Merge branch 'dev' into update-install-scripts

Refactored Windows and Linux setup scripts to streamline prerequisite checks, repository detection, and service startup. Removed Sentry configuration and related prompts for a simpler setup experience. Updated user messaging and improved error handling for common Docker issues.

.github/copilot-instructions.md

@@ -1,322 +0,0 @@
-# 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
-
-**📖 Complete Frontend Guide**: See `autogpt_platform/frontend/CONTRIBUTING.md` and `autogpt_platform/frontend/.cursorrules` for comprehensive patterns and conventions.
-
-**Quick Reference:**
-
-**Component Structure:**
-
-- Separate render logic from data/behavior
-- Structure: `ComponentName/ComponentName.tsx` + `useComponentName.ts` + `helpers.ts`
-- Exception: Small components (3-4 lines of logic) can be inline
-- Render-only components can be direct files without folders
-
-**Data Fetching:**
-
-- Use generated API hooks from `@/app/api/__generated__/endpoints/`
-- Generated via Orval from backend OpenAPI spec
-- Pattern: `use{Method}{Version}{OperationName}`
-- Example: `useGetV2ListLibraryAgents`
-- Regenerate with: `pnpm generate:api`
-- **Never** use deprecated `BackendAPI` or `src/lib/autogpt-server-api/*`
-
-**Code Conventions:**
-
-- Use function declarations for components and handlers (not arrow functions)
-- Only arrow functions for small inline lambdas (map, filter, etc.)
-- Components: `PascalCase`, Hooks: `camelCase` with `use` prefix
-- No barrel files or `index.ts` re-exports
-- Minimal comments (code should be self-documenting)
-
-**Styling:**
-
-- Use Tailwind CSS utilities only
-- Use design system components from `src/components/` (atoms, molecules, organisms)
-- Never use `src/components/__legacy__/*`
-- Only use Phosphor Icons (`@phosphor-icons/react`)
-- Prefer design tokens over hardcoded values
-
-**Error Handling:**
-
-- Render errors: Use `<ErrorCard />` component
-- Mutation errors: Display with toast notifications
-- Manual exceptions: Use `Sentry.captureException()`
-- Global error boundaries already configured
-
-**Testing:**
-
-- Add/update Storybook stories for UI components (`pnpm storybook`)
-- Run Playwright E2E tests with `pnpm test`
-- Verify in Chromatic after PR
-
-**Architecture:**
-
-- Default to client components ("use client")
-- Server components only for SEO or extreme TTFB needs
-- Use React Query for server state (via generated hooks)
-- Co-locate UI state in components/hooks
-
-### 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

@@ -1,97 +0,0 @@
-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

@@ -1,379 +0,0 @@
-# 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

@@ -30,296 +30,18 @@ jobs:
         github.event.issue.author_association == 'COLLABORATOR'
       )
     runs-on: ubuntu-latest
-    timeout-minutes: 45
-
     permissions:
-      contents: write
+      contents: read
       pull-requests: read
       issues: read
       id-token: write
-      actions: read # Required for CI access
     steps:
-      - name: Checkout code
+      - name: Checkout repository
         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@v1
+        uses: anthropics/claude-code-action@beta
         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

@@ -1,302 +0,0 @@
-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-autgpt-deploy-prod.yml

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

.github/workflows/platform-autogpt-deploy-dev.yaml

@@ -5,13 +5,6 @@ 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'
@@ -26,8 +19,6 @@ 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
@@ -57,4 +48,4 @@ jobs:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
           event-type: build_deploy_dev
-          client-payload: '{"ref": "${{ github.event.inputs.git_ref || github.ref }}", "repository": "${{ github.repository }}"}'
+          client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}", "repository": "${{ github.repository }}"}'

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

@@ -32,12 +32,14 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.11", "3.12", "3.13"]
+        python-version: ["3.11"]
     runs-on: ubuntu-latest
 
     services:
       redis:
-        image: redis:latest
+        image: bitnami/redis:6.2
+        env:
+          REDIS_PASSWORD: testpassword
         ports:
           - 6379:6379
       rabbitmq:
@@ -199,9 +201,10 @@ 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 }}
-          JWT_VERIFY_KEY: ${{ steps.supabase.outputs.JWT_SECRET }}
+          SUPABASE_JWT_SECRET: ${{ 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

@@ -30,7 +30,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "22.18.0"
+          node-version: "21"
 
       - name: Enable corepack
         run: corepack enable
@@ -62,7 +62,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "22.18.0"
+          node-version: "21"
 
       - name: Enable corepack
         run: corepack enable
@@ -97,7 +97,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "22.18.0"
+          node-version: "21"
 
       - name: Enable corepack
         run: corepack enable
@@ -138,7 +138,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "22.18.0"
+          node-version: "21"
 
       - name: Enable corepack
         run: corepack enable
@@ -160,7 +160,7 @@ jobs:
 
       - name: Run docker compose
         run: |
-          NEXT_PUBLIC_PW_TEST=true docker compose -f ../docker-compose.yml up -d
+          docker compose -f ../docker-compose.yml up -d
         env:
           DOCKER_BUILDKIT: 1
           BUILDX_CACHE_FROM: type=local,src=/tmp/.buildx-cache

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

@@ -30,7 +30,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "22.18.0"
+          node-version: "21"
 
       - name: Enable corepack
         run: corepack enable
@@ -66,7 +66,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "22.18.0"
+          node-version: "21"
 
       - name: Enable corepack
         run: corepack enable

.gitignore

@@ -178,4 +178,3 @@ autogpt_platform/backend/settings.py
 *.ign.*
 .test-contents
 .claude/settings.local.json
-/autogpt_platform/backend/logs

.pr_agent.toml

@@ -1,3 +1,6 @@
+[pr_reviewer]
+num_code_suggestions=0
+
 [pr_code_suggestions]
 commitable_code_suggestions=false
 num_code_suggestions=0

autogpt_platform/CLAUDE.md

@@ -61,41 +61,24 @@ poetry run pytest path/to/test.py --snapshot-update
 
 ```bash
 # Install dependencies
-cd frontend && pnpm i
-
-# Generate API client from OpenAPI spec
-pnpm generate:api
+cd frontend && npm install
 
 # Start development server
-pnpm dev
+npm run dev
 
 # Run E2E tests
-pnpm test
+npm run test
 
 # Run Storybook for component development
-pnpm storybook
+npm run storybook
 
 # Build production
-pnpm build
-
-# Format and lint
-pnpm format
+npm run build
 
 # Type checking
-pnpm types
+npm run types
 ```
 
-**📖 Complete Guide**: See `/frontend/CONTRIBUTING.md` and `/frontend/.cursorrules` for comprehensive frontend patterns.
-
-**Key Frontend Conventions:**
-
-- Separate render logic from data/behavior in components
-- Use generated API hooks from `@/app/api/__generated__/endpoints/`
-- Use function declarations (not arrow functions) for components/handlers
-- Use design system components from `src/components/` (atoms, molecules, organisms)
-- Only use Phosphor Icons
-- Never use `src/components/__legacy__/*` or deprecated `BackendAPI`
-
 ## Architecture Overview
 
 ### Backend Architecture
@@ -109,16 +92,11 @@ pnpm types
 
 ### Frontend Architecture
 
-- **Framework**: Next.js 15 App Router (client-first approach)
-- **Data Fetching**: Type-safe generated API hooks via Orval + React Query
-- **State Management**: React Query for server state, co-located UI state in components/hooks
-- **Component Structure**: Separate render logic (`.tsx`) from business logic (`use*.ts` hooks)
+- **Framework**: Next.js App Router with React Server Components
+- **State Management**: React hooks + Supabase client for real-time updates
 - **Workflow Builder**: Visual graph editor using @xyflow/react
-- **UI Components**: shadcn/ui (Radix UI primitives) with Tailwind CSS styling
-- **Icons**: Phosphor Icons only
+- **UI Components**: Radix UI primitives with Tailwind CSS styling
 - **Feature Flags**: LaunchDarkly integration
-- **Error Handling**: ErrorCard for render errors, toast for mutations, Sentry for exceptions
-- **Testing**: Playwright for E2E, Storybook for component development
 
 ### Key Concepts
 
@@ -171,29 +149,16 @@ Key models (defined in `/backend/schema.prisma`):
 
 **Adding a new block:**
 
-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
-
-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`
+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()`
 
-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?
+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?
 ex: do the inputs and outputs tie well together?
 
-If you get any pushback or hit complex block conditions check the new_blocks guide in the docs.
-
 **Modifying the API:**
 
 1. Update route in `/backend/backend/server/routers/`
@@ -203,20 +168,10 @@ If you get any pushback or hit complex block conditions check the new_blocks gui
 
 **Frontend feature development:**
 
-See `/frontend/CONTRIBUTING.md` for complete patterns. Quick reference:
-
-1. **Pages**: Create in `src/app/(platform)/feature-name/page.tsx`
-   - Add `usePageName.ts` hook for logic
-   - Put sub-components in local `components/` folder
-2. **Components**: Structure as `ComponentName/ComponentName.tsx` + `useComponentName.ts` + `helpers.ts`
-   - Use design system components from `src/components/` (atoms, molecules, organisms)
-   - Never use `src/components/__legacy__/*`
-3. **Data fetching**: Use generated API hooks from `@/app/api/__generated__/endpoints/`
-   - Regenerate with `pnpm generate:api`
-   - Pattern: `use{Method}{Version}{OperationName}`
-4. **Styling**: Tailwind CSS only, use design tokens, Phosphor Icons only
-5. **Testing**: Add Storybook stories for new components, Playwright for E2E
-6. **Code conventions**: Function declarations (not arrow functions) for components/handlers
+1. Components go in `/frontend/src/components/`
+2. Use existing UI components from `/frontend/src/components/ui/`
+3. Add Storybook stories for new components
+4. Test with Playwright if user-facing
 
 ### Security Implementation
 

autogpt_platform/Makefile

@@ -1,57 +0,0 @@
-.PHONY: start-core stop-core logs-core format lint migrate run-backend run-frontend
-
-# Run just Supabase + Redis + RabbitMQ
-start-core:
-	docker compose up -d deps
-
-# Stop core services
-stop-core:
-	docker compose stop deps
-
-reset-db:
-	rm -rf db/docker/volumes/db/data
-	cd backend && poetry run prisma migrate deploy
-	cd backend && poetry run prisma generate
-	
-# View logs for core services
-logs-core:
-	docker compose logs -f deps
-
-# Run formatting and linting for backend and frontend
-format:
-	cd backend && poetry run format
-	cd frontend && pnpm format
-	cd frontend && pnpm lint
-
-init-env:
-	cp -n .env.default .env || true
-	cd backend && cp -n .env.default .env || true
-	cd frontend && cp -n .env.default .env || true
-
-
-# Run migrations for backend
-migrate:
-	cd backend && poetry run prisma migrate deploy
-	cd backend && poetry run prisma generate
-
-run-backend:
-	cd backend && poetry run app
-
-run-frontend:
-	cd frontend && pnpm dev
-
-test-data:
-	cd backend && poetry run python test/test_data_creator.py
-	
-help:
-	@echo "Usage: make <target>"
-	@echo "Targets:"
-	@echo "  start-core - Start just the core services (Supabase, Redis, RabbitMQ) in background"
-	@echo "  stop-core - Stop the core services"
-	@echo "  reset-db - Reset the database by deleting the volume"
-	@echo "  logs-core - Tail the logs for core services"
-	@echo "  format - Format & lint backend (Python) and frontend (TypeScript) code"
-	@echo "  migrate - Run backend database migrations"
-	@echo "  run-backend - Run the backend FastAPI server"
-	@echo "  run-frontend - Run the frontend Next.js development server"
-	@echo "  test-data - Run the test data creator"

autogpt_platform/README.md

@@ -38,37 +38,6 @@ To run the AutoGPT Platform, follow these steps:
 
 4. After all the services are in ready state, open your browser and navigate to `http://localhost:3000` to access the AutoGPT Platform frontend.
 
-### Running Just Core services
-
-You can now run the following to enable just the core services.
-
-```
-# For help
-make help
-
-# Run just Supabase + Redis + RabbitMQ
-make start-core
-
-# Stop core services
-make stop-core
-
-# View logs from core services 
-make logs-core
-
-# Run formatting and linting for backend and frontend
-make format
-
-# Run migrations for backend database
-make migrate
-
-# Run backend server
-make run-backend
-
-# Run frontend development server
-make run-frontend
-
-```
-
 ### Docker Compose Commands
 
 Here are some useful Docker Compose commands for managing your AutoGPT Platform:

autogpt_platform/autogpt_libs/autogpt_libs/api_key/key_manager.py

@@ -0,0 +1,35 @@
+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

@@ -1,78 +0,0 @@
-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

@@ -1,79 +0,0 @@
-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

@@ -1,19 +1,13 @@
-from .config import verify_settings
-from .dependencies import (
-    get_optional_user_id,
-    get_user_id,
-    requires_admin_user,
-    requires_user,
-)
-from .helpers import add_auth_responses_to_openapi
+from .depends import requires_admin_user, requires_user
+from .jwt_utils import parse_jwt_token
+from .middleware import APIKeyValidator, auth_middleware
 from .models import User
 
 __all__ = [
-    "verify_settings",
-    "get_user_id",
-    "requires_admin_user",
+    "parse_jwt_token",
     "requires_user",
-    "get_optional_user_id",
-    "add_auth_responses_to_openapi",
+    "requires_admin_user",
+    "APIKeyValidator",
+    "auth_middleware",
     "User",
 ]

autogpt_platform/autogpt_libs/autogpt_libs/auth/config.py

@@ -1,90 +1,11 @@
-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_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
-            )
+        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"
 
 
-_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()
+settings = Settings()

autogpt_platform/autogpt_libs/autogpt_libs/auth/config_test.py

@@ -1,306 +0,0 @@
-"""
-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

@@ -1,117 +0,0 @@
-"""
-FastAPI dependency functions for JWT-based authentication and authorization.
-
-These are the high-level dependency functions used in route definitions.
-"""
-
-import logging
-
-import fastapi
-from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
-
-from .jwt_utils import get_jwt_payload, verify_user
-from .models import User
-
-optional_bearer = HTTPBearer(auto_error=False)
-
-# Header name for admin impersonation
-IMPERSONATION_HEADER_NAME = "X-Act-As-User-Id"
-
-logger = logging.getLogger(__name__)
-
-
-def get_optional_user_id(
-    credentials: HTTPAuthorizationCredentials | None = fastapi.Security(
-        optional_bearer
-    ),
-) -> str | None:
-    """
-    Attempts to extract the user ID ("sub" claim) from a Bearer JWT if provided.
-
-    This dependency allows for both authenticated and anonymous access. If a valid bearer token is
-    supplied, it parses the JWT and extracts the user ID. If the token is missing or invalid, it returns None,
-    treating the request as anonymous.
-
-    Args:
-        credentials: Optional HTTPAuthorizationCredentials object from FastAPI Security dependency.
-
-    Returns:
-        The user ID (str) extracted from the JWT "sub" claim, or None if no valid token is present.
-    """
-    if not credentials:
-        return None
-
-    try:
-        # Parse JWT token to get user ID
-        from autogpt_libs.auth.jwt_utils import parse_jwt_token
-
-        payload = parse_jwt_token(credentials.credentials)
-        return payload.get("sub")
-    except Exception as e:
-        logger.debug(f"Auth token validation failed (anonymous access): {e}")
-        return None
-
-
-async 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)
-
-
-async 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)
-
-
-async def get_user_id(
-    request: fastapi.Request, jwt_payload: dict = fastapi.Security(get_jwt_payload)
-) -> str:
-    """
-    FastAPI dependency that returns the ID of the authenticated user.
-
-    Supports admin impersonation via X-Act-As-User-Id header:
-    - If the header is present and user is admin, returns the impersonated user ID
-    - Otherwise returns the authenticated user's own ID
-    - Logs all impersonation actions for audit trail
-
-    Raises:
-        HTTPException: 401 for authentication failures or missing user ID
-        HTTPException: 403 if non-admin tries to use impersonation
-    """
-    # Get the authenticated user's ID from JWT
-    user_id = jwt_payload.get("sub")
-    if not user_id:
-        raise fastapi.HTTPException(
-            status_code=401, detail="User ID not found in token"
-        )
-
-    # Check for admin impersonation header
-    impersonate_header = request.headers.get(IMPERSONATION_HEADER_NAME, "").strip()
-    if impersonate_header:
-        # Verify the authenticated user is an admin
-        authenticated_user = verify_user(jwt_payload, admin_only=False)
-        if authenticated_user.role != "admin":
-            raise fastapi.HTTPException(
-                status_code=403, detail="Only admin users can impersonate other users"
-            )
-
-        # Log the impersonation for audit trail
-        logger.info(
-            f"Admin impersonation: {authenticated_user.user_id} ({authenticated_user.email}) "
-            f"acting as user {impersonate_header} for requesting {request.method} {request.url}"
-        )
-
-        return impersonate_header
-
-    return user_id

autogpt_platform/autogpt_libs/autogpt_libs/auth/dependencies_test.py

@@ -1,554 +0,0 @@
-"""
-Comprehensive integration tests for authentication dependencies.
-Tests the full authentication flow from HTTP requests to user validation.
-"""
-
-import os
-from unittest.mock import Mock
-
-import pytest
-from fastapi import FastAPI, HTTPException, Request, 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)
-
-    @pytest.mark.asyncio
-    async 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 = await requires_user(jwt_payload)
-        assert isinstance(user, User)
-        assert user.user_id == "user-123"
-        assert user.role == "user"
-
-    @pytest.mark.asyncio
-    async 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 = await requires_user(jwt_payload)
-        assert user.user_id == "admin-456"
-        assert user.role == "admin"
-
-    @pytest.mark.asyncio
-    async 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:
-            await requires_user(jwt_payload)
-        assert exc_info.value.status_code == 401
-        assert "User ID not found" in exc_info.value.detail
-
-    @pytest.mark.asyncio
-    async 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:
-            await requires_user(jwt_payload)
-        assert exc_info.value.status_code == 401
-
-    @pytest.mark.asyncio
-    async 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 = await requires_admin_user(jwt_payload)
-        assert user.user_id == "admin-789"
-        assert user.role == "admin"
-
-    @pytest.mark.asyncio
-    async 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:
-            await requires_admin_user(jwt_payload)
-        assert exc_info.value.status_code == 403
-        assert "Admin access required" in exc_info.value.detail
-
-    @pytest.mark.asyncio
-    async 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):
-            await requires_admin_user(jwt_payload)
-
-    @pytest.mark.asyncio
-    async def test_get_user_id_with_valid_payload(self, mocker: MockerFixture):
-        """Test get_user_id extracts user ID correctly."""
-        request = Mock(spec=Request)
-        request.headers = {}
-        jwt_payload = {"sub": "user-id-xyz", "role": "user"}
-
-        mocker.patch(
-            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
-        )
-        user_id = await get_user_id(request, jwt_payload)
-        assert user_id == "user-id-xyz"
-
-    @pytest.mark.asyncio
-    async def test_get_user_id_missing_sub(self):
-        """Test get_user_id with missing user ID."""
-        request = Mock(spec=Request)
-        request.headers = {}
-        jwt_payload = {"role": "user"}
-
-        with pytest.raises(HTTPException) as exc_info:
-            await get_user_id(request, jwt_payload)
-        assert exc_info.value.status_code == 401
-        assert "User ID not found" in exc_info.value.detail
-
-    @pytest.mark.asyncio
-    async def test_get_user_id_none_sub(self):
-        """Test get_user_id with None user ID."""
-        request = Mock(spec=Request)
-        request.headers = {}
-        jwt_payload = {"sub": None, "role": "user"}
-
-        with pytest.raises(HTTPException) as exc_info:
-            await get_user_id(request, 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
-
-    @pytest.mark.asyncio
-    async 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
-
-    @pytest.mark.asyncio
-    async 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"
-
-    @pytest.mark.asyncio
-    async 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."""
-
-    @pytest.mark.asyncio
-    async 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 = await requires_user(complex_payload)
-        assert user.user_id == "user-123"
-        assert user.email == "test@example.com"
-
-        admin = await requires_admin_user(complex_payload)
-        assert admin.role == "admin"
-
-    @pytest.mark.asyncio
-    async 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 = await requires_user(unicode_payload)
-        assert "😀" in user.user_id
-        assert user.email == "测试@example.com"
-
-    @pytest.mark.asyncio
-    async 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 = await requires_user(null_payload)
-        assert user.user_id == "user-123"
-        assert user.email is None
-
-    @pytest.mark.asyncio
-    async 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 = await requires_user(payload1)
-        user2 = await 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),
-        ],
-    )
-    @pytest.mark.asyncio
-    async 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
-
-    @pytest.mark.asyncio
-    async 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"
-
-
-class TestAdminImpersonation:
-    """Test suite for admin user impersonation functionality."""
-
-    @pytest.mark.asyncio
-    async def test_admin_impersonation_success(self, mocker: MockerFixture):
-        """Test admin successfully impersonating another user."""
-        request = Mock(spec=Request)
-        request.headers = {"X-Act-As-User-Id": "target-user-123"}
-        jwt_payload = {
-            "sub": "admin-456",
-            "role": "admin",
-            "email": "admin@example.com",
-        }
-
-        # Mock verify_user to return admin user data
-        mock_verify_user = mocker.patch("autogpt_libs.auth.dependencies.verify_user")
-        mock_verify_user.return_value = Mock(
-            user_id="admin-456", email="admin@example.com", role="admin"
-        )
-
-        # Mock logger to verify audit logging
-        mock_logger = mocker.patch("autogpt_libs.auth.dependencies.logger")
-
-        mocker.patch(
-            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
-        )
-
-        user_id = await get_user_id(request, jwt_payload)
-
-        # Should return the impersonated user ID
-        assert user_id == "target-user-123"
-
-        # Should log the impersonation attempt
-        mock_logger.info.assert_called_once()
-        log_call = mock_logger.info.call_args[0][0]
-        assert "Admin impersonation:" in log_call
-        assert "admin@example.com" in log_call
-        assert "target-user-123" in log_call
-
-    @pytest.mark.asyncio
-    async def test_non_admin_impersonation_attempt(self, mocker: MockerFixture):
-        """Test non-admin user attempting impersonation returns 403."""
-        request = Mock(spec=Request)
-        request.headers = {"X-Act-As-User-Id": "target-user-123"}
-        jwt_payload = {
-            "sub": "regular-user",
-            "role": "user",
-            "email": "user@example.com",
-        }
-
-        # Mock verify_user to return regular user data
-        mock_verify_user = mocker.patch("autogpt_libs.auth.dependencies.verify_user")
-        mock_verify_user.return_value = Mock(
-            user_id="regular-user", email="user@example.com", role="user"
-        )
-
-        mocker.patch(
-            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
-        )
-
-        with pytest.raises(HTTPException) as exc_info:
-            await get_user_id(request, jwt_payload)
-
-        assert exc_info.value.status_code == 403
-        assert "Only admin users can impersonate other users" in exc_info.value.detail
-
-    @pytest.mark.asyncio
-    async def test_impersonation_empty_header(self, mocker: MockerFixture):
-        """Test impersonation with empty header falls back to regular user ID."""
-        request = Mock(spec=Request)
-        request.headers = {"X-Act-As-User-Id": ""}
-        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_id = await get_user_id(request, jwt_payload)
-
-        # Should fall back to the admin's own user ID
-        assert user_id == "admin-456"
-
-    @pytest.mark.asyncio
-    async def test_impersonation_missing_header(self, mocker: MockerFixture):
-        """Test normal behavior when impersonation header is missing."""
-        request = Mock(spec=Request)
-        request.headers = {}  # No impersonation header
-        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_id = await get_user_id(request, jwt_payload)
-
-        # Should return the admin's own user ID
-        assert user_id == "admin-456"
-
-    @pytest.mark.asyncio
-    async def test_impersonation_audit_logging_details(self, mocker: MockerFixture):
-        """Test that impersonation audit logging includes all required details."""
-        request = Mock(spec=Request)
-        request.headers = {"X-Act-As-User-Id": "victim-user-789"}
-        jwt_payload = {
-            "sub": "admin-999",
-            "role": "admin",
-            "email": "superadmin@company.com",
-        }
-
-        # Mock verify_user to return admin user data
-        mock_verify_user = mocker.patch("autogpt_libs.auth.dependencies.verify_user")
-        mock_verify_user.return_value = Mock(
-            user_id="admin-999", email="superadmin@company.com", role="admin"
-        )
-
-        # Mock logger to capture audit trail
-        mock_logger = mocker.patch("autogpt_libs.auth.dependencies.logger")
-
-        mocker.patch(
-            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
-        )
-
-        user_id = await get_user_id(request, jwt_payload)
-
-        # Verify all audit details are logged
-        assert user_id == "victim-user-789"
-        mock_logger.info.assert_called_once()
-
-        log_message = mock_logger.info.call_args[0][0]
-        assert "Admin impersonation:" in log_message
-        assert "superadmin@company.com" in log_message
-        assert "victim-user-789" in log_message
-
-    @pytest.mark.asyncio
-    async def test_impersonation_header_case_sensitivity(self, mocker: MockerFixture):
-        """Test that impersonation header is case-sensitive."""
-        request = Mock(spec=Request)
-        # Use wrong case - should not trigger impersonation
-        request.headers = {"x-act-as-user-id": "target-user-123"}
-        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_id = await get_user_id(request, jwt_payload)
-
-        # Should fall back to admin's own ID (header case mismatch)
-        assert user_id == "admin-456"
-
-    @pytest.mark.asyncio
-    async def test_impersonation_with_whitespace_header(self, mocker: MockerFixture):
-        """Test impersonation with whitespace in header value."""
-        request = Mock(spec=Request)
-        request.headers = {"X-Act-As-User-Id": "  target-user-123  "}
-        jwt_payload = {
-            "sub": "admin-456",
-            "role": "admin",
-            "email": "admin@example.com",
-        }
-
-        # Mock verify_user to return admin user data
-        mock_verify_user = mocker.patch("autogpt_libs.auth.dependencies.verify_user")
-        mock_verify_user.return_value = Mock(
-            user_id="admin-456", email="admin@example.com", role="admin"
-        )
-
-        # Mock logger
-        mock_logger = mocker.patch("autogpt_libs.auth.dependencies.logger")
-
-        mocker.patch(
-            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
-        )
-
-        user_id = await get_user_id(request, jwt_payload)
-
-        # Should strip whitespace and impersonate successfully
-        assert user_id == "target-user-123"
-        mock_logger.info.assert_called_once()

autogpt_platform/autogpt_libs/autogpt_libs/auth/depends.py

@@ -0,0 +1,46 @@
+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

@@ -0,0 +1,68 @@
+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

@@ -1,68 +0,0 @@
-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

@@ -1,435 +0,0 @@
-"""
-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

@@ -1,48 +1,11 @@
-import logging
-from typing import Any
+from typing import Any, Dict
 
 import jwt
-from fastapi import HTTPException, Security
-from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
 
-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
-)
+from .config import settings
 
 
-async 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]:
+def parse_jwt_token(token: str) -> Dict[str, Any]:
     """
     Parse and validate a JWT token.
 
@@ -50,11 +13,10 @@ 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_VERIFY_KEY,
+            settings.JWT_SECRET_KEY,
             algorithms=[settings.JWT_ALGORITHM],
             audience="authenticated",
         )
@@ -63,18 +25,3 @@ 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

@@ -1,308 +0,0 @@
-"""
-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)
-
-
-async 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 = await jwt_utils.get_jwt_payload(credentials)
-    assert result["sub"] == "test-user-id"
-    assert result["role"] == "user"
-
-
-async def test_get_jwt_payload_no_credentials():
-    """Test JWT payload when no credentials provided."""
-    with pytest.raises(HTTPException) as exc_info:
-        await jwt_utils.get_jwt_payload(None)
-    assert exc_info.value.status_code == 401
-    assert "Authorization header is missing" in exc_info.value.detail
-
-
-async 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:
-        await 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

@@ -0,0 +1,140 @@
+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/logging/config.py

@@ -4,7 +4,6 @@ import logging
 import os
 import socket
 import sys
-from logging.handlers import RotatingFileHandler
 from pathlib import Path
 
 from pydantic import Field, field_validator
@@ -94,36 +93,42 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
     config = LoggingConfig()
     log_handlers: list[logging.Handler] = []
 
-    structured_logging = config.enable_cloud_logging or force_cloud_logging
-
     # Console output handlers
-    if not structured_logging:
-        stdout = logging.StreamHandler(stream=sys.stdout)
-        stdout.setLevel(config.level)
-        stdout.addFilter(BelowLevelFilter(logging.WARNING))
-        if config.level == logging.DEBUG:
-            stdout.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
-        else:
-            stdout.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
+    stdout = logging.StreamHandler(stream=sys.stdout)
+    stdout.setLevel(config.level)
+    stdout.addFilter(BelowLevelFilter(logging.WARNING))
+    if config.level == logging.DEBUG:
+        stdout.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
+    else:
+        stdout.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
 
-        stderr = logging.StreamHandler()
-        stderr.setLevel(logging.WARNING)
-        if config.level == logging.DEBUG:
-            stderr.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
-        else:
-            stderr.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
+    stderr = logging.StreamHandler()
+    stderr.setLevel(logging.WARNING)
+    if config.level == logging.DEBUG:
+        stderr.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
+    else:
+        stderr.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
 
-        log_handlers += [stdout, stderr]
+    log_handlers += [stdout, stderr]
 
     # Cloud logging setup
-    else:
-        # Use Google Cloud Structured Log Handler. Log entries are printed to stdout
-        # in a JSON format which is automatically picked up by Google Cloud Logging.
-        from google.cloud.logging.handlers import StructuredLogHandler
+    if config.enable_cloud_logging or force_cloud_logging:
+        import google.cloud.logging
+        from google.cloud.logging.handlers import CloudLoggingHandler
+        from google.cloud.logging_v2.handlers.transports import (
+            BackgroundThreadTransport,
+        )
 
-        structured_log_handler = StructuredLogHandler(stream=sys.stdout)
-        structured_log_handler.setLevel(config.level)
-        log_handlers.append(structured_log_handler)
+        client = google.cloud.logging.Client()
+        # Use BackgroundThreadTransport to prevent blocking the main thread
+        # and deadlocks when gRPC calls to Google Cloud Logging hang
+        cloud_handler = CloudLoggingHandler(
+            client,
+            name="autogpt_logs",
+            transport=BackgroundThreadTransport,
+        )
+        cloud_handler.setLevel(config.level)
+        log_handlers.append(cloud_handler)
 
     # File logging setup
     if config.enable_file_logging:
@@ -134,13 +139,8 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
         print(f"Log directory: {config.log_dir}")
 
         # Activity log handler (INFO and above)
-        # Security fix: Use RotatingFileHandler with size limits to prevent disk exhaustion
-        activity_log_handler = RotatingFileHandler(
-            config.log_dir / LOG_FILE,
-            mode="a",
-            encoding="utf-8",
-            maxBytes=10 * 1024 * 1024,  # 10MB per file
-            backupCount=3,  # Keep 3 backup files (40MB total)
+        activity_log_handler = logging.FileHandler(
+            config.log_dir / LOG_FILE, "a", "utf-8"
         )
         activity_log_handler.setLevel(config.level)
         activity_log_handler.setFormatter(
@@ -150,13 +150,8 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
 
         if config.level == logging.DEBUG:
             # Debug log handler (all levels)
-            # Security fix: Use RotatingFileHandler with size limits
-            debug_log_handler = RotatingFileHandler(
-                config.log_dir / DEBUG_LOG_FILE,
-                mode="a",
-                encoding="utf-8",
-                maxBytes=10 * 1024 * 1024,  # 10MB per file
-                backupCount=3,  # Keep 3 backup files (40MB total)
+            debug_log_handler = logging.FileHandler(
+                config.log_dir / DEBUG_LOG_FILE, "a", "utf-8"
             )
             debug_log_handler.setLevel(logging.DEBUG)
             debug_log_handler.setFormatter(
@@ -165,13 +160,8 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
             log_handlers.append(debug_log_handler)
 
         # Error log handler (ERROR and above)
-        # Security fix: Use RotatingFileHandler with size limits
-        error_log_handler = RotatingFileHandler(
-            config.log_dir / ERROR_LOG_FILE,
-            mode="a",
-            encoding="utf-8",
-            maxBytes=10 * 1024 * 1024,  # 10MB per file
-            backupCount=3,  # Keep 3 backup files (40MB total)
+        error_log_handler = logging.FileHandler(
+            config.log_dir / ERROR_LOG_FILE, "a", "utf-8"
         )
         error_log_handler.setLevel(logging.ERROR)
         error_log_handler.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT, no_color=True))
@@ -179,13 +169,7 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
 
     # Configure the root logger
     logging.basicConfig(
-        format=(
-            "%(levelname)s  %(message)s"
-            if structured_logging
-            else (
-                DEBUG_LOG_FORMAT if config.level == logging.DEBUG else SIMPLE_LOG_FORMAT
-            )
-        ),
+        format=DEBUG_LOG_FORMAT if config.level == logging.DEBUG else SIMPLE_LOG_FORMAT,
         level=config.level,
         handlers=log_handlers,
     )

autogpt_platform/autogpt_libs/autogpt_libs/rate_limit/config.py

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

@@ -0,0 +1,266 @@
+import inspect
+import logging
+import threading
+import time
+from functools import wraps
+from typing import (
+    Awaitable,
+    Callable,
+    ParamSpec,
+    Protocol,
+    Tuple,
+    TypeVar,
+    cast,
+    overload,
+    runtime_checkable,
+)
+
+P = ParamSpec("P")
+R = TypeVar("R")
+
+logger = logging.getLogger(__name__)
+
+
+@overload
+def thread_cached(func: Callable[P, Awaitable[R]]) -> Callable[P, Awaitable[R]]:
+    pass
+
+
+@overload
+def thread_cached(func: Callable[P, R]) -> Callable[P, R]:
+    pass
+
+
+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)
+
+
+@runtime_checkable
+class AsyncCachedFunction(Protocol[P, R_co]):
+    """Protocol for async functions with cache management methods."""
+
+    def cache_clear(self) -> None:
+        """Clear all cached entries."""
+        return None
+
+    def cache_info(self) -> dict[str, int | None]:
+        """Get cache statistics."""
+        return {}
+
+    async 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]]:
+    """
+    TTL (Time To Live) cache decorator for async functions.
+
+    Similar to functools.lru_cache but works with async functions and includes optional TTL.
+
+    Args:
+        maxsize: Maximum number of cached entries
+        ttl_seconds: Time to live in seconds. If None, entries never expire (like lru_cache)
+
+    Returns:
+        Decorator function
+
+    Example:
+        # With TTL
+        @async_ttl_cache(maxsize=1000, ttl_seconds=300)
+        async def api_call(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:
+            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]] = {}
+
+        @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()
+
+            # 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)
+                        else:
+                            # Expired entry
+                            del cache_storage[key]
+                            logger.debug(
+                                f"Cache entry expired for {async_func.__name__}"
+                            )
+
+            # 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)
+
+            # Store in cache
+            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__}"
+                )
+
+            return result
+
+        # Add cache management methods (similar to functools.lru_cache)
+        def cache_clear() -> None:
+            cache_storage.clear()
+
+        def cache_info() -> dict[str, int | None]:
+            return {
+                "size": len(cache_storage),
+                "maxsize": maxsize,
+                "ttl_seconds": ttl_seconds,
+            }
+
+        # Attach methods to wrapper
+        setattr(wrapper, "cache_clear", cache_clear)
+        setattr(wrapper, "cache_info", cache_info)
+
+        return cast(AsyncCachedFunction[P, R], 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]]
+):
+    """
+    Process-level cache decorator for async functions (no TTL).
+
+    Similar to functools.lru_cache but works with async functions.
+    This is a convenience wrapper around async_ttl_cache with ttl_seconds=None.
+
+    Args:
+        func: The async function to cache (when used without parentheses)
+        maxsize: Maximum number of cached entries
+
+    Returns:
+        Decorated function or decorator
+
+    Example:
+        # Without parentheses (uses default maxsize=128)
+        @async_cache
+        async def get_data(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
+            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)
+    else:
+        # Called without parentheses @async_cache
+        decorator = async_ttl_cache(maxsize=maxsize, ttl_seconds=None)
+        return decorator(func)

autogpt_platform/autogpt_libs/autogpt_libs/utils/cache_test.py

@@ -0,0 +1,705 @@
+"""Tests for the @thread_cached decorator.
+
+This module tests the thread-local caching functionality including:
+- Basic caching for sync and async functions
+- Thread isolation (each thread has its own cache)
+- Cache clearing functionality
+- Exception handling (exceptions are not cached)
+- Argument handling (positional vs keyword arguments)
+"""
+
+import asyncio
+import threading
+import time
+from concurrent.futures import ThreadPoolExecutor
+from unittest.mock import Mock
+
+import pytest
+
+from autogpt_libs.utils.cache import (
+    async_cache,
+    async_ttl_cache,
+    clear_thread_cache,
+    thread_cached,
+)
+
+
+class TestThreadCached:
+    def test_sync_function_caching(self):
+        call_count = 0
+
+        @thread_cached
+        def expensive_function(x: int, y: int = 0) -> int:
+            nonlocal call_count
+            call_count += 1
+            return x + y
+
+        assert expensive_function(1, 2) == 3
+        assert call_count == 1
+
+        assert expensive_function(1, 2) == 3
+        assert call_count == 1
+
+        assert expensive_function(1, y=2) == 3
+        assert call_count == 2
+
+        assert expensive_function(2, 3) == 5
+        assert call_count == 3
+
+        assert expensive_function(1) == 1
+        assert call_count == 4
+
+    @pytest.mark.asyncio
+    async def test_async_function_caching(self):
+        call_count = 0
+
+        @thread_cached
+        async def expensive_async_function(x: int, y: int = 0) -> int:
+            nonlocal call_count
+            call_count += 1
+            await asyncio.sleep(0.01)
+            return x + y
+
+        assert await expensive_async_function(1, 2) == 3
+        assert call_count == 1
+
+        assert await expensive_async_function(1, 2) == 3
+        assert call_count == 1
+
+        assert await expensive_async_function(1, y=2) == 3
+        assert call_count == 2
+
+        assert await expensive_async_function(2, 3) == 5
+        assert call_count == 3
+
+    def test_thread_isolation(self):
+        call_count = 0
+        results = {}
+
+        @thread_cached
+        def thread_specific_function(x: int) -> str:
+            nonlocal call_count
+            call_count += 1
+            return f"{threading.current_thread().name}-{x}"
+
+        def worker(thread_id: int):
+            result1 = thread_specific_function(1)
+            result2 = thread_specific_function(1)
+            result3 = thread_specific_function(2)
+            results[thread_id] = (result1, result2, result3)
+
+        with ThreadPoolExecutor(max_workers=3) as executor:
+            futures = [executor.submit(worker, i) for i in range(3)]
+            for future in futures:
+                future.result()
+
+        assert call_count >= 2
+
+        for thread_id, (r1, r2, r3) in results.items():
+            assert r1 == r2
+            assert r1 != r3
+
+    @pytest.mark.asyncio
+    async def test_async_thread_isolation(self):
+        call_count = 0
+        results = {}
+
+        @thread_cached
+        async def async_thread_specific_function(x: int) -> str:
+            nonlocal call_count
+            call_count += 1
+            await asyncio.sleep(0.01)
+            return f"{threading.current_thread().name}-{x}"
+
+        async def async_worker(worker_id: int):
+            result1 = await async_thread_specific_function(1)
+            result2 = await async_thread_specific_function(1)
+            result3 = await async_thread_specific_function(2)
+            results[worker_id] = (result1, result2, result3)
+
+        tasks = [async_worker(i) for i in range(3)]
+        await asyncio.gather(*tasks)
+
+        for worker_id, (r1, r2, r3) in results.items():
+            assert r1 == r2
+            assert r1 != r3
+
+    def test_clear_cache_sync(self):
+        call_count = 0
+
+        @thread_cached
+        def clearable_function(x: int) -> int:
+            nonlocal call_count
+            call_count += 1
+            return x * 2
+
+        assert clearable_function(5) == 10
+        assert call_count == 1
+
+        assert clearable_function(5) == 10
+        assert call_count == 1
+
+        clear_thread_cache(clearable_function)
+
+        assert clearable_function(5) == 10
+        assert call_count == 2
+
+    @pytest.mark.asyncio
+    async def test_clear_cache_async(self):
+        call_count = 0
+
+        @thread_cached
+        async def clearable_async_function(x: int) -> int:
+            nonlocal call_count
+            call_count += 1
+            await asyncio.sleep(0.01)
+            return x * 2
+
+        assert await clearable_async_function(5) == 10
+        assert call_count == 1
+
+        assert await clearable_async_function(5) == 10
+        assert call_count == 1
+
+        clear_thread_cache(clearable_async_function)
+
+        assert await clearable_async_function(5) == 10
+        assert call_count == 2
+
+    def test_simple_arguments(self):
+        call_count = 0
+
+        @thread_cached
+        def simple_function(a: str, b: int, c: str = "default") -> str:
+            nonlocal call_count
+            call_count += 1
+            return f"{a}-{b}-{c}"
+
+        # First call with all positional args
+        result1 = simple_function("test", 42, "custom")
+        assert call_count == 1
+
+        # Same args, all positional - should hit cache
+        result2 = simple_function("test", 42, "custom")
+        assert call_count == 1
+        assert result1 == result2
+
+        # Same values but last arg as keyword - creates different cache key
+        result3 = simple_function("test", 42, c="custom")
+        assert call_count == 2
+        assert result1 == result3  # Same result, different cache entry
+
+        # Different value - new cache entry
+        result4 = simple_function("test", 43, "custom")
+        assert call_count == 3
+        assert result1 != result4
+
+    def test_positional_vs_keyword_args(self):
+        """Test that positional and keyword arguments create different cache entries."""
+        call_count = 0
+
+        @thread_cached
+        def func(a: int, b: int = 10) -> str:
+            nonlocal call_count
+            call_count += 1
+            return f"result-{a}-{b}"
+
+        # All positional
+        result1 = func(1, 2)
+        assert call_count == 1
+        assert result1 == "result-1-2"
+
+        # Same values, but second arg as keyword
+        result2 = func(1, b=2)
+        assert call_count == 2  # Different cache key!
+        assert result2 == "result-1-2"  # Same result
+
+        # Verify both are cached separately
+        func(1, 2)  # Uses first cache entry
+        assert call_count == 2
+
+        func(1, b=2)  # Uses second cache entry
+        assert call_count == 2
+
+    def test_exception_handling(self):
+        call_count = 0
+
+        @thread_cached
+        def failing_function(x: int) -> int:
+            nonlocal call_count
+            call_count += 1
+            if x < 0:
+                raise ValueError("Negative value")
+            return x * 2
+
+        assert failing_function(5) == 10
+        assert call_count == 1
+
+        with pytest.raises(ValueError):
+            failing_function(-1)
+        assert call_count == 2
+
+        with pytest.raises(ValueError):
+            failing_function(-1)
+        assert call_count == 3
+
+        assert failing_function(5) == 10
+        assert call_count == 3
+
+    @pytest.mark.asyncio
+    async def test_async_exception_handling(self):
+        call_count = 0
+
+        @thread_cached
+        async def async_failing_function(x: int) -> int:
+            nonlocal call_count
+            call_count += 1
+            await asyncio.sleep(0.01)
+            if x < 0:
+                raise ValueError("Negative value")
+            return x * 2
+
+        assert await async_failing_function(5) == 10
+        assert call_count == 1
+
+        with pytest.raises(ValueError):
+            await async_failing_function(-1)
+        assert call_count == 2
+
+        with pytest.raises(ValueError):
+            await async_failing_function(-1)
+        assert call_count == 3
+
+    def test_sync_caching_performance(self):
+        @thread_cached
+        def slow_function(x: int) -> int:
+            print(f"slow_function called with x={x}")
+            time.sleep(0.1)
+            return x * 2
+
+        start = time.time()
+        result1 = slow_function(5)
+        first_call_time = time.time() - start
+        print(f"First call took {first_call_time:.4f} seconds")
+
+        start = time.time()
+        result2 = slow_function(5)
+        second_call_time = time.time() - start
+        print(f"Second call took {second_call_time:.4f} seconds")
+
+        assert result1 == result2 == 10
+        assert first_call_time > 0.09
+        assert second_call_time < 0.01
+
+    @pytest.mark.asyncio
+    async def test_async_caching_performance(self):
+        @thread_cached
+        async def slow_async_function(x: int) -> int:
+            print(f"slow_async_function called with x={x}")
+            await asyncio.sleep(0.1)
+            return x * 2
+
+        start = time.time()
+        result1 = await slow_async_function(5)
+        first_call_time = time.time() - start
+        print(f"First async call took {first_call_time:.4f} seconds")
+
+        start = time.time()
+        result2 = await slow_async_function(5)
+        second_call_time = time.time() - start
+        print(f"Second async call took {second_call_time:.4f} seconds")
+
+        assert result1 == result2 == 10
+        assert first_call_time > 0.09
+        assert second_call_time < 0.01
+
+    def test_with_mock_objects(self):
+        mock = Mock(return_value=42)
+
+        @thread_cached
+        def function_using_mock(x: int) -> int:
+            return mock(x)
+
+        assert function_using_mock(1) == 42
+        assert mock.call_count == 1
+
+        assert function_using_mock(1) == 42
+        assert mock.call_count == 1
+
+        assert function_using_mock(2) == 42
+        assert mock.call_count == 2
+
+
+class TestAsyncTTLCache:
+    """Tests for the @async_ttl_cache decorator."""
+
+    @pytest.mark.asyncio
+    async def test_basic_caching(self):
+        """Test basic caching functionality."""
+        call_count = 0
+
+        @async_ttl_cache(maxsize=10, ttl_seconds=60)
+        async def cached_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)
+        assert result1 == 3
+        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
+
+        # Different args - should call function again
+        result3 = await cached_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."""
+        call_count = 0
+
+        @async_ttl_cache(maxsize=10, ttl_seconds=1)  # Short TTL
+        async def short_lived_cache(x: int) -> int:
+            nonlocal call_count
+            call_count += 1
+            return x * 2
+
+        # First call
+        result1 = await short_lived_cache(5)
+        assert result1 == 10
+        assert call_count == 1
+
+        # Second call immediately - should use cache
+        result2 = await short_lived_cache(5)
+        assert result2 == 10
+        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
+        assert call_count == 2
+
+    @pytest.mark.asyncio
+    async 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:
+            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
+
+        # Add an entry
+        await info_test_function(1)
+        info = info_test_function.cache_info()
+        assert info["size"] == 1
+
+    @pytest.mark.asyncio
+    async 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:
+            nonlocal call_count
+            call_count += 1
+            return x * 4
+
+        # First call
+        result1 = await clearable_function(2)
+        assert result1 == 8
+        assert call_count == 1
+
+        # Second call - should use cache
+        result2 = await clearable_function(2)
+        assert result2 == 8
+        assert call_count == 1
+
+        # Clear cache
+        clearable_function.cache_clear()
+
+        # Third call after clear - should call function again
+        result3 = await 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."""
+        call_count = 0
+
+        @async_ttl_cache(maxsize=3, ttl_seconds=60)
+        async def size_limited_function(x: int) -> int:
+            nonlocal call_count
+            call_count += 1
+            return x**2
+
+        # 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)
+        assert result1 == 10
+        assert call_count == 1
+
+        # Same successful call - should use cache
+        result2 = await exception_function(5)
+        assert result2 == 10
+        assert call_count == 1
+
+        # Exception call - should not be cached
+        with pytest.raises(ValueError):
+            await exception_function(-1)
+        assert call_count == 2
+
+        # Same exception call - should call again (not cached)
+        with pytest.raises(ValueError):
+            await exception_function(-1)
+        assert call_count == 3
+
+    @pytest.mark.asyncio
+    async def test_concurrent_calls(self):
+        """Test caching behavior with concurrent calls."""
+        call_count = 0
+
+        @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)."""
+
+    @pytest.mark.asyncio
+    async def test_basic_caching_no_ttl(self):
+        """Test basic caching functionality without TTL."""
+        call_count = 0
+
+        @async_cache(maxsize=10)
+        async def cached_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)
+        assert result1 == 3
+        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
+        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
+
+        @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
+
+        @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
+
+        # First calls
+        await ttl_function(5)
+        await no_ttl_function(5)
+        assert ttl_call_count == 1
+        assert no_ttl_call_count == 1
+
+        # 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

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 = ["dev"]
+groups = ["main"]
 markers = "python_version < \"3.11\""
 files = [
     {file = "backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5"},
@@ -85,87 +85,6 @@ files = [
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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"
@@ -480,7 +235,7 @@ version = "1.3.0"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["main"]
 markers = "python_version < \"3.11\""
 files = [
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@@ -955,7 +710,7 @@ version = "2.1.0"
 description = "brain-dead simple config-ini parsing"
 optional = false
 python-versions = ">=3.8"
-groups = ["dev"]
+groups = ["main"]
 files = [
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@@ -1002,18 +757,6 @@ 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 = [
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-]
-
 [[package]]
 name = "opentelemetry-api"
 version = "1.35.0"
@@ -1036,7 +779,7 @@ version = "25.0"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["main"]
 files = [
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@@ -1048,7 +791,7 @@ version = "1.6.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
 python-versions = ">=3.9"
-groups = ["dev"]
+groups = ["main"]
 files = [
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@@ -1140,19 +883,6 @@ 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 = [
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-
 [[package]]
 name = "pydantic"
 version = "2.11.7"
@@ -1317,7 +1047,7 @@ version = "2.19.2"
 description = "Pygments is a syntax highlighting package written in Python."
 optional = false
 python-versions = ">=3.8"
-groups = ["dev"]
+groups = ["main"]
 files = [
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@@ -1338,9 +1068,6 @@ files = [
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 ]
 
-[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"]
@@ -1359,34 +1086,13 @@ files = [
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 ]
 
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-name = "pyright"
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-description = "Command line wrapper for pyright"
-optional = false
-python-versions = ">=3.7"
-groups = ["dev"]
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-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 = ["dev"]
+groups = ["main"]
 files = [
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@@ -1410,7 +1116,7 @@ version = "1.1.0"
 description = "Pytest support for asyncio"
 optional = false
 python-versions = ">=3.9"
-groups = ["dev"]
+groups = ["main"]
 files = [
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@@ -1424,33 +1130,13 @@ 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 = [
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-
-[package.dependencies]
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-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 = ["dev"]
+groups = ["main"]
 files = [
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@@ -1567,31 +1253,30 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.12.11"
+version = "0.12.3"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
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+    {file = "ruff-0.12.3-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:883d844967bffff5ab28bba1a4d246c1a1b2933f48cb9840f3fdc5111c603b07"},
+    {file = "ruff-0.12.3-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:2120d3aa855ff385e0e562fdee14d564c9675edbe41625c87eeab744a7830d12"},
+    {file = "ruff-0.12.3-py3-none-musllinux_1_2_i686.whl", hash = "sha256:6b16647cbb470eaf4750d27dddc6ebf7758b918887b56d39e9c22cce2049082b"},
+    {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"},
 ]
 
 [[package]]
@@ -1725,7 +1410,7 @@ version = "2.2.1"
 description = "A lil' TOML parser"
 optional = false
 python-versions = ">=3.8"
-groups = ["dev"]
+groups = ["main"]
 markers = "python_version < \"3.11\""
 files = [
     {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
@@ -1768,7 +1453,7 @@ version = "4.14.1"
 description = "Backported and Experimental Type Hints for Python 3.9+"
 optional = false
 python-versions = ">=3.9"
-groups = ["main", "dev"]
+groups = ["main"]
 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"},
@@ -1929,4 +1614,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "0c40b63c3c921846cf05ccfb4e685d4959854b29c2c302245f9832e20aac6954"
+content-hash = "f67db13e6f68b1d67a55eee908c1c560bfa44da8509f98f842889a7570a9830f"

autogpt_platform/autogpt_libs/pyproject.toml

@@ -9,25 +9,21 @@ 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 = { version = "^2.10.1", extras = ["crypto"] }
+pyjwt = "^2.10.1"
+pytest-asyncio = "^1.1.0"
+pytest-mock = "^3.14.1"
 redis = "^6.2.0"
 supabase = "^2.16.0"
 uvicorn = "^0.35.0"
 
 [tool.poetry.group.dev.dependencies]
-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"
+ruff = "^0.12.3"
 
 [build-system]
 requires = ["poetry-core"]

autogpt_platform/backend/.env.default

@@ -16,12 +16,13 @@ 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=
+REDIS_PASSWORD=password
 
 # RabbitMQ Credentials
 RABBITMQ_DEFAULT_USER=rabbitmq_user_default
@@ -30,7 +31,7 @@ RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
 # Supabase Authentication
 SUPABASE_URL=http://localhost:8000
 SUPABASE_SERVICE_ROLE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
-JWT_VERIFY_KEY=your-super-secret-jwt-token-with-at-least-32-characters-long
+SUPABASE_JWT_SECRET=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()
@@ -66,11 +67,6 @@ 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):
@@ -110,15 +106,6 @@ 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=
 
@@ -179,4 +166,4 @@ SMARTLEAD_API_KEY=
 ZEROBOUNCE_API_KEY=
 
 # Other Services
-AUTOMOD_API_KEY=
+AUTOMOD_API_KEY=

autogpt_platform/backend/.gitignore

@@ -9,12 +9,4 @@ secrets/*
 !secrets/.gitkeep
 
 *.ignore.*
-*.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/*
+*.ign.*

autogpt_platform/backend/Dockerfile

@@ -1,43 +1,31 @@
-FROM debian:13-slim AS builder
+FROM python:3.11.10-slim-bookworm AS builder
 
 # Set environment variables
-ENV PYTHONDONTWRITEBYTECODE=1
-ENV PYTHONUNBUFFERED=1
-ENV DEBIAN_FRONTEND=noninteractive
+ENV PYTHONDONTWRITEBYTECODE 1
+ENV PYTHONUNBUFFERED 1
 
 WORKDIR /app
 
 RUN echo 'Acquire::http::Pipeline-Depth 0;\nAcquire::http::No-Cache true;\nAcquire::BrokenProxy true;\n' > /etc/apt/apt.conf.d/99fixbadproxy
 
-# Install Node.js repository key and setup
+# Update package list and install build dependencies in a single layer
 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 \
-    nodejs \
-    && rm -rf /var/lib/apt/lists/*
+    postgresql-client
 
 ENV POETRY_HOME=/opt/poetry
 ENV POETRY_NO_INTERACTION=1
-ENV POETRY_VIRTUALENVS_CREATE=true
-ENV POETRY_VIRTUALENVS_IN_PROJECT=true
+ENV POETRY_VIRTUALENVS_CREATE=false
 ENV PATH=/opt/poetry/bin:$PATH
 
-RUN pip3 install poetry --break-system-packages
+# Upgrade pip and setuptools to fix security vulnerabilities
+RUN pip3 install --upgrade pip setuptools
+
+RUN pip3 install poetry
 
 # Copy and install dependencies
 COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
@@ -47,38 +35,29 @@ RUN poetry install --no-ansi --no-root
 
 # Generate Prisma client
 COPY autogpt_platform/backend/schema.prisma ./
-COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
 RUN poetry run prisma generate
 
-FROM debian:13-slim AS server_dependencies
+FROM python:3.11.10-slim-bookworm AS server_dependencies
 
 WORKDIR /app
 
 ENV POETRY_HOME=/opt/poetry \
     POETRY_NO_INTERACTION=1 \
-    POETRY_VIRTUALENVS_CREATE=true \
-    POETRY_VIRTUALENVS_IN_PROJECT=true \
-    DEBIAN_FRONTEND=noninteractive
+    POETRY_VIRTUALENVS_CREATE=false
 ENV PATH=/opt/poetry/bin:$PATH
 
-# 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/*
+# Upgrade pip and setuptools to fix security vulnerabilities
+RUN pip3 install --upgrade pip setuptools
 
 # Copy only necessary files from builder
 COPY --from=builder /app /app
-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 /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 /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
 
-ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
+
+ENV PATH="/app/.venv/bin:$PATH"
 
 RUN mkdir -p /app/autogpt_platform/autogpt_libs
 RUN mkdir -p /app/autogpt_platform/backend
@@ -93,7 +72,6 @@ FROM server_dependencies AS migrate
 
 # Migration stage only needs schema and migrations - much lighter than full backend
 COPY autogpt_platform/backend/schema.prisma /app/autogpt_platform/backend/
-COPY autogpt_platform/backend/backend/data/partial_types.py /app/autogpt_platform/backend/backend/data/partial_types.py
 COPY autogpt_platform/backend/migrations /app/autogpt_platform/backend/migrations
 
 FROM server_dependencies AS server

autogpt_platform/backend/TESTING.md

@@ -132,58 +132,17 @@ 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
-import fastapi
-import fastapi.testclient
-import pytest
-from backend.server.v2.myroute import router
+def override_auth_middleware():
+    return {"sub": "test-user-id"}
 
-app = fastapi.FastAPI()
-app.include_router(router)
-client = fastapi.testclient.TestClient(app)
+def override_get_user_id():
+    return "test-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()
+app.dependency_overrides[auth_middleware] = override_auth_middleware
+app.dependency_overrides[get_user_id] = override_get_user_id
 ```
 
-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
@@ -194,10 +153,10 @@ 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),
@@ -228,17 +187,6 @@ 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
@@ -254,18 +202,9 @@ 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
 
@@ -277,19 +216,16 @@ 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
@@ -298,4 +234,4 @@ 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

@@ -1,3 +1,4 @@
+import functools
 import importlib
 import logging
 import os
@@ -5,8 +6,6 @@ import re
 from pathlib import Path
 from typing import TYPE_CHECKING, TypeVar
 
-from backend.util.cache import cached
-
 logger = logging.getLogger(__name__)
 
 
@@ -16,7 +15,7 @@ if TYPE_CHECKING:
 T = TypeVar("T")
 
 
-@cached(ttl_seconds=3600)
+@functools.cache
 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

@@ -1,17 +1,18 @@
 import logging
 from typing import Any, Optional
 
+from pydantic import JsonValue
+
 from backend.data.block import (
     Block,
     BlockCategory,
     BlockInput,
     BlockOutput,
     BlockSchema,
-    BlockSchemaInput,
     BlockType,
     get_block,
 )
-from backend.data.execution import ExecutionStatus, NodesInputMasks
+from backend.data.execution import ExecutionStatus
 from backend.data.model import NodeExecutionStats, SchemaField
 from backend.util.json import validate_with_jsonschema
 from backend.util.retry import func_retry
@@ -20,19 +21,16 @@ _logger = logging.getLogger(__name__)
 
 
 class AgentExecutorBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         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[NodesInputMasks] = SchemaField(
+        nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = SchemaField(
             default=None, hidden=True
         )
 
@@ -54,7 +52,6 @@ class AgentExecutorBlock(Block):
             return validate_with_jsonschema(cls.get_input_schema(data), data)
 
     class Output(BlockSchema):
-        # Use BlockSchema to avoid automatic error field that could clash with graph outputs
         pass
 
     def __init__(self):
@@ -67,13 +64,7 @@ class AgentExecutorBlock(Block):
             categories={BlockCategory.AGENT},
         )
 
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        graph_exec_id: str,
-        **kwargs,
-    ) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
 
         from backend.executor import utils as execution_utils
 
@@ -83,8 +74,6 @@ class AgentExecutorBlock(Block):
             user_id=input_data.user_id,
             inputs=input_data.inputs,
             nodes_input_masks=input_data.nodes_input_masks,
-            parent_graph_exec_id=graph_exec_id,
-            is_sub_graph=True,  # AgentExecutorBlock executions are always sub-graphs
         )
 
         logger = execution_utils.LogMetadata(

autogpt_platform/backend/backend/blocks/ai_condition.py

@@ -1,219 +0,0 @@
-from typing import Any
-
-from backend.blocks.llm import (
-    TEST_CREDENTIALS,
-    TEST_CREDENTIALS_INPUT,
-    AIBlockBase,
-    AICredentials,
-    AICredentialsField,
-    LlmModel,
-    LLMResponse,
-    llm_call,
-)
-from backend.data.block import (
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
-from backend.data.model import APIKeyCredentials, NodeExecutionStats, SchemaField
-
-
-class AIConditionBlock(AIBlockBase):
-    """
-    An AI-powered condition block that uses natural language to evaluate conditions.
-
-    This block allows users to define conditions in plain English (e.g., "the input is an email address",
-    "the input is a city in the USA") and uses AI to determine if the input satisfies the condition.
-    It provides the same yes/no data pass-through functionality as the standard ConditionBlock.
-    """
-
-    class Input(BlockSchemaInput):
-        input_value: Any = SchemaField(
-            description="The input value to evaluate with the AI condition",
-            placeholder="Enter the value to be evaluated (text, number, or any data)",
-        )
-        condition: str = SchemaField(
-            description="A plaintext English description of the condition to evaluate",
-            placeholder="E.g., 'the input is the body of an email', 'the input is a City in the USA', 'the input is an error or a refusal'",
-        )
-        yes_value: Any = SchemaField(
-            description="(Optional) Value to output if the condition is true. If not provided, input_value will be used.",
-            placeholder="Leave empty to use input_value, or enter a specific value",
-            default=None,
-        )
-        no_value: Any = SchemaField(
-            description="(Optional) Value to output if the condition is false. If not provided, input_value will be used.",
-            placeholder="Leave empty to use input_value, or enter a specific value",
-            default=None,
-        )
-        model: LlmModel = SchemaField(
-            title="LLM Model",
-            default=LlmModel.GPT4O,
-            description="The language model to use for evaluating the condition.",
-            advanced=False,
-        )
-        credentials: AICredentials = AICredentialsField()
-
-    class Output(BlockSchemaOutput):
-        result: bool = SchemaField(
-            description="The result of the AI condition evaluation (True or False)"
-        )
-        yes_output: Any = SchemaField(
-            description="The output value if the condition is true"
-        )
-        no_output: Any = SchemaField(
-            description="The output value if the condition is false"
-        )
-        error: str = SchemaField(
-            description="Error message if the AI evaluation is uncertain or fails"
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="553ec5b8-6c45-4299-8d75-b394d05f72ff",
-            input_schema=AIConditionBlock.Input,
-            output_schema=AIConditionBlock.Output,
-            description="Uses AI to evaluate natural language conditions and provide conditional outputs",
-            categories={BlockCategory.AI, BlockCategory.LOGIC},
-            test_input={
-                "input_value": "john@example.com",
-                "condition": "the input is an email address",
-                "yes_value": "Valid email",
-                "no_value": "Not an email",
-                "model": LlmModel.GPT4O,
-                "credentials": TEST_CREDENTIALS_INPUT,
-            },
-            test_credentials=TEST_CREDENTIALS,
-            test_output=[
-                ("result", True),
-                ("yes_output", "Valid email"),
-            ],
-            test_mock={
-                "llm_call": lambda *args, **kwargs: LLMResponse(
-                    raw_response="",
-                    prompt=[],
-                    response="true",
-                    tool_calls=None,
-                    prompt_tokens=50,
-                    completion_tokens=10,
-                    reasoning=None,
-                )
-            },
-        )
-
-    async def llm_call(
-        self,
-        credentials: APIKeyCredentials,
-        llm_model: LlmModel,
-        prompt: list,
-        max_tokens: int,
-    ) -> LLMResponse:
-        """Wrapper method for llm_call to enable mocking in tests."""
-        return await llm_call(
-            credentials=credentials,
-            llm_model=llm_model,
-            prompt=prompt,
-            force_json_output=False,
-            max_tokens=max_tokens,
-        )
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        """
-        Evaluate the AI condition and return appropriate outputs.
-        """
-        # Prepare the yes and no values, using input_value as default
-        yes_value = (
-            input_data.yes_value
-            if input_data.yes_value is not None
-            else input_data.input_value
-        )
-        no_value = (
-            input_data.no_value
-            if input_data.no_value is not None
-            else input_data.input_value
-        )
-
-        # Convert input_value to string for AI evaluation
-        input_str = str(input_data.input_value)
-
-        # Create the prompt for AI evaluation
-        prompt = [
-            {
-                "role": "system",
-                "content": (
-                    "You are an AI assistant that evaluates conditions based on input data. "
-                    "You must respond with only 'true' or 'false' (lowercase) to indicate whether "
-                    "the given condition is met by the input value. Be accurate and consider the "
-                    "context and meaning of both the input and the condition."
-                ),
-            },
-            {
-                "role": "user",
-                "content": (
-                    f"Input value: {input_str}\n"
-                    f"Condition to evaluate: {input_data.condition}\n\n"
-                    f"Does the input value satisfy the condition? Respond with only 'true' or 'false'."
-                ),
-            },
-        ]
-
-        # Call the LLM
-        try:
-            response = await self.llm_call(
-                credentials=credentials,
-                llm_model=input_data.model,
-                prompt=prompt,
-                max_tokens=10,  # We only expect a true/false response
-            )
-
-            # Extract the boolean result from the response
-            response_text = response.response.strip().lower()
-            if response_text == "true":
-                result = True
-            elif response_text == "false":
-                result = False
-            else:
-                # If the response is not clear, try to interpret it using word boundaries
-                import re
-
-                # Use word boundaries to avoid false positives like 'untrue' or '10'
-                tokens = set(re.findall(r"\b(true|false|yes|no|1|0)\b", response_text))
-
-                if tokens == {"true"} or tokens == {"yes"} or tokens == {"1"}:
-                    result = True
-                elif tokens == {"false"} or tokens == {"no"} or tokens == {"0"}:
-                    result = False
-                else:
-                    # Unclear or conflicting response - default to False and yield error
-                    result = False
-                    yield "error", f"Unclear AI response: '{response.response}'"
-
-            # Update internal stats
-            self.merge_stats(
-                NodeExecutionStats(
-                    input_token_count=response.prompt_tokens,
-                    output_token_count=response.completion_tokens,
-                )
-            )
-            self.prompt = response.prompt
-
-        except Exception as e:
-            # In case of any error, default to False to be safe
-            result = False
-            # Log the error but don't fail the block execution
-            import logging
-
-            logger = logging.getLogger(__name__)
-            logger.error(f"AI condition evaluation failed: {str(e)}")
-            yield "error", f"AI evaluation failed: {str(e)}"
-
-        # Yield results
-        yield "result", result
-
-        if result:
-            yield "yes_output", yes_value
-        else:
-            yield "no_output", no_value

autogpt_platform/backend/backend/blocks/ai_image_customizer.py

@@ -1,159 +0,0 @@
-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,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
-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(BlockSchemaInput):
-        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(BlockSchemaOutput):
-        image_url: MediaFileType = SchemaField(description="URL of the generated image")
-
-    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_image_generator_block.py

@@ -5,7 +5,7 @@ from pydantic import SecretStr
 from replicate.client import Client as ReplicateClient
 from replicate.helpers import FileOutput
 
-from backend.data.block import Block, BlockCategory, BlockSchemaInput, BlockSchemaOutput
+from backend.data.block import Block, BlockCategory, BlockSchema
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -101,7 +101,7 @@ class ImageGenModel(str, Enum):
 
 
 class AIImageGeneratorBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REPLICATE], Literal["api_key"]
         ] = CredentialsField(
@@ -135,8 +135,9 @@ class AIImageGeneratorBlock(Block):
             title="Image Style",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         image_url: str = SchemaField(description="URL of the generated image")
+        error: str = SchemaField(description="Error message if generation failed")
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/ai_music_generator.py

@@ -6,13 +6,7 @@ from typing import Literal
 from pydantic import SecretStr
 from replicate.client import Client as ReplicateClient
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -60,7 +54,7 @@ class NormalizationStrategy(str, Enum):
 
 
 class AIMusicGeneratorBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REPLICATE], Literal["api_key"]
         ] = CredentialsField(
@@ -113,8 +107,9 @@ class AIMusicGeneratorBlock(Block):
             title="Normalization Strategy",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         result: str = SchemaField(description="URL of the generated audio file")
+        error: str = SchemaField(description="Error message if the model run failed")
 
     def __init__(self):
         super().__init__(
@@ -171,7 +166,7 @@ class AIMusicGeneratorBlock(Block):
                     output_format=input_data.output_format,
                     normalization_strategy=input_data.normalization_strategy,
                 )
-                if result and isinstance(result, str) and result.startswith("http"):
+                if result and result != "No output received":
                     yield "result", result
                     return
                 else:

autogpt_platform/backend/backend/blocks/ai_shortform_video_block.py

@@ -6,13 +6,7 @@ from typing import Literal
 
 from pydantic import SecretStr
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -154,7 +148,7 @@ logger = logging.getLogger(__name__)
 class AIShortformVideoCreatorBlock(Block):
     """Creates a short‑form text‑to‑video clip using stock or AI imagery."""
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REVID], Literal["api_key"]
         ] = CredentialsField(
@@ -193,8 +187,9 @@ class AIShortformVideoCreatorBlock(Block):
             placeholder=VisualMediaType.STOCK_VIDEOS,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         video_url: str = SchemaField(description="The URL of the created video")
+        error: str = SchemaField(description="Error message if the request failed")
 
     async def create_webhook(self) -> tuple[str, str]:
         """Create a new webhook URL for receiving notifications."""
@@ -341,7 +336,7 @@ class AIShortformVideoCreatorBlock(Block):
 class AIAdMakerVideoCreatorBlock(Block):
     """Generates a 30‑second vertical AI advert using optional user‑supplied imagery."""
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REVID], Literal["api_key"]
         ] = CredentialsField(
@@ -369,8 +364,9 @@ class AIAdMakerVideoCreatorBlock(Block):
             description="Restrict visuals to supplied images only.", default=True
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         video_url: str = SchemaField(description="URL of the finished advert")
+        error: str = SchemaField(description="Error message on failure")
 
     async def create_webhook(self) -> tuple[str, str]:
         """Create a new webhook URL for receiving notifications."""
@@ -528,7 +524,7 @@ class AIAdMakerVideoCreatorBlock(Block):
 class AIScreenshotToVideoAdBlock(Block):
     """Creates an advert where the supplied screenshot is narrated by an AI avatar."""
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REVID], Literal["api_key"]
         ] = CredentialsField(description="Revid.ai API key")
@@ -546,8 +542,9 @@ class AIScreenshotToVideoAdBlock(Block):
             default=AudioTrack.DONT_STOP_ME_ABSTRACT_FUTURE_BASS
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         video_url: str = SchemaField(description="Rendered video URL")
+        error: str = SchemaField(description="Error, if encountered")
 
     async def create_webhook(self) -> tuple[str, str]:
         """Create a new webhook URL for receiving notifications."""

autogpt_platform/backend/backend/blocks/airtable/_api.py

@@ -661,167 +661,6 @@ 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,
@@ -1410,26 +1249,3 @@ 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

@@ -9,22 +9,21 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
+    BlockSchema,
     CredentialsMetaInput,
     SchemaField,
 )
 
-from ._api import create_base, get_base_tables, list_bases
+from ._api import create_base, list_bases
 from ._config import airtable
 
 
 class AirtableCreateBaseBlock(Block):
     """
-    Creates a new base in an Airtable workspace, or returns existing base if one with the same name exists.
+    Creates a new base in an Airtable workspace.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -32,10 +31,6 @@ 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=[
@@ -54,19 +49,15 @@ class AirtableCreateBaseBlock(Block):
             ],
         )
 
-    class Output(BlockSchemaOutput):
-        base_id: str = SchemaField(description="The ID of the created or found base")
+    class Output(BlockSchema):
+        base_id: str = SchemaField(description="The ID of the created 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 or find a base in Airtable",
+            description="Create a new base in Airtable",
             categories={BlockCategory.DATA},
             input_schema=self.Input,
             output_schema=self.Output,
@@ -75,31 +66,6 @@ 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,
@@ -108,7 +74,6 @@ 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
@@ -119,7 +84,7 @@ class AirtableListBasesBlock(Block):
     Lists all bases in an Airtable workspace that the user has access to.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -130,7 +95,7 @@ class AirtableListBasesBlock(Block):
             description="Pagination offset from previous request", default=""
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         bases: list[dict] = SchemaField(description="Array of base objects")
         offset: Optional[str] = SchemaField(
             description="Offset for next page (null if no more bases)", default=None

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

@@ -2,15 +2,14 @@
 Airtable record operation blocks.
 """
 
-from typing import Optional, cast
+from typing import Optional
 
 from backend.sdk import (
     APIKeyCredentials,
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
+    BlockSchema,
     CredentialsMetaInput,
     SchemaField,
 )
@@ -19,9 +18,7 @@ from ._api import (
     create_record,
     delete_multiple_records,
     get_record,
-    get_table_schema,
     list_records,
-    normalize_records,
     update_multiple_records,
 )
 from ._config import airtable
@@ -32,7 +29,7 @@ class AirtableListRecordsBlock(Block):
     Lists records from an Airtable table with optional filtering, sorting, and pagination.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -57,24 +54,12 @@ 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(BlockSchemaOutput):
+    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__(
@@ -88,7 +73,6 @@ class AirtableListRecordsBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-
         data = await list_records(
             credentials,
             input_data.base_id,
@@ -104,33 +88,8 @@ class AirtableListRecordsBlock(Block):
             fields=input_data.return_fields if input_data.return_fields else 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)
+        yield "records", data.get("records", [])
+        yield "offset", data.get("offset", None)
 
 
 class AirtableGetRecordBlock(Block):
@@ -138,30 +97,18 @@ class AirtableGetRecordBlock(Block):
     Retrieves a single record from an Airtable table by its ID.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
         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(BlockSchemaOutput):
+    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__(
@@ -175,7 +122,6 @@ class AirtableGetRecordBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-
         record = await get_record(
             credentials,
             input_data.base_id,
@@ -183,34 +129,9 @@ class AirtableGetRecordBlock(Block):
             input_data.record_id,
         )
 
-        # 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)
+        yield "id", record.get("id", None)
+        yield "fields", record.get("fields", None)
+        yield "created_time", record.get("createdTime", None)
 
 
 class AirtableCreateRecordsBlock(Block):
@@ -218,7 +139,7 @@ class AirtableCreateRecordsBlock(Block):
     Creates one or more records in an Airtable table.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -227,10 +148,6 @@ 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,
@@ -240,7 +157,7 @@ class AirtableCreateRecordsBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         records: list[dict] = SchemaField(description="Array of created record objects")
         details: dict = SchemaField(description="Details of the created records")
 
@@ -256,7 +173,7 @@ 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,
@@ -265,22 +182,8 @@ 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", []))
 
-        # 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
+        yield "records", data.get("records", [])
         details = data.get("details", None)
         if details:
             yield "details", details
@@ -291,7 +194,7 @@ class AirtableUpdateRecordsBlock(Block):
     Updates one or more existing records in an Airtable table.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -307,7 +210,7 @@ class AirtableUpdateRecordsBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         records: list[dict] = SchemaField(description="Array of updated record objects")
 
     def __init__(self):
@@ -340,7 +243,7 @@ class AirtableDeleteRecordsBlock(Block):
     Deletes one or more records from an Airtable table.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -352,7 +255,7 @@ class AirtableDeleteRecordsBlock(Block):
             description="Array of upto 10 record IDs to delete"
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         records: list[dict] = SchemaField(description="Array of deletion results")
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/airtable/schema.py

@@ -7,8 +7,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
+    BlockSchema,
     CredentialsMetaInput,
     Requests,
     SchemaField,
@@ -24,13 +23,13 @@ class AirtableListSchemaBlock(Block):
     fields, and views.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
         base_id: str = SchemaField(description="The Airtable base ID")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         base_schema: dict = SchemaField(
             description="Complete base schema with tables, fields, and views"
         )
@@ -67,7 +66,7 @@ class AirtableCreateTableBlock(Block):
     Creates a new table in an Airtable base with specified fields and views.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -78,7 +77,7 @@ class AirtableCreateTableBlock(Block):
             default=[{"name": "Name", "type": "singleLineText"}],
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         table: dict = SchemaField(description="Created table object")
         table_id: str = SchemaField(description="ID of the created table")
 
@@ -110,7 +109,7 @@ class AirtableUpdateTableBlock(Block):
     Updates an existing table's properties such as name or description.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -126,7 +125,7 @@ class AirtableUpdateTableBlock(Block):
             description="The date dependency of the table to update", default=None
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         table: dict = SchemaField(description="Updated table object")
 
     def __init__(self):
@@ -158,7 +157,7 @@ class AirtableCreateFieldBlock(Block):
     Adds a new field (column) to an existing Airtable table.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -177,7 +176,7 @@ class AirtableCreateFieldBlock(Block):
             description="The options of the field to create", default=None
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         field: dict = SchemaField(description="Created field object")
         field_id: str = SchemaField(description="ID of the created field")
 
@@ -210,7 +209,7 @@ class AirtableUpdateFieldBlock(Block):
     Updates an existing field's properties in an Airtable table.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -226,7 +225,7 @@ class AirtableUpdateFieldBlock(Block):
             advanced=False,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         field: dict = SchemaField(description="Updated field object")
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/airtable/triggers.py

@@ -3,8 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     BlockWebhookConfig,
     CredentialsMetaInput,
@@ -33,7 +32,7 @@ class AirtableWebhookTriggerBlock(Block):
     Thin wrapper just forwards the payloads one at a time to the next block.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -44,7 +43,7 @@ class AirtableWebhookTriggerBlock(Block):
             description="Airtable webhook event filter"
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         payload: WebhookPayload = SchemaField(description="Airtable webhook payload")
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/apollo/organization.py

@@ -10,20 +10,14 @@ from backend.blocks.apollo.models import (
     PrimaryPhone,
     SearchOrganizationsRequest,
 )
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import CredentialsField, SchemaField
 
 
 class SearchOrganizationsBlock(Block):
     """Search for organizations in Apollo"""
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         organization_num_employees_range: list[int] = SchemaField(
             description="""The number range of employees working for the company. This enables you to find companies based on headcount. You can add multiple ranges to expand your search results.
 
@@ -75,7 +69,7 @@ To find IDs, identify the values for organization_id when you call this endpoint
             description="Apollo credentials",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         organizations: list[Organization] = SchemaField(
             description="List of organizations found",
             default_factory=list,

autogpt_platform/backend/backend/blocks/apollo/people.py

@@ -14,20 +14,14 @@ from backend.blocks.apollo.models import (
     SearchPeopleRequest,
     SenorityLevels,
 )
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import CredentialsField, SchemaField
 
 
 class SearchPeopleBlock(Block):
     """Search for people in Apollo"""
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         person_titles: list[str] = SchemaField(
             description="""Job titles held by the people you want to find. For a person to be included in search results, they only need to match 1 of the job titles you add. Adding more job titles expands your search results.
 
@@ -115,7 +109,7 @@ class SearchPeopleBlock(Block):
             description="Apollo credentials",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         people: list[Contact] = SchemaField(
             description="List of people found",
             default_factory=list,

autogpt_platform/backend/backend/blocks/apollo/person.py

@@ -6,20 +6,14 @@ from backend.blocks.apollo._auth import (
     ApolloCredentialsInput,
 )
 from backend.blocks.apollo.models import Contact, EnrichPersonRequest
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import CredentialsField, SchemaField
 
 
 class GetPersonDetailBlock(Block):
     """Get detailed person data with Apollo API, including email reveal"""
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         person_id: str = SchemaField(
             description="Apollo person ID to enrich (most accurate method)",
             default="",
@@ -74,7 +68,7 @@ class GetPersonDetailBlock(Block):
             description="Apollo credentials",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         contact: Contact = SchemaField(
             description="Enriched contact information",
         )

autogpt_platform/backend/backend/blocks/ayrshare/_util.py

@@ -3,7 +3,7 @@ from typing import Optional
 
 from pydantic import BaseModel, Field
 
-from backend.data.block import BlockSchemaInput
+from backend.data.block import BlockSchema
 from backend.data.model import SchemaField, UserIntegrations
 from backend.integrations.ayrshare import AyrshareClient
 from backend.util.clients import get_database_manager_async_client
@@ -17,7 +17,7 @@ async def get_profile_key(user_id: str):
     return user_integrations.managed_credentials.ayrshare_profile_key
 
 
-class BaseAyrshareInput(BlockSchemaInput):
+class BaseAyrshareInput(BlockSchema):
     """Base input model for Ayrshare social media posts with common fields."""
 
     post: str = SchemaField(

autogpt_platform/backend/backend/blocks/ayrshare/post_to_bluesky.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -38,7 +38,7 @@ class PostToBlueskyBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_facebook.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -101,7 +101,7 @@ class PostToFacebookBlock(Block):
             description="URL for custom link preview", default="", advanced=True
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_gmb.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -94,7 +94,7 @@ class PostToGMBBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_instagram.py

@@ -5,7 +5,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -94,7 +94,7 @@ class PostToInstagramBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_linkedin.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -94,7 +94,7 @@ class PostToLinkedInBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_pinterest.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -73,7 +73,7 @@ class PostToPinterestBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_reddit.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -19,7 +19,7 @@ class PostToRedditBlock(Block):
 
         pass  # Uses all base fields
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_snapchat.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -43,7 +43,7 @@ class PostToSnapchatBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_telegram.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -38,7 +38,7 @@ class PostToTelegramBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_threads.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -31,7 +31,7 @@ class PostToThreadsBlock(Block):
             advanced=False,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_tiktok.py

@@ -5,7 +5,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -98,7 +98,7 @@ class PostToTikTokBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_x.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -97,7 +97,7 @@ class PostToXBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_youtube.py

@@ -6,7 +6,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaOutput,
+    BlockSchema,
     BlockType,
     SchemaField,
 )
@@ -119,7 +119,7 @@ class PostToYouTubeBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

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

@@ -1,205 +0,0 @@
-"""
-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

@@ -1,13 +0,0 @@
-"""
-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

@@ -1,218 +0,0 @@
-"""
-Meeting BaaS bot (recording) blocks.
-"""
-
-from typing import Optional
-
-from backend.sdk import (
-    APIKeyCredentials,
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    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(BlockSchemaInput):
-        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(BlockSchemaOutput):
-        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(BlockSchemaInput):
-        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(BlockSchemaOutput):
-        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(BlockSchemaInput):
-        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(BlockSchemaOutput):
-        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(BlockSchemaInput):
-        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(BlockSchemaOutput):
-        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

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

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

@@ -1,8 +0,0 @@
-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

@@ -1,239 +0,0 @@
-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,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    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(BlockSchemaInput):
-    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(BlockSchemaInput):
-        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(BlockSchemaOutput):
-        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")
-
-    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/basic.py

@@ -1,21 +1,14 @@
 import enum
 from typing import Any
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    BlockType,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema, BlockType
 from backend.data.model import SchemaField
 from backend.util.file import store_media_file
 from backend.util.type import MediaFileType, convert
 
 
 class FileStoreBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         file_in: MediaFileType = SchemaField(
             description="The file to store in the temporary directory, it can be a URL, data URI, or local path."
         )
@@ -26,7 +19,7 @@ class FileStoreBlock(Block):
             title="Produce Base64 Output",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         file_out: MediaFileType = SchemaField(
             description="The relative path to the stored file in the temporary directory."
         )
@@ -64,7 +57,7 @@ class StoreValueBlock(Block):
     The block output will be static, the output can be consumed multiple times.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         input: Any = SchemaField(
             description="Trigger the block to produce the output. "
             "The value is only used when `data` is None."
@@ -75,7 +68,7 @@ class StoreValueBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         output: Any = SchemaField(description="The stored data retained in the block.")
 
     def __init__(self):
@@ -101,10 +94,10 @@ class StoreValueBlock(Block):
 
 
 class PrintToConsoleBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         text: Any = SchemaField(description="The data to print to the console.")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         output: Any = SchemaField(description="The data printed to the console.")
         status: str = SchemaField(description="The status of the print operation.")
 
@@ -128,10 +121,10 @@ class PrintToConsoleBlock(Block):
 
 
 class NoteBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         text: str = SchemaField(description="The text to display in the sticky note.")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         output: str = SchemaField(description="The text to display in the sticky note.")
 
     def __init__(self):
@@ -161,14 +154,15 @@ class TypeOptions(enum.Enum):
 
 
 class UniversalTypeConverterBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         value: Any = SchemaField(
             description="The value to convert to a universal type."
         )
         type: TypeOptions = SchemaField(description="The type to convert the value to.")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         value: Any = SchemaField(description="The converted value.")
+        error: str = SchemaField(description="Error message if conversion failed.")
 
     def __init__(self):
         super().__init__(
@@ -201,10 +195,10 @@ class ReverseListOrderBlock(Block):
     A block which takes in a list and returns it in the opposite order.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         input_list: list[Any] = SchemaField(description="The list to reverse")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         reversed_list: list[Any] = SchemaField(description="The list in reversed order")
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/block.py

@@ -2,13 +2,7 @@ import os
 import re
 from typing import Type
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
 
 
@@ -21,12 +15,12 @@ class BlockInstallationBlock(Block):
         for development purposes only.
     """
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         code: str = SchemaField(
             description="Python code of the block to be installed",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         success: str = SchemaField(
             description="Success message if the block is installed successfully",
         )

autogpt_platform/backend/backend/blocks/branching.py

@@ -1,13 +1,7 @@
 from enum import Enum
 from typing import Any
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
 from backend.util.type import convert
 
@@ -22,7 +16,7 @@ class ComparisonOperator(Enum):
 
 
 class ConditionBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         value1: Any = SchemaField(
             description="Enter the first value for comparison",
             placeholder="For example: 10 or 'hello' or True",
@@ -46,7 +40,7 @@ class ConditionBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         result: bool = SchemaField(
             description="The result of the condition evaluation (True or False)"
         )
@@ -117,7 +111,7 @@ class ConditionBlock(Block):
 
 
 class IfInputMatchesBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         input: Any = SchemaField(
             description="The input to match against",
             placeholder="For example: 10 or 'hello' or True",
@@ -137,7 +131,7 @@ class IfInputMatchesBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         result: bool = SchemaField(
             description="The result of the condition evaluation (True or False)"
         )

autogpt_platform/backend/backend/blocks/code_executor.py

@@ -1,18 +1,10 @@
 from enum import Enum
-from typing import Any, Literal, Optional
+from typing import Literal
 
 from e2b_code_interpreter import AsyncSandbox
-from e2b_code_interpreter import Result as E2BExecutionResult
-from e2b_code_interpreter.charts import Chart as E2BExecutionResultChart
-from pydantic import BaseModel, Field, JsonValue, SecretStr
+from pydantic import SecretStr
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -44,135 +36,14 @@ class ProgrammingLanguage(Enum):
     JAVA = "java"
 
 
-class MainCodeExecutionResult(BaseModel):
-    """
-    *Pydantic model mirroring `e2b_code_interpreter.Result`*
-
-    Represents the data to be displayed as a result of executing a cell in a Jupyter notebook.
-    The result is similar to the structure returned by ipython kernel: https://ipython.readthedocs.io/en/stable/development/execution.html#execution-semantics
-
-    The result can contain multiple types of data, such as text, images, plots, etc. Each type of data is represented
-    as a string, and the result can contain multiple types of data. The display calls don't have to have text representation,
-    for the actual result the representation is always present for the result, the other representations are always optional.
-    """  # noqa
-
-    class Chart(BaseModel, E2BExecutionResultChart):
-        pass
-
-    text: Optional[str] = None
-    html: Optional[str] = None
-    markdown: Optional[str] = None
-    svg: Optional[str] = None
-    png: Optional[str] = None
-    jpeg: Optional[str] = None
-    pdf: Optional[str] = None
-    latex: Optional[str] = None
-    json_data: Optional[JsonValue] = Field(None, alias="json")
-    javascript: Optional[str] = None
-    data: Optional[dict] = None
-    chart: Optional[Chart] = None
-    extra: Optional[dict] = None
-    """Extra data that can be included. Not part of the standard types."""
-
-
-class CodeExecutionResult(MainCodeExecutionResult):
-    __doc__ = MainCodeExecutionResult.__doc__
-
-    is_main_result: bool = False
-    """Whether this data is the main result of the cell. Data can be produced by display calls of which can be multiple in a cell."""  # noqa
-
-
-class BaseE2BExecutorMixin:
-    """Shared implementation methods for E2B executor blocks."""
-
-    async def execute_code(
-        self,
-        api_key: str,
-        code: str,
-        language: ProgrammingLanguage,
-        template_id: str = "",
-        setup_commands: Optional[list[str]] = None,
-        timeout: Optional[int] = None,
-        sandbox_id: Optional[str] = None,
-        dispose_sandbox: bool = False,
-    ):
-        """
-        Unified code execution method that handles all three use cases:
-        1. Create new sandbox and execute (ExecuteCodeBlock)
-        2. Create new sandbox, execute, and return sandbox_id (InstantiateCodeSandboxBlock)
-        3. Connect to existing sandbox and execute (ExecuteCodeStepBlock)
-        """  # noqa
-        sandbox = None
-        try:
-            if sandbox_id:
-                # Connect to existing sandbox (ExecuteCodeStepBlock case)
-                sandbox = await AsyncSandbox.connect(
-                    sandbox_id=sandbox_id, api_key=api_key
-                )
-            else:
-                # Create new sandbox (ExecuteCodeBlock/InstantiateCodeSandboxBlock case)
-                sandbox = await AsyncSandbox.create(
-                    api_key=api_key, template=template_id, timeout=timeout
-                )
-                if setup_commands:
-                    for cmd in setup_commands:
-                        await sandbox.commands.run(cmd)
-
-            # Execute the code
-            execution = await sandbox.run_code(
-                code,
-                language=language.value,
-                on_error=lambda e: sandbox.kill(),  # Kill the sandbox on error
-            )
-
-            if execution.error:
-                raise Exception(execution.error)
-
-            results = execution.results
-            text_output = execution.text
-            stdout_logs = "".join(execution.logs.stdout)
-            stderr_logs = "".join(execution.logs.stderr)
-
-            return results, text_output, stdout_logs, stderr_logs, sandbox.sandbox_id
-        finally:
-            # Dispose of sandbox if requested to reduce usage costs
-            if dispose_sandbox and sandbox:
-                await sandbox.kill()
-
-    def process_execution_results(
-        self, results: list[E2BExecutionResult]
-    ) -> tuple[dict[str, Any] | None, list[dict[str, Any]]]:
-        """Process and filter execution results."""
-        # Filter out empty formats and convert to dicts
-        processed_results = [
-            {
-                f: value
-                for f in [*r.formats(), "extra", "is_main_result"]
-                if (value := getattr(r, f, None)) is not None
-            }
-            for r in results
-        ]
-        if main_result := next(
-            (r for r in processed_results if r.get("is_main_result")), None
-        ):
-            # Make main_result a copy we can modify & remove is_main_result
-            (main_result := {**main_result}).pop("is_main_result")
-
-        return main_result, processed_results
-
-
-class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
+class CodeExecutionBlock(Block):
     # TODO : Add support to upload and download files
-    # NOTE: Currently, you can only customize the CPU and Memory
-    #       by creating a pre customized sandbox template
-    class Input(BlockSchemaInput):
+    # Currently, You can customized the CPU and Memory, only by creating a pre customized sandbox template
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.E2B], Literal["api_key"]
         ] = CredentialsField(
-            description=(
-                "Enter your API key for the E2B platform. "
-                "You can get it in here - https://e2b.dev/docs"
-            ),
+            description="Enter your api key for the E2B Sandbox. You can get it in here - https://e2b.dev/docs",
         )
 
         # Todo : Option to run commond in background
@@ -205,14 +76,6 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
             description="Execution timeout in seconds", default=300
         )
 
-        dispose_sandbox: bool = SchemaField(
-            description=(
-                "Whether to dispose of the sandbox immediately after execution. "
-                "If disabled, the sandbox will run until its timeout expires."
-            ),
-            default=True,
-        )
-
         template_id: str = SchemaField(
             description=(
                 "You can use an E2B sandbox template by entering its ID here. "
@@ -223,29 +86,21 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
-        main_result: MainCodeExecutionResult = SchemaField(
-            title="Main Result", description="The main result from the code execution"
-        )
-        results: list[CodeExecutionResult] = SchemaField(
-            description="List of results from the code execution"
-        )
-        response: str = SchemaField(
-            title="Main Text Output",
-            description="Text output (if any) of the main execution result",
-        )
+    class Output(BlockSchema):
+        response: str = SchemaField(description="Response from code execution")
         stdout_logs: str = SchemaField(
             description="Standard output logs from execution"
         )
         stderr_logs: str = SchemaField(description="Standard error logs from execution")
+        error: str = SchemaField(description="Error message if execution failed")
 
     def __init__(self):
         super().__init__(
             id="0b02b072-abe7-11ef-8372-fb5d162dd712",
-            description="Executes code in a sandbox environment with internet access.",
+            description="Executes code in an isolated sandbox environment with internet access.",
             categories={BlockCategory.DEVELOPER_TOOLS},
-            input_schema=ExecuteCodeBlock.Input,
-            output_schema=ExecuteCodeBlock.Output,
+            input_schema=CodeExecutionBlock.Input,
+            output_schema=CodeExecutionBlock.Output,
             test_credentials=TEST_CREDENTIALS,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
@@ -256,59 +111,91 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
                 "template_id": "",
             },
             test_output=[
-                ("results", []),
                 ("response", "Hello World"),
                 ("stdout_logs", "Hello World\n"),
             ],
             test_mock={
-                "execute_code": lambda api_key, code, language, template_id, setup_commands, timeout, dispose_sandbox: (  # noqa
-                    [],  # results
-                    "Hello World",  # text_output
-                    "Hello World\n",  # stdout_logs
-                    "",  # stderr_logs
-                    "sandbox_id",  # sandbox_id
+                "execute_code": lambda code, language, setup_commands, timeout, api_key, template_id: (
+                    "Hello World",
+                    "Hello World\n",
+                    "",
                 ),
             },
         )
 
+    async def execute_code(
+        self,
+        code: str,
+        language: ProgrammingLanguage,
+        setup_commands: list[str],
+        timeout: int,
+        api_key: str,
+        template_id: str,
+    ):
+        try:
+            sandbox = None
+            if template_id:
+                sandbox = await AsyncSandbox.create(
+                    template=template_id, api_key=api_key, timeout=timeout
+                )
+            else:
+                sandbox = await AsyncSandbox.create(api_key=api_key, timeout=timeout)
+
+            if not sandbox:
+                raise Exception("Sandbox not created")
+
+            # Running setup commands
+            for cmd in setup_commands:
+                await sandbox.commands.run(cmd)
+
+            # Executing the code
+            execution = await sandbox.run_code(
+                code,
+                language=language.value,
+                on_error=lambda e: sandbox.kill(),  # Kill the sandbox if there is an error
+            )
+
+            if execution.error:
+                raise Exception(execution.error)
+
+            response = execution.text
+            stdout_logs = "".join(execution.logs.stdout)
+            stderr_logs = "".join(execution.logs.stderr)
+
+            return response, stdout_logs, stderr_logs
+
+        except Exception as e:
+            raise e
+
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            results, text_output, stdout, stderr, _ = await self.execute_code(
-                api_key=credentials.api_key.get_secret_value(),
-                code=input_data.code,
-                language=input_data.language,
-                template_id=input_data.template_id,
-                setup_commands=input_data.setup_commands,
-                timeout=input_data.timeout,
-                dispose_sandbox=input_data.dispose_sandbox,
+            response, stdout_logs, stderr_logs = await self.execute_code(
+                input_data.code,
+                input_data.language,
+                input_data.setup_commands,
+                input_data.timeout,
+                credentials.api_key.get_secret_value(),
+                input_data.template_id,
             )
 
-            # Determine result object shape & filter out empty formats
-            main_result, results = self.process_execution_results(results)
-            if main_result:
-                yield "main_result", main_result
-            yield "results", results
-            if text_output:
-                yield "response", text_output
-            if stdout:
-                yield "stdout_logs", stdout
-            if stderr:
-                yield "stderr_logs", stderr
+            if response:
+                yield "response", response
+            if stdout_logs:
+                yield "stdout_logs", stdout_logs
+            if stderr_logs:
+                yield "stderr_logs", stderr_logs
         except Exception as e:
             yield "error", str(e)
 
 
-class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
-    class Input(BlockSchemaInput):
+class InstantiationBlock(Block):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.E2B], Literal["api_key"]
         ] = CredentialsField(
-            description=(
-                "Enter your API key for the E2B platform. "
-                "You can get it in here - https://e2b.dev/docs"
-            )
+            description="Enter your api key for the E2B Sandbox. You can get it in here - https://e2b.dev/docs",
         )
 
         # Todo : Option to run commond in background
@@ -351,27 +238,22 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         sandbox_id: str = SchemaField(description="ID of the sandbox instance")
-        response: str = SchemaField(
-            title="Text Result",
-            description="Text result (if any) of the setup code execution",
-        )
+        response: str = SchemaField(description="Response from code execution")
         stdout_logs: str = SchemaField(
             description="Standard output logs from execution"
         )
         stderr_logs: str = SchemaField(description="Standard error logs from execution")
+        error: str = SchemaField(description="Error message if execution failed")
 
     def __init__(self):
         super().__init__(
             id="ff0861c9-1726-4aec-9e5b-bf53f3622112",
-            description=(
-                "Instantiate a sandbox environment with internet access "
-                "in which you can execute code with the Execute Code Step block."
-            ),
+            description="Instantiate an isolated sandbox environment with internet access where to execute code in.",
             categories={BlockCategory.DEVELOPER_TOOLS},
-            input_schema=InstantiateCodeSandboxBlock.Input,
-            output_schema=InstantiateCodeSandboxBlock.Output,
+            input_schema=InstantiationBlock.Input,
+            output_schema=InstantiationBlock.Output,
             test_credentials=TEST_CREDENTIALS,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
@@ -387,12 +269,11 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
                 ("stdout_logs", "Hello World\n"),
             ],
             test_mock={
-                "execute_code": lambda api_key, code, language, template_id, setup_commands, timeout: (  # noqa
-                    [],  # results
-                    "Hello World",  # text_output
-                    "Hello World\n",  # stdout_logs
-                    "",  # stderr_logs
-                    "sandbox_id",  # sandbox_id
+                "execute_code": lambda setup_code, language, setup_commands, timeout, api_key, template_id: (
+                    "sandbox_id",
+                    "Hello World",
+                    "Hello World\n",
+                    "",
                 ),
             },
         )
@@ -401,38 +282,78 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            _, text_output, stdout, stderr, sandbox_id = await self.execute_code(
-                api_key=credentials.api_key.get_secret_value(),
-                code=input_data.setup_code,
-                language=input_data.language,
-                template_id=input_data.template_id,
-                setup_commands=input_data.setup_commands,
-                timeout=input_data.timeout,
+            sandbox_id, response, stdout_logs, stderr_logs = await self.execute_code(
+                input_data.setup_code,
+                input_data.language,
+                input_data.setup_commands,
+                input_data.timeout,
+                credentials.api_key.get_secret_value(),
+                input_data.template_id,
             )
             if sandbox_id:
                 yield "sandbox_id", sandbox_id
             else:
                 yield "error", "Sandbox ID not found"
-
-            if text_output:
-                yield "response", text_output
-            if stdout:
-                yield "stdout_logs", stdout
-            if stderr:
-                yield "stderr_logs", stderr
+            if response:
+                yield "response", response
+            if stdout_logs:
+                yield "stdout_logs", stdout_logs
+            if stderr_logs:
+                yield "stderr_logs", stderr_logs
         except Exception as e:
             yield "error", str(e)
 
+    async def execute_code(
+        self,
+        code: str,
+        language: ProgrammingLanguage,
+        setup_commands: list[str],
+        timeout: int,
+        api_key: str,
+        template_id: str,
+    ):
+        try:
+            sandbox = None
+            if template_id:
+                sandbox = await AsyncSandbox.create(
+                    template=template_id, api_key=api_key, timeout=timeout
+                )
+            else:
+                sandbox = await AsyncSandbox.create(api_key=api_key, timeout=timeout)
 
-class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
-    class Input(BlockSchemaInput):
+            if not sandbox:
+                raise Exception("Sandbox not created")
+
+            # Running setup commands
+            for cmd in setup_commands:
+                await sandbox.commands.run(cmd)
+
+            # Executing the code
+            execution = await sandbox.run_code(
+                code,
+                language=language.value,
+                on_error=lambda e: sandbox.kill(),  # Kill the sandbox if there is an error
+            )
+
+            if execution.error:
+                raise Exception(execution.error)
+
+            response = execution.text
+            stdout_logs = "".join(execution.logs.stdout)
+            stderr_logs = "".join(execution.logs.stderr)
+
+            return sandbox.sandbox_id, response, stdout_logs, stderr_logs
+
+        except Exception as e:
+            raise e
+
+
+class StepExecutionBlock(Block):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.E2B], Literal["api_key"]
         ] = CredentialsField(
-            description=(
-                "Enter your API key for the E2B platform. "
-                "You can get it in here - https://e2b.dev/docs"
-            ),
+            description="Enter your api key for the E2B Sandbox. You can get it in here - https://e2b.dev/docs",
         )
 
         sandbox_id: str = SchemaField(
@@ -453,34 +374,21 @@ class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
             advanced=False,
         )
 
-        dispose_sandbox: bool = SchemaField(
-            description="Whether to dispose of the sandbox after executing this code.",
-            default=False,
-        )
-
-    class Output(BlockSchemaOutput):
-        main_result: MainCodeExecutionResult = SchemaField(
-            title="Main Result", description="The main result from the code execution"
-        )
-        results: list[CodeExecutionResult] = SchemaField(
-            description="List of results from the code execution"
-        )
-        response: str = SchemaField(
-            title="Main Text Output",
-            description="Text output (if any) of the main execution result",
-        )
+    class Output(BlockSchema):
+        response: str = SchemaField(description="Response from code execution")
         stdout_logs: str = SchemaField(
             description="Standard output logs from execution"
         )
         stderr_logs: str = SchemaField(description="Standard error logs from execution")
+        error: str = SchemaField(description="Error message if execution failed")
 
     def __init__(self):
         super().__init__(
             id="82b59b8e-ea10-4d57-9161-8b169b0adba6",
-            description="Execute code in a previously instantiated sandbox.",
+            description="Execute code in a previously instantiated sandbox environment.",
             categories={BlockCategory.DEVELOPER_TOOLS},
-            input_schema=ExecuteCodeStepBlock.Input,
-            output_schema=ExecuteCodeStepBlock.Output,
+            input_schema=StepExecutionBlock.Input,
+            output_schema=StepExecutionBlock.Output,
             test_credentials=TEST_CREDENTIALS,
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
@@ -489,43 +397,61 @@ class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
                 "language": ProgrammingLanguage.PYTHON.value,
             },
             test_output=[
-                ("results", []),
                 ("response", "Hello World"),
                 ("stdout_logs", "Hello World\n"),
             ],
             test_mock={
-                "execute_code": lambda api_key, code, language, sandbox_id, dispose_sandbox: (  # noqa
-                    [],  # results
-                    "Hello World",  # text_output
-                    "Hello World\n",  # stdout_logs
-                    "",  # stderr_logs
-                    sandbox_id,  # sandbox_id
+                "execute_step_code": lambda sandbox_id, step_code, language, api_key: (
+                    "Hello World",
+                    "Hello World\n",
+                    "",
                 ),
             },
         )
 
+    async def execute_step_code(
+        self,
+        sandbox_id: str,
+        code: str,
+        language: ProgrammingLanguage,
+        api_key: str,
+    ):
+        try:
+            sandbox = await AsyncSandbox.connect(sandbox_id=sandbox_id, api_key=api_key)
+            if not sandbox:
+                raise Exception("Sandbox not found")
+
+            # Executing the code
+            execution = await sandbox.run_code(code, language=language.value)
+
+            if execution.error:
+                raise Exception(execution.error)
+
+            response = execution.text
+            stdout_logs = "".join(execution.logs.stdout)
+            stderr_logs = "".join(execution.logs.stderr)
+
+            return response, stdout_logs, stderr_logs
+
+        except Exception as e:
+            raise e
+
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            results, text_output, stdout, stderr, _ = await self.execute_code(
-                api_key=credentials.api_key.get_secret_value(),
-                code=input_data.step_code,
-                language=input_data.language,
-                sandbox_id=input_data.sandbox_id,
-                dispose_sandbox=input_data.dispose_sandbox,
+            response, stdout_logs, stderr_logs = await self.execute_step_code(
+                input_data.sandbox_id,
+                input_data.step_code,
+                input_data.language,
+                credentials.api_key.get_secret_value(),
             )
 
-            # Determine result object shape & filter out empty formats
-            main_result, results = self.process_execution_results(results)
-            if main_result:
-                yield "main_result", main_result
-            yield "results", results
-            if text_output:
-                yield "response", text_output
-            if stdout:
-                yield "stdout_logs", stdout
-            if stderr:
-                yield "stderr_logs", stderr
+            if response:
+                yield "response", response
+            if stdout_logs:
+                yield "stdout_logs", stdout_logs
+            if stderr_logs:
+                yield "stderr_logs", stderr_logs
         except Exception as e:
             yield "error", str(e)

autogpt_platform/backend/backend/blocks/code_extraction_block.py

@@ -1,23 +1,17 @@
 import re
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
 
 
 class CodeExtractionBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         text: str = SchemaField(
             description="Text containing code blocks to extract (e.g., AI response)",
             placeholder="Enter text containing code blocks",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         html: str = SchemaField(description="Extracted HTML code")
         css: str = SchemaField(description="Extracted CSS code")
         javascript: str = SchemaField(description="Extracted JavaScript code")
@@ -96,7 +90,7 @@ class CodeExtractionBlock(Block):
                 for aliases in language_aliases.values()
                 for alias in aliases
             )
-            + r")[ \t]*\n[\s\S]*?```"
+            + r")\s+[\s\S]*?```"
         )
 
         remaining_text = re.sub(pattern, "", input_data.text).strip()
@@ -109,9 +103,7 @@ class CodeExtractionBlock(Block):
         # Escape special regex characters in the language string
         language = re.escape(language)
         # Extract all code blocks enclosed in ```language``` blocks
-        pattern = re.compile(
-            rf"```{language}[ \t]*\n(.*?)\n```", re.DOTALL | re.IGNORECASE
-        )
+        pattern = re.compile(rf"```{language}\s+(.*?)```", re.DOTALL | re.IGNORECASE)
         matches = pattern.finditer(text)
         # Combine all code blocks for this language with newlines between them
         code_blocks = [match.group(1).strip() for match in matches]

autogpt_platform/backend/backend/blocks/compass/triggers.py

@@ -5,8 +5,7 @@ from backend.data.block import (
     BlockCategory,
     BlockManualWebhookConfig,
     BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
+    BlockSchema,
 )
 from backend.data.model import SchemaField
 from backend.integrations.providers import ProviderName
@@ -28,10 +27,10 @@ class TranscriptionDataModel(BaseModel):
 
 
 class CompassAITriggerBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         payload: TranscriptionDataModel = SchemaField(hidden=True)
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         transcription: str = SchemaField(
             description="The contents of the compass transcription."
         )

autogpt_platform/backend/backend/blocks/count_words_and_char_block.py

@@ -1,22 +1,16 @@
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
 
 
 class WordCharacterCountBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         text: str = SchemaField(
             description="Input text to count words and characters",
             placeholder="Enter your text here",
             advanced=False,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         word_count: int = SchemaField(description="Number of words in the input text")
         character_count: int = SchemaField(
             description="Number of characters in the input text"

autogpt_platform/backend/backend/blocks/data_manipulation.py

@@ -1,12 +1,6 @@
 from typing import Any, List
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
 from backend.util.json import loads
 from backend.util.mock import MockObject
@@ -18,13 +12,13 @@ from backend.util.prompt import estimate_token_count_str
 
 
 class CreateDictionaryBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         values: dict[str, Any] = SchemaField(
             description="Key-value pairs to create the dictionary with",
             placeholder="e.g., {'name': 'Alice', 'age': 25}",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         dictionary: dict[str, Any] = SchemaField(
             description="The created dictionary containing the specified key-value pairs"
         )
@@ -68,11 +62,10 @@ class CreateDictionaryBlock(Block):
 
 
 class AddToDictionaryBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         dictionary: dict[Any, Any] = SchemaField(
             default_factory=dict,
             description="The dictionary to add the entry to. If not provided, a new dictionary will be created.",
-            advanced=False,
         )
         key: str = SchemaField(
             default="",
@@ -92,10 +85,11 @@ class AddToDictionaryBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         updated_dictionary: dict = SchemaField(
             description="The dictionary with the new entry added."
         )
+        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -146,11 +140,11 @@ class AddToDictionaryBlock(Block):
 
 
 class FindInDictionaryBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         input: Any = SchemaField(description="Dictionary to lookup from")
         key: str | int = SchemaField(description="Key to lookup in the dictionary")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         output: Any = SchemaField(description="Value found for the given key")
         missing: Any = SchemaField(
             description="Value of the input that missing the key"
@@ -206,7 +200,7 @@ class FindInDictionaryBlock(Block):
 
 
 class RemoveFromDictionaryBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         dictionary: dict[Any, Any] = SchemaField(
             description="The dictionary to modify."
         )
@@ -215,11 +209,12 @@ class RemoveFromDictionaryBlock(Block):
             default=False, description="Whether to return the removed value."
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         updated_dictionary: dict[Any, Any] = SchemaField(
             description="The dictionary after removal."
         )
         removed_value: Any = SchemaField(description="The removed value if requested.")
+        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -255,18 +250,19 @@ class RemoveFromDictionaryBlock(Block):
 
 
 class ReplaceDictionaryValueBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         dictionary: dict[Any, Any] = SchemaField(
             description="The dictionary to modify."
         )
         key: str | int = SchemaField(description="Key to replace the value for.")
         value: Any = SchemaField(description="The new value for the given key.")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         updated_dictionary: dict[Any, Any] = SchemaField(
             description="The dictionary after replacement."
         )
         old_value: Any = SchemaField(description="The value that was replaced.")
+        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -303,10 +299,10 @@ class ReplaceDictionaryValueBlock(Block):
 
 
 class DictionaryIsEmptyBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         dictionary: dict[Any, Any] = SchemaField(description="The dictionary to check.")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         is_empty: bool = SchemaField(description="True if the dictionary is empty.")
 
     def __init__(self):
@@ -330,7 +326,7 @@ class DictionaryIsEmptyBlock(Block):
 
 
 class CreateListBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         values: List[Any] = SchemaField(
             description="A list of values to be combined into a new list.",
             placeholder="e.g., ['Alice', 25, True]",
@@ -346,10 +342,11 @@ class CreateListBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         list: List[Any] = SchemaField(
             description="The created list containing the specified values."
         )
+        error: str = SchemaField(description="Error message if list creation failed.")
 
     def __init__(self):
         super().__init__(
@@ -406,7 +403,7 @@ class CreateListBlock(Block):
 
 
 class AddToListBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         list: List[Any] = SchemaField(
             default_factory=list,
             advanced=False,
@@ -427,10 +424,11 @@ class AddToListBlock(Block):
             description="The position to insert the new entry. If not provided, the entry will be appended to the end of the list.",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         updated_list: List[Any] = SchemaField(
             description="The list with the new entry added."
         )
+        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -485,11 +483,11 @@ class AddToListBlock(Block):
 
 
 class FindInListBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         list: List[Any] = SchemaField(description="The list to search in.")
         value: Any = SchemaField(description="The value to search for.")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         index: int = SchemaField(description="The index of the value in the list.")
         found: bool = SchemaField(
             description="Whether the value was found in the list."
@@ -527,14 +525,15 @@ class FindInListBlock(Block):
 
 
 class GetListItemBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         list: List[Any] = SchemaField(description="The list to get the item from.")
         index: int = SchemaField(
             description="The 0-based index of the item (supports negative indices)."
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         item: Any = SchemaField(description="The item at the specified index.")
+        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -561,7 +560,7 @@ class GetListItemBlock(Block):
 
 
 class RemoveFromListBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         list: List[Any] = SchemaField(description="The list to modify.")
         value: Any = SchemaField(
             default=None, description="Value to remove from the list."
@@ -574,9 +573,10 @@ class RemoveFromListBlock(Block):
             default=False, description="Whether to return the removed item."
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         updated_list: List[Any] = SchemaField(description="The list after removal.")
         removed_item: Any = SchemaField(description="The removed item if requested.")
+        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -617,16 +617,17 @@ class RemoveFromListBlock(Block):
 
 
 class ReplaceListItemBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         list: List[Any] = SchemaField(description="The list to modify.")
         index: int = SchemaField(
             description="Index of the item to replace (supports negative indices)."
         )
         value: Any = SchemaField(description="The new value for the given index.")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         updated_list: List[Any] = SchemaField(description="The list after replacement.")
         old_item: Any = SchemaField(description="The item that was replaced.")
+        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -661,10 +662,10 @@ class ReplaceListItemBlock(Block):
 
 
 class ListIsEmptyBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         list: List[Any] = SchemaField(description="The list to check.")
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         is_empty: bool = SchemaField(description="True if the list is empty.")
 
     def __init__(self):

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

@@ -1,182 +0,0 @@
-"""
-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

@@ -1,17 +0,0 @@
-"""
-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

@@ -1,283 +0,0 @@
-"""
-DataForSEO Google Keyword Suggestions block.
-"""
-
-from typing import Any, Dict, List, Optional
-
-from backend.sdk import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    CredentialsMetaInput,
-    SchemaField,
-    UserPasswordCredentials,
-)
-
-from ._api import DataForSeoClient
-from ._config import dataforseo
-
-
-class KeywordSuggestion(BlockSchemaInput):
-    """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(BlockSchemaInput):
-        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(BlockSchemaOutput):
-        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."""
-        try:
-            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 []
-                )
-                if items is None:
-                    items = []
-                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
-        except Exception as e:
-            yield "error", f"Failed to fetch keyword suggestions: {str(e)}"
-
-
-class KeywordSuggestionExtractorBlock(Block):
-    """Extracts individual fields from a KeywordSuggestion object."""
-
-    class Input(BlockSchemaInput):
-        suggestion: KeywordSuggestion = SchemaField(
-            description="The keyword suggestion object to extract fields from"
-        )
-
-    class Output(BlockSchemaOutput):
-        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

@@ -1,301 +0,0 @@
-"""
-DataForSEO Google Related Keywords block.
-"""
-
-from typing import Any, Dict, List, Optional
-
-from backend.sdk import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    CredentialsMetaInput,
-    SchemaField,
-    UserPasswordCredentials,
-)
-
-from ._api import DataForSeoClient
-from ._config import dataforseo
-
-
-class RelatedKeyword(BlockSchemaInput):
-    """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(BlockSchemaInput):
-        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(BlockSchemaOutput):
-        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."""
-        try:
-            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 []
-                )
-                # Ensure items is never None
-                if items is None:
-                    items = []
-                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
-        except Exception as e:
-            yield "error", f"Failed to fetch related keywords: {str(e)}"
-
-
-class RelatedKeywordExtractorBlock(Block):
-    """Extracts individual fields from a RelatedKeyword object."""
-
-    class Input(BlockSchemaInput):
-        related_keyword: RelatedKeyword = SchemaField(
-            description="The related keyword object to extract fields from"
-        )
-
-    class Output(BlockSchemaOutput):
-        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/decoder_block.py

@@ -1,23 +1,17 @@
 import codecs
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
 
 
 class TextDecoderBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         text: str = SchemaField(
             description="A string containing escaped characters to be decoded",
             placeholder='Your entire text block with \\n and \\" escaped characters',
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         decoded_text: str = SchemaField(
             description="The decoded text with escape sequences processed"
         )

autogpt_platform/backend/backend/blocks/discord.py

@@ -2,42 +2,52 @@ import base64
 import io
 import mimetypes
 from pathlib import Path
-from typing import Any
+from typing import Any, Literal
 
+import aiohttp
 import discord
 from pydantic import SecretStr
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import (
+    APIKeyCredentials,
+    CredentialsField,
+    CredentialsMetaInput,
+    SchemaField,
 )
-from backend.data.model import APIKeyCredentials, SchemaField
+from backend.integrations.providers import ProviderName
 from backend.util.file import store_media_file
-from backend.util.request import Requests
 from backend.util.type import MediaFileType
 
-from ._auth import (
-    TEST_BOT_CREDENTIALS,
-    TEST_BOT_CREDENTIALS_INPUT,
-    DiscordBotCredentialsField,
-    DiscordBotCredentialsInput,
-)
+DiscordCredentials = CredentialsMetaInput[
+    Literal[ProviderName.DISCORD], Literal["api_key"]
+]
 
-# Keep backward compatibility alias
-DiscordCredentials = DiscordBotCredentialsInput
-DiscordCredentialsField = DiscordBotCredentialsField
-TEST_CREDENTIALS = TEST_BOT_CREDENTIALS
-TEST_CREDENTIALS_INPUT = TEST_BOT_CREDENTIALS_INPUT
+
+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,
+)
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.type,
+}
 
 
 class ReadDiscordMessagesBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: DiscordCredentials = DiscordCredentialsField()
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         message_content: str = SchemaField(
             description="The content of the message received"
         )
@@ -120,9 +130,10 @@ class ReadDiscordMessagesBlock(Block):
             if message.attachments:
                 attachment = message.attachments[0]  # Process the first attachment
                 if attachment.filename.endswith((".txt", ".py")):
-                    response = await Requests().get(attachment.url)
-                    file_content = response.text()
-                    self.output_data += f"\n\nFile from user: {attachment.filename}\nContent: {file_content}"
+                    async with aiohttp.ClientSession() as session:
+                        async with session.get(attachment.url) as response:
+                            file_content = response.text()
+                            self.output_data += f"\n\nFile from user: {attachment.filename}\nContent: {file_content}"
 
             await client.close()
 
@@ -170,21 +181,21 @@ class ReadDiscordMessagesBlock(Block):
 
 
 class SendDiscordMessageBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: DiscordCredentials = DiscordCredentialsField()
         message_content: str = SchemaField(
             description="The content of the message to send"
         )
         channel_name: str = SchemaField(
-            description="Channel ID or channel name to send the message to"
+            description="The name of the channel the message will be sent to"
         )
         server_name: str = SchemaField(
-            description="Server name (only needed if using channel name)",
-            advanced=True,
+            description="The name of the server where the channel is located",
+            advanced=True,  # Optional field for server name
             default="",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         status: str = SchemaField(
             description="The status of the operation (e.g., 'Message sent', 'Error')"
         )
@@ -236,49 +247,25 @@ class SendDiscordMessageBlock(Block):
         @client.event
         async def on_ready():
             print(f"Logged in as {client.user}")
-            channel = None
+            for guild in client.guilds:
+                if server_name and guild.name != server_name:
+                    continue
+                for channel in guild.text_channels:
+                    if channel.name == channel_name:
+                        # Split message into chunks if it exceeds 2000 characters
+                        chunks = self.chunk_message(message_content)
+                        last_message = None
+                        for chunk in chunks:
+                            last_message = await channel.send(chunk)
+                        result["status"] = "Message sent"
+                        result["message_id"] = (
+                            str(last_message.id) if last_message else ""
+                        )
+                        result["channel_id"] = str(channel.id)
+                        await client.close()
+                        return
 
-            # Try to parse as channel ID first
-            try:
-                channel_id = int(channel_name)
-                channel = client.get_channel(channel_id)
-            except ValueError:
-                # Not a valid ID, will try name lookup
-                pass
-
-            # If not found by ID (or not an ID), try name lookup
-            if not channel:
-                for guild in client.guilds:
-                    if server_name and guild.name != server_name:
-                        continue
-                    for ch in guild.text_channels:
-                        if ch.name == channel_name:
-                            channel = ch
-                            break
-                    if channel:
-                        break
-
-            if not channel:
-                result["status"] = f"Channel not found: {channel_name}"
-                await client.close()
-                return
-
-            # Type check - ensure it's a text channel that can send messages
-            if not hasattr(channel, "send"):
-                result["status"] = (
-                    f"Channel {channel_name} cannot receive messages (not a text channel)"
-                )
-                await client.close()
-                return
-
-            # Split message into chunks if it exceeds 2000 characters
-            chunks = self.chunk_message(message_content)
-            last_message = None
-            for chunk in chunks:
-                last_message = await channel.send(chunk)  # type: ignore
-            result["status"] = "Message sent"
-            result["message_id"] = str(last_message.id) if last_message else ""
-            result["channel_id"] = str(channel.id)
+            result["status"] = "Channel not found"
             await client.close()
 
         await client.start(token)
@@ -316,7 +303,7 @@ class SendDiscordMessageBlock(Block):
 
 
 class SendDiscordDMBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: DiscordCredentials = DiscordCredentialsField()
         user_id: str = SchemaField(
             description="The Discord user ID to send the DM to (e.g., '123456789012345678')"
@@ -325,7 +312,7 @@ class SendDiscordDMBlock(Block):
             description="The content of the direct message to send"
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         status: str = SchemaField(description="The status of the operation")
         message_id: str = SchemaField(description="The ID of the sent message")
 
@@ -405,7 +392,7 @@ class SendDiscordDMBlock(Block):
 
 
 class SendDiscordEmbedBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: DiscordCredentials = DiscordCredentialsField()
         channel_identifier: str = SchemaField(
             description="Channel ID or channel name to send the embed to"
@@ -442,7 +429,7 @@ class SendDiscordEmbedBlock(Block):
             default=[],
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         status: str = SchemaField(description="Operation status")
         message_id: str = SchemaField(description="ID of the sent embed message")
 
@@ -592,7 +579,7 @@ class SendDiscordEmbedBlock(Block):
 
 
 class SendDiscordFileBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: DiscordCredentials = DiscordCredentialsField()
         channel_identifier: str = SchemaField(
             description="Channel ID or channel name to send the file to"
@@ -613,7 +600,7 @@ class SendDiscordFileBlock(Block):
             description="Optional message to send with the file", default=""
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         status: str = SchemaField(description="Operation status")
         message_id: str = SchemaField(description="ID of the sent message")
 
@@ -704,15 +691,16 @@ class SendDiscordFileBlock(Block):
 
                 elif file.startswith(("http://", "https://")):
                     # URL - download the file
-                    response = await Requests().get(file)
-                    file_bytes = response.content
+                    async with aiohttp.ClientSession() as session:
+                        async with session.get(file) as response:
+                            file_bytes = await response.read()
 
-                    # Try to get filename from URL if not provided
-                    if not filename:
-                        from urllib.parse import urlparse
+                            # Try to get filename from URL if not provided
+                            if not filename:
+                                from urllib.parse import urlparse
 
-                        path = urlparse(file).path
-                        detected_filename = Path(path).name or "download"
+                                path = urlparse(file).path
+                                detected_filename = Path(path).name or "download"
                 else:
                     # Local file path - read from stored media file
                     # This would be a path from a previous block's output
@@ -794,7 +782,7 @@ class SendDiscordFileBlock(Block):
 
 
 class ReplyToDiscordMessageBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: DiscordCredentials = DiscordCredentialsField()
         channel_id: str = SchemaField(
             description="The channel ID where the message to reply to is located"
@@ -805,7 +793,7 @@ class ReplyToDiscordMessageBlock(Block):
             description="Whether to mention the original message author", default=True
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         status: str = SchemaField(description="Operation status")
         reply_id: str = SchemaField(description="ID of the reply message")
 
@@ -919,13 +907,13 @@ class ReplyToDiscordMessageBlock(Block):
 
 
 class DiscordUserInfoBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: DiscordCredentials = DiscordCredentialsField()
         user_id: str = SchemaField(
             description="The Discord user ID to get information about"
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         user_id: str = SchemaField(
             description="The user's ID (passed through for chaining)"
         )
@@ -1036,7 +1024,7 @@ class DiscordUserInfoBlock(Block):
 
 
 class DiscordChannelInfoBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: DiscordCredentials = DiscordCredentialsField()
         channel_identifier: str = SchemaField(
             description="Channel name or channel ID to look up"
@@ -1047,7 +1035,7 @@ class DiscordChannelInfoBlock(Block):
             default="",
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         channel_id: str = SchemaField(description="The channel's ID")
         channel_name: str = SchemaField(description="The channel's name")
         server_id: str = SchemaField(description="The server's ID")

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

@@ -1,117 +0,0 @@
-"""
-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

@@ -1,74 +0,0 @@
-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/oauth_blocks.py

@@ -1,105 +0,0 @@
-"""
-Discord OAuth-based blocks.
-"""
-
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
-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(BlockSchemaInput):
-        credentials: DiscordOAuthCredentialsInput = DiscordOAuthCredentialsField(
-            ["identify"]
-        )
-
-    class Output(BlockSchemaOutput):
-        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/email_block.py

@@ -5,13 +5,7 @@ from typing import Literal
 
 from pydantic import BaseModel, ConfigDict, SecretStr
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import (
     CredentialsField,
     CredentialsMetaInput,
@@ -57,7 +51,7 @@ class SMTPConfig(BaseModel):
 
 
 class SendEmailBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         to_email: str = SchemaField(
             description="Recipient email address", placeholder="recipient@example.com"
         )
@@ -73,7 +67,7 @@ class SendEmailBlock(Block):
         )
         credentials: SMTPCredentialsInput = SMTPCredentialsField()
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         status: str = SchemaField(description="Status of the email sending operation")
         error: str = SchemaField(
             description="Error message if the email sending failed"

autogpt_platform/backend/backend/blocks/enrichlayer/linkedin.py

@@ -8,13 +8,7 @@ which provides access to LinkedIn profile data and related information.
 import logging
 from typing import Optional
 
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import APIKeyCredentials, CredentialsField, SchemaField
 from backend.util.type import MediaFileType
 
@@ -35,7 +29,7 @@ logger = logging.getLogger(__name__)
 class GetLinkedinProfileBlock(Block):
     """Block to fetch LinkedIn profile data using Enrichlayer API."""
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         """Input schema for GetLinkedinProfileBlock."""
 
         linkedin_url: str = SchemaField(
@@ -86,12 +80,13 @@ class GetLinkedinProfileBlock(Block):
             description="Enrichlayer API credentials"
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         """Output schema for GetLinkedinProfileBlock."""
 
         profile: PersonProfileResponse = SchemaField(
             description="LinkedIn profile data"
         )
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         """Initialize GetLinkedinProfileBlock."""
@@ -204,7 +199,7 @@ class GetLinkedinProfileBlock(Block):
 class LinkedinPersonLookupBlock(Block):
     """Block to look up LinkedIn profiles by person's information using Enrichlayer API."""
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         """Input schema for LinkedinPersonLookupBlock."""
 
         first_name: str = SchemaField(
@@ -247,12 +242,13 @@ class LinkedinPersonLookupBlock(Block):
             description="Enrichlayer API credentials"
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         """Output schema for LinkedinPersonLookupBlock."""
 
         lookup_result: PersonLookupResponse = SchemaField(
             description="LinkedIn profile lookup result"
         )
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         """Initialize LinkedinPersonLookupBlock."""
@@ -350,7 +346,7 @@ class LinkedinPersonLookupBlock(Block):
 class LinkedinRoleLookupBlock(Block):
     """Block to look up LinkedIn profiles by role in a company using Enrichlayer API."""
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         """Input schema for LinkedinRoleLookupBlock."""
 
         role: str = SchemaField(
@@ -370,12 +366,13 @@ class LinkedinRoleLookupBlock(Block):
             description="Enrichlayer API credentials"
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         """Output schema for LinkedinRoleLookupBlock."""
 
         role_lookup_result: RoleLookupResponse = SchemaField(
             description="LinkedIn role lookup result"
         )
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         """Initialize LinkedinRoleLookupBlock."""
@@ -452,7 +449,7 @@ class LinkedinRoleLookupBlock(Block):
 class GetLinkedinProfilePictureBlock(Block):
     """Block to get LinkedIn profile pictures using Enrichlayer API."""
 
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         """Input schema for GetLinkedinProfilePictureBlock."""
 
         linkedin_profile_url: str = SchemaField(
@@ -463,12 +460,13 @@ class GetLinkedinProfilePictureBlock(Block):
             description="Enrichlayer API credentials"
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         """Output schema for GetLinkedinProfilePictureBlock."""
 
         profile_picture_url: MediaFileType = SchemaField(
             description="LinkedIn profile picture URL"
         )
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         """Initialize GetLinkedinProfilePictureBlock."""

autogpt_platform/backend/backend/blocks/exa/_test.py

@@ -1,22 +0,0 @@
-"""
-Test credentials and helpers for Exa blocks.
-"""
-
-from pydantic import SecretStr
-
-from backend.data.model import APIKeyCredentials
-
-TEST_CREDENTIALS = APIKeyCredentials(
-    id="01234567-89ab-cdef-0123-456789abcdef",
-    provider="exa",
-    api_key=SecretStr("mock-exa-api-key"),
-    title="Mock Exa API key",
-    expires_at=None,
-)
-
-TEST_CREDENTIALS_INPUT = {
-    "provider": TEST_CREDENTIALS.provider,
-    "id": TEST_CREDENTIALS.id,
-    "type": TEST_CREDENTIALS.type,
-    "title": TEST_CREDENTIALS.title,
-}

autogpt_platform/backend/backend/blocks/exa/answers.py

@@ -1,59 +1,55 @@
-from typing import Optional
-
-from exa_py import AsyncExa
-from exa_py.api import AnswerResponse
-from pydantic import BaseModel
-
 from backend.sdk import (
     APIKeyCredentials,
+    BaseModel,
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
+    BlockSchema,
     CredentialsMetaInput,
-    MediaFileType,
+    Requests,
     SchemaField,
 )
 
 from ._config import exa
 
 
-class AnswerCitation(BaseModel):
-    """Citation model for answer endpoint."""
+class CostBreakdown(BaseModel):
+    keywordSearch: float
+    neuralSearch: float
+    contentText: float
+    contentHighlight: float
+    contentSummary: float
 
-    id: str = SchemaField(description="The temporary ID for the document")
-    url: str = SchemaField(description="The URL of the search result")
-    title: Optional[str] = SchemaField(description="The title of the search result")
-    author: Optional[str] = SchemaField(description="The author of the content")
-    publishedDate: Optional[str] = SchemaField(
-        description="An estimate of the creation date"
-    )
-    text: Optional[str] = SchemaField(description="The full text content of the source")
-    image: Optional[MediaFileType] = SchemaField(
-        description="The URL of the image associated with the result"
-    )
-    favicon: Optional[MediaFileType] = SchemaField(
-        description="The URL of the favicon for the domain"
-    )
 
-    @classmethod
-    def from_sdk(cls, sdk_citation) -> "AnswerCitation":
-        """Convert SDK AnswerResult (dataclass) to our Pydantic model."""
-        return cls(
-            id=getattr(sdk_citation, "id", ""),
-            url=getattr(sdk_citation, "url", ""),
-            title=getattr(sdk_citation, "title", None),
-            author=getattr(sdk_citation, "author", None),
-            publishedDate=getattr(sdk_citation, "published_date", None),
-            text=getattr(sdk_citation, "text", None),
-            image=getattr(sdk_citation, "image", None),
-            favicon=getattr(sdk_citation, "favicon", None),
-        )
+class SearchBreakdown(BaseModel):
+    search: float
+    contents: float
+    breakdown: CostBreakdown
+
+
+class PerRequestPrices(BaseModel):
+    neuralSearch_1_25_results: float
+    neuralSearch_26_100_results: float
+    neuralSearch_100_plus_results: float
+    keywordSearch_1_100_results: float
+    keywordSearch_100_plus_results: float
+
+
+class PerPagePrices(BaseModel):
+    contentText: float
+    contentHighlight: float
+    contentSummary: float
+
+
+class CostDollars(BaseModel):
+    total: float
+    breakDown: list[SearchBreakdown]
+    perRequestPrices: PerRequestPrices
+    perPagePrices: PerPagePrices
 
 
 class ExaAnswerBlock(Block):
-    class Input(BlockSchemaInput):
+    class Input(BlockSchema):
         credentials: CredentialsMetaInput = exa.credentials_field(
             description="The Exa integration requires an API Key."
         )
@@ -62,21 +58,31 @@ class ExaAnswerBlock(Block):
             placeholder="What is the latest valuation of SpaceX?",
         )
         text: bool = SchemaField(
-            description="Include full text content in the search results used for the answer",
-            default=True,
+            default=False,
+            description="If true, the response includes full text content in the search results",
+            advanced=True,
+        )
+        model: str = SchemaField(
+            default="exa",
+            description="The search model to use (exa or exa-pro)",
+            placeholder="exa",
+            advanced=True,
         )
 
-    class Output(BlockSchemaOutput):
+    class Output(BlockSchema):
         answer: str = SchemaField(
             description="The generated answer based on search results"
         )
-        citations: list[AnswerCitation] = SchemaField(
-            description="Search results used to generate the answer"
+        citations: list[dict] = SchemaField(
+            description="Search results used to generate the answer",
+            default_factory=list,
         )
-        citation: AnswerCitation = SchemaField(
-            description="Individual citation from the answer"
+        cost_dollars: CostDollars = SchemaField(
+            description="Cost breakdown of the request"
+        )
+        error: str = SchemaField(
+            description="Error message if the request failed", default=""
         )
-        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         super().__init__(
@@ -90,24 +96,26 @@ class ExaAnswerBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+        url = "https://api.exa.ai/answer"
+        headers = {
+            "Content-Type": "application/json",
+            "x-api-key": credentials.api_key.get_secret_value(),
+        }
 
-        # Get answer using SDK (stream=False for blocks) - this IS async, needs await
-        response = await aexa.answer(
-            query=input_data.query, text=input_data.text, stream=False
-        )
+        # Build the payload
+        payload = {
+            "query": input_data.query,
+            "text": input_data.text,
+            "model": input_data.model,
+        }
 
-        # this should remain true as long as they don't start defaulting to streaming only.
-        # provides a bit of safety for sdk updates.
-        assert type(response) is AnswerResponse
+        try:
+            response = await Requests().post(url, headers=headers, json=payload)
+            data = response.json()
 
-        yield "answer", response.answer
+            yield "answer", data.get("answer", "")
+            yield "citations", data.get("citations", [])
+            yield "cost_dollars", data.get("costDollars", {})
 
-        citations = [
-            AnswerCitation.from_sdk(sdk_citation)
-            for sdk_citation in response.citations or []
-        ]
-
-        yield "citations", citations
-        for citation in citations:
-            yield "citation", citation
+        except Exception as e:
+            yield "error", str(e)

autogpt_platform/backend/backend/blocks/exa/code_context.py

@@ -1,118 +0,0 @@
-"""
-Exa Code Context Block
-
-Provides code search capabilities to find relevant code snippets and examples
-from open source repositories, documentation, and Stack Overflow.
-"""
-
-from typing import Union
-
-from pydantic import BaseModel
-
-from backend.sdk import (
-    APIKeyCredentials,
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    CredentialsMetaInput,
-    Requests,
-    SchemaField,
-)
-
-from ._config import exa
-
-
-class CodeContextResponse(BaseModel):
-    """Stable output model for code context responses."""
-
-    request_id: str
-    query: str
-    response: str
-    results_count: int
-    cost_dollars: str
-    search_time: float
-    output_tokens: int
-
-    @classmethod
-    def from_api(cls, data: dict) -> "CodeContextResponse":
-        """Convert API response to our stable model."""
-        return cls(
-            request_id=data.get("requestId", ""),
-            query=data.get("query", ""),
-            response=data.get("response", ""),
-            results_count=data.get("resultsCount", 0),
-            cost_dollars=data.get("costDollars", ""),
-            search_time=data.get("searchTime", 0.0),
-            output_tokens=data.get("outputTokens", 0),
-        )
-
-
-class ExaCodeContextBlock(Block):
-    """Get relevant code snippets and examples from open source repositories."""
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = exa.credentials_field(
-            description="The Exa integration requires an API Key."
-        )
-        query: str = SchemaField(
-            description="Search query to find relevant code snippets. Describe what you're trying to do or what code you're looking for.",
-            placeholder="how to use React hooks for state management",
-        )
-        tokens_num: Union[str, int] = SchemaField(
-            default="dynamic",
-            description="Token limit for response. Use 'dynamic' for automatic sizing, 5000 for standard queries, or 10000 for comprehensive examples.",
-            placeholder="dynamic",
-        )
-
-    class Output(BlockSchemaOutput):
-        request_id: str = SchemaField(description="Unique identifier for this request")
-        query: str = SchemaField(description="The search query used")
-        response: str = SchemaField(
-            description="Formatted code snippets and contextual examples with sources"
-        )
-        results_count: int = SchemaField(
-            description="Number of code sources found and included"
-        )
-        cost_dollars: str = SchemaField(description="Cost of this request in dollars")
-        search_time: float = SchemaField(
-            description="Time taken to search in milliseconds"
-        )
-        output_tokens: int = SchemaField(description="Number of tokens in the response")
-
-    def __init__(self):
-        super().__init__(
-            id="8f9e0d1c-2b3a-4567-8901-23456789abcd",
-            description="Search billions of GitHub repos, docs, and Stack Overflow for relevant code examples",
-            categories={BlockCategory.SEARCH, BlockCategory.DEVELOPER_TOOLS},
-            input_schema=ExaCodeContextBlock.Input,
-            output_schema=ExaCodeContextBlock.Output,
-        )
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        url = "https://api.exa.ai/context"
-        headers = {
-            "Content-Type": "application/json",
-            "x-api-key": credentials.api_key.get_secret_value(),
-        }
-
-        payload = {
-            "query": input_data.query,
-            "tokensNum": input_data.tokens_num,
-        }
-
-        response = await Requests().post(url, headers=headers, json=payload)
-        data = response.json()
-
-        context = CodeContextResponse.from_api(data)
-
-        yield "request_id", context.request_id
-        yield "query", context.query
-        yield "response", context.response
-        yield "results_count", context.results_count
-        yield "cost_dollars", context.cost_dollars
-        yield "search_time", context.search_time
-        yield "output_tokens", context.output_tokens