)",
+            default=True,
+        )
+        include_field_metadata: bool = SchemaField(
+            description="Include field type and configuration metadata (requires normalize_output=true)",
+            default=False,
+        )
 
     class Output(BlockSchema):
         id: str = SchemaField(description="The record ID")
         fields: dict = SchemaField(description="The record fields")
         created_time: str = SchemaField(description="The record created time")
+        field_metadata: Optional[dict] = SchemaField(
+            description="Field type and configuration metadata (only when include_field_metadata=true)",
+            default=None,
+        )
 
     def __init__(self):
         super().__init__(
@@ -122,6 +174,7 @@ class AirtableGetRecordBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
+
         record = await get_record(
             credentials,
             input_data.base_id,
@@ -129,9 +182,34 @@ class AirtableGetRecordBlock(Block):
             input_data.record_id,
         )
 
-        yield "id", record.get("id", None)
-        yield "fields", record.get("fields", None)
-        yield "created_time", record.get("createdTime", None)
+        # Normalize output if requested
+        if input_data.normalize_output:
+            # Fetch table schema
+            table_schema = await get_table_schema(
+                credentials, input_data.base_id, input_data.table_id_or_name
+            )
+
+            # Normalize the single record (wrap in list and unwrap result)
+            normalized_data = await normalize_records(
+                [record],
+                table_schema,
+                include_field_metadata=input_data.include_field_metadata,
+            )
+
+            normalized_record = normalized_data["records"][0]
+            yield "id", normalized_record.get("id", None)
+            yield "fields", normalized_record.get("fields", None)
+            yield "created_time", normalized_record.get("createdTime", None)
+
+            if (
+                input_data.include_field_metadata
+                and "field_metadata" in normalized_data
+            ):
+                yield "field_metadata", normalized_data["field_metadata"]
+        else:
+            yield "id", record.get("id", None)
+            yield "fields", record.get("fields", None)
+            yield "created_time", record.get("createdTime", None)
 
 
 class AirtableCreateRecordsBlock(Block):
@@ -148,6 +226,10 @@ class AirtableCreateRecordsBlock(Block):
         records: list[dict] = SchemaField(
             description="Array of records to create (each with 'fields' object)"
         )
+        skip_normalization: bool = SchemaField(
+            description="Skip output normalization to get raw Airtable response (faster but may have missing fields)",
+            default=False,
+        )
         typecast: bool = SchemaField(
             description="Automatically convert string values to appropriate types",
             default=False,
@@ -173,7 +255,7 @@ class AirtableCreateRecordsBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        # The create_record API expects records in a specific format
+
         data = await create_record(
             credentials,
             input_data.base_id,
@@ -182,8 +264,22 @@ class AirtableCreateRecordsBlock(Block):
             typecast=input_data.typecast if input_data.typecast else None,
             return_fields_by_field_id=input_data.return_fields_by_field_id,
         )
+        result_records = cast(list[dict], data.get("records", []))
 
-        yield "records", data.get("records", [])
+        # Normalize output unless explicitly disabled
+        if not input_data.skip_normalization and result_records:
+            # Fetch table schema
+            table_schema = await get_table_schema(
+                credentials, input_data.base_id, input_data.table_id_or_name
+            )
+
+            # Normalize the records
+            normalized_data = await normalize_records(
+                result_records, table_schema, include_field_metadata=False
+            )
+            result_records = normalized_data["records"]
+
+        yield "records", result_records
         details = data.get("details", None)
         if details:
             yield "details", details

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/bannerbear/__init__.py

@@ -0,0 +1,3 @@
+from .text_overlay import BannerbearTextOverlayBlock
+
+__all__ = ["BannerbearTextOverlayBlock"]

autogpt_platform/backend/backend/blocks/bannerbear/_config.py

@@ -0,0 +1,8 @@
+from backend.sdk import BlockCostType, ProviderBuilder
+
+bannerbear = (
+    ProviderBuilder("bannerbear")
+    .with_api_key("BANNERBEAR_API_KEY", "Bannerbear API Key")
+    .with_base_cost(1, BlockCostType.RUN)
+    .build()
+)

autogpt_platform/backend/backend/blocks/bannerbear/text_overlay.py

@@ -0,0 +1,239 @@
+import uuid
+from typing import TYPE_CHECKING, Any, Dict, List
+
+if TYPE_CHECKING:
+    pass
+
+from pydantic import SecretStr
+
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchema,
+    CredentialsMetaInput,
+    Requests,
+    SchemaField,
+)
+
+from ._config import bannerbear
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="bannerbear",
+    api_key=SecretStr("mock-bannerbear-api-key"),
+    title="Mock Bannerbear API Key",
+)
+
+
+class TextModification(BlockSchema):
+    name: str = SchemaField(
+        description="The name of the layer to modify in the template"
+    )
+    text: str = SchemaField(description="The text content to add to this layer")
+    color: str = SchemaField(
+        description="Hex color code for the text (e.g., '#FF0000')",
+        default="",
+        advanced=True,
+    )
+    font_family: str = SchemaField(
+        description="Font family to use for the text",
+        default="",
+        advanced=True,
+    )
+    font_size: int = SchemaField(
+        description="Font size in pixels",
+        default=0,
+        advanced=True,
+    )
+    font_weight: str = SchemaField(
+        description="Font weight (e.g., 'bold', 'normal')",
+        default="",
+        advanced=True,
+    )
+    text_align: str = SchemaField(
+        description="Text alignment (left, center, right)",
+        default="",
+        advanced=True,
+    )
+
+
+class BannerbearTextOverlayBlock(Block):
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput = bannerbear.credentials_field(
+            description="API credentials for Bannerbear"
+        )
+        template_id: str = SchemaField(
+            description="The unique ID of your Bannerbear template"
+        )
+        project_id: str = SchemaField(
+            description="Optional: Project ID (required when using Master API Key)",
+            default="",
+            advanced=True,
+        )
+        text_modifications: List[TextModification] = SchemaField(
+            description="List of text layers to modify in the template"
+        )
+        image_url: str = SchemaField(
+            description="Optional: URL of an image to use in the template",
+            default="",
+            advanced=True,
+        )
+        image_layer_name: str = SchemaField(
+            description="Optional: Name of the image layer in the template",
+            default="photo",
+            advanced=True,
+        )
+        webhook_url: str = SchemaField(
+            description="Optional: URL to receive webhook notification when image is ready",
+            default="",
+            advanced=True,
+        )
+        metadata: str = SchemaField(
+            description="Optional: Custom metadata to attach to the image",
+            default="",
+            advanced=True,
+        )
+
+    class Output(BlockSchema):
+        success: bool = SchemaField(
+            description="Whether the image generation was successfully initiated"
+        )
+        image_url: str = SchemaField(
+            description="URL of the generated image (if synchronous) or placeholder"
+        )
+        uid: str = SchemaField(description="Unique identifier for the generated image")
+        status: str = SchemaField(description="Status of the image generation")
+        error: str = SchemaField(description="Error message if the operation failed")
+
+    def __init__(self):
+        super().__init__(
+            id="c7d3a5c2-05fc-450e-8dce-3b0e04626009",
+            description="Add text overlay to images using Bannerbear templates. Perfect for creating social media graphics, marketing materials, and dynamic image content.",
+            categories={BlockCategory.PRODUCTIVITY, BlockCategory.AI},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "template_id": "jJWBKNELpQPvbX5R93Gk",
+                "text_modifications": [
+                    {
+                        "name": "headline",
+                        "text": "Amazing Product Launch!",
+                        "color": "#FF0000",
+                    },
+                    {
+                        "name": "subtitle",
+                        "text": "50% OFF Today Only",
+                    },
+                ],
+                "credentials": {
+                    "provider": "bannerbear",
+                    "id": str(uuid.uuid4()),
+                    "type": "api_key",
+                },
+            },
+            test_output=[
+                ("success", True),
+                ("image_url", "https://cdn.bannerbear.com/test-image.jpg"),
+                ("uid", "test-uid-123"),
+                ("status", "completed"),
+            ],
+            test_mock={
+                "_make_api_request": lambda *args, **kwargs: {
+                    "uid": "test-uid-123",
+                    "status": "completed",
+                    "image_url": "https://cdn.bannerbear.com/test-image.jpg",
+                }
+            },
+            test_credentials=TEST_CREDENTIALS,
+        )
+
+    async def _make_api_request(self, payload: dict, api_key: str) -> dict:
+        """Make the actual API request to Bannerbear. This is separated for easy mocking in tests."""
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+
+        response = await Requests().post(
+            "https://sync.api.bannerbear.com/v2/images",
+            headers=headers,
+            json=payload,
+        )
+
+        if response.status in [200, 201, 202]:
+            return response.json()
+        else:
+            error_msg = f"API request failed with status {response.status}"
+            if response.text:
+                try:
+                    error_data = response.json()
+                    error_msg = (
+                        f"{error_msg}: {error_data.get('message', response.text)}"
+                    )
+                except Exception:
+                    error_msg = f"{error_msg}: {response.text}"
+            raise Exception(error_msg)
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Build the modifications array
+        modifications = []
+
+        # Add text modifications
+        for text_mod in input_data.text_modifications:
+            mod_data: Dict[str, Any] = {
+                "name": text_mod.name,
+                "text": text_mod.text,
+            }
+
+            # Add optional text styling parameters only if they have values
+            if text_mod.color and text_mod.color.strip():
+                mod_data["color"] = text_mod.color
+            if text_mod.font_family and text_mod.font_family.strip():
+                mod_data["font_family"] = text_mod.font_family
+            if text_mod.font_size and text_mod.font_size > 0:
+                mod_data["font_size"] = text_mod.font_size
+            if text_mod.font_weight and text_mod.font_weight.strip():
+                mod_data["font_weight"] = text_mod.font_weight
+            if text_mod.text_align and text_mod.text_align.strip():
+                mod_data["text_align"] = text_mod.text_align
+
+            modifications.append(mod_data)
+
+        # Add image modification if provided and not empty
+        if input_data.image_url and input_data.image_url.strip():
+            modifications.append(
+                {
+                    "name": input_data.image_layer_name,
+                    "image_url": input_data.image_url,
+                }
+            )
+
+        # Build the request payload - only include non-empty optional fields
+        payload = {
+            "template": input_data.template_id,
+            "modifications": modifications,
+        }
+
+        # Add project_id if provided (required for Master API keys)
+        if input_data.project_id and input_data.project_id.strip():
+            payload["project_id"] = input_data.project_id
+
+        if input_data.webhook_url and input_data.webhook_url.strip():
+            payload["webhook_url"] = input_data.webhook_url
+        if input_data.metadata and input_data.metadata.strip():
+            payload["metadata"] = input_data.metadata
+
+        # Make the API request using the private method
+        data = await self._make_api_request(
+            payload, credentials.api_key.get_secret_value()
+        )
+
+        # Synchronous request - image should be ready
+        yield "success", True
+        yield "image_url", data.get("image_url", "")
+        yield "uid", data.get("uid", "")
+        yield "status", data.get("status", "completed")

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

@@ -0,0 +1,182 @@
+"""
+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,
+        depth: Optional[int] = None,
+    ) -> 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)
+            depth: Keyword search depth (0-4), controls number of returned keywords
+
+        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
+        if depth is not None:
+            task_data["depth"] = depth
+
+        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 +1,290 @@
+"""
+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,
+        )
+        depth: int = SchemaField(
+            description="Keyword search depth (0-4). Controls the number of returned keywords: 0=1 keyword, 1=~8 keywords, 2=~72 keywords, 3=~584 keywords, 4=~4680 keywords",
+            default=1,
+            ge=0,
+            le=4,
+        )
+
+    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,
+            depth=input_data.depth,
+        )
+
+    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/exa/websets.py

@@ -93,11 +93,11 @@ class Webset(BaseModel):
     """
     Set of key-value pairs you want to associate with this object.
     """
-    created_at: Annotated[datetime, Field(alias="createdAt")] | None = None
+    created_at: Annotated[datetime | None, Field(alias="createdAt")] = None
     """
     The date and time the webset was created
     """
-    updated_at: Annotated[datetime, Field(alias="updatedAt")] | None = None
+    updated_at: Annotated[datetime | None, Field(alias="updatedAt")] = None
     """
     The date and time the webset was last updated
     """

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

@@ -1094,6 +1094,117 @@ class GmailGetThreadBlock(GmailBase):
         return thread
 
 
+async def _build_reply_message(
+    service, input_data, graph_exec_id: str, user_id: str
+) -> tuple[str, str]:
+    """
+    Builds a reply MIME message for Gmail threads.
+
+    Returns:
+        tuple: (base64-encoded raw message, threadId)
+    """
+    # Get parent message for reply context
+    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()
+    )
+
+    # Build headers dictionary, preserving all values for duplicate headers
+    headers = {}
+    for h in parent.get("payload", {}).get("headers", []):
+        name = h["name"].lower()
+        value = h["value"]
+        if name in headers:
+            # For duplicate headers, keep the first occurrence (most relevant for reply context)
+            continue
+        headers[name] = value
+
+    # Determine recipients if not specified
+    if not (input_data.to or input_data.cc or input_data.bcc):
+        if input_data.replyAll:
+            recipients = [parseaddr(headers.get("from", ""))[1]]
+            recipients += [addr for _, addr in getaddresses([headers.get("to", "")])]
+            recipients += [addr for _, addr in getaddresses([headers.get("cc", "")])]
+            # Use dict.fromkeys() for O(n) deduplication while preserving order
+            input_data.to = list(dict.fromkeys(filter(None, recipients)))
+        else:
+            # Check Reply-To header first, fall back to From header
+            reply_to = headers.get("reply-to", "")
+            from_addr = headers.get("from", "")
+            sender = parseaddr(reply_to if reply_to else from_addr)[1]
+            input_data.to = [sender] if sender else []
+
+    # Set subject with Re: prefix if not already present
+    if input_data.subject:
+        subject = input_data.subject
+    else:
+        parent_subject = headers.get("subject", "").strip()
+        # Only add "Re:" if not already present (case-insensitive check)
+        if parent_subject.lower().startswith("re:"):
+            subject = parent_subject
+        else:
+            subject = f"Re: {parent_subject}" if parent_subject else "Re:"
+
+    # Build references header for proper threading
+    references = headers.get("references", "").split()
+    if headers.get("message-id"):
+        references.append(headers["message-id"])
+
+    # Create MIME message
+    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
+    if headers.get("message-id"):
+        msg["In-Reply-To"] = headers["message-id"]
+    if references:
+        msg["References"] = " ".join(references)
+
+    # Use the helper function for consistent content type handling
+    msg.attach(_make_mime_text(input_data.body, input_data.content_type))
+
+    # Handle attachments
+    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
+    raw = base64.urlsafe_b64encode(msg.as_bytes()).decode("utf-8")
+    return raw, input_data.threadId
+
+
 class GmailReplyBlock(GmailBase):
     """
     Replies to Gmail threads with intelligent content type detection.
@@ -1230,93 +1341,146 @@ class GmailReplyBlock(GmailBase):
     async def _reply(
         self, service, input_data: Input, graph_exec_id: str, user_id: str
     ) -> dict:
-        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()
+        # Build the reply message using the shared helper
+        raw, thread_id = await _build_reply_message(
+            service, input_data, graph_exec_id, user_id
         )
 
-        headers = {
-            h["name"].lower(): h["value"]
-            for h in parent.get("payload", {}).get("headers", [])
-        }
-        if not (input_data.to or input_data.cc or input_data.bcc):
-            if input_data.replyAll:
-                recipients = [parseaddr(headers.get("from", ""))[1]]
-                recipients += [
-                    addr for _, addr in getaddresses([headers.get("to", "")])
-                ]
-                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
-            else:
-                sender = parseaddr(headers.get("reply-to", headers.get("from", "")))[1]
-                input_data.to = [sender] if sender else []
-        subject = input_data.subject or (f"Re: {headers.get('subject', '')}".strip())
-        references = headers.get("references", "").split()
-        if headers.get("message-id"):
-            references.append(headers["message-id"])
-
-        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
-        if headers.get("message-id"):
-            msg["In-Reply-To"] = headers["message-id"]
-        if references:
-            msg["References"] = " ".join(references)
-        # Use the new helper function for consistent content type handling
-        msg.attach(_make_mime_text(input_data.body, input_data.content_type))
-
-        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)
-
-        raw = base64.urlsafe_b64encode(msg.as_bytes()).decode("utf-8")
+        # Send the message
         return await asyncio.to_thread(
             lambda: service.users()
             .messages()
-            .send(userId="me", body={"threadId": input_data.threadId, "raw": raw})
+            .send(userId="me", body={"threadId": thread_id, "raw": raw})
             .execute()
         )
 
 
+class GmailDraftReplyBlock(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 draft replies preserve natural line flow
+    - Manual content type override: Use content_type parameter to force specific format
+    - Reply-all functionality: Option to reply to all original recipients
+    - Thread preservation: Maintains proper email threading with headers
+    - Full Unicode/emoji support with UTF-8 encoding
+    """
+
+    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="d7a9f3e2-8b4c-4d6f-9e1a-3c5b7f8d2a6e",
+            description="Create draft replies to Gmail threads with automatic HTML detection and proper text formatting. Plain text draft replies maintain natural paragraph flow without 78-character line wrapping. HTML content is automatically detected and formatted correctly.",
+            categories={BlockCategory.COMMUNICATION},
+            input_schema=GmailDraftReplyBlock.Input,
+            output_schema=GmailDraftReplyBlock.Output,
+            disabled=not GOOGLE_OAUTH_IS_CONFIGURED,
+            test_input={
+                "threadId": "t1",
+                "parentMessageId": "m1",
+                "body": "Thanks for your message. I'll review and get back to you.",
+                "replyAll": False,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("draftId", "draft1"),
+                ("messageId", "m2"),
+                ("threadId", "t1"),
+                ("status", "draft_created"),
+            ],
+            test_mock={
+                "_create_draft_reply": lambda *args, **kwargs: {
+                    "id": "draft1",
+                    "message": {"id": "m2", "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)
+        draft = await self._create_draft_reply(
+            service,
+            input_data,
+            graph_exec_id,
+            user_id,
+        )
+        yield "draftId", draft["id"]
+        yield "messageId", draft["message"]["id"]
+        yield "threadId", draft["message"].get("threadId", input_data.threadId)
+        yield "status", "draft_created"
+
+    async def _create_draft_reply(
+        self, service, input_data: Input, graph_exec_id: str, user_id: str
+    ) -> dict:
+        # Build the reply message using the shared helper
+        raw, thread_id = await _build_reply_message(
+            service, input_data, graph_exec_id, user_id
+        )
+
+        # Create draft with proper thread association
+        draft = await asyncio.to_thread(
+            lambda: service.users()
+            .drafts()
+            .create(
+                userId="me",
+                body={
+                    "message": {
+                        "threadId": thread_id,
+                        "raw": raw,
+                    }
+                },
+            )
+            .execute()
+        )
+
+        return draft
+
+
 class GmailGetProfileBlock(GmailBase):
     class Input(BlockSchema):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(

autogpt_platform/backend/backend/blocks/ideogram.py

@@ -30,6 +30,7 @@ TEST_CREDENTIALS_INPUT = {
 
 
 class IdeogramModelName(str, Enum):
+    V3 = "V_3"
     V2 = "V_2"
     V1 = "V_1"
     V1_TURBO = "V_1_TURBO"
@@ -95,8 +96,8 @@ class IdeogramModelBlock(Block):
             title="Prompt",
         )
         ideogram_model_name: IdeogramModelName = SchemaField(
-            description="The name of the Image Generation Model, e.g., V_2",
-            default=IdeogramModelName.V2,
+            description="The name of the Image Generation Model, e.g., V_3",
+            default=IdeogramModelName.V3,
             title="Image Generation Model",
             advanced=False,
         )
@@ -236,6 +237,111 @@ class IdeogramModelBlock(Block):
         negative_prompt: Optional[str],
         color_palette_name: str,
         custom_colors: Optional[list[str]],
+    ):
+        # Use V3 endpoint for V3 model, legacy endpoint for others
+        if model_name == "V_3":
+            return await self._run_model_v3(
+                api_key,
+                prompt,
+                seed,
+                aspect_ratio,
+                magic_prompt_option,
+                style_type,
+                negative_prompt,
+                color_palette_name,
+                custom_colors,
+            )
+        else:
+            return await self._run_model_legacy(
+                api_key,
+                model_name,
+                prompt,
+                seed,
+                aspect_ratio,
+                magic_prompt_option,
+                style_type,
+                negative_prompt,
+                color_palette_name,
+                custom_colors,
+            )
+
+    async def _run_model_v3(
+        self,
+        api_key: SecretStr,
+        prompt: str,
+        seed: Optional[int],
+        aspect_ratio: str,
+        magic_prompt_option: str,
+        style_type: str,
+        negative_prompt: Optional[str],
+        color_palette_name: str,
+        custom_colors: Optional[list[str]],
+    ):
+        url = "https://api.ideogram.ai/v1/ideogram-v3/generate"
+        headers = {
+            "Api-Key": api_key.get_secret_value(),
+            "Content-Type": "application/json",
+        }
+
+        # Map legacy aspect ratio values to V3 format
+        aspect_ratio_map = {
+            "ASPECT_10_16": "10x16",
+            "ASPECT_16_10": "16x10",
+            "ASPECT_9_16": "9x16",
+            "ASPECT_16_9": "16x9",
+            "ASPECT_3_2": "3x2",
+            "ASPECT_2_3": "2x3",
+            "ASPECT_4_3": "4x3",
+            "ASPECT_3_4": "3x4",
+            "ASPECT_1_1": "1x1",
+            "ASPECT_1_3": "1x3",
+            "ASPECT_3_1": "3x1",
+            # Additional V3 supported ratios
+            "ASPECT_1_2": "1x2",
+            "ASPECT_2_1": "2x1",
+            "ASPECT_4_5": "4x5",
+            "ASPECT_5_4": "5x4",
+        }
+
+        v3_aspect_ratio = aspect_ratio_map.get(
+            aspect_ratio, "1x1"
+        )  # Default to 1x1 if not found
+
+        # Use JSON for V3 endpoint (simpler than multipart/form-data)
+        data: Dict[str, Any] = {
+            "prompt": prompt,
+            "aspect_ratio": v3_aspect_ratio,
+            "magic_prompt": magic_prompt_option,
+            "style_type": style_type,
+        }
+
+        if seed is not None:
+            data["seed"] = seed
+
+        if negative_prompt:
+            data["negative_prompt"] = negative_prompt
+
+        # Note: V3 endpoint may have different color palette support
+        # For now, we'll omit color palettes for V3 to avoid errors
+
+        try:
+            response = await Requests().post(url, headers=headers, json=data)
+            return response.json()["data"][0]["url"]
+        except RequestException as e:
+            raise Exception(f"Failed to fetch image with V3 endpoint: {str(e)}")
+
+    async def _run_model_legacy(
+        self,
+        api_key: SecretStr,
+        model_name: str,
+        prompt: str,
+        seed: Optional[int],
+        aspect_ratio: str,
+        magic_prompt_option: str,
+        style_type: str,
+        negative_prompt: Optional[str],
+        color_palette_name: str,
+        custom_colors: Optional[list[str]],
     ):
         url = "https://api.ideogram.ai/generate"
         headers = {
@@ -249,28 +355,33 @@ class IdeogramModelBlock(Block):
                 "model": model_name,
                 "aspect_ratio": aspect_ratio,
                 "magic_prompt_option": magic_prompt_option,
-                "style_type": style_type,
             }
         }
 
+        # Only add style_type for V2, V2_TURBO, and V3 models (V1 models don't support it)
+        if model_name in ["V_2", "V_2_TURBO", "V_3"]:
+            data["image_request"]["style_type"] = style_type
+
         if seed is not None:
             data["image_request"]["seed"] = seed
 
         if negative_prompt:
             data["image_request"]["negative_prompt"] = negative_prompt
 
-        if color_palette_name != "NONE":
-            data["color_palette"] = {"name": color_palette_name}
-        elif custom_colors:
-            data["color_palette"] = {
-                "members": [{"color_hex": color} for color in custom_colors]
-            }
+        # Only add color palette for V2 and V2_TURBO models (V1 models don't support it)
+        if model_name in ["V_2", "V_2_TURBO"]:
+            if color_palette_name != "NONE":
+                data["color_palette"] = {"name": color_palette_name}
+            elif custom_colors:
+                data["color_palette"] = {
+                    "members": [{"color_hex": color} for color in custom_colors]
+                }
 
         try:
             response = await Requests().post(url, headers=headers, json=data)
             return response.json()["data"][0]["url"]
         except RequestException as e:
-            raise Exception(f"Failed to fetch image: {str(e)}")
+            raise Exception(f"Failed to fetch image with legacy endpoint: {str(e)}")
 
     async def upscale_image(self, api_key: SecretStr, image_url: str):
         url = "https://api.ideogram.ai/upscale"

autogpt_platform/backend/backend/blocks/io.py

@@ -10,7 +10,6 @@ from backend.util.settings import Config
 from backend.util.text import TextFormatter
 from backend.util.type import LongTextType, MediaFileType, ShortTextType
 
-formatter = TextFormatter()
 config = Config()
 
 
@@ -132,6 +131,11 @@ class AgentOutputBlock(Block):
             default="",
             advanced=True,
         )
+        escape_html: bool = SchemaField(
+            default=False,
+            advanced=True,
+            description="Whether to escape special characters in the inserted values to be HTML-safe. Enable for HTML output, disable for plain text.",
+        )
         advanced: bool = SchemaField(
             description="Whether to treat the output as advanced.",
             default=False,
@@ -193,6 +197,7 @@ class AgentOutputBlock(Block):
         """
         if input_data.format:
             try:
+                formatter = TextFormatter(autoescape=input_data.escape_html)
                 yield "output", formatter.format_string(
                     input_data.format, {input_data.name: input_data.value}
                 )

autogpt_platform/backend/backend/blocks/llm.py

@@ -1,5 +1,9 @@
+# This file contains a lot of prompt block strings that would trigger "line too long"
+# flake8: noqa: E501
 import ast
 import logging
+import re
+import secrets
 from abc import ABC
 from enum import Enum, EnumMeta
 from json import JSONDecodeError
@@ -27,7 +31,7 @@ from backend.util.prompt import compress_prompt, estimate_token_count
 from backend.util.text import TextFormatter
 
 logger = TruncatedLogger(logging.getLogger(__name__), "[LLM-Block]")
-fmt = TextFormatter()
+fmt = TextFormatter(autoescape=False)
 
 LLMProviderName = Literal[
     ProviderName.AIML_API,
@@ -204,13 +208,13 @@ MODEL_METADATA = {
         "anthropic", 200000, 32000
     ),  # claude-opus-4-1-20250805
     LlmModel.CLAUDE_4_OPUS: ModelMetadata(
-        "anthropic", 200000, 8192
+        "anthropic", 200000, 32000
     ),  # claude-4-opus-20250514
     LlmModel.CLAUDE_4_SONNET: ModelMetadata(
-        "anthropic", 200000, 8192
+        "anthropic", 200000, 64000
     ),  # claude-4-sonnet-20250514
     LlmModel.CLAUDE_3_7_SONNET: ModelMetadata(
-        "anthropic", 200000, 8192
+        "anthropic", 200000, 64000
     ),  # claude-3-7-sonnet-20250219
     LlmModel.CLAUDE_3_5_SONNET: ModelMetadata(
         "anthropic", 200000, 8192
@@ -382,7 +386,9 @@ def extract_openai_tool_calls(response) -> list[ToolContentBlock] | None:
     return None
 
 
-def get_parallel_tool_calls_param(llm_model: LlmModel, parallel_tool_calls):
+def get_parallel_tool_calls_param(
+    llm_model: LlmModel, parallel_tool_calls: bool | None
+):
     """Get the appropriate parallel_tool_calls parameter for OpenAI-compatible APIs."""
     if llm_model.startswith("o") or parallel_tool_calls is None:
         return openai.NOT_GIVEN
@@ -393,8 +399,8 @@ async def llm_call(
     credentials: APIKeyCredentials,
     llm_model: LlmModel,
     prompt: list[dict],
-    json_format: bool,
     max_tokens: int | None,
+    force_json_output: bool = False,
     tools: list[dict] | None = None,
     ollama_host: str = "localhost:11434",
     parallel_tool_calls=None,
@@ -407,7 +413,7 @@ async def llm_call(
         credentials: The API key credentials to use.
         llm_model: The LLM model to use.
         prompt: The prompt to send to the LLM.
-        json_format: Whether the response should be in JSON format.
+        force_json_output: Whether the response should be in JSON format.
         max_tokens: The maximum number of tokens to generate in the chat completion.
         tools: The tools to use in the chat completion.
         ollama_host: The host for ollama to use.
@@ -446,7 +452,7 @@ async def llm_call(
             llm_model, parallel_tool_calls
         )
 
-        if json_format:
+        if force_json_output:
             response_format = {"type": "json_object"}
 
         response = await oai_client.chat.completions.create(
@@ -559,7 +565,7 @@ async def llm_call(
             raise ValueError("Groq does not support tools.")
 
         client = AsyncGroq(api_key=credentials.api_key.get_secret_value())
-        response_format = {"type": "json_object"} if json_format else None
+        response_format = {"type": "json_object"} if force_json_output else None
         response = await client.chat.completions.create(
             model=llm_model.value,
             messages=prompt,  # type: ignore
@@ -717,7 +723,7 @@ async def llm_call(
         )
 
         response_format = None
-        if json_format:
+        if force_json_output:
             response_format = {"type": "json_object"}
 
         parallel_tool_calls_param = get_parallel_tool_calls_param(
@@ -780,6 +786,17 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             description="The language model to use for answering the prompt.",
             advanced=False,
         )
+        force_json_output: bool = SchemaField(
+            title="Restrict LLM to pure JSON output",
+            default=False,
+            description=(
+                "Whether to force the LLM to produce a JSON-only response. "
+                "This can increase the block's reliability, "
+                "but may also reduce the quality of the response "
+                "because it prohibits the LLM from reasoning "
+                "before providing its JSON response."
+            ),
+        )
         credentials: AICredentials = AICredentialsField()
         sys_prompt: str = SchemaField(
             title="System Prompt",
@@ -848,17 +865,18 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                 "llm_call": lambda *args, **kwargs: LLMResponse(
                     raw_response="",
                     prompt=[""],
-                    response=json.dumps(
-                        {
-                            "key1": "key1Value",
-                            "key2": "key2Value",
-                        }
+                    response=(
+                        '<json_output id="test123456">{\n'
+                        '  "key1": "key1Value",\n'
+                        '  "key2": "key2Value"\n'
+                        "}</json_output>"
                     ),
                     tool_calls=None,
                     prompt_tokens=0,
                     completion_tokens=0,
                     reasoning=None,
-                )
+                ),
+                "get_collision_proof_output_tag_id": lambda *args: "test123456",
             },
         )
 
@@ -867,9 +885,9 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         credentials: APIKeyCredentials,
         llm_model: LlmModel,
         prompt: list[dict],
-        json_format: bool,
-        compress_prompt_to_fit: bool,
         max_tokens: int | None,
+        force_json_output: bool = False,
+        compress_prompt_to_fit: bool = True,
         tools: list[dict] | None = None,
         ollama_host: str = "localhost:11434",
     ) -> LLMResponse:
@@ -882,8 +900,8 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             credentials=credentials,
             llm_model=llm_model,
             prompt=prompt,
-            json_format=json_format,
             max_tokens=max_tokens,
+            force_json_output=force_json_output,
             tools=tools,
             ollama_host=ollama_host,
             compress_prompt_to_fit=compress_prompt_to_fit,
@@ -895,10 +913,6 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         logger.debug(f"Calling LLM with input data: {input_data}")
         prompt = [json.to_dict(p) for p in input_data.conversation_history]
 
-        def trim_prompt(s: str) -> str:
-            lines = s.strip().split("\n")
-            return "\n".join([line.strip().lstrip("|") for line in lines])
-
         values = input_data.prompt_values
         if values:
             input_data.prompt = fmt.format_string(input_data.prompt, values)
@@ -907,27 +921,15 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         if input_data.sys_prompt:
             prompt.append({"role": "system", "content": input_data.sys_prompt})
 
+        # Use a one-time unique tag to prevent collisions with user/LLM content
+        output_tag_id = self.get_collision_proof_output_tag_id()
+        output_tag_start = f'<json_output id="{output_tag_id}">'
         if input_data.expected_format:
-            expected_format = [
-                f'"{k}": "{v}"' for k, v in input_data.expected_format.items()
-            ]
-            if input_data.list_result:
-                format_prompt = (
-                    f'"results": [\n  {{\n  {", ".join(expected_format)}\n  }}\n]'
-                )
-            else:
-                format_prompt = "\n  ".join(expected_format)
-
-            sys_prompt = trim_prompt(
-                f"""
-                  |Reply strictly only in the following JSON format:
-                  |{{
-                  |  {format_prompt}
-                  |}}
-                  |
-                  |Ensure the response is valid JSON. Do not include any additional text outside of the JSON.
-                  |If you cannot provide all the keys, provide an empty string for the values you cannot answer.
-                """
+            sys_prompt = self.response_format_instructions(
+                input_data.expected_format,
+                list_mode=input_data.list_result,
+                pure_json_mode=input_data.force_json_output,
+                output_tag_start=output_tag_start,
             )
             prompt.append({"role": "system", "content": sys_prompt})
 
@@ -945,18 +947,21 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             except JSONDecodeError as e:
                 return f"JSON decode error: {e}"
 
-        logger.debug(f"LLM request: {prompt}")
-        retry_prompt = ""
+        error_feedback_message = ""
         llm_model = input_data.model
 
         for retry_count in range(input_data.retry):
+            logger.debug(f"LLM request: {prompt}")
             try:
                 llm_response = await self.llm_call(
                     credentials=credentials,
                     llm_model=llm_model,
                     prompt=prompt,
                     compress_prompt_to_fit=input_data.compress_prompt_to_fit,
-                    json_format=bool(input_data.expected_format),
+                    force_json_output=(
+                        input_data.force_json_output
+                        and bool(input_data.expected_format)
+                    ),
                     ollama_host=input_data.ollama_host,
                     max_tokens=input_data.max_tokens,
                 )
@@ -970,16 +975,55 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                 logger.debug(f"LLM attempt-{retry_count} response: {response_text}")
 
                 if input_data.expected_format:
+                    try:
+                        response_obj = self.get_json_from_response(
+                            response_text,
+                            pure_json_mode=input_data.force_json_output,
+                            output_tag_start=output_tag_start,
+                        )
+                    except (ValueError, JSONDecodeError) as parse_error:
+                        censored_response = re.sub(r"[A-Za-z0-9]", "*", response_text)
+                        response_snippet = (
+                            f"{censored_response[:50]}...{censored_response[-30:]}"
+                        )
+                        logger.warning(
+                            f"Error getting JSON from LLM response: {parse_error}\n\n"
+                            f"Response start+end: `{response_snippet}`"
+                        )
+                        prompt.append({"role": "assistant", "content": response_text})
 
-                    response_obj = json.loads(response_text)
+                        error_feedback_message = self.invalid_response_feedback(
+                            parse_error,
+                            was_parseable=False,
+                            list_mode=input_data.list_result,
+                            pure_json_mode=input_data.force_json_output,
+                            output_tag_start=output_tag_start,
+                        )
+                        prompt.append(
+                            {"role": "user", "content": error_feedback_message}
+                        )
+                        continue
 
+                    # Handle object response for `force_json_output`+`list_result`
                     if input_data.list_result and isinstance(response_obj, dict):
-                        if "results" in response_obj:
-                            response_obj = response_obj.get("results", [])
-                        elif len(response_obj) == 1:
-                            response_obj = list(response_obj.values())
+                        if "results" in response_obj and isinstance(
+                            response_obj["results"], list
+                        ):
+                            response_obj = response_obj["results"]
+                        else:
+                            error_feedback_message = (
+                                "Expected an array of objects in the 'results' key, "
+                                f"but got: {response_obj}"
+                            )
+                            prompt.append(
+                                {"role": "assistant", "content": response_text}
+                            )
+                            prompt.append(
+                                {"role": "user", "content": error_feedback_message}
+                            )
+                            continue
 
-                    response_error = "\n".join(
+                    validation_errors = "\n".join(
                         [
                             validation_error
                             for response_item in (
@@ -991,7 +1035,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                         ]
                     )
 
-                    if not response_error:
+                    if not validation_errors:
                         self.merge_stats(
                             NodeExecutionStats(
                                 llm_call_count=retry_count + 1,
@@ -1001,6 +1045,16 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                         yield "response", response_obj
                         yield "prompt", self.prompt
                         return
+
+                    prompt.append({"role": "assistant", "content": response_text})
+                    error_feedback_message = self.invalid_response_feedback(
+                        validation_errors,
+                        was_parseable=True,
+                        list_mode=input_data.list_result,
+                        pure_json_mode=input_data.force_json_output,
+                        output_tag_start=output_tag_start,
+                    )
+                    prompt.append({"role": "user", "content": error_feedback_message})
                 else:
                     self.merge_stats(
                         NodeExecutionStats(
@@ -1011,21 +1065,6 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                     yield "response", {"response": response_text}
                     yield "prompt", self.prompt
                     return
-
-                retry_prompt = trim_prompt(
-                    f"""
-                  |This is your previous error response:
-                  |--
-                  |{response_text}
-                  |--
-                  |
-                  |And this is the error:
-                  |--
-                  |{response_error}
-                  |--
-                """
-                )
-                prompt.append({"role": "user", "content": retry_prompt})
             except Exception as e:
                 logger.exception(f"Error calling LLM: {e}")
                 if (
@@ -1038,9 +1077,133 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                     logger.debug(
                         f"Reducing max_tokens to {input_data.max_tokens} for next attempt"
                     )
-                retry_prompt = f"Error calling LLM: {e}"
+                    # Don't add retry prompt for token limit errors,
+                    # just retry with lower maximum output tokens
 
-        raise RuntimeError(retry_prompt)
+                error_feedback_message = f"Error calling LLM: {e}"
+
+        raise RuntimeError(error_feedback_message)
+
+    def response_format_instructions(
+        self,
+        expected_object_format: dict[str, str],
+        *,
+        list_mode: bool,
+        pure_json_mode: bool,
+        output_tag_start: str,
+    ) -> str:
+        expected_output_format = json.dumps(expected_object_format, indent=2)
+        output_type = "object" if not list_mode else "array"
+        outer_output_type = "object" if pure_json_mode else output_type
+
+        if output_type == "array":
+            indented_obj_format = expected_output_format.replace("\n", "\n  ")
+            expected_output_format = f"[\n  {indented_obj_format},\n  ...\n]"
+            if pure_json_mode:
+                indented_list_format = expected_output_format.replace("\n", "\n  ")
+                expected_output_format = (
+                    "{\n"
+                    '  "reasoning": "... (optional)",\n'  # for better performance
+                    f'  "results": {indented_list_format}\n'
+                    "}"
+                )
+
+        # Preserve indentation in prompt
+        expected_output_format = expected_output_format.replace("\n", "\n|")
+
+        # Prepare prompt
+        if not pure_json_mode:
+            expected_output_format = (
+                f"{output_tag_start}\n{expected_output_format}\n</json_output>"
+            )
+
+        instructions = f"""
+        |In your response you MUST include a valid JSON {outer_output_type} strictly following this format:
+        |{expected_output_format}
+        |
+        |If you cannot provide all the keys, you MUST provide an empty string for the values you cannot answer.
+        """.strip()
+
+        if not pure_json_mode:
+            instructions += f"""
+            |
+            |You MUST enclose your final JSON answer in {output_tag_start}...</json_output> tags, even if the user specifies a different tag.
+            |There MUST be exactly ONE {output_tag_start}...</json_output> block in your response, which MUST ONLY contain the JSON {outer_output_type} and nothing else. Other text outside this block is allowed.
+            """.strip()
+
+        return trim_prompt(instructions)
+
+    def invalid_response_feedback(
+        self,
+        error,
+        *,
+        was_parseable: bool,
+        list_mode: bool,
+        pure_json_mode: bool,
+        output_tag_start: str,
+    ) -> str:
+        outer_output_type = "object" if not list_mode or pure_json_mode else "array"
+
+        if was_parseable:
+            complaint = f"Your previous response did not match the expected {outer_output_type} format."
+        else:
+            complaint = f"Your previous response did not contain a parseable JSON {outer_output_type}."
+
+        indented_parse_error = str(error).replace("\n", "\n|")
+
+        instruction = (
+            f"Please provide a {output_tag_start}...</json_output> block containing a"
+            if not pure_json_mode
+            else "Please provide a"
+        ) + f" valid JSON {outer_output_type} that matches the expected format."
+
+        return trim_prompt(
+            f"""
+            |{complaint}
+            |
+            |{indented_parse_error}
+            |
+            |{instruction}
+        """
+        )
+
+    def get_json_from_response(
+        self, response_text: str, *, pure_json_mode: bool, output_tag_start: str
+    ) -> dict[str, Any] | list[dict[str, Any]]:
+        if pure_json_mode:
+            # Handle pure JSON responses
+            try:
+                return json.loads(response_text)
+            except JSONDecodeError as first_parse_error:
+                # If that didn't work, try finding the { and } to deal with possible ```json fences etc.
+                json_start = response_text.find("{")
+                json_end = response_text.rfind("}")
+                try:
+                    return json.loads(response_text[json_start : json_end + 1])
+                except JSONDecodeError:
+                    # Raise the original error, as it's more likely to be relevant
+                    raise first_parse_error from None
+
+        if output_tag_start not in response_text:
+            raise ValueError(
+                "Response does not contain the expected "
+                f"{output_tag_start}...</json_output> block."
+            )
+        json_output = (
+            response_text.split(output_tag_start, 1)[1]
+            .rsplit("</json_output>", 1)[0]
+            .strip()
+        )
+        return json.loads(json_output)
+
+    def get_collision_proof_output_tag_id(self) -> str:
+        return secrets.token_hex(8)
+
+
+def trim_prompt(s: str) -> str:
+    """Removes indentation up to and including `|` from a multi-line prompt."""
+    lines = s.strip().split("\n")
+    return "\n".join([line.strip().lstrip("|") for line in lines])
 
 
 class AITextGeneratorBlock(AIBlockBase):

autogpt_platform/backend/backend/blocks/notion/_api.py

@@ -0,0 +1,536 @@
+"""
+Notion API helper functions and client for making authenticated requests.
+"""
+
+from typing import Any, Dict, List, Optional
+
+from backend.data.model import OAuth2Credentials
+from backend.util.request import Requests
+
+NOTION_VERSION = "2022-06-28"
+
+
+class NotionAPIException(Exception):
+    """Exception raised for Notion API errors."""
+
+    def __init__(self, message: str, status_code: int):
+        super().__init__(message)
+        self.status_code = status_code
+
+
+class NotionClient:
+    """Client for interacting with the Notion API."""
+
+    def __init__(self, credentials: OAuth2Credentials):
+        self.credentials = credentials
+        self.headers = {
+            "Authorization": credentials.auth_header(),
+            "Notion-Version": NOTION_VERSION,
+            "Content-Type": "application/json",
+        }
+        self.requests = Requests()
+
+    async def get_page(self, page_id: str) -> dict:
+        """
+        Fetch a page by ID.
+
+        Args:
+            page_id: The ID of the page to fetch.
+
+        Returns:
+            The page object from Notion API.
+        """
+        url = f"https://api.notion.com/v1/pages/{page_id}"
+        response = await self.requests.get(url, headers=self.headers)
+
+        if not response.ok:
+            raise NotionAPIException(
+                f"Failed to fetch page: {response.status} - {response.text()}",
+                response.status,
+            )
+
+        return response.json()
+
+    async def get_blocks(self, block_id: str, recursive: bool = True) -> List[dict]:
+        """
+        Fetch all blocks from a page or block.
+
+        Args:
+            block_id: The ID of the page or block to fetch children from.
+            recursive: Whether to fetch nested blocks recursively.
+
+        Returns:
+            List of block objects.
+        """
+        blocks = []
+        cursor = None
+
+        while True:
+            url = f"https://api.notion.com/v1/blocks/{block_id}/children"
+            params = {"page_size": 100}
+            if cursor:
+                params["start_cursor"] = cursor
+
+            response = await self.requests.get(url, headers=self.headers, params=params)
+
+            if not response.ok:
+                raise NotionAPIException(
+                    f"Failed to fetch blocks: {response.status} - {response.text()}",
+                    response.status,
+                )
+
+            data = response.json()
+            current_blocks = data.get("results", [])
+
+            # If recursive, fetch children for blocks that have them
+            if recursive:
+                for block in current_blocks:
+                    if block.get("has_children"):
+                        block["children"] = await self.get_blocks(
+                            block["id"], recursive=True
+                        )
+
+            blocks.extend(current_blocks)
+
+            if not data.get("has_more"):
+                break
+            cursor = data.get("next_cursor")
+
+        return blocks
+
+    async def query_database(
+        self,
+        database_id: str,
+        filter_obj: Optional[dict] = None,
+        sorts: Optional[List[dict]] = None,
+        page_size: int = 100,
+    ) -> dict:
+        """
+        Query a database with optional filters and sorts.
+
+        Args:
+            database_id: The ID of the database to query.
+            filter_obj: Optional filter object for the query.
+            sorts: Optional list of sort objects.
+            page_size: Number of results per page.
+
+        Returns:
+            Query results including pages and pagination info.
+        """
+        url = f"https://api.notion.com/v1/databases/{database_id}/query"
+
+        payload: Dict[str, Any] = {"page_size": page_size}
+        if filter_obj:
+            payload["filter"] = filter_obj
+        if sorts:
+            payload["sorts"] = sorts
+
+        response = await self.requests.post(url, headers=self.headers, json=payload)
+
+        if not response.ok:
+            raise NotionAPIException(
+                f"Failed to query database: {response.status} - {response.text()}",
+                response.status,
+            )
+
+        return response.json()
+
+    async def create_page(
+        self,
+        parent: dict,
+        properties: dict,
+        children: Optional[List[dict]] = None,
+        icon: Optional[dict] = None,
+        cover: Optional[dict] = None,
+    ) -> dict:
+        """
+        Create a new page.
+
+        Args:
+            parent: Parent object (page_id or database_id).
+            properties: Page properties.
+            children: Optional list of block children.
+            icon: Optional icon object.
+            cover: Optional cover object.
+
+        Returns:
+            The created page object.
+        """
+        url = "https://api.notion.com/v1/pages"
+
+        payload: Dict[str, Any] = {"parent": parent, "properties": properties}
+
+        if children:
+            payload["children"] = children
+        if icon:
+            payload["icon"] = icon
+        if cover:
+            payload["cover"] = cover
+
+        response = await self.requests.post(url, headers=self.headers, json=payload)
+
+        if not response.ok:
+            raise NotionAPIException(
+                f"Failed to create page: {response.status} - {response.text()}",
+                response.status,
+            )
+
+        return response.json()
+
+    async def update_page(self, page_id: str, properties: dict) -> dict:
+        """
+        Update a page's properties.
+
+        Args:
+            page_id: The ID of the page to update.
+            properties: Properties to update.
+
+        Returns:
+            The updated page object.
+        """
+        url = f"https://api.notion.com/v1/pages/{page_id}"
+
+        response = await self.requests.patch(
+            url, headers=self.headers, json={"properties": properties}
+        )
+
+        if not response.ok:
+            raise NotionAPIException(
+                f"Failed to update page: {response.status} - {response.text()}",
+                response.status,
+            )
+
+        return response.json()
+
+    async def append_blocks(self, block_id: str, children: List[dict]) -> dict:
+        """
+        Append blocks to a page or block.
+
+        Args:
+            block_id: The ID of the page or block to append to.
+            children: List of block objects to append.
+
+        Returns:
+            Response with the created blocks.
+        """
+        url = f"https://api.notion.com/v1/blocks/{block_id}/children"
+
+        response = await self.requests.patch(
+            url, headers=self.headers, json={"children": children}
+        )
+
+        if not response.ok:
+            raise NotionAPIException(
+                f"Failed to append blocks: {response.status} - {response.text()}",
+                response.status,
+            )
+
+        return response.json()
+
+    async def search(
+        self,
+        query: str = "",
+        filter_obj: Optional[dict] = None,
+        sort: Optional[dict] = None,
+        page_size: int = 100,
+    ) -> dict:
+        """
+        Search for pages and databases.
+
+        Args:
+            query: Search query text.
+            filter_obj: Optional filter object.
+            sort: Optional sort object.
+            page_size: Number of results per page.
+
+        Returns:
+            Search results.
+        """
+        url = "https://api.notion.com/v1/search"
+
+        payload: Dict[str, Any] = {"page_size": page_size}
+        if query:
+            payload["query"] = query
+        if filter_obj:
+            payload["filter"] = filter_obj
+        if sort:
+            payload["sort"] = sort
+
+        response = await self.requests.post(url, headers=self.headers, json=payload)
+
+        if not response.ok:
+            raise NotionAPIException(
+                f"Search failed: {response.status} - {response.text()}", response.status
+            )
+
+        return response.json()
+
+
+# Conversion helper functions
+
+
+def parse_rich_text(rich_text_array: List[dict]) -> str:
+    """
+    Extract plain text from a Notion rich text array.
+
+    Args:
+        rich_text_array: Array of rich text objects from Notion.
+
+    Returns:
+        Plain text string.
+    """
+    if not rich_text_array:
+        return ""
+
+    text_parts = []
+    for text_obj in rich_text_array:
+        if "plain_text" in text_obj:
+            text_parts.append(text_obj["plain_text"])
+
+    return "".join(text_parts)
+
+
+def rich_text_to_markdown(rich_text_array: List[dict]) -> str:
+    """
+    Convert Notion rich text array to markdown with formatting.
+
+    Args:
+        rich_text_array: Array of rich text objects from Notion.
+
+    Returns:
+        Markdown formatted string.
+    """
+    if not rich_text_array:
+        return ""
+
+    markdown_parts = []
+
+    for text_obj in rich_text_array:
+        text = text_obj.get("plain_text", "")
+        annotations = text_obj.get("annotations", {})
+
+        # Apply formatting based on annotations
+        if annotations.get("code"):
+            text = f"`{text}`"
+        else:
+            if annotations.get("bold"):
+                text = f"**{text}**"
+            if annotations.get("italic"):
+                text = f"*{text}*"
+            if annotations.get("strikethrough"):
+                text = f"~~{text}~~"
+            if annotations.get("underline"):
+                text = f"<u>{text}</u>"
+
+        # Handle links
+        if text_obj.get("href"):
+            text = f"[{text}]({text_obj['href']})"
+
+        markdown_parts.append(text)
+
+    return "".join(markdown_parts)
+
+
+def block_to_markdown(block: dict, indent_level: int = 0) -> str:
+    """
+    Convert a single Notion block to markdown.
+
+    Args:
+        block: Block object from Notion API.
+        indent_level: Current indentation level for nested blocks.
+
+    Returns:
+        Markdown string representation of the block.
+    """
+    block_type = block.get("type")
+    indent = "  " * indent_level
+    markdown_lines = []
+
+    # Handle different block types
+    if block_type == "paragraph":
+        text = rich_text_to_markdown(block["paragraph"].get("rich_text", []))
+        if text:
+            markdown_lines.append(f"{indent}{text}")
+
+    elif block_type == "heading_1":
+        text = parse_rich_text(block["heading_1"].get("rich_text", []))
+        markdown_lines.append(f"{indent}# {text}")
+
+    elif block_type == "heading_2":
+        text = parse_rich_text(block["heading_2"].get("rich_text", []))
+        markdown_lines.append(f"{indent}## {text}")
+
+    elif block_type == "heading_3":
+        text = parse_rich_text(block["heading_3"].get("rich_text", []))
+        markdown_lines.append(f"{indent}### {text}")
+
+    elif block_type == "bulleted_list_item":
+        text = rich_text_to_markdown(block["bulleted_list_item"].get("rich_text", []))
+        markdown_lines.append(f"{indent}- {text}")
+
+    elif block_type == "numbered_list_item":
+        text = rich_text_to_markdown(block["numbered_list_item"].get("rich_text", []))
+        # Note: This is simplified - proper numbering would need context
+        markdown_lines.append(f"{indent}1. {text}")
+
+    elif block_type == "to_do":
+        text = rich_text_to_markdown(block["to_do"].get("rich_text", []))
+        checked = "x" if block["to_do"].get("checked") else " "
+        markdown_lines.append(f"{indent}- [{checked}] {text}")
+
+    elif block_type == "toggle":
+        text = rich_text_to_markdown(block["toggle"].get("rich_text", []))
+        markdown_lines.append(f"{indent}<details>")
+        markdown_lines.append(f"{indent}<summary>{text}</summary>")
+        markdown_lines.append(f"{indent}")
+        # Process children if they exist
+        if block.get("children"):
+            for child in block["children"]:
+                child_markdown = block_to_markdown(child, indent_level + 1)
+                if child_markdown:
+                    markdown_lines.append(child_markdown)
+        markdown_lines.append(f"{indent}</details>")
+
+    elif block_type == "code":
+        code = parse_rich_text(block["code"].get("rich_text", []))
+        language = block["code"].get("language", "")
+        markdown_lines.append(f"{indent}```{language}")
+        markdown_lines.append(f"{indent}{code}")
+        markdown_lines.append(f"{indent}```")
+
+    elif block_type == "quote":
+        text = rich_text_to_markdown(block["quote"].get("rich_text", []))
+        markdown_lines.append(f"{indent}> {text}")
+
+    elif block_type == "divider":
+        markdown_lines.append(f"{indent}---")
+
+    elif block_type == "image":
+        image = block["image"]
+        url = image.get("external", {}).get("url") or image.get("file", {}).get(
+            "url", ""
+        )
+        caption = parse_rich_text(image.get("caption", []))
+        alt_text = caption if caption else "Image"
+        markdown_lines.append(f"{indent}![{alt_text}]({url})")
+        if caption:
+            markdown_lines.append(f"{indent}*{caption}*")
+
+    elif block_type == "video":
+        video = block["video"]
+        url = video.get("external", {}).get("url") or video.get("file", {}).get(
+            "url", ""
+        )
+        caption = parse_rich_text(video.get("caption", []))
+        markdown_lines.append(f"{indent}[Video]({url})")
+        if caption:
+            markdown_lines.append(f"{indent}*{caption}*")
+
+    elif block_type == "file":
+        file = block["file"]
+        url = file.get("external", {}).get("url") or file.get("file", {}).get("url", "")
+        caption = parse_rich_text(file.get("caption", []))
+        name = caption if caption else "File"
+        markdown_lines.append(f"{indent}[{name}]({url})")
+
+    elif block_type == "bookmark":
+        url = block["bookmark"].get("url", "")
+        caption = parse_rich_text(block["bookmark"].get("caption", []))
+        markdown_lines.append(f"{indent}[{caption if caption else url}]({url})")
+
+    elif block_type == "equation":
+        expression = block["equation"].get("expression", "")
+        markdown_lines.append(f"{indent}$${expression}$$")
+
+    elif block_type == "callout":
+        text = rich_text_to_markdown(block["callout"].get("rich_text", []))
+        icon = block["callout"].get("icon", {})
+        if icon.get("emoji"):
+            markdown_lines.append(f"{indent}> {icon['emoji']} {text}")
+        else:
+            markdown_lines.append(f"{indent}> ℹ️ {text}")
+
+    elif block_type == "child_page":
+        title = block["child_page"].get("title", "Untitled")
+        markdown_lines.append(f"{indent}📄 [{title}](notion://page/{block['id']})")
+
+    elif block_type == "child_database":
+        title = block["child_database"].get("title", "Untitled Database")
+        markdown_lines.append(f"{indent}🗂️ [{title}](notion://database/{block['id']})")
+
+    elif block_type == "table":
+        # Tables are complex - for now just indicate there's a table
+        markdown_lines.append(
+            f"{indent}[Table with {block['table'].get('table_width', 0)} columns]"
+        )
+
+    elif block_type == "column_list":
+        # Process columns
+        if block.get("children"):
+            markdown_lines.append(f"{indent}<div style='display: flex'>")
+            for column in block["children"]:
+                markdown_lines.append(f"{indent}<div style='flex: 1'>")
+                if column.get("children"):
+                    for child in column["children"]:
+                        child_markdown = block_to_markdown(child, indent_level + 1)
+                        if child_markdown:
+                            markdown_lines.append(child_markdown)
+                markdown_lines.append(f"{indent}</div>")
+            markdown_lines.append(f"{indent}</div>")
+
+    # Handle children for blocks that haven't been processed yet
+    elif block.get("children") and block_type not in ["toggle", "column_list"]:
+        for child in block["children"]:
+            child_markdown = block_to_markdown(child, indent_level)
+            if child_markdown:
+                markdown_lines.append(child_markdown)
+
+    return "\n".join(markdown_lines) if markdown_lines else ""
+
+
+def blocks_to_markdown(blocks: List[dict]) -> str:
+    """
+    Convert a list of Notion blocks to a markdown document.
+
+    Args:
+        blocks: List of block objects from Notion API.
+
+    Returns:
+        Complete markdown document as a string.
+    """
+    markdown_parts = []
+
+    for i, block in enumerate(blocks):
+        markdown = block_to_markdown(block)
+        if markdown:
+            markdown_parts.append(markdown)
+            # Add spacing between top-level blocks (except lists)
+            if i < len(blocks) - 1:
+                next_type = blocks[i + 1].get("type", "")
+                current_type = block.get("type", "")
+                # Don't add extra spacing between list items
+                list_types = {"bulleted_list_item", "numbered_list_item", "to_do"}
+                if not (current_type in list_types and next_type in list_types):
+                    markdown_parts.append("")
+
+    return "\n".join(markdown_parts)
+
+
+def extract_page_title(page: dict) -> str:
+    """
+    Extract the title from a Notion page object.
+
+    Args:
+        page: Page object from Notion API.
+
+    Returns:
+        Page title as a string.
+    """
+    properties = page.get("properties", {})
+
+    # Find the title property (it has type "title")
+    for prop_name, prop_value in properties.items():
+        if prop_value.get("type") == "title":
+            return parse_rich_text(prop_value.get("title", []))
+
+    return "Untitled"

autogpt_platform/backend/backend/blocks/notion/_auth.py

@@ -0,0 +1,42 @@
+from typing import Literal
+
+from pydantic import SecretStr
+
+from backend.data.model import CredentialsField, CredentialsMetaInput, OAuth2Credentials
+from backend.integrations.providers import ProviderName
+from backend.util.settings import Secrets
+
+secrets = Secrets()
+NOTION_OAUTH_IS_CONFIGURED = bool(
+    secrets.notion_client_id and secrets.notion_client_secret
+)
+
+NotionCredentials = OAuth2Credentials
+NotionCredentialsInput = CredentialsMetaInput[
+    Literal[ProviderName.NOTION], Literal["oauth2"]
+]
+
+
+def NotionCredentialsField() -> NotionCredentialsInput:
+    """Creates a Notion OAuth2 credentials field."""
+    return CredentialsField(
+        description="Connect your Notion account. Ensure the pages/databases are shared with the integration."
+    )
+
+
+# Test credentials for Notion OAuth2
+TEST_CREDENTIALS = OAuth2Credentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="notion",
+    access_token=SecretStr("test_access_token"),
+    title="Mock Notion OAuth",
+    scopes=["read_content", "insert_content", "update_content"],
+    username="testuser",
+)
+
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}

autogpt_platform/backend/backend/blocks/notion/create_page.py

@@ -0,0 +1,360 @@
+from __future__ import annotations
+
+from typing import Any, Dict, List, Optional
+
+from pydantic import model_validator
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import OAuth2Credentials, SchemaField
+
+from ._api import NotionClient
+from ._auth import (
+    NOTION_OAUTH_IS_CONFIGURED,
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    NotionCredentialsField,
+    NotionCredentialsInput,
+)
+
+
+class NotionCreatePageBlock(Block):
+    """Create a new page in Notion with content."""
+
+    class Input(BlockSchema):
+        credentials: NotionCredentialsInput = NotionCredentialsField()
+        parent_page_id: Optional[str] = SchemaField(
+            description="Parent page ID to create the page under. Either this OR parent_database_id is required.",
+            default=None,
+        )
+        parent_database_id: Optional[str] = SchemaField(
+            description="Parent database ID to create the page in. Either this OR parent_page_id is required.",
+            default=None,
+        )
+        title: str = SchemaField(
+            description="Title of the new page",
+        )
+        content: Optional[str] = SchemaField(
+            description="Content for the page. Can be plain text or markdown - will be converted to Notion blocks.",
+            default=None,
+        )
+        properties: Optional[Dict[str, Any]] = SchemaField(
+            description="Additional properties for database pages (e.g., {'Status': 'In Progress', 'Priority': 'High'})",
+            default=None,
+        )
+        icon_emoji: Optional[str] = SchemaField(
+            description="Emoji to use as the page icon (e.g., '📄', '🚀')", default=None
+        )
+
+        @model_validator(mode="after")
+        def validate_parent(self):
+            """Ensure either parent_page_id or parent_database_id is provided."""
+            if not self.parent_page_id and not self.parent_database_id:
+                raise ValueError(
+                    "Either parent_page_id or parent_database_id must be provided"
+                )
+            if self.parent_page_id and self.parent_database_id:
+                raise ValueError(
+                    "Only one of parent_page_id or parent_database_id should be provided, not both"
+                )
+            return self
+
+    class Output(BlockSchema):
+        page_id: str = SchemaField(description="ID of the created page.")
+        page_url: str = SchemaField(description="URL of the created page.")
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="c15febe0-66ce-4c6f-aebd-5ab351653804",
+            description="Create a new page in Notion. Requires EITHER a parent_page_id OR parent_database_id. Supports markdown content.",
+            categories={BlockCategory.PRODUCTIVITY},
+            input_schema=NotionCreatePageBlock.Input,
+            output_schema=NotionCreatePageBlock.Output,
+            disabled=not NOTION_OAUTH_IS_CONFIGURED,
+            test_input={
+                "parent_page_id": "00000000-0000-0000-0000-000000000000",
+                "title": "Test Page",
+                "content": "This is test content.",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[
+                ("page_id", "12345678-1234-1234-1234-123456789012"),
+                (
+                    "page_url",
+                    "https://notion.so/Test-Page-12345678123412341234123456789012",
+                ),
+            ],
+            test_credentials=TEST_CREDENTIALS,
+            test_mock={
+                "create_page": lambda *args, **kwargs: (
+                    "12345678-1234-1234-1234-123456789012",
+                    "https://notion.so/Test-Page-12345678123412341234123456789012",
+                )
+            },
+        )
+
+    @staticmethod
+    def _markdown_to_blocks(content: str) -> List[dict]:
+        """Convert markdown content to Notion block objects."""
+        if not content:
+            return []
+
+        blocks = []
+        lines = content.split("\n")
+        i = 0
+
+        while i < len(lines):
+            line = lines[i]
+
+            # Skip empty lines
+            if not line.strip():
+                i += 1
+                continue
+
+            # Headings
+            if line.startswith("### "):
+                blocks.append(
+                    {
+                        "type": "heading_3",
+                        "heading_3": {
+                            "rich_text": [
+                                {"type": "text", "text": {"content": line[4:].strip()}}
+                            ]
+                        },
+                    }
+                )
+            elif line.startswith("## "):
+                blocks.append(
+                    {
+                        "type": "heading_2",
+                        "heading_2": {
+                            "rich_text": [
+                                {"type": "text", "text": {"content": line[3:].strip()}}
+                            ]
+                        },
+                    }
+                )
+            elif line.startswith("# "):
+                blocks.append(
+                    {
+                        "type": "heading_1",
+                        "heading_1": {
+                            "rich_text": [
+                                {"type": "text", "text": {"content": line[2:].strip()}}
+                            ]
+                        },
+                    }
+                )
+            # Bullet points
+            elif line.strip().startswith("- "):
+                blocks.append(
+                    {
+                        "type": "bulleted_list_item",
+                        "bulleted_list_item": {
+                            "rich_text": [
+                                {
+                                    "type": "text",
+                                    "text": {"content": line.strip()[2:].strip()},
+                                }
+                            ]
+                        },
+                    }
+                )
+            # Numbered list
+            elif line.strip() and line.strip()[0].isdigit() and ". " in line:
+                content_start = line.find(". ") + 2
+                blocks.append(
+                    {
+                        "type": "numbered_list_item",
+                        "numbered_list_item": {
+                            "rich_text": [
+                                {
+                                    "type": "text",
+                                    "text": {"content": line[content_start:].strip()},
+                                }
+                            ]
+                        },
+                    }
+                )
+            # Code block
+            elif line.strip().startswith("```"):
+                code_lines = []
+                language = line[3:].strip() or "plain text"
+                i += 1
+                while i < len(lines) and not lines[i].strip().startswith("```"):
+                    code_lines.append(lines[i])
+                    i += 1
+                blocks.append(
+                    {
+                        "type": "code",
+                        "code": {
+                            "rich_text": [
+                                {
+                                    "type": "text",
+                                    "text": {"content": "\n".join(code_lines)},
+                                }
+                            ],
+                            "language": language,
+                        },
+                    }
+                )
+            # Quote
+            elif line.strip().startswith("> "):
+                blocks.append(
+                    {
+                        "type": "quote",
+                        "quote": {
+                            "rich_text": [
+                                {
+                                    "type": "text",
+                                    "text": {"content": line.strip()[2:].strip()},
+                                }
+                            ]
+                        },
+                    }
+                )
+            # Horizontal rule
+            elif line.strip() in ["---", "***", "___"]:
+                blocks.append({"type": "divider", "divider": {}})
+            # Regular paragraph
+            else:
+                # Parse for basic markdown formatting
+                text_content = line.strip()
+                rich_text = []
+
+                # Simple bold/italic parsing (this is simplified)
+                if "**" in text_content or "*" in text_content:
+                    # For now, just pass as plain text
+                    # A full implementation would parse and create proper annotations
+                    rich_text = [{"type": "text", "text": {"content": text_content}}]
+                else:
+                    rich_text = [{"type": "text", "text": {"content": text_content}}]
+
+                blocks.append(
+                    {"type": "paragraph", "paragraph": {"rich_text": rich_text}}
+                )
+
+            i += 1
+
+        return blocks
+
+    @staticmethod
+    def _build_properties(
+        title: str, additional_properties: Optional[Dict[str, Any]] = None
+    ) -> Dict[str, Any]:
+        """Build properties object for page creation."""
+        properties: Dict[str, Any] = {
+            "title": {"title": [{"type": "text", "text": {"content": title}}]}
+        }
+
+        if additional_properties:
+            for key, value in additional_properties.items():
+                if key.lower() == "title":
+                    continue  # Skip title as we already have it
+
+                # Try to intelligently map property types
+                if isinstance(value, bool):
+                    properties[key] = {"checkbox": value}
+                elif isinstance(value, (int, float)):
+                    properties[key] = {"number": value}
+                elif isinstance(value, list):
+                    # Assume multi-select
+                    properties[key] = {
+                        "multi_select": [{"name": str(item)} for item in value]
+                    }
+                elif isinstance(value, str):
+                    # Could be select, rich_text, or other types
+                    # For simplicity, try common patterns
+                    if key.lower() in ["status", "priority", "type", "category"]:
+                        properties[key] = {"select": {"name": value}}
+                    elif key.lower() in ["url", "link"]:
+                        properties[key] = {"url": value}
+                    elif key.lower() in ["email"]:
+                        properties[key] = {"email": value}
+                    else:
+                        properties[key] = {
+                            "rich_text": [{"type": "text", "text": {"content": value}}]
+                        }
+
+        return properties
+
+    @staticmethod
+    async def create_page(
+        credentials: OAuth2Credentials,
+        title: str,
+        parent_page_id: Optional[str] = None,
+        parent_database_id: Optional[str] = None,
+        content: Optional[str] = None,
+        properties: Optional[Dict[str, Any]] = None,
+        icon_emoji: Optional[str] = None,
+    ) -> tuple[str, str]:
+        """
+        Create a new Notion page.
+
+        Returns:
+            Tuple of (page_id, page_url)
+        """
+        if not parent_page_id and not parent_database_id:
+            raise ValueError(
+                "Either parent_page_id or parent_database_id must be provided"
+            )
+        if parent_page_id and parent_database_id:
+            raise ValueError(
+                "Only one of parent_page_id or parent_database_id should be provided, not both"
+            )
+
+        client = NotionClient(credentials)
+
+        # Build parent object
+        if parent_page_id:
+            parent = {"type": "page_id", "page_id": parent_page_id}
+        else:
+            parent = {"type": "database_id", "database_id": parent_database_id}
+
+        # Build properties
+        page_properties = NotionCreatePageBlock._build_properties(title, properties)
+
+        # Convert content to blocks if provided
+        children = None
+        if content:
+            children = NotionCreatePageBlock._markdown_to_blocks(content)
+
+        # Build icon if provided
+        icon = None
+        if icon_emoji:
+            icon = {"type": "emoji", "emoji": icon_emoji}
+
+        # Create the page
+        result = await client.create_page(
+            parent=parent, properties=page_properties, children=children, icon=icon
+        )
+
+        page_id = result.get("id", "")
+        page_url = result.get("url", "")
+
+        if not page_id or not page_url:
+            raise ValueError("Failed to get page ID or URL from Notion response")
+
+        return page_id, page_url
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: OAuth2Credentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            page_id, page_url = await self.create_page(
+                credentials,
+                input_data.title,
+                input_data.parent_page_id,
+                input_data.parent_database_id,
+                input_data.content,
+                input_data.properties,
+                input_data.icon_emoji,
+            )
+            yield "page_id", page_id
+            yield "page_url", page_url
+        except Exception as e:
+            yield "error", str(e) if str(e) else "Unknown error"

autogpt_platform/backend/backend/blocks/notion/read_database.py

@@ -0,0 +1,285 @@
+from __future__ import annotations
+
+from typing import Any, Dict, List, Optional
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import OAuth2Credentials, SchemaField
+
+from ._api import NotionClient, parse_rich_text
+from ._auth import (
+    NOTION_OAUTH_IS_CONFIGURED,
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    NotionCredentialsField,
+    NotionCredentialsInput,
+)
+
+
+class NotionReadDatabaseBlock(Block):
+    """Query a Notion database and retrieve entries with their properties."""
+
+    class Input(BlockSchema):
+        credentials: NotionCredentialsInput = NotionCredentialsField()
+        database_id: str = SchemaField(
+            description="Notion database ID. Must be accessible by the connected integration.",
+        )
+        filter_property: Optional[str] = SchemaField(
+            description="Property name to filter by (e.g., 'Status', 'Priority')",
+            default=None,
+        )
+        filter_value: Optional[str] = SchemaField(
+            description="Value to filter for in the specified property", default=None
+        )
+        sort_property: Optional[str] = SchemaField(
+            description="Property name to sort by", default=None
+        )
+        sort_direction: Optional[str] = SchemaField(
+            description="Sort direction: 'ascending' or 'descending'",
+            default="ascending",
+        )
+        limit: int = SchemaField(
+            description="Maximum number of entries to retrieve",
+            default=100,
+            ge=1,
+            le=100,
+        )
+
+    class Output(BlockSchema):
+        entries: List[Dict[str, Any]] = SchemaField(
+            description="List of database entries with their properties."
+        )
+        entry: Dict[str, Any] = SchemaField(
+            description="Individual database entry (yields one per entry found)."
+        )
+        entry_ids: List[str] = SchemaField(
+            description="List of entry IDs for batch operations."
+        )
+        entry_id: str = SchemaField(
+            description="Individual entry ID (yields one per entry found)."
+        )
+        count: int = SchemaField(description="Number of entries retrieved.")
+        database_title: str = SchemaField(description="Title of the database.")
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="fcd53135-88c9-4ba3-be50-cc6936286e6c",
+            description="Query a Notion database with optional filtering and sorting, returning structured entries.",
+            categories={BlockCategory.PRODUCTIVITY},
+            input_schema=NotionReadDatabaseBlock.Input,
+            output_schema=NotionReadDatabaseBlock.Output,
+            disabled=not NOTION_OAUTH_IS_CONFIGURED,
+            test_input={
+                "database_id": "00000000-0000-0000-0000-000000000000",
+                "limit": 10,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[
+                (
+                    "entries",
+                    [{"Name": "Test Entry", "Status": "Active", "_id": "test-123"}],
+                ),
+                ("entry_ids", ["test-123"]),
+                (
+                    "entry",
+                    {"Name": "Test Entry", "Status": "Active", "_id": "test-123"},
+                ),
+                ("entry_id", "test-123"),
+                ("count", 1),
+                ("database_title", "Test Database"),
+            ],
+            test_credentials=TEST_CREDENTIALS,
+            test_mock={
+                "query_database": lambda *args, **kwargs: (
+                    [{"Name": "Test Entry", "Status": "Active", "_id": "test-123"}],
+                    1,
+                    "Test Database",
+                )
+            },
+        )
+
+    @staticmethod
+    def _parse_property_value(prop: dict) -> Any:
+        """Parse a Notion property value into a simple Python type."""
+        prop_type = prop.get("type")
+
+        if prop_type == "title":
+            return parse_rich_text(prop.get("title", []))
+        elif prop_type == "rich_text":
+            return parse_rich_text(prop.get("rich_text", []))
+        elif prop_type == "number":
+            return prop.get("number")
+        elif prop_type == "select":
+            select = prop.get("select")
+            return select.get("name") if select else None
+        elif prop_type == "multi_select":
+            return [item.get("name") for item in prop.get("multi_select", [])]
+        elif prop_type == "date":
+            date = prop.get("date")
+            if date:
+                return date.get("start")
+            return None
+        elif prop_type == "checkbox":
+            return prop.get("checkbox", False)
+        elif prop_type == "url":
+            return prop.get("url")
+        elif prop_type == "email":
+            return prop.get("email")
+        elif prop_type == "phone_number":
+            return prop.get("phone_number")
+        elif prop_type == "people":
+            return [
+                person.get("name", person.get("id"))
+                for person in prop.get("people", [])
+            ]
+        elif prop_type == "files":
+            files = prop.get("files", [])
+            return [
+                f.get(
+                    "name",
+                    f.get("external", {}).get("url", f.get("file", {}).get("url")),
+                )
+                for f in files
+            ]
+        elif prop_type == "relation":
+            return [rel.get("id") for rel in prop.get("relation", [])]
+        elif prop_type == "formula":
+            formula = prop.get("formula", {})
+            return formula.get(formula.get("type"))
+        elif prop_type == "rollup":
+            rollup = prop.get("rollup", {})
+            return rollup.get(rollup.get("type"))
+        elif prop_type == "created_time":
+            return prop.get("created_time")
+        elif prop_type == "created_by":
+            return prop.get("created_by", {}).get(
+                "name", prop.get("created_by", {}).get("id")
+            )
+        elif prop_type == "last_edited_time":
+            return prop.get("last_edited_time")
+        elif prop_type == "last_edited_by":
+            return prop.get("last_edited_by", {}).get(
+                "name", prop.get("last_edited_by", {}).get("id")
+            )
+        else:
+            # Return the raw value for unknown types
+            return prop
+
+    @staticmethod
+    def _build_filter(property_name: str, value: str) -> dict:
+        """Build a simple filter object for a property."""
+        # This is a simplified filter - in reality, you'd need to know the property type
+        # For now, we'll try common filter types
+        return {
+            "or": [
+                {"property": property_name, "rich_text": {"contains": value}},
+                {"property": property_name, "title": {"contains": value}},
+                {"property": property_name, "select": {"equals": value}},
+                {"property": property_name, "multi_select": {"contains": value}},
+            ]
+        }
+
+    @staticmethod
+    async def query_database(
+        credentials: OAuth2Credentials,
+        database_id: str,
+        filter_property: Optional[str] = None,
+        filter_value: Optional[str] = None,
+        sort_property: Optional[str] = None,
+        sort_direction: str = "ascending",
+        limit: int = 100,
+    ) -> tuple[List[Dict[str, Any]], int, str]:
+        """
+        Query a Notion database and parse the results.
+
+        Returns:
+            Tuple of (entries_list, count, database_title)
+        """
+        client = NotionClient(credentials)
+
+        # Build filter if specified
+        filter_obj = None
+        if filter_property and filter_value:
+            filter_obj = NotionReadDatabaseBlock._build_filter(
+                filter_property, filter_value
+            )
+
+        # Build sorts if specified
+        sorts = None
+        if sort_property:
+            sorts = [{"property": sort_property, "direction": sort_direction}]
+
+        # Query the database
+        result = await client.query_database(
+            database_id, filter_obj=filter_obj, sorts=sorts, page_size=limit
+        )
+
+        # Parse the entries
+        entries = []
+        for page in result.get("results", []):
+            entry = {}
+            properties = page.get("properties", {})
+
+            for prop_name, prop_value in properties.items():
+                entry[prop_name] = NotionReadDatabaseBlock._parse_property_value(
+                    prop_value
+                )
+
+            # Add metadata
+            entry["_id"] = page.get("id")
+            entry["_url"] = page.get("url")
+            entry["_created_time"] = page.get("created_time")
+            entry["_last_edited_time"] = page.get("last_edited_time")
+
+            entries.append(entry)
+
+        # Get database title (we need to make a separate call for this)
+        try:
+            database_url = f"https://api.notion.com/v1/databases/{database_id}"
+            db_response = await client.requests.get(
+                database_url, headers=client.headers
+            )
+            if db_response.ok:
+                db_data = db_response.json()
+                db_title = parse_rich_text(db_data.get("title", []))
+            else:
+                db_title = "Unknown Database"
+        except Exception:
+            db_title = "Unknown Database"
+
+        return entries, len(entries), db_title
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: OAuth2Credentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            entries, count, db_title = await self.query_database(
+                credentials,
+                input_data.database_id,
+                input_data.filter_property,
+                input_data.filter_value,
+                input_data.sort_property,
+                input_data.sort_direction or "ascending",
+                input_data.limit,
+            )
+            # Yield the complete list for batch operations
+            yield "entries", entries
+
+            # Extract and yield IDs as a list for batch operations
+            entry_ids = [entry["_id"] for entry in entries if "_id" in entry]
+            yield "entry_ids", entry_ids
+
+            # Yield each individual entry and its ID for single connections
+            for entry in entries:
+                yield "entry", entry
+                if "_id" in entry:
+                    yield "entry_id", entry["_id"]
+
+            yield "count", count
+            yield "database_title", db_title
+        except Exception as e:
+            yield "error", str(e) if str(e) else "Unknown error"

autogpt_platform/backend/backend/blocks/notion/read_page.py

@@ -0,0 +1,64 @@
+from __future__ import annotations
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import OAuth2Credentials, SchemaField
+
+from ._api import NotionClient
+from ._auth import (
+    NOTION_OAUTH_IS_CONFIGURED,
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    NotionCredentialsField,
+    NotionCredentialsInput,
+)
+
+
+class NotionReadPageBlock(Block):
+    """Read a Notion page by ID and return its raw JSON."""
+
+    class Input(BlockSchema):
+        credentials: NotionCredentialsInput = NotionCredentialsField()
+        page_id: str = SchemaField(
+            description="Notion page ID. Must be accessible by the connected integration. You can get this from the page URL notion.so/A-Page-586edd711467478da59fe3ce29a1ffab would be 586edd711467478da59fe35e29a1ffab",
+        )
+
+    class Output(BlockSchema):
+        page: dict = SchemaField(description="Raw Notion page JSON.")
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="5246cc1d-34b7-452b-8fc5-3fb25fd8f542",
+            description="Read a Notion page by its ID and return its raw JSON.",
+            categories={BlockCategory.PRODUCTIVITY},
+            input_schema=NotionReadPageBlock.Input,
+            output_schema=NotionReadPageBlock.Output,
+            disabled=not NOTION_OAUTH_IS_CONFIGURED,
+            test_input={
+                "page_id": "00000000-0000-0000-0000-000000000000",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[("page", dict)],
+            test_credentials=TEST_CREDENTIALS,
+            test_mock={
+                "get_page": lambda *args, **kwargs: {"object": "page", "id": "mocked"}
+            },
+        )
+
+    @staticmethod
+    async def get_page(credentials: OAuth2Credentials, page_id: str) -> dict:
+        client = NotionClient(credentials)
+        return await client.get_page(page_id)
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: OAuth2Credentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            page = await self.get_page(credentials, input_data.page_id)
+            yield "page", page
+        except Exception as e:
+            yield "error", str(e) if str(e) else "Unknown error"

autogpt_platform/backend/backend/blocks/notion/read_page_markdown.py

@@ -0,0 +1,109 @@
+from __future__ import annotations
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import OAuth2Credentials, SchemaField
+
+from ._api import NotionClient, blocks_to_markdown, extract_page_title
+from ._auth import (
+    NOTION_OAUTH_IS_CONFIGURED,
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    NotionCredentialsField,
+    NotionCredentialsInput,
+)
+
+
+class NotionReadPageMarkdownBlock(Block):
+    """Read a Notion page and convert it to clean Markdown format."""
+
+    class Input(BlockSchema):
+        credentials: NotionCredentialsInput = NotionCredentialsField()
+        page_id: str = SchemaField(
+            description="Notion page ID. Must be accessible by the connected integration. You can get this from the page URL notion.so/A-Page-586edd711467478da59fe35e29a1ffab would be 586edd711467478da59fe35e29a1ffab",
+        )
+        include_title: bool = SchemaField(
+            description="Whether to include the page title as a header in the markdown",
+            default=True,
+        )
+
+    class Output(BlockSchema):
+        markdown: str = SchemaField(description="Page content in Markdown format.")
+        title: str = SchemaField(description="Page title.")
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="d1312c4d-fae2-4e70-893d-f4d07cce1d4e",
+            description="Read a Notion page and convert it to Markdown format with proper formatting for headings, lists, links, and rich text.",
+            categories={BlockCategory.PRODUCTIVITY},
+            input_schema=NotionReadPageMarkdownBlock.Input,
+            output_schema=NotionReadPageMarkdownBlock.Output,
+            disabled=not NOTION_OAUTH_IS_CONFIGURED,
+            test_input={
+                "page_id": "00000000-0000-0000-0000-000000000000",
+                "include_title": True,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[
+                ("markdown", "# Test Page\n\nThis is test content."),
+                ("title", "Test Page"),
+            ],
+            test_credentials=TEST_CREDENTIALS,
+            test_mock={
+                "get_page_markdown": lambda *args, **kwargs: (
+                    "# Test Page\n\nThis is test content.",
+                    "Test Page",
+                )
+            },
+        )
+
+    @staticmethod
+    async def get_page_markdown(
+        credentials: OAuth2Credentials, page_id: str, include_title: bool = True
+    ) -> tuple[str, str]:
+        """
+        Get a Notion page and convert it to markdown.
+
+        Args:
+            credentials: OAuth2 credentials for Notion.
+            page_id: The ID of the page to fetch.
+            include_title: Whether to include the page title in the markdown.
+
+        Returns:
+            Tuple of (markdown_content, title)
+        """
+        client = NotionClient(credentials)
+
+        # Get page metadata
+        page = await client.get_page(page_id)
+        title = extract_page_title(page)
+
+        # Get all blocks from the page
+        blocks = await client.get_blocks(page_id, recursive=True)
+
+        # Convert blocks to markdown
+        content_markdown = blocks_to_markdown(blocks)
+
+        # Combine title and content if requested
+        if include_title and title:
+            full_markdown = f"# {title}\n\n{content_markdown}"
+        else:
+            full_markdown = content_markdown
+
+        return full_markdown, title
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: OAuth2Credentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            markdown, title = await self.get_page_markdown(
+                credentials, input_data.page_id, input_data.include_title
+            )
+            yield "markdown", markdown
+            yield "title", title
+        except Exception as e:
+            yield "error", str(e) if str(e) else "Unknown error"

autogpt_platform/backend/backend/blocks/notion/search.py

@@ -0,0 +1,225 @@
+from __future__ import annotations
+
+from typing import List, Optional
+
+from pydantic import BaseModel
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import OAuth2Credentials, SchemaField
+
+from ._api import NotionClient, extract_page_title, parse_rich_text
+from ._auth import (
+    NOTION_OAUTH_IS_CONFIGURED,
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    NotionCredentialsField,
+    NotionCredentialsInput,
+)
+
+
+class NotionSearchResult(BaseModel):
+    """Typed model for Notion search results."""
+
+    id: str
+    type: str  # 'page' or 'database'
+    title: str
+    url: str
+    created_time: Optional[str] = None
+    last_edited_time: Optional[str] = None
+    parent_type: Optional[str] = None  # 'page', 'database', or 'workspace'
+    parent_id: Optional[str] = None
+    icon: Optional[str] = None  # emoji icon if present
+    is_inline: Optional[bool] = None  # for databases only
+
+
+class NotionSearchBlock(Block):
+    """Search across your Notion workspace for pages and databases."""
+
+    class Input(BlockSchema):
+        credentials: NotionCredentialsInput = NotionCredentialsField()
+        query: str = SchemaField(
+            description="Search query text. Leave empty to get all accessible pages/databases.",
+            default="",
+        )
+        filter_type: Optional[str] = SchemaField(
+            description="Filter results by type: 'page' or 'database'. Leave empty for both.",
+            default=None,
+        )
+        limit: int = SchemaField(
+            description="Maximum number of results to return", default=20, ge=1, le=100
+        )
+
+    class Output(BlockSchema):
+        results: List[NotionSearchResult] = SchemaField(
+            description="List of search results with title, type, URL, and metadata."
+        )
+        result: NotionSearchResult = SchemaField(
+            description="Individual search result (yields one per result found)."
+        )
+        result_ids: List[str] = SchemaField(
+            description="List of IDs from search results for batch operations."
+        )
+        count: int = SchemaField(description="Number of results found.")
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="313515dd-9848-46ea-9cd6-3c627c892c56",
+            description="Search your Notion workspace for pages and databases by text query.",
+            categories={BlockCategory.PRODUCTIVITY, BlockCategory.SEARCH},
+            input_schema=NotionSearchBlock.Input,
+            output_schema=NotionSearchBlock.Output,
+            disabled=not NOTION_OAUTH_IS_CONFIGURED,
+            test_input={
+                "query": "project",
+                "limit": 5,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[
+                (
+                    "results",
+                    [
+                        NotionSearchResult(
+                            id="123",
+                            type="page",
+                            title="Project Plan",
+                            url="https://notion.so/Project-Plan-123",
+                        )
+                    ],
+                ),
+                ("result_ids", ["123"]),
+                (
+                    "result",
+                    NotionSearchResult(
+                        id="123",
+                        type="page",
+                        title="Project Plan",
+                        url="https://notion.so/Project-Plan-123",
+                    ),
+                ),
+                ("count", 1),
+            ],
+            test_credentials=TEST_CREDENTIALS,
+            test_mock={
+                "search_workspace": lambda *args, **kwargs: (
+                    [
+                        NotionSearchResult(
+                            id="123",
+                            type="page",
+                            title="Project Plan",
+                            url="https://notion.so/Project-Plan-123",
+                        )
+                    ],
+                    1,
+                )
+            },
+        )
+
+    @staticmethod
+    async def search_workspace(
+        credentials: OAuth2Credentials,
+        query: str = "",
+        filter_type: Optional[str] = None,
+        limit: int = 20,
+    ) -> tuple[List[NotionSearchResult], int]:
+        """
+        Search the Notion workspace.
+
+        Returns:
+            Tuple of (results_list, count)
+        """
+        client = NotionClient(credentials)
+
+        # Build filter if type is specified
+        filter_obj = None
+        if filter_type:
+            filter_obj = {"property": "object", "value": filter_type}
+
+        # Execute search
+        response = await client.search(
+            query=query, filter_obj=filter_obj, page_size=limit
+        )
+
+        # Parse results
+        results = []
+        for item in response.get("results", []):
+            result_data = {
+                "id": item.get("id", ""),
+                "type": item.get("object", ""),
+                "url": item.get("url", ""),
+                "created_time": item.get("created_time"),
+                "last_edited_time": item.get("last_edited_time"),
+                "title": "",  # Will be set below
+            }
+
+            # Extract title based on type
+            if item.get("object") == "page":
+                # For pages, get the title from properties
+                result_data["title"] = extract_page_title(item)
+
+                # Add parent info
+                parent = item.get("parent", {})
+                if parent.get("type") == "page_id":
+                    result_data["parent_type"] = "page"
+                    result_data["parent_id"] = parent.get("page_id")
+                elif parent.get("type") == "database_id":
+                    result_data["parent_type"] = "database"
+                    result_data["parent_id"] = parent.get("database_id")
+                elif parent.get("type") == "workspace":
+                    result_data["parent_type"] = "workspace"
+
+                # Add icon if present
+                icon = item.get("icon")
+                if icon and icon.get("type") == "emoji":
+                    result_data["icon"] = icon.get("emoji")
+
+            elif item.get("object") == "database":
+                # For databases, get title from the title array
+                result_data["title"] = parse_rich_text(item.get("title", []))
+
+                # Add database-specific metadata
+                result_data["is_inline"] = item.get("is_inline", False)
+
+                # Add parent info
+                parent = item.get("parent", {})
+                if parent.get("type") == "page_id":
+                    result_data["parent_type"] = "page"
+                    result_data["parent_id"] = parent.get("page_id")
+                elif parent.get("type") == "workspace":
+                    result_data["parent_type"] = "workspace"
+
+                # Add icon if present
+                icon = item.get("icon")
+                if icon and icon.get("type") == "emoji":
+                    result_data["icon"] = icon.get("emoji")
+
+            results.append(NotionSearchResult(**result_data))
+
+        return results, len(results)
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: OAuth2Credentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            results, count = await self.search_workspace(
+                credentials, input_data.query, input_data.filter_type, input_data.limit
+            )
+
+            # Yield the complete list for batch operations
+            yield "results", results
+
+            # Extract and yield IDs as a list for batch operations
+            result_ids = [r.id for r in results]
+            yield "result_ids", result_ids
+
+            # Yield each individual result for single connections
+            for result in results:
+                yield "result", result
+
+            yield "count", count
+        except Exception as e:
+            yield "error", str(e) if str(e) else "Unknown error"

autogpt_platform/backend/backend/blocks/smart_decision_maker.py

@@ -523,7 +523,6 @@ class SmartDecisionMakerBlock(Block):
             credentials=credentials,
             llm_model=input_data.model,
             prompt=prompt,
-            json_format=False,
             max_tokens=input_data.max_tokens,
             tools=tool_functions,
             ollama_host=input_data.ollama_host,

autogpt_platform/backend/backend/blocks/stagehand/_config.py

@@ -0,0 +1,8 @@
+from backend.sdk import BlockCostType, ProviderBuilder
+
+stagehand = (
+    ProviderBuilder("stagehand")
+    .with_api_key("STAGEHAND_API_KEY", "Stagehand API Key")
+    .with_base_cost(1, BlockCostType.RUN)
+    .build()
+)

autogpt_platform/backend/backend/blocks/stagehand/blocks.py

@@ -0,0 +1,393 @@
+import logging
+import signal
+import threading
+from contextlib import contextmanager
+from enum import Enum
+
+# Monkey patch Stagehands to prevent signal handling in worker threads
+import stagehand.main
+from stagehand import Stagehand
+
+from backend.blocks.llm import (
+    MODEL_METADATA,
+    AICredentials,
+    AICredentialsField,
+    LlmModel,
+    ModelMetadata,
+)
+from backend.blocks.stagehand._config import stagehand as stagehand_provider
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchema,
+    CredentialsMetaInput,
+    SchemaField,
+)
+
+# Store the original method
+original_register_signal_handlers = stagehand.main.Stagehand._register_signal_handlers
+
+
+def safe_register_signal_handlers(self):
+    """Only register signal handlers in the main thread"""
+    if threading.current_thread() is threading.main_thread():
+        original_register_signal_handlers(self)
+    else:
+        # Skip signal handling in worker threads
+        pass
+
+
+# Replace the method
+stagehand.main.Stagehand._register_signal_handlers = safe_register_signal_handlers
+
+
+@contextmanager
+def disable_signal_handling():
+    """Context manager to temporarily disable signal handling"""
+    if threading.current_thread() is not threading.main_thread():
+        # In worker threads, temporarily replace signal.signal with a no-op
+        original_signal = signal.signal
+
+        def noop_signal(*args, **kwargs):
+            pass
+
+        signal.signal = noop_signal
+        try:
+            yield
+        finally:
+            signal.signal = original_signal
+    else:
+        # In main thread, don't modify anything
+        yield
+
+
+logger = logging.getLogger(__name__)
+
+
+class StagehandRecommendedLlmModel(str, Enum):
+    """
+    This is subset of LLModel from autogpt_platform/backend/backend/blocks/llm.py
+
+    It contains only the models recommended by Stagehand
+    """
+
+    # OpenAI
+    GPT41 = "gpt-4.1-2025-04-14"
+    GPT41_MINI = "gpt-4.1-mini-2025-04-14"
+
+    # Anthropic
+    CLAUDE_3_7_SONNET = "claude-3-7-sonnet-20250219"
+
+    @property
+    def provider_name(self) -> str:
+        """
+        Returns the provider name for the model in the required format for Stagehand:
+        provider/model_name
+        """
+        model_metadata = MODEL_METADATA[LlmModel(self.value)]
+        model_name = self.value
+
+        if len(model_name.split("/")) == 1 and not self.value.startswith(
+            model_metadata.provider
+        ):
+            assert (
+                model_metadata.provider != "open_router"
+            ), "Logic failed and open_router provider attempted to be prepended to model name! in stagehand/_config.py"
+            model_name = f"{model_metadata.provider}/{model_name}"
+
+        logger.error(f"Model name: {model_name}")
+        return model_name
+
+    @property
+    def provider(self) -> str:
+        return MODEL_METADATA[LlmModel(self.value)].provider
+
+    @property
+    def metadata(self) -> ModelMetadata:
+        return MODEL_METADATA[LlmModel(self.value)]
+
+    @property
+    def context_window(self) -> int:
+        return MODEL_METADATA[LlmModel(self.value)].context_window
+
+    @property
+    def max_output_tokens(self) -> int | None:
+        return MODEL_METADATA[LlmModel(self.value)].max_output_tokens
+
+
+class StagehandObserveBlock(Block):
+    class Input(BlockSchema):
+        # Browserbase credentials (Stagehand provider) or raw API key
+        stagehand_credentials: CredentialsMetaInput = (
+            stagehand_provider.credentials_field(
+                description="Stagehand/Browserbase API key"
+            )
+        )
+        browserbase_project_id: str = SchemaField(
+            description="Browserbase project ID (required if using Browserbase)",
+        )
+        # Model selection and credentials (provider-discriminated like llm.py)
+        model: StagehandRecommendedLlmModel = SchemaField(
+            title="LLM Model",
+            description="LLM to use for Stagehand (provider is inferred)",
+            default=StagehandRecommendedLlmModel.CLAUDE_3_7_SONNET,
+            advanced=False,
+        )
+        model_credentials: AICredentials = AICredentialsField()
+        url: str = SchemaField(
+            description="URL to navigate to.",
+        )
+        instruction: str = SchemaField(
+            description="Natural language description of elements or actions to discover.",
+        )
+        iframes: bool = SchemaField(
+            description="Whether to search within iframes. If True, Stagehand will search for actions within iframes.",
+            default=True,
+        )
+        domSettleTimeoutMs: int = SchemaField(
+            description="Timeout in milliseconds for DOM settlement.Wait longer for dynamic content",
+            default=45000,
+        )
+
+    class Output(BlockSchema):
+        selector: str = SchemaField(description="XPath selector to locate element.")
+        description: str = SchemaField(description="Human-readable description")
+        method: str | None = SchemaField(description="Suggested action method")
+        arguments: list[str] | None = SchemaField(
+            description="Additional action parameters"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="d3863944-0eaf-45c4-a0c9-63e0fe1ee8b9",
+            description="Find suggested actions for your workflows",
+            categories={BlockCategory.AI, BlockCategory.DEVELOPER_TOOLS},
+            input_schema=StagehandObserveBlock.Input,
+            output_schema=StagehandObserveBlock.Output,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        stagehand_credentials: APIKeyCredentials,
+        model_credentials: APIKeyCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+
+        logger.info(f"OBSERVE: Stagehand credentials: {stagehand_credentials}")
+        logger.info(
+            f"OBSERVE: Model credentials: {model_credentials} for provider {model_credentials.provider} secret: {model_credentials.api_key.get_secret_value()}"
+        )
+
+        with disable_signal_handling():
+            stagehand = Stagehand(
+                api_key=stagehand_credentials.api_key.get_secret_value(),
+                project_id=input_data.browserbase_project_id,
+                model_name=input_data.model.provider_name,
+                model_api_key=model_credentials.api_key.get_secret_value(),
+            )
+
+            await stagehand.init()
+
+        page = stagehand.page
+
+        assert page is not None, "Stagehand page is not initialized"
+
+        await page.goto(input_data.url)
+
+        observe_results = await page.observe(
+            input_data.instruction,
+            iframes=input_data.iframes,
+            domSettleTimeoutMs=input_data.domSettleTimeoutMs,
+        )
+        for result in observe_results:
+            yield "selector", result.selector
+            yield "description", result.description
+            yield "method", result.method
+            yield "arguments", result.arguments
+
+
+class StagehandActBlock(Block):
+    class Input(BlockSchema):
+        # Browserbase credentials (Stagehand provider) or raw API key
+        stagehand_credentials: CredentialsMetaInput = (
+            stagehand_provider.credentials_field(
+                description="Stagehand/Browserbase API key"
+            )
+        )
+        browserbase_project_id: str = SchemaField(
+            description="Browserbase project ID (required if using Browserbase)",
+        )
+        # Model selection and credentials (provider-discriminated like llm.py)
+        model: StagehandRecommendedLlmModel = SchemaField(
+            title="LLM Model",
+            description="LLM to use for Stagehand (provider is inferred)",
+            default=StagehandRecommendedLlmModel.CLAUDE_3_7_SONNET,
+            advanced=False,
+        )
+        model_credentials: AICredentials = AICredentialsField()
+        url: str = SchemaField(
+            description="URL to navigate to.",
+        )
+        action: list[str] = SchemaField(
+            description="Action to perform. Suggested actions are: click, fill, type, press, scroll, select from dropdown. For multi-step actions, add an entry for each step.",
+        )
+        variables: dict[str, str] = SchemaField(
+            description="Variables to use in the action. Variables contains data you want the action to use.",
+            default_factory=dict,
+        )
+        iframes: bool = SchemaField(
+            description="Whether to search within iframes. If True, Stagehand will search for actions within iframes.",
+            default=True,
+        )
+        domSettleTimeoutMs: int = SchemaField(
+            description="Timeout in milliseconds for DOM settlement.Wait longer for dynamic content",
+            default=45000,
+        )
+        timeoutMs: int = SchemaField(
+            description="Timeout in milliseconds for DOM ready. Extended timeout for slow-loading forms",
+            default=60000,
+        )
+
+    class Output(BlockSchema):
+        success: bool = SchemaField(
+            description="Whether the action was completed successfully"
+        )
+        message: str = SchemaField(description="Details about the action’s execution.")
+        action: str = SchemaField(description="Action performed")
+
+    def __init__(self):
+        super().__init__(
+            id="86eba68b-9549-4c0b-a0db-47d85a56cc27",
+            description="Interact with a web page by performing actions on a web page. Use it to build self-healing and deterministic automations that adapt to website chang.",
+            categories={BlockCategory.AI, BlockCategory.DEVELOPER_TOOLS},
+            input_schema=StagehandActBlock.Input,
+            output_schema=StagehandActBlock.Output,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        stagehand_credentials: APIKeyCredentials,
+        model_credentials: APIKeyCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+
+        logger.info(f"ACT: Stagehand credentials: {stagehand_credentials}")
+        logger.info(
+            f"ACT: Model credentials: {model_credentials} for provider {model_credentials.provider} secret: {model_credentials.api_key.get_secret_value()}"
+        )
+
+        with disable_signal_handling():
+            stagehand = Stagehand(
+                api_key=stagehand_credentials.api_key.get_secret_value(),
+                project_id=input_data.browserbase_project_id,
+                model_name=input_data.model.provider_name,
+                model_api_key=model_credentials.api_key.get_secret_value(),
+            )
+
+            await stagehand.init()
+
+        page = stagehand.page
+
+        assert page is not None, "Stagehand page is not initialized"
+
+        await page.goto(input_data.url)
+        for action in input_data.action:
+            action_results = await page.act(
+                action,
+                variables=input_data.variables,
+                iframes=input_data.iframes,
+                domSettleTimeoutMs=input_data.domSettleTimeoutMs,
+                timeoutMs=input_data.timeoutMs,
+            )
+            yield "success", action_results.success
+            yield "message", action_results.message
+            yield "action", action_results.action
+
+
+class StagehandExtractBlock(Block):
+    class Input(BlockSchema):
+        # Browserbase credentials (Stagehand provider) or raw API key
+        stagehand_credentials: CredentialsMetaInput = (
+            stagehand_provider.credentials_field(
+                description="Stagehand/Browserbase API key"
+            )
+        )
+        browserbase_project_id: str = SchemaField(
+            description="Browserbase project ID (required if using Browserbase)",
+        )
+        # Model selection and credentials (provider-discriminated like llm.py)
+        model: StagehandRecommendedLlmModel = SchemaField(
+            title="LLM Model",
+            description="LLM to use for Stagehand (provider is inferred)",
+            default=StagehandRecommendedLlmModel.CLAUDE_3_7_SONNET,
+            advanced=False,
+        )
+        model_credentials: AICredentials = AICredentialsField()
+        url: str = SchemaField(
+            description="URL to navigate to.",
+        )
+        instruction: str = SchemaField(
+            description="Natural language description of elements or actions to discover.",
+        )
+        iframes: bool = SchemaField(
+            description="Whether to search within iframes. If True, Stagehand will search for actions within iframes.",
+            default=True,
+        )
+        domSettleTimeoutMs: int = SchemaField(
+            description="Timeout in milliseconds for DOM settlement.Wait longer for dynamic content",
+            default=45000,
+        )
+
+    class Output(BlockSchema):
+        extraction: str = SchemaField(description="Extracted data from the page.")
+
+    def __init__(self):
+        super().__init__(
+            id="fd3c0b18-2ba6-46ae-9339-fcb40537ad98",
+            description="Extract structured data from a webpage.",
+            categories={BlockCategory.AI, BlockCategory.DEVELOPER_TOOLS},
+            input_schema=StagehandExtractBlock.Input,
+            output_schema=StagehandExtractBlock.Output,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        stagehand_credentials: APIKeyCredentials,
+        model_credentials: APIKeyCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+
+        logger.info(f"EXTRACT: Stagehand credentials: {stagehand_credentials}")
+        logger.info(
+            f"EXTRACT: Model credentials: {model_credentials} for provider {model_credentials.provider} secret: {model_credentials.api_key.get_secret_value()}"
+        )
+
+        with disable_signal_handling():
+            stagehand = Stagehand(
+                api_key=stagehand_credentials.api_key.get_secret_value(),
+                project_id=input_data.browserbase_project_id,
+                model_name=input_data.model.provider_name,
+                model_api_key=model_credentials.api_key.get_secret_value(),
+            )
+
+            await stagehand.init()
+
+        page = stagehand.page
+
+        assert page is not None, "Stagehand page is not initialized"
+
+        await page.goto(input_data.url)
+        extraction = await page.extract(
+            input_data.instruction,
+            iframes=input_data.iframes,
+            domSettleTimeoutMs=input_data.domSettleTimeoutMs,
+        )
+        yield "extraction", str(extraction.model_dump()["extraction"])

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_llm.py

@@ -30,7 +30,6 @@ class TestLLMStatsTracking:
                 credentials=llm.TEST_CREDENTIALS,
                 llm_model=llm.LlmModel.GPT4O,
                 prompt=[{"role": "user", "content": "Hello"}],
-                json_format=False,
                 max_tokens=100,
             )
 
@@ -42,6 +41,8 @@ class TestLLMStatsTracking:
     @pytest.mark.asyncio
     async def test_ai_structured_response_block_tracks_stats(self):
         """Test that AIStructuredResponseGeneratorBlock correctly tracks stats."""
+        from unittest.mock import patch
+
         import backend.blocks.llm as llm
 
         block = llm.AIStructuredResponseGeneratorBlock()
@@ -51,7 +52,7 @@ class TestLLMStatsTracking:
             return llm.LLMResponse(
                 raw_response="",
                 prompt=[],
-                response='{"key1": "value1", "key2": "value2"}',
+                response='<json_output id="test123456">{"key1": "value1", "key2": "value2"}</json_output>',
                 tool_calls=None,
                 prompt_tokens=15,
                 completion_tokens=25,
@@ -69,10 +70,12 @@ class TestLLMStatsTracking:
         )
 
         outputs = {}
-        async for output_name, output_data in block.run(
-            input_data, credentials=llm.TEST_CREDENTIALS
-        ):
-            outputs[output_name] = output_data
+        # Mock secrets.token_hex to return consistent ID
+        with patch("secrets.token_hex", return_value="test123456"):
+            async for output_name, output_data in block.run(
+                input_data, credentials=llm.TEST_CREDENTIALS
+            ):
+                outputs[output_name] = output_data
 
         # Check stats
         assert block.execution_stats.input_token_count == 15
@@ -143,7 +146,7 @@ class TestLLMStatsTracking:
                 return llm.LLMResponse(
                     raw_response="",
                     prompt=[],
-                    response='{"wrong": "format"}',
+                    response='<json_output id="test123456">{"wrong": "format"}</json_output>',
                     tool_calls=None,
                     prompt_tokens=10,
                     completion_tokens=15,
@@ -154,7 +157,7 @@ class TestLLMStatsTracking:
                 return llm.LLMResponse(
                     raw_response="",
                     prompt=[],
-                    response='{"key1": "value1", "key2": "value2"}',
+                    response='<json_output id="test123456">{"key1": "value1", "key2": "value2"}</json_output>',
                     tool_calls=None,
                     prompt_tokens=20,
                     completion_tokens=25,
@@ -173,10 +176,12 @@ class TestLLMStatsTracking:
         )
 
         outputs = {}
-        async for output_name, output_data in block.run(
-            input_data, credentials=llm.TEST_CREDENTIALS
-        ):
-            outputs[output_name] = output_data
+        # Mock secrets.token_hex to return consistent ID
+        with patch("secrets.token_hex", return_value="test123456"):
+            async for output_name, output_data in block.run(
+                input_data, credentials=llm.TEST_CREDENTIALS
+            ):
+                outputs[output_name] = output_data
 
         # Check stats - should accumulate both calls
         # For 2 attempts: attempt 1 (failed) + attempt 2 (success) = 2 total
@@ -269,7 +274,8 @@ class TestLLMStatsTracking:
                 mock_response.choices = [
                     MagicMock(
                         message=MagicMock(
-                            content='{"summary": "Test chunk summary"}', tool_calls=None
+                            content='<json_output id="test123456">{"summary": "Test chunk summary"}</json_output>',
+                            tool_calls=None,
                         )
                     )
                 ]
@@ -277,7 +283,7 @@ class TestLLMStatsTracking:
                 mock_response.choices = [
                     MagicMock(
                         message=MagicMock(
-                            content='{"final_summary": "Test final summary"}',
+                            content='<json_output id="test123456">{"final_summary": "Test final summary"}</json_output>',
                             tool_calls=None,
                         )
                     )
@@ -298,11 +304,13 @@ class TestLLMStatsTracking:
                 max_tokens=1000,  # Large enough to avoid chunking
             )
 
-            outputs = {}
-            async for output_name, output_data in block.run(
-                input_data, credentials=llm.TEST_CREDENTIALS
-            ):
-                outputs[output_name] = output_data
+            # Mock secrets.token_hex to return consistent ID
+            with patch("secrets.token_hex", return_value="test123456"):
+                outputs = {}
+                async for output_name, output_data in block.run(
+                    input_data, credentials=llm.TEST_CREDENTIALS
+                ):
+                    outputs[output_name] = output_data
 
             print(f"Actual calls made: {call_count}")
             print(f"Block stats: {block.execution_stats}")
@@ -457,7 +465,7 @@ class TestLLMStatsTracking:
             return llm.LLMResponse(
                 raw_response="",
                 prompt=[],
-                response='{"result": "test"}',
+                response='<json_output id="test123456">{"result": "test"}</json_output>',
                 tool_calls=None,
                 prompt_tokens=10,
                 completion_tokens=20,
@@ -476,10 +484,12 @@ class TestLLMStatsTracking:
 
         # Run the block
         outputs = {}
-        async for output_name, output_data in block.run(
-            input_data, credentials=llm.TEST_CREDENTIALS
-        ):
-            outputs[output_name] = output_data
+        # Mock secrets.token_hex to return consistent ID
+        with patch("secrets.token_hex", return_value="test123456"):
+            async for output_name, output_data in block.run(
+                input_data, credentials=llm.TEST_CREDENTIALS
+            ):
+                outputs[output_name] = output_data
 
         # Block finished - now grab and assert stats
         assert block.execution_stats is not None

autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker.py

@@ -35,20 +35,19 @@ async def execute_graph(
     logger.info("Input data: %s", input_data)
 
     # --- Test adding new executions --- #
-    response = await agent_server.test_execute_graph(
+    graph_exec = await agent_server.test_execute_graph(
         user_id=test_user.id,
         graph_id=test_graph.id,
         graph_version=test_graph.version,
         node_input=input_data,
     )
-    graph_exec_id = response.graph_exec_id
-    logger.info("Created execution with ID: %s", graph_exec_id)
+    logger.info("Created execution with ID: %s", graph_exec.id)
 
     # Execution queue should be empty
     logger.info("Waiting for execution to complete...")
-    result = await wait_execution(test_user.id, graph_exec_id, 30)
+    result = await wait_execution(test_user.id, graph_exec.id, 30)
     logger.info("Execution completed with %d results", len(result))
-    return graph_exec_id
+    return graph_exec.id
 
 
 @pytest.mark.asyncio(loop_scope="session")

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/text.py

@@ -172,6 +172,11 @@ class FillTextTemplateBlock(Block):
         format: str = SchemaField(
             description="Template to format the text using `values`. Use Jinja2 syntax."
         )
+        escape_html: bool = SchemaField(
+            default=False,
+            advanced=True,
+            description="Whether to escape special characters in the inserted values to be HTML-safe. Enable for HTML output, disable for plain text.",
+        )
 
     class Output(BlockSchema):
         output: str = SchemaField(description="Formatted text")
@@ -205,6 +210,7 @@ class FillTextTemplateBlock(Block):
         )
 
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        formatter = text.TextFormatter(autoescape=input_data.escape_html)
         yield "output", formatter.format_string(input_data.format, input_data.values)
 
 

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/blocks/wordpress/_api.py

@@ -4,6 +4,8 @@ from logging import getLogger
 from typing import Any, Dict, List, Union
 from urllib.parse import urlencode
 
+from pydantic import field_serializer
+
 from backend.sdk import BaseModel, Credentials, Requests
 
 logger = getLogger(__name__)
@@ -382,8 +384,9 @@ class CreatePostRequest(BaseModel):
     # Advanced
     metadata: List[Dict[str, Any]] | None = None
 
-    class Config:
-        json_encoders = {datetime: lambda v: v.isoformat()}
+    @field_serializer("date")
+    def serialize_date(self, value: datetime | None) -> str | None:
+        return value.isoformat() if value else None
 
 
 class PostAuthor(BaseModel):

autogpt_platform/backend/backend/conftest.py

@@ -6,8 +6,6 @@ from dotenv import load_dotenv
 
 from backend.util.logging import configure_logging
 
-os.environ["ENABLE_AUTH"] = "false"
-
 load_dotenv()
 
 #  NOTE: You can run tests like with the --log-cli-level=INFO to see the logs

autogpt_platform/backend/backend/data/__init__.py

@@ -1,5 +1,8 @@
+from backend.server.v2.library.model import LibraryAgentPreset
+
 from .graph import NodeModel
 from .integrations import Webhook  # noqa: F401
 
-# Resolve Webhook <- NodeModel forward reference
+# Resolve Webhook forward references
 NodeModel.model_rebuild()
+LibraryAgentPreset.model_rebuild()

autogpt_platform/backend/backend/data/api_key.py

@@ -1,57 +1,31 @@
 import logging
 import uuid
 from datetime import datetime, timezone
-from typing import List, Optional
+from typing import Optional
 
-from autogpt_libs.api_key.key_manager import APIKeyManager
+from autogpt_libs.api_key.keysmith import APIKeySmith
 from prisma.enums import APIKeyPermission, APIKeyStatus
-from prisma.errors import PrismaError
 from prisma.models import APIKey as PrismaAPIKey
-from prisma.types import (
-    APIKeyCreateInput,
-    APIKeyUpdateInput,
-    APIKeyWhereInput,
-    APIKeyWhereUniqueInput,
-)
-from pydantic import BaseModel
+from prisma.types import APIKeyWhereUniqueInput
+from pydantic import BaseModel, Field
 
-from backend.data.db import BaseDbModel
+from backend.util.exceptions import NotAuthorizedError, NotFoundError
 
 logger = logging.getLogger(__name__)
+keysmith = APIKeySmith()
 
 
-# Some basic exceptions
-class APIKeyError(Exception):
-    """Base exception for API key operations"""
-
-    pass
-
-
-class APIKeyNotFoundError(APIKeyError):
-    """Raised when an API key is not found"""
-
-    pass
-
-
-class APIKeyPermissionError(APIKeyError):
-    """Raised when there are permission issues with API key operations"""
-
-    pass
-
-
-class APIKeyValidationError(APIKeyError):
-    """Raised when API key validation fails"""
-
-    pass
-
-
-class APIKey(BaseDbModel):
+class APIKeyInfo(BaseModel):
+    id: str
     name: str
-    prefix: str
-    key: str
-    status: APIKeyStatus = APIKeyStatus.ACTIVE
-    permissions: List[APIKeyPermission]
-    postfix: str
+    head: str = Field(
+        description=f"The first {APIKeySmith.HEAD_LENGTH} characters of the key"
+    )
+    tail: str = Field(
+        description=f"The last {APIKeySmith.TAIL_LENGTH} characters of the key"
+    )
+    status: APIKeyStatus
+    permissions: list[APIKeyPermission]
     created_at: datetime
     last_used_at: Optional[datetime] = None
     revoked_at: Optional[datetime] = None
@@ -60,266 +34,211 @@ class APIKey(BaseDbModel):
 
     @staticmethod
     def from_db(api_key: PrismaAPIKey):
-        try:
-            return APIKey(
-                id=api_key.id,
-                name=api_key.name,
-                prefix=api_key.prefix,
-                postfix=api_key.postfix,
-                key=api_key.key,
-                status=APIKeyStatus(api_key.status),
-                permissions=[APIKeyPermission(p) for p in api_key.permissions],
-                created_at=api_key.createdAt,
-                last_used_at=api_key.lastUsedAt,
-                revoked_at=api_key.revokedAt,
-                description=api_key.description,
-                user_id=api_key.userId,
-            )
-        except Exception as e:
-            logger.error(f"Error creating APIKey from db: {str(e)}")
-            raise APIKeyError(f"Failed to create API key object: {str(e)}")
+        return APIKeyInfo(
+            id=api_key.id,
+            name=api_key.name,
+            head=api_key.head,
+            tail=api_key.tail,
+            status=APIKeyStatus(api_key.status),
+            permissions=[APIKeyPermission(p) for p in api_key.permissions],
+            created_at=api_key.createdAt,
+            last_used_at=api_key.lastUsedAt,
+            revoked_at=api_key.revokedAt,
+            description=api_key.description,
+            user_id=api_key.userId,
+        )
 
 
-class APIKeyWithoutHash(BaseModel):
-    id: str
-    name: str
-    prefix: str
-    postfix: str
-    status: APIKeyStatus
-    permissions: List[APIKeyPermission]
-    created_at: datetime
-    last_used_at: Optional[datetime]
-    revoked_at: Optional[datetime]
-    description: Optional[str]
-    user_id: str
+class APIKeyInfoWithHash(APIKeyInfo):
+    hash: str
+    salt: str | None = None  # None for legacy keys
+
+    def match(self, plaintext_key: str) -> bool:
+        """Returns whether the given key matches this API key object."""
+        return keysmith.verify_key(plaintext_key, self.hash, self.salt)
 
     @staticmethod
     def from_db(api_key: PrismaAPIKey):
-        try:
-            return APIKeyWithoutHash(
-                id=api_key.id,
-                name=api_key.name,
-                prefix=api_key.prefix,
-                postfix=api_key.postfix,
-                status=APIKeyStatus(api_key.status),
-                permissions=[APIKeyPermission(p) for p in api_key.permissions],
-                created_at=api_key.createdAt,
-                last_used_at=api_key.lastUsedAt,
-                revoked_at=api_key.revokedAt,
-                description=api_key.description,
-                user_id=api_key.userId,
-            )
-        except Exception as e:
-            logger.error(f"Error creating APIKeyWithoutHash from db: {str(e)}")
-            raise APIKeyError(f"Failed to create API key object: {str(e)}")
+        return APIKeyInfoWithHash(
+            **APIKeyInfo.from_db(api_key).model_dump(),
+            hash=api_key.hash,
+            salt=api_key.salt,
+        )
+
+    def without_hash(self) -> APIKeyInfo:
+        return APIKeyInfo(**self.model_dump(exclude={"hash", "salt"}))
 
 
-async def generate_api_key(
+async def create_api_key(
     name: str,
     user_id: str,
-    permissions: List[APIKeyPermission],
+    permissions: list[APIKeyPermission],
     description: Optional[str] = None,
-) -> tuple[APIKeyWithoutHash, str]:
+) -> tuple[APIKeyInfo, str]:
     """
     Generate a new API key and store it in the database.
     Returns the API key object (without hash) and the plain text key.
     """
-    try:
-        api_manager = APIKeyManager()
-        key = api_manager.generate_api_key()
+    generated_key = keysmith.generate_key()
 
-        api_key = await PrismaAPIKey.prisma().create(
-            data=APIKeyCreateInput(
-                id=str(uuid.uuid4()),
-                name=name,
-                prefix=key.prefix,
-                postfix=key.postfix,
-                key=key.hash,
-                permissions=[p for p in permissions],
-                description=description,
-                userId=user_id,
-            )
-        )
+    saved_key_obj = await PrismaAPIKey.prisma().create(
+        data={
+            "id": str(uuid.uuid4()),
+            "name": name,
+            "head": generated_key.head,
+            "tail": generated_key.tail,
+            "hash": generated_key.hash,
+            "salt": generated_key.salt,
+            "permissions": [p for p in permissions],
+            "description": description,
+            "userId": user_id,
+        }
+    )
 
-        api_key_without_hash = APIKeyWithoutHash.from_db(api_key)
-        return api_key_without_hash, key.raw
-    except PrismaError as e:
-        logger.error(f"Database error while generating API key: {str(e)}")
-        raise APIKeyError(f"Failed to generate API key: {str(e)}")
-    except Exception as e:
-        logger.error(f"Unexpected error while generating API key: {str(e)}")
-        raise APIKeyError(f"Failed to generate API key: {str(e)}")
+    return APIKeyInfo.from_db(saved_key_obj), generated_key.key
 
 
-async def validate_api_key(plain_text_key: str) -> Optional[APIKey]:
+async def get_active_api_keys_by_head(head: str) -> list[APIKeyInfoWithHash]:
+    results = await PrismaAPIKey.prisma().find_many(
+        where={"head": head, "status": APIKeyStatus.ACTIVE}
+    )
+    return [APIKeyInfoWithHash.from_db(key) for key in results]
+
+
+async def validate_api_key(plaintext_key: str) -> Optional[APIKeyInfo]:
     """
-    Validate an API key and return the API key object if valid.
+    Validate an API key and return the API key object if valid and active.
     """
     try:
-        if not plain_text_key.startswith(APIKeyManager.PREFIX):
+        if not plaintext_key.startswith(APIKeySmith.PREFIX):
             logger.warning("Invalid API key format")
             return None
 
-        prefix = plain_text_key[: APIKeyManager.PREFIX_LENGTH]
-        api_manager = APIKeyManager()
+        head = plaintext_key[: APIKeySmith.HEAD_LENGTH]
+        potential_matches = await get_active_api_keys_by_head(head)
 
-        api_key = await PrismaAPIKey.prisma().find_first(
-            where=APIKeyWhereInput(prefix=prefix, status=(APIKeyStatus.ACTIVE))
+        matched_api_key = next(
+            (pm for pm in potential_matches if pm.match(plaintext_key)),
+            None,
         )
-
-        if not api_key:
-            logger.warning(f"No active API key found with prefix {prefix}")
+        if not matched_api_key:
+            # API key not found or invalid
             return None
 
-        is_valid = api_manager.verify_api_key(plain_text_key, api_key.key)
-        if not is_valid:
-            logger.warning("API key verification failed")
-            return None
-
-        return APIKey.from_db(api_key)
-    except Exception as e:
-        logger.error(f"Error validating API key: {str(e)}")
-        raise APIKeyValidationError(f"Failed to validate API key: {str(e)}")
-
-
-async def revoke_api_key(key_id: str, user_id: str) -> Optional[APIKeyWithoutHash]:
-    try:
-        api_key = await PrismaAPIKey.prisma().find_unique(where={"id": key_id})
-
-        if not api_key:
-            raise APIKeyNotFoundError(f"API key with id {key_id} not found")
-
-        if api_key.userId != user_id:
-            raise APIKeyPermissionError(
-                "You do not have permission to revoke this API key."
+        # Migrate legacy keys to secure format on successful validation
+        if matched_api_key.salt is None:
+            matched_api_key = await _migrate_key_to_secure_hash(
+                plaintext_key, matched_api_key
             )
 
-        where_clause: APIKeyWhereUniqueInput = {"id": key_id}
-        updated_api_key = await PrismaAPIKey.prisma().update(
-            where=where_clause,
-            data=APIKeyUpdateInput(
-                status=APIKeyStatus.REVOKED, revokedAt=datetime.now(timezone.utc)
-            ),
-        )
+        return matched_api_key.without_hash()
+    except Exception as e:
+        logger.error(f"Error while validating API key: {e}")
+        raise RuntimeError("Failed to validate API key") from e
 
-        if updated_api_key:
-            return APIKeyWithoutHash.from_db(updated_api_key)
+
+async def _migrate_key_to_secure_hash(
+    plaintext_key: str, key_obj: APIKeyInfoWithHash
+) -> APIKeyInfoWithHash:
+    """Replace the SHA256 hash of a legacy API key with a salted Scrypt hash."""
+    try:
+        new_hash, new_salt = keysmith.hash_key(plaintext_key)
+        await PrismaAPIKey.prisma().update(
+            where={"id": key_obj.id}, data={"hash": new_hash, "salt": new_salt}
+        )
+        logger.info(f"Migrated legacy API key #{key_obj.id} to secure format")
+        # Update the API key object with new values for return
+        key_obj.hash = new_hash
+        key_obj.salt = new_salt
+    except Exception as e:
+        logger.error(f"Failed to migrate legacy API key #{key_obj.id}: {e}")
+
+    return key_obj
+
+
+async def revoke_api_key(key_id: str, user_id: str) -> APIKeyInfo:
+    api_key = await PrismaAPIKey.prisma().find_unique(where={"id": key_id})
+
+    if not api_key:
+        raise NotFoundError(f"API key with id {key_id} not found")
+
+    if api_key.userId != user_id:
+        raise NotAuthorizedError("You do not have permission to revoke this API key.")
+
+    updated_api_key = await PrismaAPIKey.prisma().update(
+        where={"id": key_id},
+        data={
+            "status": APIKeyStatus.REVOKED,
+            "revokedAt": datetime.now(timezone.utc),
+        },
+    )
+    if not updated_api_key:
+        raise NotFoundError(f"API key #{key_id} vanished while trying to revoke.")
+
+    return APIKeyInfo.from_db(updated_api_key)
+
+
+async def list_user_api_keys(user_id: str) -> list[APIKeyInfo]:
+    api_keys = await PrismaAPIKey.prisma().find_many(
+        where={"userId": user_id}, order={"createdAt": "desc"}
+    )
+
+    return [APIKeyInfo.from_db(key) for key in api_keys]
+
+
+async def suspend_api_key(key_id: str, user_id: str) -> APIKeyInfo:
+    selector: APIKeyWhereUniqueInput = {"id": key_id}
+    api_key = await PrismaAPIKey.prisma().find_unique(where=selector)
+
+    if not api_key:
+        raise NotFoundError(f"API key with id {key_id} not found")
+
+    if api_key.userId != user_id:
+        raise NotAuthorizedError("You do not have permission to suspend this API key.")
+
+    updated_api_key = await PrismaAPIKey.prisma().update(
+        where=selector, data={"status": APIKeyStatus.SUSPENDED}
+    )
+    if not updated_api_key:
+        raise NotFoundError(f"API key #{key_id} vanished while trying to suspend.")
+
+    return APIKeyInfo.from_db(updated_api_key)
+
+
+def has_permission(api_key: APIKeyInfo, required_permission: APIKeyPermission) -> bool:
+    return required_permission in api_key.permissions
+
+
+async def get_api_key_by_id(key_id: str, user_id: str) -> Optional[APIKeyInfo]:
+    api_key = await PrismaAPIKey.prisma().find_first(
+        where={"id": key_id, "userId": user_id}
+    )
+
+    if not api_key:
         return None
-    except (APIKeyNotFoundError, APIKeyPermissionError) as e:
-        raise e
-    except PrismaError as e:
-        logger.error(f"Database error while revoking API key: {str(e)}")
-        raise APIKeyError(f"Failed to revoke API key: {str(e)}")
-    except Exception as e:
-        logger.error(f"Unexpected error while revoking API key: {str(e)}")
-        raise APIKeyError(f"Failed to revoke API key: {str(e)}")
 
-
-async def list_user_api_keys(user_id: str) -> List[APIKeyWithoutHash]:
-    try:
-        where_clause: APIKeyWhereInput = {"userId": user_id}
-
-        api_keys = await PrismaAPIKey.prisma().find_many(
-            where=where_clause, order={"createdAt": "desc"}
-        )
-
-        return [APIKeyWithoutHash.from_db(key) for key in api_keys]
-    except PrismaError as e:
-        logger.error(f"Database error while listing API keys: {str(e)}")
-        raise APIKeyError(f"Failed to list API keys: {str(e)}")
-    except Exception as e:
-        logger.error(f"Unexpected error while listing API keys: {str(e)}")
-        raise APIKeyError(f"Failed to list API keys: {str(e)}")
-
-
-async def suspend_api_key(key_id: str, user_id: str) -> Optional[APIKeyWithoutHash]:
-    try:
-        api_key = await PrismaAPIKey.prisma().find_unique(where={"id": key_id})
-
-        if not api_key:
-            raise APIKeyNotFoundError(f"API key with id {key_id} not found")
-
-        if api_key.userId != user_id:
-            raise APIKeyPermissionError(
-                "You do not have permission to suspend this API key."
-            )
-
-        where_clause: APIKeyWhereUniqueInput = {"id": key_id}
-        updated_api_key = await PrismaAPIKey.prisma().update(
-            where=where_clause,
-            data=APIKeyUpdateInput(status=APIKeyStatus.SUSPENDED),
-        )
-
-        if updated_api_key:
-            return APIKeyWithoutHash.from_db(updated_api_key)
-        return None
-    except (APIKeyNotFoundError, APIKeyPermissionError) as e:
-        raise e
-    except PrismaError as e:
-        logger.error(f"Database error while suspending API key: {str(e)}")
-        raise APIKeyError(f"Failed to suspend API key: {str(e)}")
-    except Exception as e:
-        logger.error(f"Unexpected error while suspending API key: {str(e)}")
-        raise APIKeyError(f"Failed to suspend API key: {str(e)}")
-
-
-def has_permission(api_key: APIKey, required_permission: APIKeyPermission) -> bool:
-    try:
-        return required_permission in api_key.permissions
-    except Exception as e:
-        logger.error(f"Error checking API key permissions: {str(e)}")
-        return False
-
-
-async def get_api_key_by_id(key_id: str, user_id: str) -> Optional[APIKeyWithoutHash]:
-    try:
-        api_key = await PrismaAPIKey.prisma().find_first(
-            where=APIKeyWhereInput(id=key_id, userId=user_id)
-        )
-
-        if not api_key:
-            return None
-
-        return APIKeyWithoutHash.from_db(api_key)
-    except PrismaError as e:
-        logger.error(f"Database error while getting API key: {str(e)}")
-        raise APIKeyError(f"Failed to get API key: {str(e)}")
-    except Exception as e:
-        logger.error(f"Unexpected error while getting API key: {str(e)}")
-        raise APIKeyError(f"Failed to get API key: {str(e)}")
+    return APIKeyInfo.from_db(api_key)
 
 
 async def update_api_key_permissions(
-    key_id: str, user_id: str, permissions: List[APIKeyPermission]
-) -> Optional[APIKeyWithoutHash]:
+    key_id: str, user_id: str, permissions: list[APIKeyPermission]
+) -> APIKeyInfo:
     """
     Update the permissions of an API key.
     """
-    try:
-        api_key = await PrismaAPIKey.prisma().find_unique(where={"id": key_id})
+    api_key = await PrismaAPIKey.prisma().find_unique(where={"id": key_id})
 
-        if api_key is None:
-            raise APIKeyNotFoundError("No such API key found.")
+    if api_key is None:
+        raise NotFoundError("No such API key found.")
 
-        if api_key.userId != user_id:
-            raise APIKeyPermissionError(
-                "You do not have permission to update this API key."
-            )
+    if api_key.userId != user_id:
+        raise NotAuthorizedError("You do not have permission to update this API key.")
 
-        where_clause: APIKeyWhereUniqueInput = {"id": key_id}
-        updated_api_key = await PrismaAPIKey.prisma().update(
-            where=where_clause,
-            data=APIKeyUpdateInput(permissions=permissions),
-        )
+    updated_api_key = await PrismaAPIKey.prisma().update(
+        where={"id": key_id},
+        data={"permissions": permissions},
+    )
+    if not updated_api_key:
+        raise NotFoundError(f"API key #{key_id} vanished while trying to update.")
 
-        if updated_api_key:
-            return APIKeyWithoutHash.from_db(updated_api_key)
-        return None
-    except (APIKeyNotFoundError, APIKeyPermissionError) as e:
-        raise e
-    except PrismaError as e:
-        logger.error(f"Database error while updating API key permissions: {str(e)}")
-        raise APIKeyError(f"Failed to update API key permissions: {str(e)}")
-    except Exception as e:
-        logger.error(f"Unexpected error while updating API key permissions: {str(e)}")
-        raise APIKeyError(f"Failed to update API key permissions: {str(e)}")
+    return APIKeyInfo.from_db(updated_api_key)

autogpt_platform/backend/backend/data/block.py

@@ -1,4 +1,3 @@
-import functools
 import inspect
 import logging
 import os
@@ -8,6 +7,7 @@ from enum import Enum
 from typing import (
     TYPE_CHECKING,
     Any,
+    Callable,
     ClassVar,
     Generic,
     Optional,
@@ -20,6 +20,7 @@ from typing import (
 
 import jsonref
 import jsonschema
+from autogpt_libs.utils.cache import cached
 from prisma.models import AgentBlock
 from prisma.types import AgentBlockCreateInput
 from pydantic import BaseModel
@@ -44,9 +45,10 @@ if TYPE_CHECKING:
 
 app_config = Config()
 
-BlockData = tuple[str, Any]  # Input & Output data should be a tuple of (name, data).
 BlockInput = dict[str, Any]  # Input: 1 input pin consumes 1 data.
-BlockOutput = AsyncGen[BlockData, None]  # Output: 1 output pin produces n data.
+BlockOutputEntry = tuple[str, Any]  # Output data should be a tuple of (name, value).
+BlockOutput = AsyncGen[BlockOutputEntry, None]  # Output: 1 output pin produces n data.
+BlockTestOutput = BlockOutputEntry | tuple[str, Callable[[Any], bool]]
 CompletedBlockOutput = dict[str, list[Any]]  # Completed stream, collected as a dict.
 
 
@@ -89,6 +91,45 @@ class BlockCategory(Enum):
         return {"category": self.name, "description": self.value}
 
 
+class BlockCostType(str, Enum):
+    RUN = "run"  # cost X credits per run
+    BYTE = "byte"  # cost X credits per byte
+    SECOND = "second"  # cost X credits per second
+
+
+class BlockCost(BaseModel):
+    cost_amount: int
+    cost_filter: BlockInput
+    cost_type: BlockCostType
+
+    def __init__(
+        self,
+        cost_amount: int,
+        cost_type: BlockCostType = BlockCostType.RUN,
+        cost_filter: Optional[BlockInput] = None,
+        **data: Any,
+    ) -> None:
+        super().__init__(
+            cost_amount=cost_amount,
+            cost_filter=cost_filter or {},
+            cost_type=cost_type,
+            **data,
+        )
+
+
+class BlockInfo(BaseModel):
+    id: str
+    name: str
+    inputSchema: dict[str, Any]
+    outputSchema: dict[str, Any]
+    costs: list[BlockCost]
+    description: str
+    categories: list[dict[str, str]]
+    contributors: list[dict[str, Any]]
+    staticOutput: bool
+    uiType: str
+
+
 class BlockSchema(BaseModel):
     cached_jsonschema: ClassVar[dict[str, Any]]
 
@@ -306,7 +347,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
         input_schema: Type[BlockSchemaInputType] = EmptySchema,
         output_schema: Type[BlockSchemaOutputType] = EmptySchema,
         test_input: BlockInput | list[BlockInput] | None = None,
-        test_output: BlockData | list[BlockData] | None = None,
+        test_output: BlockTestOutput | list[BlockTestOutput] | None = None,
         test_mock: dict[str, Any] | None = None,
         test_credentials: Optional[Credentials | dict[str, Credentials]] = None,
         disabled: bool = False,
@@ -452,6 +493,24 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
             "uiType": self.block_type.value,
         }
 
+    def get_info(self) -> BlockInfo:
+        from backend.data.credit import get_block_cost
+
+        return BlockInfo(
+            id=self.id,
+            name=self.name,
+            inputSchema=self.input_schema.jsonschema(),
+            outputSchema=self.output_schema.jsonschema(),
+            costs=get_block_cost(self),
+            description=self.description,
+            categories=[category.dict() for category in self.categories],
+            contributors=[
+                contributor.model_dump() for contributor in self.contributors
+            ],
+            staticOutput=self.static_output,
+            uiType=self.block_type.value,
+        )
+
     async def execute(self, input_data: BlockInput, **kwargs) -> BlockOutput:
         if error := self.input_schema.validate_data(input_data):
             raise ValueError(
@@ -663,7 +722,7 @@ def get_block(block_id: str) -> Block[BlockSchema, BlockSchema] | None:
     return cls() if cls else None
 
 
-@functools.cache
+@cached()
 def get_webhook_block_ids() -> Sequence[str]:
     return [
         id
@@ -672,7 +731,7 @@ def get_webhook_block_ids() -> Sequence[str]:
     ]
 
 
-@functools.cache
+@cached()
 def get_io_block_ids() -> Sequence[str]:
     return [
         id

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -29,8 +29,7 @@ from backend.blocks.replicate.replicate_block import ReplicateModelBlock
 from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
 from backend.blocks.talking_head import CreateTalkingAvatarVideoBlock
 from backend.blocks.text_to_speech_block import UnrealTextToSpeechBlock
-from backend.data.block import Block
-from backend.data.cost import BlockCost, BlockCostType
+from backend.data.block import Block, BlockCost, BlockCostType
 from backend.integrations.credentials_store import (
     aiml_api_credentials,
     anthropic_credentials,
@@ -307,7 +306,18 @@ BLOCK_COSTS: dict[Type[Block], list[BlockCost]] = {
                     "type": ideogram_credentials.type,
                 }
             },
-        )
+        ),
+        BlockCost(
+            cost_amount=18,
+            cost_filter={
+                "ideogram_model_name": "V_3",
+                "credentials": {
+                    "id": ideogram_credentials.id,
+                    "provider": ideogram_credentials.provider,
+                    "type": ideogram_credentials.type,
+                },
+            },
+        ),
     ],
     AIShortformVideoCreatorBlock: [
         BlockCost(

autogpt_platform/backend/backend/data/cost.py

@@ -1,32 +0,0 @@
-from enum import Enum
-from typing import Any, Optional
-
-from pydantic import BaseModel
-
-from backend.data.block import BlockInput
-
-
-class BlockCostType(str, Enum):
-    RUN = "run"  # cost X credits per run
-    BYTE = "byte"  # cost X credits per byte
-    SECOND = "second"  # cost X credits per second
-
-
-class BlockCost(BaseModel):
-    cost_amount: int
-    cost_filter: BlockInput
-    cost_type: BlockCostType
-
-    def __init__(
-        self,
-        cost_amount: int,
-        cost_type: BlockCostType = BlockCostType.RUN,
-        cost_filter: Optional[BlockInput] = None,
-        **data: Any,
-    ) -> None:
-        super().__init__(
-            cost_amount=cost_amount,
-            cost_filter=cost_filter or {},
-            cost_type=cost_type,
-            **data,
-        )

autogpt_platform/backend/backend/data/credit.py

@@ -2,7 +2,7 @@ import logging
 from abc import ABC, abstractmethod
 from collections import defaultdict
 from datetime import datetime, timezone
-from typing import Any, cast
+from typing import TYPE_CHECKING, Any, cast
 
 import stripe
 from prisma import Json
@@ -23,7 +23,6 @@ from pydantic import BaseModel
 
 from backend.data import db
 from backend.data.block_cost_config import BLOCK_COSTS
-from backend.data.cost import BlockCost
 from backend.data.model import (
     AutoTopUpConfig,
     RefundRequest,
@@ -34,13 +33,16 @@ 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
 
+if TYPE_CHECKING:
+    from backend.data.block import Block, BlockCost
+
 settings = Settings()
 stripe.api_key = settings.secrets.stripe_api_key
 logger = logging.getLogger(__name__)
@@ -997,10 +999,14 @@ def get_user_credit_model() -> UserCreditBase:
     return UserCredit()
 
 
-def get_block_costs() -> dict[str, list[BlockCost]]:
+def get_block_costs() -> dict[str, list["BlockCost"]]:
     return {block().id: costs for block, costs in BLOCK_COSTS.items()}
 
 
+def get_block_cost(block: "Block") -> list["BlockCost"]:
+    return BLOCK_COSTS.get(block.__class__, [])
+
+
 async def get_stripe_customer_id(user_id: str) -> str:
     user = await get_user_by_id(user_id)
 

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/db.py

@@ -83,7 +83,7 @@ async def disconnect():
 
 
 # Transaction timeout constant (in milliseconds)
-TRANSACTION_TIMEOUT = 15000  # 15 seconds - Increased from 5s to prevent timeout errors
+TRANSACTION_TIMEOUT = 30000  # 30 seconds - Increased from 15s to prevent timeout errors during graph creation under load
 
 
 @asynccontextmanager

autogpt_platform/backend/backend/data/execution.py

@@ -11,11 +11,14 @@ from typing import (
     Generator,
     Generic,
     Literal,
+    Mapping,
     Optional,
     TypeVar,
+    cast,
     overload,
 )
 
+from prisma import Json
 from prisma.enums import AgentExecutionStatus
 from prisma.models import (
     AgentGraphExecution,
@@ -24,7 +27,6 @@ from prisma.models import (
     AgentNodeExecutionKeyValueData,
 )
 from prisma.types import (
-    AgentGraphExecutionCreateInput,
     AgentGraphExecutionUpdateManyMutationInput,
     AgentGraphExecutionWhereInput,
     AgentNodeExecutionCreateInput,
@@ -39,6 +41,7 @@ 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
@@ -59,7 +62,7 @@ from .includes import (
     GRAPH_EXECUTION_INCLUDE_WITH_NODES,
     graph_execution_include,
 )
-from .model import GraphExecutionStats, NodeExecutionStats
+from .model import CredentialsMetaInput, GraphExecutionStats, NodeExecutionStats
 
 T = TypeVar("T")
 
@@ -86,16 +89,49 @@ class BlockErrorStats(BaseModel):
 
 
 ExecutionStatus = AgentExecutionStatus
+NodeInputMask = Mapping[str, JsonValue]
+NodesInputMasks = Mapping[str, NodeInputMask]
+
+# dest: source
+VALID_STATUS_TRANSITIONS = {
+    ExecutionStatus.QUEUED: [
+        ExecutionStatus.INCOMPLETE,
+    ],
+    ExecutionStatus.RUNNING: [
+        ExecutionStatus.INCOMPLETE,
+        ExecutionStatus.QUEUED,
+        ExecutionStatus.TERMINATED,  # For resuming halted execution
+    ],
+    ExecutionStatus.COMPLETED: [
+        ExecutionStatus.RUNNING,
+    ],
+    ExecutionStatus.FAILED: [
+        ExecutionStatus.INCOMPLETE,
+        ExecutionStatus.QUEUED,
+        ExecutionStatus.RUNNING,
+    ],
+    ExecutionStatus.TERMINATED: [
+        ExecutionStatus.INCOMPLETE,
+        ExecutionStatus.QUEUED,
+        ExecutionStatus.RUNNING,
+    ],
+}
 
 
 class GraphExecutionMeta(BaseDbModel):
+    id: str  # type: ignore # Override base class to make this required
     user_id: str
     graph_id: str
     graph_version: int
-    preset_id: Optional[str] = None
+    inputs: Optional[BlockInput]  # no default -> required in the OpenAPI spec
+    credential_inputs: Optional[dict[str, CredentialsMetaInput]]
+    nodes_input_masks: Optional[dict[str, BlockInput]]
+    preset_id: Optional[str]
     status: ExecutionStatus
     started_at: datetime
     ended_at: datetime
+    is_shared: bool = False
+    share_token: Optional[str] = None
 
     class Stats(BaseModel):
         model_config = ConfigDict(
@@ -177,6 +213,18 @@ class GraphExecutionMeta(BaseDbModel):
             user_id=_graph_exec.userId,
             graph_id=_graph_exec.agentGraphId,
             graph_version=_graph_exec.agentGraphVersion,
+            inputs=cast(BlockInput | None, _graph_exec.inputs),
+            credential_inputs=(
+                {
+                    name: CredentialsMetaInput.model_validate(cmi)
+                    for name, cmi in cast(dict, _graph_exec.credentialInputs).items()
+                }
+                if _graph_exec.credentialInputs
+                else None
+            ),
+            nodes_input_masks=cast(
+                dict[str, BlockInput] | None, _graph_exec.nodesInputMasks
+            ),
             preset_id=_graph_exec.agentPresetId,
             status=ExecutionStatus(_graph_exec.executionStatus),
             started_at=start_time,
@@ -200,11 +248,13 @@ class GraphExecutionMeta(BaseDbModel):
                 if stats
                 else None
             ),
+            is_shared=_graph_exec.isShared,
+            share_token=_graph_exec.shareToken,
         )
 
 
 class GraphExecution(GraphExecutionMeta):
-    inputs: BlockInput
+    inputs: BlockInput  # type: ignore - incompatible override is intentional
     outputs: CompletedBlockOutput
 
     @staticmethod
@@ -224,15 +274,18 @@ class GraphExecution(GraphExecutionMeta):
         )
 
         inputs = {
-            **{
-                # inputs from Agent Input Blocks
-                exec.input_data["name"]: exec.input_data.get("value")
-                for exec in complete_node_executions
-                if (
-                    (block := get_block(exec.block_id))
-                    and block.block_type == BlockType.INPUT
-                )
-            },
+            **(
+                graph_exec.inputs
+                or {
+                    # fallback: extract inputs from Agent Input Blocks
+                    exec.input_data["name"]: exec.input_data.get("value")
+                    for exec in complete_node_executions
+                    if (
+                        (block := get_block(exec.block_id))
+                        and block.block_type == BlockType.INPUT
+                    )
+                }
+            ),
             **{
                 # input from webhook-triggered block
                 "payload": exec.input_data["payload"]
@@ -250,14 +303,13 @@ class GraphExecution(GraphExecutionMeta):
             if (
                 block := get_block(exec.block_id)
             ) and block.block_type == BlockType.OUTPUT:
-                outputs[exec.input_data["name"]].append(
-                    exec.input_data.get("value", None)
-                )
+                outputs[exec.input_data["name"]].append(exec.input_data.get("value"))
 
         return GraphExecution(
             **{
                 field_name: getattr(graph_exec, field_name)
                 for field_name in GraphExecutionMeta.model_fields
+                if field_name != "inputs"
             },
             inputs=inputs,
             outputs=outputs,
@@ -290,13 +342,18 @@ class GraphExecutionWithNodes(GraphExecution):
             node_executions=node_executions,
         )
 
-    def to_graph_execution_entry(self):
+    def to_graph_execution_entry(
+        self,
+        user_context: "UserContext",
+        compiled_nodes_input_masks: Optional[NodesInputMasks] = None,
+    ):
         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
+            nodes_input_masks=compiled_nodes_input_masks,
+            user_context=user_context,
         )
 
 
@@ -332,7 +389,7 @@ class NodeExecutionResult(BaseModel):
         else:
             input_data: BlockInput = defaultdict()
             for data in _node_exec.Input or []:
-                input_data[data.name] = type_utils.convert(data.data, type[Any])
+                input_data[data.name] = type_utils.convert(data.data, JsonValue)
 
         output_data: CompletedBlockOutput = defaultdict(list)
 
@@ -341,7 +398,7 @@ class NodeExecutionResult(BaseModel):
                 output_data[name].extend(messages)
         else:
             for data in _node_exec.Output or []:
-                output_data[data.name].append(type_utils.convert(data.data, type[Any]))
+                output_data[data.name].append(type_utils.convert(data.data, JsonValue))
 
         graph_execution: AgentGraphExecution | None = _node_exec.GraphExecution
         if graph_execution:
@@ -368,7 +425,9 @@ 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 +436,7 @@ class NodeExecutionResult(BaseModel):
             node_id=self.node_id,
             block_id=self.block_id,
             inputs=self.input_data,
+            user_context=user_context,
         )
 
 
@@ -384,13 +444,13 @@ 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 +478,60 @@ 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:
@@ -479,9 +593,12 @@ async def get_graph_execution(
 async def create_graph_execution(
     graph_id: str,
     graph_version: int,
-    starting_nodes_input: list[tuple[str, BlockInput]],
+    starting_nodes_input: list[tuple[str, BlockInput]],  # list[(node_id, BlockInput)]
+    inputs: Mapping[str, JsonValue],
     user_id: str,
-    preset_id: str | None = None,
+    preset_id: Optional[str] = None,
+    credential_inputs: Optional[Mapping[str, CredentialsMetaInput]] = None,
+    nodes_input_masks: Optional[NodesInputMasks] = None,
 ) -> GraphExecutionWithNodes:
     """
     Create a new AgentGraphExecution record.
@@ -489,11 +606,18 @@ async def create_graph_execution(
         The id of the AgentGraphExecution and the list of ExecutionResult for each node.
     """
     result = await AgentGraphExecution.prisma().create(
-        data=AgentGraphExecutionCreateInput(
-            agentGraphId=graph_id,
-            agentGraphVersion=graph_version,
-            executionStatus=ExecutionStatus.QUEUED,
-            NodeExecutions={
+        data={
+            "agentGraphId": graph_id,
+            "agentGraphVersion": graph_version,
+            "executionStatus": ExecutionStatus.INCOMPLETE,
+            "inputs": SafeJson(inputs),
+            "credentialInputs": (
+                SafeJson(credential_inputs) if credential_inputs else Json({})
+            ),
+            "nodesInputMasks": (
+                SafeJson(nodes_input_masks) if nodes_input_masks else Json({})
+            ),
+            "NodeExecutions": {
                 "create": [
                     AgentNodeExecutionCreateInput(
                         agentNodeId=node_id,
@@ -509,9 +633,9 @@ async def create_graph_execution(
                     for node_id, node_input in starting_nodes_input
                 ]
             },
-            userId=user_id,
-            agentPresetId=preset_id,
-        ),
+            "userId": user_id,
+            "agentPresetId": preset_id,
+        },
         include=GRAPH_EXECUTION_INCLUDE_WITH_NODES,
     )
 
@@ -522,7 +646,7 @@ async def upsert_execution_input(
     node_id: str,
     graph_exec_id: str,
     input_name: str,
-    input_data: Any,
+    input_data: JsonValue,
     node_exec_id: str | None = None,
 ) -> tuple[str, BlockInput]:
     """
@@ -571,7 +695,7 @@ async def upsert_execution_input(
         )
         return existing_execution.id, {
             **{
-                input_data.name: type_utils.convert(input_data.data, type[Any])
+                input_data.name: type_utils.convert(input_data.data, JsonValue)
                 for input_data in existing_execution.Input or []
             },
             input_name: input_data,
@@ -632,6 +756,11 @@ async def update_graph_execution_stats(
     status: ExecutionStatus | None = None,
     stats: GraphExecutionStats | None = None,
 ) -> GraphExecution | None:
+    if not status and not stats:
+        raise ValueError(
+            f"Must provide either status or stats to update for execution {graph_exec_id}"
+        )
+
     update_data: AgentGraphExecutionUpdateManyMutationInput = {}
 
     if stats:
@@ -643,20 +772,25 @@ async def update_graph_execution_stats(
     if status:
         update_data["executionStatus"] = status
 
-    updated_count = await AgentGraphExecution.prisma().update_many(
-        where={
-            "id": graph_exec_id,
-            "OR": [
-                {"executionStatus": ExecutionStatus.RUNNING},
-                {"executionStatus": ExecutionStatus.QUEUED},
-                # Terminated graph can be resumed.
-                {"executionStatus": ExecutionStatus.TERMINATED},
-            ],
-        },
+    where_clause: AgentGraphExecutionWhereInput = {"id": graph_exec_id}
+
+    if status:
+        if allowed_from := VALID_STATUS_TRANSITIONS.get(status, []):
+            # Add OR clause to check if current status is one of the allowed source statuses
+            where_clause["AND"] = [
+                {"id": graph_exec_id},
+                {"OR": [{"executionStatus": s} for s in allowed_from]},
+            ]
+        else:
+            raise ValueError(
+                f"Status {status} cannot be set via update for execution {graph_exec_id}. "
+                f"This status can only be set at creation or is not a valid target status."
+            )
+
+    await AgentGraphExecution.prisma().update_many(
+        where=where_clause,
         data=update_data,
     )
-    if updated_count == 0:
-        return None
 
     graph_exec = await AgentGraphExecution.prisma().find_unique_or_raise(
         where={"id": graph_exec_id},
@@ -664,6 +798,7 @@ async def update_graph_execution_stats(
             [*get_io_block_ids(), *get_webhook_block_ids()]
         ),
     )
+
     return GraphExecution.from_db(graph_exec)
 
 
@@ -817,12 +952,19 @@ 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
+    nodes_input_masks: Optional[NodesInputMasks] = None
+    user_context: UserContext
 
 
 class NodeExecutionEntry(BaseModel):
@@ -833,6 +975,7 @@ class NodeExecutionEntry(BaseModel):
     node_id: str
     block_id: str
     inputs: BlockInput
+    user_context: UserContext
 
 
 class ExecutionQueue(Generic[T]):
@@ -882,6 +1025,18 @@ class NodeExecutionEvent(NodeExecutionResult):
     )
 
 
+class SharedExecutionResponse(BaseModel):
+    """Public-safe response for shared executions"""
+
+    id: str
+    graph_name: str
+    graph_description: Optional[str]
+    status: ExecutionStatus
+    created_at: datetime
+    outputs: CompletedBlockOutput  # Only the final outputs, no intermediate data
+    # Deliberately exclude: user_id, inputs, credentials, node details
+
+
 ExecutionEvent = Annotated[
     GraphExecutionEvent | NodeExecutionEvent, Field(discriminator="event_type")
 ]
@@ -1059,3 +1214,98 @@ async def get_block_error_stats(
         )
         for row in result
     ]
+
+
+async def update_graph_execution_share_status(
+    execution_id: str,
+    user_id: str,
+    is_shared: bool,
+    share_token: str | None,
+    shared_at: datetime | None,
+) -> None:
+    """Update the sharing status of a graph execution."""
+    await AgentGraphExecution.prisma().update(
+        where={"id": execution_id},
+        data={
+            "isShared": is_shared,
+            "shareToken": share_token,
+            "sharedAt": shared_at,
+        },
+    )
+
+
+async def get_graph_execution_by_share_token(
+    share_token: str,
+) -> SharedExecutionResponse | None:
+    """Get a shared execution with limited public-safe data."""
+    execution = await AgentGraphExecution.prisma().find_first(
+        where={
+            "shareToken": share_token,
+            "isShared": True,
+            "isDeleted": False,
+        },
+        include={
+            "AgentGraph": True,
+            "NodeExecutions": {
+                "include": {
+                    "Output": True,
+                    "Node": {
+                        "include": {
+                            "AgentBlock": True,
+                        }
+                    },
+                },
+            },
+        },
+    )
+
+    if not execution:
+        return None
+
+    # Extract outputs from OUTPUT blocks only (consistent with GraphExecution.from_db)
+    outputs: CompletedBlockOutput = defaultdict(list)
+    if execution.NodeExecutions:
+        for node_exec in execution.NodeExecutions:
+            if node_exec.Node and node_exec.Node.agentBlockId:
+                # Get the block definition to check its type
+                block = get_block(node_exec.Node.agentBlockId)
+
+                if block and block.block_type == BlockType.OUTPUT:
+                    # For OUTPUT blocks, the data is stored in executionData or Input
+                    # The executionData contains the structured input with 'name' and 'value' fields
+                    if hasattr(node_exec, "executionData") and node_exec.executionData:
+                        exec_data = type_utils.convert(
+                            node_exec.executionData, dict[str, Any]
+                        )
+                        if "name" in exec_data:
+                            name = exec_data["name"]
+                            value = exec_data.get("value")
+                            outputs[name].append(value)
+                    elif node_exec.Input:
+                        # Build input_data from Input relation
+                        input_data = {}
+                        for data in node_exec.Input:
+                            if data.name and data.data is not None:
+                                input_data[data.name] = type_utils.convert(
+                                    data.data, JsonValue
+                                )
+
+                        if "name" in input_data:
+                            name = input_data["name"]
+                            value = input_data.get("value")
+                            outputs[name].append(value)
+
+    return SharedExecutionResponse(
+        id=execution.id,
+        graph_name=(
+            execution.AgentGraph.name
+            if (execution.AgentGraph and execution.AgentGraph.name)
+            else "Untitled Agent"
+        ),
+        graph_description=(
+            execution.AgentGraph.description if execution.AgentGraph else None
+        ),
+        status=ExecutionStatus(execution.executionStatus),
+        created_at=execution.createdAt,
+        outputs=outputs,
+    )

autogpt_platform/backend/backend/data/graph.py

@@ -1,6 +1,7 @@
 import logging
 import uuid
 from collections import defaultdict
+from datetime import datetime, timezone
 from typing import TYPE_CHECKING, Any, Literal, Optional, cast
 
 from prisma.enums import SubmissionStatus
@@ -12,7 +13,7 @@ from prisma.types import (
     AgentNodeLinkCreateInput,
     StoreListingVersionWhereInput,
 )
-from pydantic import Field, JsonValue, create_model
+from pydantic import BaseModel, Field, create_model
 from pydantic.fields import computed_field
 
 from backend.blocks.agent import AgentExecutorBlock
@@ -28,12 +29,14 @@ from backend.data.model import (
 from backend.integrations.providers import ProviderName
 from backend.util import type as type_utils
 from backend.util.json import SafeJson
+from backend.util.models import Pagination
 
 from .block import Block, BlockInput, BlockSchema, BlockType, get_block, get_blocks
 from .db import BaseDbModel, query_raw_with_schema, transaction
 from .includes import AGENT_GRAPH_INCLUDE, AGENT_NODE_INCLUDE
 
 if TYPE_CHECKING:
+    from .execution import NodesInputMasks
     from .integrations import Webhook
 
 logger = logging.getLogger(__name__)
@@ -159,6 +162,8 @@ class BaseGraph(BaseDbModel):
     is_active: bool = True
     name: str
     description: str
+    instructions: str | None = None
+    recommended_schedule_cron: str | None = None
     nodes: list[Node] = []
     links: list[Link] = []
     forked_from_id: str | None = None
@@ -205,6 +210,35 @@ class BaseGraph(BaseDbModel):
             None,
         )
 
+    @computed_field
+    @property
+    def trigger_setup_info(self) -> "GraphTriggerInfo | None":
+        if not (
+            self.webhook_input_node
+            and (trigger_block := self.webhook_input_node.block).webhook_config
+        ):
+            return None
+
+        return GraphTriggerInfo(
+            provider=trigger_block.webhook_config.provider,
+            config_schema={
+                **(json_schema := trigger_block.input_schema.jsonschema()),
+                "properties": {
+                    pn: sub_schema
+                    for pn, sub_schema in json_schema["properties"].items()
+                    if not is_credentials_field_name(pn)
+                },
+                "required": [
+                    pn
+                    for pn in json_schema.get("required", [])
+                    if not is_credentials_field_name(pn)
+                ],
+            },
+            credentials_input_name=next(
+                iter(trigger_block.input_schema.get_credentials_fields()), None
+            ),
+        )
+
     @staticmethod
     def _generate_schema(
         *props: tuple[type[AgentInputBlock.Input] | type[AgentOutputBlock.Input], dict],
@@ -238,6 +272,14 @@ class BaseGraph(BaseDbModel):
         }
 
 
+class GraphTriggerInfo(BaseModel):
+    provider: ProviderName
+    config_schema: dict[str, Any] = Field(
+        description="Input schema for the trigger block"
+    )
+    credentials_input_name: Optional[str]
+
+
 class Graph(BaseGraph):
     sub_graphs: list[BaseGraph] = []  # Flattened sub-graphs
 
@@ -342,6 +384,8 @@ class GraphModel(Graph):
     user_id: str
     nodes: list[NodeModel] = []  # type: ignore
 
+    created_at: datetime
+
     @property
     def starting_nodes(self) -> list[NodeModel]:
         outbound_nodes = {link.sink_id for link in self.links}
@@ -354,6 +398,10 @@ class GraphModel(Graph):
             if node.id not in outbound_nodes or node.id in input_nodes
         ]
 
+    @property
+    def webhook_input_node(self) -> NodeModel | None:  # type: ignore
+        return cast(NodeModel, super().webhook_input_node)
+
     def meta(self) -> "GraphMeta":
         """
         Returns a GraphMeta object with metadata about the graph.
@@ -414,7 +462,7 @@ class GraphModel(Graph):
     def validate_graph(
         self,
         for_run: bool = False,
-        nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
+        nodes_input_masks: Optional["NodesInputMasks"] = None,
     ):
         """
         Validate graph structure and raise `ValueError` on issues.
@@ -428,7 +476,7 @@ class GraphModel(Graph):
     def _validate_graph(
         graph: BaseGraph,
         for_run: bool = False,
-        nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
+        nodes_input_masks: Optional["NodesInputMasks"] = None,
     ) -> None:
         errors = GraphModel._validate_graph_get_errors(
             graph, for_run, nodes_input_masks
@@ -442,7 +490,7 @@ class GraphModel(Graph):
     def validate_graph_get_errors(
         self,
         for_run: bool = False,
-        nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
+        nodes_input_masks: Optional["NodesInputMasks"] = None,
     ) -> dict[str, dict[str, str]]:
         """
         Validate graph and return structured errors per node.
@@ -464,7 +512,7 @@ class GraphModel(Graph):
     def _validate_graph_get_errors(
         graph: BaseGraph,
         for_run: bool = False,
-        nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
+        nodes_input_masks: Optional["NodesInputMasks"] = None,
     ) -> dict[str, dict[str, str]]:
         """
         Validate graph and return structured errors per node.
@@ -655,9 +703,12 @@ class GraphModel(Graph):
             version=graph.version,
             forked_from_id=graph.forkedFromId,
             forked_from_version=graph.forkedFromVersion,
+            created_at=graph.createdAt,
             is_active=graph.isActive,
             name=graph.name or "",
             description=graph.description or "",
+            instructions=graph.instructions,
+            recommended_schedule_cron=graph.recommendedScheduleCron,
             nodes=[NodeModel.from_db(node, for_export) for node in graph.Nodes or []],
             links=list(
                 {
@@ -696,6 +747,13 @@ class GraphMeta(Graph):
         return GraphMeta(**graph.model_dump())
 
 
+class GraphsPaginated(BaseModel):
+    """Response schema for paginated graphs."""
+
+    graphs: list[GraphMeta]
+    pagination: Pagination
+
+
 # --------------------- CRUD functions --------------------- #
 
 
@@ -724,31 +782,42 @@ async def set_node_webhook(node_id: str, webhook_id: str | None) -> NodeModel:
     return NodeModel.from_db(node)
 
 
-async def list_graphs(
+async def list_graphs_paginated(
     user_id: str,
+    page: int = 1,
+    page_size: int = 25,
     filter_by: Literal["active"] | None = "active",
-) -> list[GraphMeta]:
+) -> GraphsPaginated:
     """
-    Retrieves graph metadata objects.
-    Default behaviour is to get all currently active graphs.
+    Retrieves paginated graph metadata objects.
 
     Args:
+        user_id: The ID of the user that owns the graphs.
+        page: Page number (1-based).
+        page_size: Number of graphs per page.
         filter_by: An optional filter to either select graphs.
-        user_id: The ID of the user that owns the graph.
 
     Returns:
-        list[GraphMeta]: A list of objects representing the retrieved graphs.
+        GraphsPaginated: Paginated list of graph metadata.
     """
     where_clause: AgentGraphWhereInput = {"userId": user_id}
 
     if filter_by == "active":
         where_clause["isActive"] = True
 
+    # Get total count
+    total_count = await AgentGraph.prisma().count(where=where_clause)
+    total_pages = (total_count + page_size - 1) // page_size
+
+    # Get paginated results
+    offset = (page - 1) * page_size
     graphs = await AgentGraph.prisma().find_many(
         where=where_clause,
         distinct=["id"],
         order={"version": "desc"},
         include=AGENT_GRAPH_INCLUDE,
+        skip=offset,
+        take=page_size,
     )
 
     graph_models: list[GraphMeta] = []
@@ -762,7 +831,15 @@ async def list_graphs(
             logger.error(f"Error processing graph {graph.id}: {e}")
             continue
 
-    return graph_models
+    return GraphsPaginated(
+        graphs=graph_models,
+        pagination=Pagination(
+            total_items=total_count,
+            total_pages=total_pages,
+            current_page=page,
+            page_size=page_size,
+        ),
+    )
 
 
 async def get_graph_metadata(graph_id: str, version: int | None = None) -> Graph | None:
@@ -1045,6 +1122,7 @@ async def __create_graph(tx, graph: Graph, user_id: str):
                 version=graph.version,
                 name=graph.name,
                 description=graph.description,
+                recommendedScheduleCron=graph.recommended_schedule_cron,
                 isActive=graph.is_active,
                 userId=user_id,
                 forkedFromId=graph.forked_from_id,
@@ -1103,6 +1181,7 @@ def make_graph_model(creatable_graph: Graph, user_id: str) -> GraphModel:
     return GraphModel(
         **creatable_graph.model_dump(exclude={"nodes"}),
         user_id=user_id,
+        created_at=datetime.now(tz=timezone.utc),
         nodes=[
             NodeModel(
                 **creatable_node.model_dump(),

autogpt_platform/backend/backend/data/graph_test.py

@@ -2,7 +2,6 @@ import json
 from typing import Any
 from uuid import UUID
 
-import autogpt_libs.auth.models
 import fastapi.exceptions
 import pytest
 from pytest_snapshot.plugin import Snapshot
@@ -317,12 +316,7 @@ async def test_access_store_listing_graph(server: SpinTestServer):
             is_approved=True,
             comments="Test comments",
         ),
-        autogpt_libs.auth.models.User(
-            user_id=admin_user.id,
-            role="admin",
-            email=admin_user.email,
-            phone_number="1234567890",
-        ),
+        user_id=admin_user.id,
     )
 
     # Now we check the graph can be accessed by a user that does not own the graph

autogpt_platform/backend/backend/data/includes.py

@@ -59,9 +59,15 @@ def graph_execution_include(
     }
 
 
+AGENT_PRESET_INCLUDE: prisma.types.AgentPresetInclude = {
+    "InputPresets": True,
+    "Webhook": True,
+}
+
+
 INTEGRATION_WEBHOOK_INCLUDE: prisma.types.IntegrationWebhookInclude = {
     "AgentNodes": {"include": AGENT_NODE_INCLUDE},
-    "AgentPresets": {"include": {"InputPresets": True}},
+    "AgentPresets": {"include": AGENT_PRESET_INCLUDE},
 }
 
 

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/redis_client.py

@@ -1,8 +1,7 @@
 import logging
 import os
-from functools import cache
 
-from autogpt_libs.utils.cache import thread_cached
+from autogpt_libs.utils.cache import cached, thread_cached
 from dotenv import load_dotenv
 from redis import Redis
 from redis.asyncio import Redis as AsyncRedis
@@ -13,7 +12,7 @@ load_dotenv()
 
 HOST = os.getenv("REDIS_HOST", "localhost")
 PORT = int(os.getenv("REDIS_PORT", "6379"))
-PASSWORD = os.getenv("REDIS_PASSWORD", "password")
+PASSWORD = os.getenv("REDIS_PASSWORD", None)
 
 logger = logging.getLogger(__name__)
 
@@ -35,7 +34,7 @@ def disconnect():
     get_redis().close()
 
 
-@cache
+@cached()
 def get_redis() -> Redis:
     return connect()