Merge branch 'dev' into gmail-reply-draft

.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/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

@@ -37,7 +37,9 @@ jobs:
 
     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

@@ -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

autogpt_platform/CLAUDE.md

@@ -61,27 +61,24 @@ poetry run pytest path/to/test.py --snapshot-update
 
 ```bash
 # Install dependencies
-cd frontend && pnpm i
+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
+npm run build
 
 # Type checking
-pnpm types
+npm run types
 ```
 
-We have a components library in autogpt_platform/frontend/src/components/atoms that should be used when adding new pages and components. 
-
-
 ## Architecture Overview
 
 ### Backend Architecture
@@ -152,21 +149,12 @@ 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?
 ex: do the inputs and outputs tie well together?

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

@@ -1,13 +1,13 @@
-from .config import verify_settings
-from .dependencies import get_user_id, requires_admin_user, requires_user
-from .helpers import add_auth_responses_to_openapi
+from .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",
-    "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

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

autogpt_platform/autogpt_libs/autogpt_libs/auth/dependencies_test.py

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

autogpt_platform/autogpt_libs/autogpt_libs/auth/depends.py

@@ -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
 
 
-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)
-
-
-def test_get_jwt_payload_with_valid_token():
-    """Test extracting JWT payload with valid bearer token."""
-    token = create_token(TEST_USER_PAYLOAD)
-    credentials = HTTPAuthorizationCredentials(scheme="Bearer", credentials=token)
-
-    result = jwt_utils.get_jwt_payload(credentials)
-    assert result["sub"] == "test-user-id"
-    assert result["role"] == "user"
-
-
-def test_get_jwt_payload_no_credentials():
-    """Test JWT payload when no credentials provided."""
-    with pytest.raises(HTTPException) as exc_info:
-        jwt_utils.get_jwt_payload(None)
-    assert exc_info.value.status_code == 401
-    assert "Authorization header is missing" in exc_info.value.detail
-
-
-def test_get_jwt_payload_invalid_token():
-    """Test JWT payload extraction with invalid token."""
-    credentials = HTTPAuthorizationCredentials(
-        scheme="Bearer", credentials="invalid.token.here"
-    )
-
-    with pytest.raises(HTTPException) as exc_info:
-        jwt_utils.get_jwt_payload(credentials)
-    assert exc_info.value.status_code == 401
-    assert "Invalid token" in exc_info.value.detail
-
-
-def test_verify_user_with_valid_user():
-    """Test verifying a valid user."""
-    user = jwt_utils.verify_user(TEST_USER_PAYLOAD, admin_only=False)
-    assert isinstance(user, User)
-    assert user.user_id == "test-user-id"
-    assert user.role == "user"
-    assert user.email == "test@example.com"
-
-
-def test_verify_user_with_admin():
-    """Test verifying an admin user."""
-    user = jwt_utils.verify_user(TEST_ADMIN_PAYLOAD, admin_only=True)
-    assert isinstance(user, User)
-    assert user.user_id == "admin-user-id"
-    assert user.role == "admin"
-
-
-def test_verify_user_admin_only_with_regular_user():
-    """Test verifying regular user when admin is required."""
-    with pytest.raises(HTTPException) as exc_info:
-        jwt_utils.verify_user(TEST_USER_PAYLOAD, admin_only=True)
-    assert exc_info.value.status_code == 403
-    assert "Admin access required" in exc_info.value.detail
-
-
-def test_verify_user_no_payload():
-    """Test verifying user with no payload."""
-    with pytest.raises(HTTPException) as exc_info:
-        jwt_utils.verify_user(None, admin_only=False)
-    assert exc_info.value.status_code == 401
-    assert "Authorization header is missing" in exc_info.value.detail
-
-
-def test_verify_user_missing_sub():
-    """Test verifying user with payload missing 'sub' field."""
-    invalid_payload = {"role": "user", "email": "test@example.com"}
-    with pytest.raises(HTTPException) as exc_info:
-        jwt_utils.verify_user(invalid_payload, admin_only=False)
-    assert exc_info.value.status_code == 401
-    assert "User ID not found in token" in exc_info.value.detail
-
-
-def test_verify_user_empty_sub():
-    """Test verifying user with empty 'sub' field."""
-    invalid_payload = {"sub": "", "role": "user"}
-    with pytest.raises(HTTPException) as exc_info:
-        jwt_utils.verify_user(invalid_payload, admin_only=False)
-    assert exc_info.value.status_code == 401
-    assert "User ID not found in token" in exc_info.value.detail
-
-
-def test_verify_user_none_sub():
-    """Test verifying user with None 'sub' field."""
-    invalid_payload = {"sub": None, "role": "user"}
-    with pytest.raises(HTTPException) as exc_info:
-        jwt_utils.verify_user(invalid_payload, admin_only=False)
-    assert exc_info.value.status_code == 401
-    assert "User ID not found in token" in exc_info.value.detail
-
-
-def test_verify_user_missing_role_admin_check():
-    """Test verifying admin when role field is missing."""
-    no_role_payload = {"sub": "user-id"}
-    with pytest.raises(KeyError):
-        # This will raise KeyError when checking payload["role"]
-        jwt_utils.verify_user(no_role_payload, admin_only=True)
-
-
-# ======================== EDGE CASES ======================== #
-
-
-def test_jwt_with_additional_claims():
-    """Test JWT token with additional custom claims."""
-    extra_claims_payload = {
-        "sub": "user-id",
-        "role": "user",
-        "aud": "authenticated",
-        "custom_claim": "custom_value",
-        "permissions": ["read", "write"],
-        "metadata": {"key": "value"},
-    }
-    token = create_token(extra_claims_payload)
-
-    result = jwt_utils.parse_jwt_token(token)
-    assert result["sub"] == "user-id"
-    assert result["custom_claim"] == "custom_value"
-    assert result["permissions"] == ["read", "write"]
-
-
-def test_jwt_with_numeric_sub():
-    """Test JWT token with numeric user ID."""
-    payload = {
-        "sub": 12345,  # Numeric ID
-        "role": "user",
-        "aud": "authenticated",
-    }
-    # Should convert to string internally
-    user = jwt_utils.verify_user(payload, admin_only=False)
-    assert user.user_id == 12345
-
-
-def test_jwt_with_very_long_sub():
-    """Test JWT token with very long user ID."""
-    long_id = "a" * 1000
-    payload = {
-        "sub": long_id,
-        "role": "user",
-        "aud": "authenticated",
-    }
-    user = jwt_utils.verify_user(payload, admin_only=False)
-    assert user.user_id == long_id
-
-
-def test_jwt_with_special_characters_in_claims():
-    """Test JWT token with special characters in claims."""
-    payload = {
-        "sub": "user@example.com/special-chars!@#$%",
-        "role": "admin",
-        "aud": "authenticated",
-        "email": "test+special@example.com",
-    }
-    user = jwt_utils.verify_user(payload, admin_only=True)
-    assert "special-chars!@#$%" in user.user_id
-
-
-def test_jwt_with_future_iat():
-    """Test JWT token with issued-at time in future."""
-    future_payload = {
-        "sub": "user-id",
-        "role": "user",
-        "aud": "authenticated",
-        "iat": datetime.now(timezone.utc) + timedelta(hours=1),
-    }
-    token = create_token(future_payload)
-
-    # PyJWT validates iat claim and should reject future tokens
-    with pytest.raises(ValueError, match="not yet valid"):
-        jwt_utils.parse_jwt_token(token)
-
-
-def test_jwt_with_different_algorithms():
-    """Test that only HS256 algorithm is accepted."""
-    payload = {
-        "sub": "user-id",
-        "role": "user",
-        "aud": "authenticated",
-    }
-
-    # Try different algorithms
-    algorithms = ["HS384", "HS512", "none"]
-    for algo in algorithms:
-        if algo == "none":
-            # Special case for 'none' algorithm (security vulnerability if accepted)
-            token = create_token(payload, "", algorithm="none")
-        else:
-            token = create_token(payload, algorithm=algo)
-
-        with pytest.raises(ValueError) as exc_info:
-            jwt_utils.parse_jwt_token(token)
-        assert "Invalid token" in str(exc_info.value)

autogpt_platform/autogpt_libs/autogpt_libs/auth/middleware.py

@@ -0,0 +1,139 @@
+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
+
+logger = logging.getLogger(__name__)
+bearer_auth = HTTPBearer(auto_error=False)
+
+
+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 {}
+
+    credentials = await bearer_auth(request)
+
+    if not credentials:
+        raise HTTPException(status_code=401, detail="Not authenticated")
+
+    try:
+        payload = parse_jwt_token(credentials.credentials)
+        request.state.user = payload
+        logger.debug("Token decoded successfully")
+    except ValueError as e:
+        raise HTTPException(status_code=401, detail=str(e))
+    return payload
+
+
+class APIKeyValidator:
+    """
+    Configurable API key validator that supports custom validation functions
+    for FastAPI applications.
+
+    This class provides a flexible way to implement API key authentication with optional
+    custom validation logic. It can be used for simple token matching
+    or more complex validation scenarios like database lookups.
+
+    Examples:
+        Simple token validation:
+        ```python
+        validator = APIKeyValidator(
+            header_name="X-API-Key",
+            expected_token="your-secret-token"
+        )
+
+        @app.get("/protected", dependencies=[Depends(validator.get_dependency())])
+        def protected_endpoint():
+            return {"message": "Access granted"}
+        ```
+
+        Custom validation with database lookup:
+        ```python
+        async def validate_with_db(api_key: str):
+            api_key_obj = await db.get_api_key(api_key)
+            return api_key_obj if api_key_obj and api_key_obj.is_active else None
+
+        validator = APIKeyValidator(
+            header_name="X-API-Key",
+            validate_fn=validate_with_db
+        )
+        ```
+
+    Args:
+        header_name (str): The name of the header containing the API key
+        expected_token (Optional[str]): The expected API key value for simple token matching
+        validate_fn (Optional[Callable]): Custom validation function that takes an API key
+            string and returns a boolean or object. Can be async.
+        error_status (int): HTTP status code to use for validation errors
+        error_message (str): Error message to return when validation fails
+    """
+
+    def __init__(
+        self,
+        header_name: str,
+        expected_token: Optional[str] = None,
+        validate_fn: Optional[Callable[[str], bool]] = None,
+        error_status: int = HTTP_401_UNAUTHORIZED,
+        error_message: str = "Invalid API key",
+    ):
+        # Create the APIKeyHeader as a class property
+        self.security_scheme = APIKeyHeader(name=header_name)
+        self.expected_token = expected_token
+        self.custom_validate_fn = validate_fn
+        self.error_status = error_status
+        self.error_message = error_message
+
+    async def default_validator(self, api_key: str) -> bool:
+        if not self.expected_token:
+            raise ValueError(
+                "Expected Token Required to be set when uisng API Key Validator default validation"
+            )
+        return secrets.compare_digest(api_key, self.expected_token)
+
+    async def __call__(
+        self, request: Request, api_key: str = Security(APIKeyHeader)
+    ) -> Any:
+        if api_key is None:
+            raise HTTPException(status_code=self.error_status, detail="Missing API key")
+
+        # Use custom validation if provided, otherwise use default equality check
+        validator = self.custom_validate_fn or self.default_validator
+        result = (
+            await validator(api_key)
+            if inspect.iscoroutinefunction(validator)
+            else validator(api_key)
+        )
+
+        if not result:
+            raise HTTPException(
+                status_code=self.error_status, detail=self.error_message
+            )
+
+        # Store validation result in request state if it's not just a boolean
+        if result is not True:
+            request.state.api_key = result
+
+        return result
+
+    def get_dependency(self):
+        """
+        Returns a callable dependency that FastAPI will recognize as a security scheme
+        """
+
+        async def validate_api_key(
+            request: Request, api_key: str = Security(self.security_scheme)
+        ) -> Any:
+            return await self(request, api_key)
+
+        # This helps FastAPI recognize it as a security dependency
+        validate_api_key.__name__ = f"validate_{self.security_scheme.model.name}"
+        return validate_api_key

autogpt_platform/autogpt_libs/autogpt_libs/rate_limit/config.py

@@ -1,5 +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

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

@@ -16,7 +16,12 @@ from unittest.mock import Mock
 
 import pytest
 
-from autogpt_libs.utils.cache import cached, clear_thread_cache, thread_cached
+from autogpt_libs.utils.cache import (
+    async_cache,
+    async_ttl_cache,
+    clear_thread_cache,
+    thread_cached,
+)
 
 
 class TestThreadCached:
@@ -325,202 +330,102 @@ class TestThreadCached:
         assert mock.call_count == 2
 
 
-class TestCache:
-    """Tests for the unified @cache decorator (works for both sync and async)."""
-
-    def test_basic_sync_caching(self):
-        """Test basic sync caching functionality."""
-        call_count = 0
-
-        @cached()
-        def expensive_sync_function(x: int, y: int = 0) -> int:
-            nonlocal call_count
-            call_count += 1
-            return x + y
-
-        # First call
-        result1 = expensive_sync_function(1, 2)
-        assert result1 == 3
-        assert call_count == 1
-
-        # Second call with same args - should use cache
-        result2 = expensive_sync_function(1, 2)
-        assert result2 == 3
-        assert call_count == 1
-
-        # Different args - should call function again
-        result3 = expensive_sync_function(2, 3)
-        assert result3 == 5
-        assert call_count == 2
+class TestAsyncTTLCache:
+    """Tests for the @async_ttl_cache decorator."""
 
     @pytest.mark.asyncio
-    async def test_basic_async_caching(self):
-        """Test basic async caching functionality."""
+    async def test_basic_caching(self):
+        """Test basic caching functionality."""
         call_count = 0
 
-        @cached()
-        async def expensive_async_function(x: int, y: int = 0) -> int:
+        @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 expensive_async_function(1, 2)
+        result1 = await cached_function(1, 2)
         assert result1 == 3
         assert call_count == 1
 
         # Second call with same args - should use cache
-        result2 = await expensive_async_function(1, 2)
+        result2 = await cached_function(1, 2)
         assert result2 == 3
-        assert call_count == 1
+        assert call_count == 1  # No additional call
 
         # Different args - should call function again
-        result3 = await expensive_async_function(2, 3)
+        result3 = await cached_function(2, 3)
         assert result3 == 5
         assert call_count == 2
 
-    def test_sync_thundering_herd_protection(self):
-        """Test that concurrent sync calls don't cause thundering herd."""
-        call_count = 0
-        results = []
-
-        @cached()
-        def slow_function(x: int) -> int:
-            nonlocal call_count
-            call_count += 1
-            time.sleep(0.1)  # Simulate expensive operation
-            return x * x
-
-        def worker():
-            result = slow_function(5)
-            results.append(result)
-
-        # Launch multiple concurrent threads
-        with ThreadPoolExecutor(max_workers=5) as executor:
-            futures = [executor.submit(worker) for _ in range(5)]
-            for future in futures:
-                future.result()
-
-        # All results should be the same
-        assert all(result == 25 for result in results)
-        # Only one thread should have executed the expensive operation
-        assert call_count == 1
-
     @pytest.mark.asyncio
-    async def test_async_thundering_herd_protection(self):
-        """Test that concurrent async calls don't cause thundering herd."""
+    async def test_ttl_expiration(self):
+        """Test that cache entries expire after TTL."""
         call_count = 0
 
-        @cached()
-        async def slow_async_function(x: int) -> int:
+        @async_ttl_cache(maxsize=10, ttl_seconds=1)  # Short TTL
+        async def short_lived_cache(x: int) -> int:
             nonlocal call_count
             call_count += 1
-            await asyncio.sleep(0.1)  # Simulate expensive operation
-            return x * x
-
-        # Launch concurrent coroutines
-        tasks = [slow_async_function(7) for _ in range(5)]
-        results = await asyncio.gather(*tasks)
-
-        # All results should be the same
-        assert all(result == 49 for result in results)
-        # Only one coroutine should have executed the expensive operation
-        assert call_count == 1
-
-    def test_ttl_functionality(self):
-        """Test TTL functionality with sync function."""
-        call_count = 0
-
-        @cached(maxsize=10, ttl_seconds=1)  # Short TTL
-        def ttl_function(x: int) -> int:
-            nonlocal call_count
-            call_count += 1
-            return x * 3
+            return x * 2
 
         # First call
-        result1 = ttl_function(3)
-        assert result1 == 9
+        result1 = await short_lived_cache(5)
+        assert result1 == 10
         assert call_count == 1
 
         # Second call immediately - should use cache
-        result2 = ttl_function(3)
-        assert result2 == 9
-        assert call_count == 1
-
-        # Wait for TTL to expire
-        time.sleep(1.1)
-
-        # Third call after expiration - should call function again
-        result3 = ttl_function(3)
-        assert result3 == 9
-        assert call_count == 2
-
-    @pytest.mark.asyncio
-    async def test_async_ttl_functionality(self):
-        """Test TTL functionality with async function."""
-        call_count = 0
-
-        @cached(maxsize=10, ttl_seconds=1)  # Short TTL
-        async def async_ttl_function(x: int) -> int:
-            nonlocal call_count
-            call_count += 1
-            await asyncio.sleep(0.01)
-            return x * 4
-
-        # First call
-        result1 = await async_ttl_function(3)
-        assert result1 == 12
-        assert call_count == 1
-
-        # Second call immediately - should use cache
-        result2 = await async_ttl_function(3)
-        assert result2 == 12
+        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 async_ttl_function(3)
-        assert result3 == 12
+        result3 = await short_lived_cache(5)
+        assert result3 == 10
         assert call_count == 2
 
-    def test_cache_info(self):
+    @pytest.mark.asyncio
+    async def test_cache_info(self):
         """Test cache info functionality."""
 
-        @cached(maxsize=10, ttl_seconds=60)
-        def info_test_function(x: int) -> int:
+        @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"] == 10
-        assert info["ttl_seconds"] == 60
+        assert info["maxsize"] == 5
+        assert info["ttl_seconds"] == 300
 
         # Add an entry
-        info_test_function(1)
+        await info_test_function(1)
         info = info_test_function.cache_info()
         assert info["size"] == 1
 
-    def test_cache_clear(self):
+    @pytest.mark.asyncio
+    async def test_cache_clear(self):
         """Test cache clearing functionality."""
         call_count = 0
 
-        @cached()
-        def clearable_function(x: int) -> int:
+        @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 = clearable_function(2)
+        result1 = await clearable_function(2)
         assert result1 == 8
         assert call_count == 1
 
         # Second call - should use cache
-        result2 = clearable_function(2)
+        result2 = await clearable_function(2)
         assert result2 == 8
         assert call_count == 1
 
@@ -528,149 +433,273 @@ class TestCache:
         clearable_function.cache_clear()
 
         # Third call after clear - should call function again
-        result3 = clearable_function(2)
+        result3 = await clearable_function(2)
         assert result3 == 8
         assert call_count == 2
 
     @pytest.mark.asyncio
-    async def test_async_cache_clear(self):
-        """Test cache clearing functionality with async function."""
+    async def test_maxsize_cleanup(self):
+        """Test that cache cleans up when maxsize is exceeded."""
         call_count = 0
 
-        @cached()
-        async def async_clearable_function(x: int) -> int:
+        @async_ttl_cache(maxsize=3, ttl_seconds=60)
+        async def size_limited_function(x: int) -> int:
             nonlocal call_count
             call_count += 1
-            await asyncio.sleep(0.01)
-            return x * 5
+            return x**2
 
-        # First call
-        result1 = await async_clearable_function(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
 
-        # Second call - should use cache
-        result2 = await async_clearable_function(2)
+        # Same successful call - should use cache
+        result2 = await exception_function(5)
         assert result2 == 10
         assert call_count == 1
 
-        # Clear cache
-        async_clearable_function.cache_clear()
-
-        # Third call after clear - should call function again
-        result3 = await async_clearable_function(2)
-        assert result3 == 10
+        # 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_async_function_returns_results_not_coroutines(self):
-        """Test that cached async functions return actual results, not coroutines."""
+    async def test_concurrent_calls(self):
+        """Test caching behavior with concurrent calls."""
         call_count = 0
 
-        @cached()
-        async def async_result_function(x: int) -> str:
+        @async_ttl_cache(maxsize=10, ttl_seconds=60)
+        async def concurrent_function(x: int) -> int:
             nonlocal call_count
             call_count += 1
-            await asyncio.sleep(0.01)
-            return f"result_{x}"
+            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 async_result_function(1)
-        assert result1 == "result_1"
-        assert isinstance(result1, str)  # Should be string, not coroutine
+        result1 = await cached_function(1, 2)
+        assert result1 == 3
         assert call_count == 1
 
-        # Second call - should return cached result (string), not coroutine
-        result2 = await async_result_function(1)
-        assert result2 == "result_1"
-        assert isinstance(result2, str)  # Should be string, not coroutine
-        assert call_count == 1  # Function should not be called again
+        # Second call with same args - should use cache
+        result2 = await cached_function(1, 2)
+        assert result2 == 3
+        assert call_count == 1  # No additional call
 
-        # Verify results are identical
-        assert result1 is result2  # Should be same cached object
+        # 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
 
-    def test_cache_delete(self):
-        """Test selective cache deletion functionality."""
-        call_count = 0
-
-        @cached()
-        def deletable_function(x: int) -> int:
-            nonlocal call_count
-            call_count += 1
-            return x * 6
-
-        # First call for x=1
-        result1 = deletable_function(1)
-        assert result1 == 6
-        assert call_count == 1
-
-        # First call for x=2
-        result2 = deletable_function(2)
-        assert result2 == 12
+        # Different args - should call function again
+        result4 = await cached_function(2, 3)
+        assert result4 == 5
         assert call_count == 2
 
-        # Second calls - should use cache
-        assert deletable_function(1) == 6
-        assert deletable_function(2) == 12
-        assert call_count == 2
-
-        # Delete specific entry for x=1
-        was_deleted = deletable_function.cache_delete(1)
-        assert was_deleted is True
-
-        # Call with x=1 should execute function again
-        result3 = deletable_function(1)
-        assert result3 == 6
-        assert call_count == 3
-
-        # Call with x=2 should still use cache
-        assert deletable_function(2) == 12
-        assert call_count == 3
-
-        # Try to delete non-existent entry
-        was_deleted = deletable_function.cache_delete(99)
-        assert was_deleted is False
-
     @pytest.mark.asyncio
-    async def test_async_cache_delete(self):
-        """Test selective cache deletion functionality with async function."""
+    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
 
-        @cached()
-        async def async_deletable_function(x: int) -> int:
+        @async_ttl_cache(maxsize=10, ttl_seconds=None)
+        async def no_ttl_via_none(x: int) -> int:
             nonlocal call_count
             call_count += 1
-            await asyncio.sleep(0.01)
-            return x * 7
+            return x**2
 
-        # First call for x=1
-        result1 = await async_deletable_function(1)
-        assert result1 == 7
+        # First call
+        result1 = await no_ttl_via_none(3)
+        assert result1 == 9
         assert call_count == 1
 
-        # First call for x=2
-        result2 = await async_deletable_function(2)
-        assert result2 == 14
-        assert call_count == 2
+        # Wait (would expire if there was TTL)
+        await asyncio.sleep(0.1)
 
-        # Second calls - should use cache
-        assert await async_deletable_function(1) == 7
-        assert await async_deletable_function(2) == 14
-        assert call_count == 2
+        # Second call - should still use cache
+        result2 = await no_ttl_via_none(3)
+        assert result2 == 9
+        assert call_count == 1  # No additional call
 
-        # Delete specific entry for x=1
-        was_deleted = async_deletable_function.cache_delete(1)
-        assert was_deleted is True
+        # Check cache info
+        info = no_ttl_via_none.cache_info()
+        assert info["ttl_seconds"] is None
 
-        # Call with x=1 should execute function again
-        result3 = await async_deletable_function(1)
-        assert result3 == 7
-        assert call_count == 3
+    @pytest.mark.asyncio
+    async def test_cache_options_comparison(self):
+        """Test different cache options work as expected."""
+        ttl_calls = 0
+        no_ttl_calls = 0
 
-        # Call with x=2 should still use cache
-        assert await async_deletable_function(2) == 14
-        assert call_count == 3
+        @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
 
-        # Try to delete non-existent entry
-        was_deleted = async_deletable_function.cache_delete(99)
-        assert was_deleted is False
+        @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 = [
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@@ -85,87 +85,6 @@ files = [
     {file = "certifi-2025.7.14.tar.gz", hash = "sha256:8ea99dbdfaaf2ba2f9bac77b9249ef62ec5218e7c2b2e903378ed5fccf765995"},
 ]
 
-[[package]]
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-version = "1.17.1"
-description = "Foreign Function Interface for Python calling C code."
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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 = [
     {file = "exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10"},
@@ -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 = [
     {file = "iniconfig-2.1.0-py3-none-any.whl", hash = "sha256:9deba5723312380e77435581c6bf4935c94cbfab9b1ed33ef8d238ea168eb760"},
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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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-    {file = "nodeenv-1.9.1.tar.gz", hash = "sha256:6ec12890a2dab7946721edbfbcd91f3319c6ccc9aec47be7c7e6b7011ee6645f"},
-]
-
 [[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 = [
     {file = "packaging-25.0-py3-none-any.whl", hash = "sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484"},
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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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-    {file = "pycparser-2.22.tar.gz", hash = "sha256:491c8be9c040f5390f5bf44a5b07752bd07f56edf992381b05c701439eec10f6"},
-]
-
 [[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 = [
     {file = "pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b"},
     {file = "pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887"},
@@ -1338,9 +1068,6 @@ files = [
     {file = "pyjwt-2.10.1.tar.gz", hash = "sha256:3cc5772eb20009233caf06e9d8a0577824723b44e6648ee0a2aedb6cf9381953"},
 ]
 
-[package.dependencies]
-cryptography = {version = ">=3.4.0", optional = true, markers = "extra == \"crypto\""}
-
 [package.extras]
 crypto = ["cryptography (>=3.4.0)"]
 dev = ["coverage[toml] (==5.0.4)", "cryptography (>=3.4.0)", "pre-commit", "pytest (>=6.0.0,<7.0.0)", "sphinx", "sphinx-rtd-theme", "zope.interface"]
@@ -1359,34 +1086,13 @@ files = [
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 ]
 
-[[package]]
-name = "pyright"
-version = "1.1.404"
-description = "Command line wrapper for pyright"
-optional = false
-python-versions = ">=3.7"
-groups = ["dev"]
-files = [
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-    {file = "pyright-1.1.404.tar.gz", hash = "sha256:455e881a558ca6be9ecca0b30ce08aa78343ecc031d37a198ffa9a7a1abeb63e"},
-]
-
-[package.dependencies]
-nodeenv = ">=1.6.0"
-typing-extensions = ">=4.1"
-
-[package.extras]
-all = ["nodejs-wheel-binaries", "twine (>=3.4.1)"]
-dev = ["twine (>=3.4.1)"]
-nodejs = ["nodejs-wheel-binaries"]
-
 [[package]]
 name = "pytest"
 version = "8.4.1"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.9"
-groups = ["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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-    {file = "pytest_cov-6.2.1.tar.gz", hash = "sha256:25cc6cc0a5358204b8108ecedc51a9b57b34cc6b8c967cc2c01a4e00d8a67da2"},
-]
-
-[package.dependencies]
-coverage = {version = ">=7.5", extras = ["toml"]}
-pluggy = ">=1.2"
-pytest = ">=6.2.5"
-
-[package.extras]
-testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
-
 [[package]]
 name = "pytest-mock"
 version = "3.14.1"
 description = "Thin-wrapper around the mock package for easier use with pytest"
 optional = false
 python-versions = ">=3.8"
-groups = ["dev"]
+groups = ["main"]
 files = [
     {file = "pytest_mock-3.14.1-py3-none-any.whl", hash = "sha256:178aefcd11307d874b4cd3100344e7e2d888d9791a6a1d9bfe90fbc1b74fd1d0"},
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@@ -1567,31 +1253,31 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.12.11"
+version = "0.12.9"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
 files = [
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-    {file = "ruff-0.12.11-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:411954eca8464595077a93e580e2918d0a01a19317af0a72132283e28ae21bee"},
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-    {file = "ruff-0.12.11-py3-none-win_amd64.whl", hash = "sha256:a3283325960307915b6deb3576b96919ee89432ebd9c48771ca12ee8afe4a0fd"},
-    {file = "ruff-0.12.11-py3-none-win_arm64.whl", hash = "sha256:bae4d6e6a2676f8fb0f98b74594a048bae1b944aab17e9f5d504062303c6dbea"},
-    {file = "ruff-0.12.11.tar.gz", hash = "sha256:c6b09ae8426a65bbee5425b9d0b82796dbb07cb1af045743c79bfb163001165d"},
+    {file = "ruff-0.12.9-py3-none-linux_armv6l.whl", hash = "sha256:fcebc6c79fcae3f220d05585229463621f5dbf24d79fdc4936d9302e177cfa3e"},
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+    {file = "ruff-0.12.9-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a03242c1522b4e0885af63320ad754d53983c9599157ee33e77d748363c561ce"},
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+    {file = "ruff-0.12.9-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:f6be1d2ca0686c54564da8e7ee9e25f93bdd6868263805f8c0b8fc6a449db6d7"},
+    {file = "ruff-0.12.9-py3-none-win32.whl", hash = "sha256:cc7a37bd2509974379d0115cc5608a1a4a6c4bff1b452ea69db83c8855d53f93"},
+    {file = "ruff-0.12.9-py3-none-win_amd64.whl", hash = "sha256:6fb15b1977309741d7d098c8a3cb7a30bc112760a00fb6efb7abc85f00ba5908"},
+    {file = "ruff-0.12.9-py3-none-win_arm64.whl", hash = "sha256:63c8c819739d86b96d500cce885956a1a48ab056bbcbc61b747ad494b2485089"},
+    {file = "ruff-0.12.9.tar.gz", hash = "sha256:fbd94b2e3c623f659962934e52c2bea6fc6da11f667a427a368adaf3af2c866a"},
 ]
 
 [[package]]
@@ -1725,7 +1411,7 @@ 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 +1454,7 @@ 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 +1615,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "0c40b63c3c921846cf05ccfb4e685d4959854b29c2c302245f9832e20aac6954"
+content-hash = "4cc687aabe5865665fb8c4ccc0ea7e0af80b41e401ca37919f57efa6e0b5be00"

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 = "^0.12.9"
 
 [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):
@@ -179,4 +175,4 @@ 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

@@ -9,15 +9,8 @@ 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 Python and build dependencies
 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 \
@@ -27,9 +20,7 @@ RUN apt-get update \
     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
@@ -63,18 +54,13 @@ 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/*
+    python3-pip
 
 # 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 Prisma binaries
 COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
 
 ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"

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 autogpt_libs.utils.cache import cached
-
 logger = logging.getLogger(__name__)
 
 
@@ -16,7 +15,7 @@ if TYPE_CHECKING:
 T = TypeVar("T")
 
 
-@cached()
+@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

@@ -1,6 +1,8 @@
 import logging
 from typing import Any, Optional
 
+from pydantic import JsonValue
+
 from backend.data.block import (
     Block,
     BlockCategory,
@@ -10,7 +12,7 @@ from backend.data.block import (
     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
@@ -31,7 +33,7 @@ class AgentExecutorBlock(Block):
         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
         )
 

autogpt_platform/backend/backend/blocks/ai_image_customizer.py

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

autogpt_platform/backend/backend/blocks/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

@@ -14,13 +14,13 @@ from backend.sdk import (
     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(BlockSchema):
@@ -31,10 +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=[
@@ -54,18 +50,14 @@ class AirtableCreateBaseBlock(Block):
         )
 
     class Output(BlockSchema):
-        base_id: str = SchemaField(description="The ID of the created or found base")
+        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,
@@ -74,31 +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,
@@ -107,7 +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

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

@@ -2,7 +2,7 @@
 Airtable record operation blocks.
 """
 
-from typing import Optional, cast
+from typing import Optional
 
 from backend.sdk import (
     APIKeyCredentials,
@@ -18,9 +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
@@ -56,24 +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(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__(
@@ -87,7 +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,
@@ -103,33 +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):
@@ -144,23 +104,11 @@ class AirtableGetRecordBlock(Block):
         base_id: str = SchemaField(description="The Airtable base ID")
         table_id_or_name: str = SchemaField(description="Table ID or name")
         record_id: str = SchemaField(description="The record ID to retrieve")
-        normalize_output: bool = SchemaField(
-            description="Normalize output to include all fields with proper empty values (disable to skip schema fetch and get raw Airtable response)",
-            default=True,
-        )
-        include_field_metadata: bool = SchemaField(
-            description="Include field type and configuration metadata (requires normalize_output=true)",
-            default=False,
-        )
 
     class Output(BlockSchema):
         id: str = SchemaField(description="The record ID")
         fields: dict = SchemaField(description="The record fields")
         created_time: str = SchemaField(description="The record created time")
-        field_metadata: Optional[dict] = SchemaField(
-            description="Field type and configuration metadata (only when include_field_metadata=true)",
-            default=None,
-        )
 
     def __init__(self):
         super().__init__(
@@ -174,7 +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,
@@ -182,34 +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):
@@ -226,10 +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,
@@ -255,7 +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,
@@ -264,22 +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

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

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

@@ -113,7 +113,6 @@ class DataForSeoClient:
         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.
@@ -126,7 +125,6 @@ class DataForSeoClient:
             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
@@ -150,8 +148,6 @@ class DataForSeoClient:
             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]
 

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

@@ -78,12 +78,6 @@ class DataForSeoRelatedKeywordsBlock(Block):
             ge=1,
             le=3000,
         )
-        depth: int = SchemaField(
-            description="Keyword search depth (0-4). Controls the number of returned keywords: 0=1 keyword, 1=~8 keywords, 2=~72 keywords, 3=~584 keywords, 4=~4680 keywords",
-            default=1,
-            ge=0,
-            le=4,
-        )
 
     class Output(BlockSchema):
         related_keywords: List[RelatedKeyword] = SchemaField(
@@ -160,7 +154,6 @@ class DataForSeoRelatedKeywordsBlock(Block):
             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(

autogpt_platform/backend/backend/blocks/exa/websets.py

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

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

@@ -39,6 +39,18 @@ def serialize_email_recipients(recipients: list[str]) -> str:
     return ", ".join(recipients)
 
 
+def deduplicate_email_addresses(addresses: list[str]) -> list[str]:
+    """Deduplicate email addresses while preserving order.
+
+    Args:
+        addresses: List of email addresses that may contain duplicates or None values
+
+    Returns:
+        List of unique email addresses with None values filtered out
+    """
+    return list(dict.fromkeys(filter(None, addresses)))
+
+
 def _make_mime_text(
     body: str,
     content_type: Optional[Literal["auto", "plain", "html"]] = None,
@@ -1094,117 +1106,6 @@ class GmailGetThreadBlock(GmailBase):
         return thread
 
 
-async def _build_reply_message(
-    service, input_data, graph_exec_id: str, user_id: str
-) -> tuple[str, str]:
-    """
-    Builds a reply MIME message for Gmail threads.
-
-    Returns:
-        tuple: (base64-encoded raw message, threadId)
-    """
-    # Get parent message for reply context
-    parent = await asyncio.to_thread(
-        lambda: service.users()
-        .messages()
-        .get(
-            userId="me",
-            id=input_data.parentMessageId,
-            format="metadata",
-            metadataHeaders=[
-                "Subject",
-                "References",
-                "Message-ID",
-                "From",
-                "To",
-                "Cc",
-                "Reply-To",
-            ],
-        )
-        .execute()
-    )
-
-    # Build headers dictionary, preserving all values for duplicate headers
-    headers = {}
-    for h in parent.get("payload", {}).get("headers", []):
-        name = h["name"].lower()
-        value = h["value"]
-        if name in headers:
-            # For duplicate headers, keep the first occurrence (most relevant for reply context)
-            continue
-        headers[name] = value
-
-    # Determine recipients if not specified
-    if not (input_data.to or input_data.cc or input_data.bcc):
-        if input_data.replyAll:
-            recipients = [parseaddr(headers.get("from", ""))[1]]
-            recipients += [addr for _, addr in getaddresses([headers.get("to", "")])]
-            recipients += [addr for _, addr in getaddresses([headers.get("cc", "")])]
-            # Use dict.fromkeys() for O(n) deduplication while preserving order
-            input_data.to = list(dict.fromkeys(filter(None, recipients)))
-        else:
-            # Check Reply-To header first, fall back to From header
-            reply_to = headers.get("reply-to", "")
-            from_addr = headers.get("from", "")
-            sender = parseaddr(reply_to if reply_to else from_addr)[1]
-            input_data.to = [sender] if sender else []
-
-    # Set subject with Re: prefix if not already present
-    if input_data.subject:
-        subject = input_data.subject
-    else:
-        parent_subject = headers.get("subject", "").strip()
-        # Only add "Re:" if not already present (case-insensitive check)
-        if parent_subject.lower().startswith("re:"):
-            subject = parent_subject
-        else:
-            subject = f"Re: {parent_subject}" if parent_subject else "Re:"
-
-    # Build references header for proper threading
-    references = headers.get("references", "").split()
-    if headers.get("message-id"):
-        references.append(headers["message-id"])
-
-    # Create MIME message
-    msg = MIMEMultipart()
-    if input_data.to:
-        msg["To"] = ", ".join(input_data.to)
-    if input_data.cc:
-        msg["Cc"] = ", ".join(input_data.cc)
-    if input_data.bcc:
-        msg["Bcc"] = ", ".join(input_data.bcc)
-    msg["Subject"] = subject
-    if headers.get("message-id"):
-        msg["In-Reply-To"] = headers["message-id"]
-    if references:
-        msg["References"] = " ".join(references)
-
-    # Use the helper function for consistent content type handling
-    msg.attach(_make_mime_text(input_data.body, input_data.content_type))
-
-    # Handle attachments
-    for attach in input_data.attachments:
-        local_path = await store_media_file(
-            user_id=user_id,
-            graph_exec_id=graph_exec_id,
-            file=attach,
-            return_content=False,
-        )
-        abs_path = get_exec_file_path(graph_exec_id, local_path)
-        part = MIMEBase("application", "octet-stream")
-        with open(abs_path, "rb") as f:
-            part.set_payload(f.read())
-        encoders.encode_base64(part)
-        part.add_header(
-            "Content-Disposition", f"attachment; filename={Path(abs_path).name}"
-        )
-        msg.attach(part)
-
-    # Encode message
-    raw = base64.urlsafe_b64encode(msg.as_bytes()).decode("utf-8")
-    return raw, input_data.threadId
-
-
 class GmailReplyBlock(GmailBase):
     """
     Replies to Gmail threads with intelligent content type detection.
@@ -1341,31 +1242,102 @@ class GmailReplyBlock(GmailBase):
     async def _reply(
         self, service, input_data: Input, graph_exec_id: str, user_id: str
     ) -> dict:
-        # Build the reply message using the shared helper
-        raw, thread_id = await _build_reply_message(
-            service, input_data, graph_exec_id, user_id
+        parent = await asyncio.to_thread(
+            lambda: service.users()
+            .messages()
+            .get(
+                userId="me",
+                id=input_data.parentMessageId,
+                format="metadata",
+                metadataHeaders=[
+                    "Subject",
+                    "References",
+                    "Message-ID",
+                    "From",
+                    "To",
+                    "Cc",
+                    "Reply-To",
+                ],
+            )
+            .execute()
         )
 
-        # Send the message
+        headers = {
+            h["name"].lower(): h["value"]
+            for h in parent.get("payload", {}).get("headers", [])
+        }
+        if not (input_data.to or input_data.cc or input_data.bcc):
+            if input_data.replyAll:
+                recipients = [parseaddr(headers.get("from", ""))[1]]
+                recipients += [
+                    addr for _, addr in getaddresses([headers.get("to", "")])
+                ]
+                recipients += [
+                    addr for _, addr in getaddresses([headers.get("cc", "")])
+                ]
+                # Deduplicate recipients while preserving order
+                input_data.to = deduplicate_email_addresses(recipients)
+            else:
+                sender = parseaddr(headers.get("reply-to", headers.get("from", "")))[1]
+                input_data.to = [sender] if sender else []
+        subject = input_data.subject or (f"Re: {headers.get('subject', '')}".strip())
+        references = headers.get("references", "").split()
+        if headers.get("message-id"):
+            references.append(headers["message-id"])
+
+        msg = MIMEMultipart()
+        if input_data.to:
+            msg["To"] = ", ".join(input_data.to)
+        if input_data.cc:
+            msg["Cc"] = ", ".join(input_data.cc)
+        if input_data.bcc:
+            msg["Bcc"] = ", ".join(input_data.bcc)
+        msg["Subject"] = subject
+        if headers.get("message-id"):
+            msg["In-Reply-To"] = headers["message-id"]
+        if references:
+            msg["References"] = " ".join(references)
+        # Use the new helper function for consistent content type handling
+        msg.attach(_make_mime_text(input_data.body, input_data.content_type))
+
+        for attach in input_data.attachments:
+            local_path = await store_media_file(
+                user_id=user_id,
+                graph_exec_id=graph_exec_id,
+                file=attach,
+                return_content=False,
+            )
+            abs_path = get_exec_file_path(graph_exec_id, local_path)
+            part = MIMEBase("application", "octet-stream")
+            with open(abs_path, "rb") as f:
+                part.set_payload(f.read())
+            encoders.encode_base64(part)
+            part.add_header(
+                "Content-Disposition", f"attachment; filename={Path(abs_path).name}"
+            )
+            msg.attach(part)
+
+        raw = base64.urlsafe_b64encode(msg.as_bytes()).decode("utf-8")
         return await asyncio.to_thread(
             lambda: service.users()
             .messages()
-            .send(userId="me", body={"threadId": thread_id, "raw": raw})
+            .send(userId="me", body={"threadId": input_data.threadId, "raw": raw})
             .execute()
         )
 
 
-class GmailDraftReplyBlock(GmailBase):
+class GmailCreateDraftReplyBlock(GmailBase):
     """
     Creates draft replies to Gmail threads with intelligent content type detection.
 
     Features:
     - Automatic HTML detection: Draft replies containing HTML tags are formatted as text/html
-    - No hard-wrap for plain text: Plain text draft replies preserve natural line flow
+    - No hard-wrap for plain text: Plain text drafts preserve natural line flow
     - Manual content type override: Use content_type parameter to force specific format
-    - Reply-all functionality: Option to reply to all original recipients
+    - Reply-all functionality: Option to draft reply to all original recipients
     - Thread preservation: Maintains proper email threading with headers
     - Full Unicode/emoji support with UTF-8 encoding
+    - Attachment support for multiple files
     """
 
     class Input(BlockSchema):
@@ -1405,31 +1377,31 @@ class GmailDraftReplyBlock(GmailBase):
 
     def __init__(self):
         super().__init__(
-            id="d7a9f3e2-8b4c-4d6f-9e1a-3c5b7f8d2a6e",
-            description="Create draft replies to Gmail threads with automatic HTML detection and proper text formatting. Plain text draft replies maintain natural paragraph flow without 78-character line wrapping. HTML content is automatically detected and formatted correctly.",
+            id="8f2e9d3c-4b1a-4c7e-9a2f-1d3e5f7a9b1c",
+            description="Create draft replies to Gmail threads with automatic HTML detection and proper text formatting. Drafts maintain proper email threading and can be edited before sending.",
             categories={BlockCategory.COMMUNICATION},
-            input_schema=GmailDraftReplyBlock.Input,
-            output_schema=GmailDraftReplyBlock.Output,
+            input_schema=GmailCreateDraftReplyBlock.Input,
+            output_schema=GmailCreateDraftReplyBlock.Output,
             disabled=not GOOGLE_OAUTH_IS_CONFIGURED,
             test_input={
                 "threadId": "t1",
                 "parentMessageId": "m1",
-                "body": "Thanks for your message. I'll review and get back to you.",
+                "body": "Thanks for your message. I'll draft a response.",
                 "replyAll": False,
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
             test_credentials=TEST_CREDENTIALS,
             test_output=[
                 ("draftId", "draft1"),
-                ("messageId", "m2"),
+                ("messageId", "msg1"),
                 ("threadId", "t1"),
-                ("status", "draft_created"),
+                ("status", "draft_reply_created"),
             ],
             test_mock={
                 "_create_draft_reply": lambda *args, **kwargs: {
                     "id": "draft1",
-                    "message": {"id": "m2", "threadId": "t1"},
-                }
+                    "message": {"id": "msg1", "threadId": "t1"},
+                },
             },
         )
 
@@ -1443,26 +1415,117 @@ class GmailDraftReplyBlock(GmailBase):
         **kwargs,
     ) -> BlockOutput:
         service = self._build_service(credentials, **kwargs)
-        draft = await self._create_draft_reply(
+        result = await self._create_draft_reply(
             service,
             input_data,
             graph_exec_id,
             user_id,
         )
-        yield "draftId", draft["id"]
-        yield "messageId", draft["message"]["id"]
-        yield "threadId", draft["message"].get("threadId", input_data.threadId)
-        yield "status", "draft_created"
+        yield "draftId", result["id"]
+        yield "messageId", result["message"]["id"]
+        yield "threadId", result["message"].get("threadId", input_data.threadId)
+        yield "status", "draft_reply_created"
 
     async def _create_draft_reply(
         self, service, input_data: Input, graph_exec_id: str, user_id: str
     ) -> dict:
-        # Build the reply message using the shared helper
-        raw, thread_id = await _build_reply_message(
-            service, input_data, graph_exec_id, user_id
+        # Fetch parent message metadata
+        parent = await asyncio.to_thread(
+            lambda: service.users()
+            .messages()
+            .get(
+                userId="me",
+                id=input_data.parentMessageId,
+                format="metadata",
+                metadataHeaders=[
+                    "Subject",
+                    "References",
+                    "Message-ID",
+                    "From",
+                    "To",
+                    "Cc",
+                    "Reply-To",
+                ],
+            )
+            .execute()
         )
 
-        # Create draft with proper thread association
+        headers = {
+            h["name"].lower(): h["value"]
+            for h in parent.get("payload", {}).get("headers", [])
+        }
+
+        # Auto-populate recipients if not provided
+        if not (input_data.to or input_data.cc or input_data.bcc):
+            if input_data.replyAll:
+                # Reply all - include all original recipients
+                recipients = [parseaddr(headers.get("from", ""))[1]]
+                recipients += [
+                    addr for _, addr in getaddresses([headers.get("to", "")])
+                ]
+                recipients += [
+                    addr for _, addr in getaddresses([headers.get("cc", "")])
+                ]
+                # Deduplicate recipients
+                dedup: list[str] = []
+                for r in recipients:
+                    if r and r not in dedup:
+                        dedup.append(r)
+                input_data.to = dedup
+            else:
+                # Reply to sender only
+                sender = parseaddr(headers.get("reply-to", headers.get("from", "")))[1]
+                input_data.to = [sender] if sender else []
+
+        # Generate subject with Re: prefix if needed
+        subject = input_data.subject or (f"Re: {headers.get('subject', '')}".strip())
+
+        # Build References header chain
+        references = headers.get("references", "").split()
+        if headers.get("message-id"):
+            references.append(headers["message-id"])
+
+        # Create MIME message with threading headers
+        msg = MIMEMultipart()
+        if input_data.to:
+            msg["To"] = ", ".join(input_data.to)
+        if input_data.cc:
+            msg["Cc"] = ", ".join(input_data.cc)
+        if input_data.bcc:
+            msg["Bcc"] = ", ".join(input_data.bcc)
+        msg["Subject"] = subject
+
+        # Set threading headers for proper conversation grouping
+        if headers.get("message-id"):
+            msg["In-Reply-To"] = headers["message-id"]
+        if references:
+            msg["References"] = " ".join(references)
+
+        # Add body with proper content type handling
+        msg.attach(_make_mime_text(input_data.body, input_data.content_type))
+
+        # Handle attachments if any
+        for attach in input_data.attachments:
+            local_path = await store_media_file(
+                user_id=user_id,
+                graph_exec_id=graph_exec_id,
+                file=attach,
+                return_content=False,
+            )
+            abs_path = get_exec_file_path(graph_exec_id, local_path)
+            part = MIMEBase("application", "octet-stream")
+            with open(abs_path, "rb") as f:
+                part.set_payload(f.read())
+            encoders.encode_base64(part)
+            part.add_header(
+                "Content-Disposition", f"attachment; filename={Path(abs_path).name}"
+            )
+            msg.attach(part)
+
+        # Encode message for Gmail API
+        raw = base64.urlsafe_b64encode(msg.as_bytes()).decode("utf-8")
+
+        # Create draft with threadId to ensure it appears as a reply
         draft = await asyncio.to_thread(
             lambda: service.users()
             .drafts()
@@ -1470,7 +1533,7 @@ class GmailDraftReplyBlock(GmailBase):
                 userId="me",
                 body={
                     "message": {
-                        "threadId": thread_id,
+                        "threadId": input_data.threadId,
                         "raw": raw,
                     }
                 },

autogpt_platform/backend/backend/blocks/ideogram.py

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

autogpt_platform/backend/backend/blocks/io.py

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

autogpt_platform/backend/backend/blocks/llm.py

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

autogpt_platform/backend/backend/blocks/smart_decision_maker.py

@@ -14,7 +14,6 @@ from backend.data.block import (
     BlockType,
 )
 from backend.data.model import NodeExecutionStats, SchemaField
-from backend.data.optional_block import get_optional_config
 from backend.util import json
 from backend.util.clients import get_database_manager_async_client
 
@@ -389,9 +388,7 @@ class SmartDecisionMakerBlock(Block):
         return {"type": "function", "function": tool_function}
 
     @staticmethod
-    async def _create_function_signature(
-        node_id: str, user_id: str | None = None, check_optional: bool = True
-    ) -> list[dict[str, Any]]:
+    async def _create_function_signature(node_id: str) -> list[dict[str, Any]]:
         """
         Creates function signatures for tools linked to a specified node within a graph.
 
@@ -401,8 +398,6 @@ class SmartDecisionMakerBlock(Block):
 
         Args:
             node_id: The node_id for which to create function signatures.
-            user_id: The ID of the user, used for checking credential-based optional blocks.
-            check_optional: Whether to check and skip optional blocks based on their conditions.
 
         Returns:
             list[dict[str, Any]]: A list of dictionaries, each representing a function signature
@@ -434,41 +429,6 @@ class SmartDecisionMakerBlock(Block):
             if not sink_node:
                 raise ValueError(f"Sink node not found: {links[0].sink_id}")
 
-            # todo: use the renamed value of metadata when available
-
-            # Check if this node is marked as optional and should be skipped
-            optional_config = get_optional_config(sink_node.metadata)
-            if optional_config and optional_config.enabled and check_optional:
-                # Check conditions to determine if block should be skipped
-                skip_block = False
-
-                # Check credential availability if configured
-                if optional_config.conditions.on_missing_credentials and user_id:
-                    # Get credential fields from the block
-                    sink_block = sink_node.block
-                    if hasattr(sink_block, "input_schema"):
-                        creds_fields = sink_block.input_schema.get_credentials_fields()
-                        if creds_fields:
-                            # For Smart Decision Maker, we simplify by assuming
-                            # credentials might be missing if optional is enabled
-                            # Full check happens at execution time
-                            logger.debug(
-                                f"Optional block {sink_node.id} may be skipped based on credentials"
-                            )
-                            # Continue to exclude from available tools
-                            continue
-
-                # If other conditions exist but can't be checked now, be conservative
-                if (
-                    optional_config.conditions.input_flag
-                    or optional_config.conditions.kv_flag
-                ):
-                    # These runtime flags can't be checked here, so exclude the block
-                    logger.debug(
-                        f"Optional block {sink_node.id} excluded due to runtime conditions"
-                    )
-                    continue
-
             if sink_node.block_id == AgentExecutorBlock().id:
                 return_tool_functions.append(
                     await SmartDecisionMakerBlock._create_agent_function_signature(
@@ -496,9 +456,7 @@ class SmartDecisionMakerBlock(Block):
         user_id: str,
         **kwargs,
     ) -> BlockOutput:
-        tool_functions = await self._create_function_signature(
-            node_id, user_id=user_id, check_optional=True
-        )
+        tool_functions = await self._create_function_signature(node_id)
         yield "tool_functions", json.dumps(tool_functions)
 
         input_data.conversation_history = input_data.conversation_history or []
@@ -565,6 +523,7 @@ class SmartDecisionMakerBlock(Block):
             credentials=credentials,
             llm_model=input_data.model,
             prompt=prompt,
+            json_format=False,
             max_tokens=input_data.max_tokens,
             tools=tool_functions,
             ollama_host=input_data.ollama_host,

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

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

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

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

autogpt_platform/backend/backend/blocks/test/test_llm.py

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

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

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

autogpt_platform/backend/backend/blocks/text.py

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

autogpt_platform/backend/backend/blocks/wordpress/_api.py

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

autogpt_platform/backend/backend/conftest.py

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

autogpt_platform/backend/backend/data/__init__.py

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

autogpt_platform/backend/backend/data/api_key.py

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

autogpt_platform/backend/backend/data/block.py

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

autogpt_platform/backend/backend/data/block_cost_config.py

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

autogpt_platform/backend/backend/data/cost.py

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

autogpt_platform/backend/backend/data/credit.py

@@ -2,7 +2,7 @@ import logging
 from abc import ABC, abstractmethod
 from collections import defaultdict
 from datetime import datetime, timezone
-from typing import TYPE_CHECKING, Any, cast
+from typing import Any, cast
 
 import stripe
 from prisma import Json
@@ -23,6 +23,7 @@ from pydantic import BaseModel
 
 from backend.data import db
 from backend.data.block_cost_config import BLOCK_COSTS
+from backend.data.cost import BlockCost
 from backend.data.model import (
     AutoTopUpConfig,
     RefundRequest,
@@ -40,9 +41,6 @@ from backend.util.models import Pagination
 from backend.util.retry import func_retry
 from backend.util.settings import Settings
 
-if TYPE_CHECKING:
-    from backend.data.block import Block, BlockCost
-
 settings = Settings()
 stripe.api_key = settings.secrets.stripe_api_key
 logger = logging.getLogger(__name__)
@@ -999,14 +997,10 @@ def get_user_credit_model() -> UserCreditBase:
     return UserCredit()
 
 
-def get_block_costs() -> dict[str, list["BlockCost"]]:
+def get_block_costs() -> dict[str, list[BlockCost]]:
     return {block().id: costs for block, costs in BLOCK_COSTS.items()}
 
 
-def get_block_cost(block: "Block") -> list["BlockCost"]:
-    return BLOCK_COSTS.get(block.__class__, [])
-
-
 async def get_stripe_customer_id(user_id: str) -> str:
     user = await get_user_by_id(user_id)
 

autogpt_platform/backend/backend/data/db.py

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

autogpt_platform/backend/backend/data/execution.py

@@ -11,14 +11,11 @@ from typing import (
     Generator,
     Generic,
     Literal,
-    Mapping,
     Optional,
     TypeVar,
-    cast,
     overload,
 )
 
-from prisma import Json
 from prisma.enums import AgentExecutionStatus
 from prisma.models import (
     AgentGraphExecution,
@@ -27,6 +24,7 @@ from prisma.models import (
     AgentNodeExecutionKeyValueData,
 )
 from prisma.types import (
+    AgentGraphExecutionCreateInput,
     AgentGraphExecutionUpdateManyMutationInput,
     AgentGraphExecutionWhereInput,
     AgentNodeExecutionCreateInput,
@@ -62,7 +60,7 @@ from .includes import (
     GRAPH_EXECUTION_INCLUDE_WITH_NODES,
     graph_execution_include,
 )
-from .model import CredentialsMetaInput, GraphExecutionStats, NodeExecutionStats
+from .model import GraphExecutionStats, NodeExecutionStats
 
 T = TypeVar("T")
 
@@ -89,37 +87,6 @@ class BlockErrorStats(BaseModel):
 
 
 ExecutionStatus = AgentExecutionStatus
-NodeInputMask = Mapping[str, JsonValue]
-NodesInputMasks = Mapping[str, NodeInputMask]
-
-# dest: source
-VALID_STATUS_TRANSITIONS = {
-    ExecutionStatus.QUEUED: [
-        ExecutionStatus.INCOMPLETE,
-    ],
-    ExecutionStatus.RUNNING: [
-        ExecutionStatus.INCOMPLETE,
-        ExecutionStatus.QUEUED,
-        ExecutionStatus.TERMINATED,  # For resuming halted execution
-    ],
-    ExecutionStatus.COMPLETED: [
-        ExecutionStatus.RUNNING,
-    ],
-    ExecutionStatus.FAILED: [
-        ExecutionStatus.INCOMPLETE,
-        ExecutionStatus.QUEUED,
-        ExecutionStatus.RUNNING,
-    ],
-    ExecutionStatus.TERMINATED: [
-        ExecutionStatus.INCOMPLETE,
-        ExecutionStatus.QUEUED,
-        ExecutionStatus.RUNNING,
-    ],
-    ExecutionStatus.SKIPPED: [
-        ExecutionStatus.INCOMPLETE,
-        ExecutionStatus.QUEUED,
-    ],
-}
 
 
 class GraphExecutionMeta(BaseDbModel):
@@ -127,15 +94,10 @@ class GraphExecutionMeta(BaseDbModel):
     user_id: str
     graph_id: str
     graph_version: int
-    inputs: Optional[BlockInput]  # no default -> required in the OpenAPI spec
-    credential_inputs: Optional[dict[str, CredentialsMetaInput]]
-    nodes_input_masks: Optional[dict[str, BlockInput]]
-    preset_id: Optional[str]
+    preset_id: Optional[str] = None
     status: ExecutionStatus
     started_at: datetime
     ended_at: datetime
-    is_shared: bool = False
-    share_token: Optional[str] = None
 
     class Stats(BaseModel):
         model_config = ConfigDict(
@@ -217,18 +179,6 @@ class GraphExecutionMeta(BaseDbModel):
             user_id=_graph_exec.userId,
             graph_id=_graph_exec.agentGraphId,
             graph_version=_graph_exec.agentGraphVersion,
-            inputs=cast(BlockInput | None, _graph_exec.inputs),
-            credential_inputs=(
-                {
-                    name: CredentialsMetaInput.model_validate(cmi)
-                    for name, cmi in cast(dict, _graph_exec.credentialInputs).items()
-                }
-                if _graph_exec.credentialInputs
-                else None
-            ),
-            nodes_input_masks=cast(
-                dict[str, BlockInput] | None, _graph_exec.nodesInputMasks
-            ),
             preset_id=_graph_exec.agentPresetId,
             status=ExecutionStatus(_graph_exec.executionStatus),
             started_at=start_time,
@@ -252,13 +202,11 @@ class GraphExecutionMeta(BaseDbModel):
                 if stats
                 else None
             ),
-            is_shared=_graph_exec.isShared,
-            share_token=_graph_exec.shareToken,
         )
 
 
 class GraphExecution(GraphExecutionMeta):
-    inputs: BlockInput  # type: ignore - incompatible override is intentional
+    inputs: BlockInput
     outputs: CompletedBlockOutput
 
     @staticmethod
@@ -278,18 +226,15 @@ class GraphExecution(GraphExecutionMeta):
         )
 
         inputs = {
-            **(
-                graph_exec.inputs
-                or {
-                    # fallback: extract inputs from Agent Input Blocks
-                    exec.input_data["name"]: exec.input_data.get("value")
-                    for exec in complete_node_executions
-                    if (
-                        (block := get_block(exec.block_id))
-                        and block.block_type == BlockType.INPUT
-                    )
-                }
-            ),
+            **{
+                # inputs from Agent Input Blocks
+                exec.input_data["name"]: exec.input_data.get("value")
+                for exec in complete_node_executions
+                if (
+                    (block := get_block(exec.block_id))
+                    and block.block_type == BlockType.INPUT
+                )
+            },
             **{
                 # input from webhook-triggered block
                 "payload": exec.input_data["payload"]
@@ -307,13 +252,14 @@ class GraphExecution(GraphExecutionMeta):
             if (
                 block := get_block(exec.block_id)
             ) and block.block_type == BlockType.OUTPUT:
-                outputs[exec.input_data["name"]].append(exec.input_data.get("value"))
+                outputs[exec.input_data["name"]].append(
+                    exec.input_data.get("value", None)
+                )
 
         return GraphExecution(
             **{
                 field_name: getattr(graph_exec, field_name)
                 for field_name in GraphExecutionMeta.model_fields
-                if field_name != "inputs"
             },
             inputs=inputs,
             outputs=outputs,
@@ -346,17 +292,13 @@ class GraphExecutionWithNodes(GraphExecution):
             node_executions=node_executions,
         )
 
-    def to_graph_execution_entry(
-        self,
-        user_context: "UserContext",
-        compiled_nodes_input_masks: Optional[NodesInputMasks] = None,
-    ):
+    def to_graph_execution_entry(self, user_context: "UserContext"):
         return GraphExecutionEntry(
             user_id=self.user_id,
             graph_id=self.graph_id,
             graph_version=self.graph_version or 0,
             graph_exec_id=self.id,
-            nodes_input_masks=compiled_nodes_input_masks,
+            nodes_input_masks={},  # FIXME: store credentials on AgentGraphExecution
             user_context=user_context,
         )
 
@@ -393,7 +335,7 @@ class NodeExecutionResult(BaseModel):
         else:
             input_data: BlockInput = defaultdict()
             for data in _node_exec.Input or []:
-                input_data[data.name] = type_utils.convert(data.data, JsonValue)
+                input_data[data.name] = type_utils.convert(data.data, type[Any])
 
         output_data: CompletedBlockOutput = defaultdict(list)
 
@@ -402,7 +344,7 @@ class NodeExecutionResult(BaseModel):
                 output_data[name].extend(messages)
         else:
             for data in _node_exec.Output or []:
-                output_data[data.name].append(type_utils.convert(data.data, JsonValue))
+                output_data[data.name].append(type_utils.convert(data.data, type[Any]))
 
         graph_execution: AgentGraphExecution | None = _node_exec.GraphExecution
         if graph_execution:
@@ -597,12 +539,9 @@ async def get_graph_execution(
 async def create_graph_execution(
     graph_id: str,
     graph_version: int,
-    starting_nodes_input: list[tuple[str, BlockInput]],  # list[(node_id, BlockInput)]
-    inputs: Mapping[str, JsonValue],
+    starting_nodes_input: list[tuple[str, BlockInput]],
     user_id: str,
-    preset_id: Optional[str] = None,
-    credential_inputs: Optional[Mapping[str, CredentialsMetaInput]] = None,
-    nodes_input_masks: Optional[NodesInputMasks] = None,
+    preset_id: str | None = None,
 ) -> GraphExecutionWithNodes:
     """
     Create a new AgentGraphExecution record.
@@ -610,18 +549,11 @@ async def create_graph_execution(
         The id of the AgentGraphExecution and the list of ExecutionResult for each node.
     """
     result = await AgentGraphExecution.prisma().create(
-        data={
-            "agentGraphId": graph_id,
-            "agentGraphVersion": graph_version,
-            "executionStatus": ExecutionStatus.INCOMPLETE,
-            "inputs": SafeJson(inputs),
-            "credentialInputs": (
-                SafeJson(credential_inputs) if credential_inputs else Json({})
-            ),
-            "nodesInputMasks": (
-                SafeJson(nodes_input_masks) if nodes_input_masks else Json({})
-            ),
-            "NodeExecutions": {
+        data=AgentGraphExecutionCreateInput(
+            agentGraphId=graph_id,
+            agentGraphVersion=graph_version,
+            executionStatus=ExecutionStatus.QUEUED,
+            NodeExecutions={
                 "create": [
                     AgentNodeExecutionCreateInput(
                         agentNodeId=node_id,
@@ -637,9 +569,9 @@ async def create_graph_execution(
                     for node_id, node_input in starting_nodes_input
                 ]
             },
-            "userId": user_id,
-            "agentPresetId": preset_id,
-        },
+            userId=user_id,
+            agentPresetId=preset_id,
+        ),
         include=GRAPH_EXECUTION_INCLUDE_WITH_NODES,
     )
 
@@ -650,7 +582,7 @@ async def upsert_execution_input(
     node_id: str,
     graph_exec_id: str,
     input_name: str,
-    input_data: JsonValue,
+    input_data: Any,
     node_exec_id: str | None = None,
 ) -> tuple[str, BlockInput]:
     """
@@ -699,7 +631,7 @@ async def upsert_execution_input(
         )
         return existing_execution.id, {
             **{
-                input_data.name: type_utils.convert(input_data.data, JsonValue)
+                input_data.name: type_utils.convert(input_data.data, type[Any])
                 for input_data in existing_execution.Input or []
             },
             input_name: input_data,
@@ -760,11 +692,6 @@ async def update_graph_execution_stats(
     status: ExecutionStatus | None = None,
     stats: GraphExecutionStats | None = None,
 ) -> GraphExecution | None:
-    if not status and not stats:
-        raise ValueError(
-            f"Must provide either status or stats to update for execution {graph_exec_id}"
-        )
-
     update_data: AgentGraphExecutionUpdateManyMutationInput = {}
 
     if stats:
@@ -776,25 +703,20 @@ async def update_graph_execution_stats(
     if status:
         update_data["executionStatus"] = status
 
-    where_clause: AgentGraphExecutionWhereInput = {"id": graph_exec_id}
-
-    if status:
-        if allowed_from := VALID_STATUS_TRANSITIONS.get(status, []):
-            # Add OR clause to check if current status is one of the allowed source statuses
-            where_clause["AND"] = [
-                {"id": graph_exec_id},
-                {"OR": [{"executionStatus": s} for s in allowed_from]},
-            ]
-        else:
-            raise ValueError(
-                f"Status {status} cannot be set via update for execution {graph_exec_id}. "
-                f"This status can only be set at creation or is not a valid target status."
-            )
-
-    await AgentGraphExecution.prisma().update_many(
-        where=where_clause,
+    updated_count = await AgentGraphExecution.prisma().update_many(
+        where={
+            "id": graph_exec_id,
+            "OR": [
+                {"executionStatus": ExecutionStatus.RUNNING},
+                {"executionStatus": ExecutionStatus.QUEUED},
+                # Terminated graph can be resumed.
+                {"executionStatus": ExecutionStatus.TERMINATED},
+            ],
+        },
         data=update_data,
     )
+    if updated_count == 0:
+        return None
 
     graph_exec = await AgentGraphExecution.prisma().find_unique_or_raise(
         where={"id": graph_exec_id},
@@ -802,7 +724,6 @@ async def update_graph_execution_stats(
             [*get_io_block_ids(), *get_webhook_block_ids()]
         ),
     )
-
     return GraphExecution.from_db(graph_exec)
 
 
@@ -967,7 +888,7 @@ class GraphExecutionEntry(BaseModel):
     graph_exec_id: str
     graph_id: str
     graph_version: int
-    nodes_input_masks: Optional[NodesInputMasks] = None
+    nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None
     user_context: UserContext
 
 
@@ -1029,18 +950,6 @@ class NodeExecutionEvent(NodeExecutionResult):
     )
 
 
-class SharedExecutionResponse(BaseModel):
-    """Public-safe response for shared executions"""
-
-    id: str
-    graph_name: str
-    graph_description: Optional[str]
-    status: ExecutionStatus
-    created_at: datetime
-    outputs: CompletedBlockOutput  # Only the final outputs, no intermediate data
-    # Deliberately exclude: user_id, inputs, credentials, node details
-
-
 ExecutionEvent = Annotated[
     GraphExecutionEvent | NodeExecutionEvent, Field(discriminator="event_type")
 ]
@@ -1218,98 +1127,3 @@ async def get_block_error_stats(
         )
         for row in result
     ]
-
-
-async def update_graph_execution_share_status(
-    execution_id: str,
-    user_id: str,
-    is_shared: bool,
-    share_token: str | None,
-    shared_at: datetime | None,
-) -> None:
-    """Update the sharing status of a graph execution."""
-    await AgentGraphExecution.prisma().update(
-        where={"id": execution_id},
-        data={
-            "isShared": is_shared,
-            "shareToken": share_token,
-            "sharedAt": shared_at,
-        },
-    )
-
-
-async def get_graph_execution_by_share_token(
-    share_token: str,
-) -> SharedExecutionResponse | None:
-    """Get a shared execution with limited public-safe data."""
-    execution = await AgentGraphExecution.prisma().find_first(
-        where={
-            "shareToken": share_token,
-            "isShared": True,
-            "isDeleted": False,
-        },
-        include={
-            "AgentGraph": True,
-            "NodeExecutions": {
-                "include": {
-                    "Output": True,
-                    "Node": {
-                        "include": {
-                            "AgentBlock": True,
-                        }
-                    },
-                },
-            },
-        },
-    )
-
-    if not execution:
-        return None
-
-    # Extract outputs from OUTPUT blocks only (consistent with GraphExecution.from_db)
-    outputs: CompletedBlockOutput = defaultdict(list)
-    if execution.NodeExecutions:
-        for node_exec in execution.NodeExecutions:
-            if node_exec.Node and node_exec.Node.agentBlockId:
-                # Get the block definition to check its type
-                block = get_block(node_exec.Node.agentBlockId)
-
-                if block and block.block_type == BlockType.OUTPUT:
-                    # For OUTPUT blocks, the data is stored in executionData or Input
-                    # The executionData contains the structured input with 'name' and 'value' fields
-                    if hasattr(node_exec, "executionData") and node_exec.executionData:
-                        exec_data = type_utils.convert(
-                            node_exec.executionData, dict[str, Any]
-                        )
-                        if "name" in exec_data:
-                            name = exec_data["name"]
-                            value = exec_data.get("value")
-                            outputs[name].append(value)
-                    elif node_exec.Input:
-                        # Build input_data from Input relation
-                        input_data = {}
-                        for data in node_exec.Input:
-                            if data.name and data.data is not None:
-                                input_data[data.name] = type_utils.convert(
-                                    data.data, JsonValue
-                                )
-
-                        if "name" in input_data:
-                            name = input_data["name"]
-                            value = input_data.get("value")
-                            outputs[name].append(value)
-
-    return SharedExecutionResponse(
-        id=execution.id,
-        graph_name=(
-            execution.AgentGraph.name
-            if (execution.AgentGraph and execution.AgentGraph.name)
-            else "Untitled Agent"
-        ),
-        graph_description=(
-            execution.AgentGraph.description if execution.AgentGraph else None
-        ),
-        status=ExecutionStatus(execution.executionStatus),
-        created_at=execution.createdAt,
-        outputs=outputs,
-    )

autogpt_platform/backend/backend/data/graph.py

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

autogpt_platform/backend/backend/data/graph_test.py

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

autogpt_platform/backend/backend/data/includes.py

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

autogpt_platform/backend/backend/data/optional_block.py

@@ -1,59 +0,0 @@
-from enum import Enum
-from typing import Optional
-
-from pydantic import BaseModel, Field
-
-
-class ConditionOperator(str, Enum):
-    AND = "and"
-    OR = "or"
-
-
-class OptionalBlockConditions(BaseModel):
-    """Conditions that determine when a block should be skipped"""
-
-    on_missing_credentials: bool = Field(
-        default=False,
-        description="Skip block if any required credentials are missing",
-    )
-    check_skip_input: bool = Field(
-        default=True,
-        description="Check the standard 'skip' input to control skip behavior",
-    )
-    kv_flag: Optional[str] = Field(
-        default=None,
-        description="Key-value store flag name that controls skip behavior",
-    )
-    operator: ConditionOperator = Field(
-        default=ConditionOperator.OR,
-        description="Logical operator for combining conditions (AND/OR)",
-    )
-
-
-class OptionalBlockConfig(BaseModel):
-    """Configuration for making a block optional/skippable"""
-
-    enabled: bool = Field(
-        default=False,
-        description="Whether this block can be optionally skipped",
-    )
-    conditions: OptionalBlockConditions = Field(
-        default_factory=OptionalBlockConditions,
-        description="Conditions that trigger skipping",
-    )
-    skip_message: Optional[str] = Field(
-        default=None,
-        description="Custom message to log when block is skipped",
-    )
-
-
-def get_optional_config(node_metadata: dict) -> Optional[OptionalBlockConfig]:
-    """Extract optional block configuration from node metadata"""
-    if "optional" not in node_metadata:
-        return None
-
-    optional_data = node_metadata.get("optional", {})
-    if not optional_data:
-        return None
-
-    return OptionalBlockConfig(**optional_data)

autogpt_platform/backend/backend/data/redis_client.py

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

autogpt_platform/backend/backend/data/user.py

@@ -7,7 +7,6 @@ from typing import Optional, cast
 from urllib.parse import quote_plus
 
 from autogpt_libs.auth.models import DEFAULT_USER_ID
-from autogpt_libs.utils.cache import cached
 from fastapi import HTTPException
 from prisma.enums import NotificationType
 from prisma.models import User as PrismaUser
@@ -24,11 +23,7 @@ from backend.util.settings import Settings
 logger = logging.getLogger(__name__)
 settings = Settings()
 
-# Cache decorator alias for consistent user lookup caching
-cache_user_lookup = cached(maxsize=1000, ttl_seconds=300)
 
-
-@cache_user_lookup
 async def get_or_create_user(user_data: dict) -> User:
     try:
         user_id = user_data.get("sub")
@@ -54,7 +49,6 @@ async def get_or_create_user(user_data: dict) -> User:
         raise DatabaseError(f"Failed to get or create user {user_data}: {e}") from e
 
 
-@cache_user_lookup
 async def get_user_by_id(user_id: str) -> User:
     user = await prisma.user.find_unique(where={"id": user_id})
     if not user:
@@ -70,7 +64,6 @@ async def get_user_email_by_id(user_id: str) -> Optional[str]:
         raise DatabaseError(f"Failed to get user email for user {user_id}: {e}") from e
 
 
-@cache_user_lookup
 async def get_user_by_email(email: str) -> Optional[User]:
     try:
         user = await prisma.user.find_unique(where={"email": email})
@@ -81,17 +74,7 @@ async def get_user_by_email(email: str) -> Optional[User]:
 
 async def update_user_email(user_id: str, email: str):
     try:
-        # Get old email first for cache invalidation
-        old_user = await prisma.user.find_unique(where={"id": user_id})
-        old_email = old_user.email if old_user else None
-
         await prisma.user.update(where={"id": user_id}, data={"email": email})
-
-        # Selectively invalidate only the specific user entries
-        get_user_by_id.cache_delete(user_id)
-        if old_email:
-            get_user_by_email.cache_delete(old_email)
-        get_user_by_email.cache_delete(email)
     except Exception as e:
         raise DatabaseError(
             f"Failed to update user email for user {user_id}: {e}"
@@ -131,8 +114,6 @@ async def update_user_integrations(user_id: str, data: UserIntegrations):
         where={"id": user_id},
         data={"integrations": encrypted_data},
     )
-    # Invalidate cache for this user
-    get_user_by_id.cache_delete(user_id)
 
 
 async def migrate_and_encrypt_user_integrations():
@@ -304,10 +285,6 @@ async def update_user_notification_preference(
         )
         if not user:
             raise ValueError(f"User not found with ID: {user_id}")
-
-        # Invalidate cache for this user since notification preferences are part of user data
-        get_user_by_id.cache_delete(user_id)
-
         preferences: dict[NotificationType, bool] = {
             NotificationType.AGENT_RUN: user.notifyOnAgentRun or True,
             NotificationType.ZERO_BALANCE: user.notifyOnZeroBalance or True,
@@ -346,8 +323,6 @@ async def set_user_email_verification(user_id: str, verified: bool) -> None:
             where={"id": user_id},
             data={"emailVerified": verified},
         )
-        # Invalidate cache for this user
-        get_user_by_id.cache_delete(user_id)
     except Exception as e:
         raise DatabaseError(
             f"Failed to set email verification status for user {user_id}: {e}"
@@ -432,10 +407,6 @@ async def update_user_timezone(user_id: str, timezone: str) -> User:
         )
         if not user:
             raise ValueError(f"User not found with ID: {user_id}")
-
-        # Invalidate cache for this user
-        get_user_by_id.cache_delete(user_id)
-
         return User.from_db(user)
     except Exception as e:
         raise DatabaseError(f"Failed to update timezone for user {user_id}: {e}") from e

autogpt_platform/backend/backend/executor/activity_status_generator.py

@@ -107,7 +107,7 @@ async def generate_activity_status_for_execution(
     # Check if we have OpenAI API key
     try:
         settings = Settings()
-        if not settings.secrets.openai_internal_api_key:
+        if not settings.secrets.openai_api_key:
             logger.debug(
                 "OpenAI API key not configured, skipping activity status generation"
             )
@@ -187,7 +187,7 @@ async def generate_activity_status_for_execution(
         credentials = APIKeyCredentials(
             id="openai",
             provider="openai",
-            api_key=SecretStr(settings.secrets.openai_internal_api_key),
+            api_key=SecretStr(settings.secrets.openai_api_key),
             title="System OpenAI",
         )
 
@@ -423,6 +423,7 @@ async def _call_llm_direct(
         credentials=credentials,
         llm_model=LlmModel.GPT4O_MINI,
         prompt=prompt,
+        json_format=False,
         max_tokens=150,
         compress_prompt_to_fit=True,
     )

autogpt_platform/backend/backend/executor/activity_status_generator_test.py

@@ -468,7 +468,7 @@ class TestGenerateActivityStatusForExecution:
         ):
 
             mock_get_block.side_effect = lambda block_id: mock_blocks.get(block_id)
-            mock_settings.return_value.secrets.openai_internal_api_key = "test_key"
+            mock_settings.return_value.secrets.openai_api_key = "test_key"
             mock_llm.return_value = (
                 "I analyzed your data and provided the requested insights."
             )
@@ -520,7 +520,7 @@ class TestGenerateActivityStatusForExecution:
             "backend.executor.activity_status_generator.is_feature_enabled",
             return_value=True,
         ):
-            mock_settings.return_value.secrets.openai_internal_api_key = ""
+            mock_settings.return_value.secrets.openai_api_key = ""
 
             result = await generate_activity_status_for_execution(
                 graph_exec_id="test_exec",
@@ -546,7 +546,7 @@ class TestGenerateActivityStatusForExecution:
             "backend.executor.activity_status_generator.is_feature_enabled",
             return_value=True,
         ):
-            mock_settings.return_value.secrets.openai_internal_api_key = "test_key"
+            mock_settings.return_value.secrets.openai_api_key = "test_key"
 
             result = await generate_activity_status_for_execution(
                 graph_exec_id="test_exec",
@@ -581,7 +581,7 @@ class TestGenerateActivityStatusForExecution:
         ):
 
             mock_get_block.side_effect = lambda block_id: mock_blocks.get(block_id)
-            mock_settings.return_value.secrets.openai_internal_api_key = "test_key"
+            mock_settings.return_value.secrets.openai_api_key = "test_key"
             mock_llm.return_value = "Agent completed execution."
 
             result = await generate_activity_status_for_execution(
@@ -633,7 +633,7 @@ class TestIntegration:
         ):
 
             mock_get_block.side_effect = lambda block_id: mock_blocks.get(block_id)
-            mock_settings.return_value.secrets.openai_internal_api_key = "test_key"
+            mock_settings.return_value.secrets.openai_api_key = "test_key"
 
             mock_response = LLMResponse(
                 raw_response={},

autogpt_platform/backend/backend/executor/database.py

@@ -85,16 +85,6 @@ class DatabaseManager(AppService):
     async def health_check(self) -> str:
         if not db.is_connected():
             raise UnhealthyServiceError("Database is not connected")
-
-        try:
-            # Test actual database connectivity by executing a simple query
-            # This will fail if Prisma query engine is not responding
-            result = await db.query_raw_with_schema("SELECT 1 as health_check")
-            if not result or result[0].get("health_check") != 1:
-                raise UnhealthyServiceError("Database query test failed")
-        except Exception as e:
-            raise UnhealthyServiceError(f"Database health check failed: {e}")
-
         return await super().health_check()
 
     @classmethod

autogpt_platform/backend/backend/executor/manager.py

@@ -10,10 +10,10 @@ from typing import TYPE_CHECKING, Any, Optional, TypeVar, cast
 
 from pika.adapters.blocking_connection import BlockingChannel
 from pika.spec import Basic, BasicProperties
+from pydantic import JsonValue
 from redis.asyncio.lock import Lock as RedisLock
 
 from backend.blocks.io import AgentOutputBlock
-from backend.blocks.persistence import get_storage_key
 from backend.data.model import GraphExecutionStats, NodeExecutionStats
 from backend.data.notifications import (
     AgentRunData,
@@ -28,7 +28,6 @@ from backend.executor.activity_status_generator import (
 )
 from backend.executor.utils import LogMetadata
 from backend.notifications.notifications import queue_notification
-from backend.util.clients import get_database_manager_async_client
 from backend.util.exceptions import InsufficientBalanceError, ModerationError
 
 if TYPE_CHECKING:
@@ -39,9 +38,9 @@ from prometheus_client import Gauge, start_http_server
 from backend.blocks.agent import AgentExecutorBlock
 from backend.data import redis_client as redis
 from backend.data.block import (
+    BlockData,
     BlockInput,
     BlockOutput,
-    BlockOutputEntry,
     BlockSchema,
     get_block,
 )
@@ -53,11 +52,9 @@ from backend.data.execution import (
     GraphExecutionEntry,
     NodeExecutionEntry,
     NodeExecutionResult,
-    NodesInputMasks,
     UserContext,
 )
 from backend.data.graph import Link, Node
-from backend.data.optional_block import get_optional_config
 from backend.executor.utils import (
     GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS,
     GRAPH_EXECUTION_CANCEL_QUEUE_NAME,
@@ -76,6 +73,7 @@ from backend.server.v2.AutoMod.manager import automod_manager
 from backend.util import json
 from backend.util.clients import (
     get_async_execution_event_bus,
+    get_database_manager_async_client,
     get_database_manager_client,
     get_execution_event_bus,
     get_notification_manager_client,
@@ -128,92 +126,12 @@ def execute_graph(
 T = TypeVar("T")
 
 
-async def should_skip_node(
-    node: Node,
-    creds_manager: IntegrationCredentialsManager,
-    user_id: str,
-    user_context: UserContext,
-    input_data: BlockInput,
-    graph_id: str,
-) -> tuple[bool, str]:
-    """
-    Check if a node should be skipped based on optional configuration.
-
-    Returns:
-        Tuple of (should_skip, skip_reason)
-    """
-    optional_config = get_optional_config(node.metadata)
-
-    if not optional_config or not optional_config.enabled:
-        return False, ""
-
-    conditions = optional_config.conditions
-    skip_reasons = []
-    conditions_met = []
-
-    # Check credential availability
-    if conditions.on_missing_credentials:
-        node_block = node.block
-        input_model = cast(type[BlockSchema], node_block.input_schema)
-        for field_name, input_type in input_model.get_credentials_fields().items():
-            if field_name in input_data:
-                credentials_meta = input_type(**input_data[field_name])
-                # Check if credentials exist without acquiring lock
-                if not await creds_manager.exists(user_id, credentials_meta.id):
-                    skip_reasons.append(f"Missing credentials: {field_name}")
-                    conditions_met.append(True)
-                    break
-        else:
-            # All credentials exist
-            if conditions.on_missing_credentials:
-                conditions_met.append(False)
-
-    # Check standard skip_run_block input (automatically added for optional blocks)
-    if conditions.check_skip_input and "skip_run_block" in input_data:
-        skip_value = input_data.get("skip_run_block", False)
-        if skip_value is True:  # Skip if input is True
-            skip_reasons.append("Skip input is true")
-            conditions_met.append(True)
-        else:
-            conditions_met.append(False)
-
-    # Check key-value flag
-    if conditions.kv_flag:
-        # Determine storage key (assume within_agent scope for now)
-        storage_key = get_storage_key(conditions.kv_flag, "within_agent", graph_id)
-
-        # Retrieve the value from KV store
-        kv_value = await get_database_manager_async_client().get_execution_kv_data(
-            user_id=user_id,
-            key=storage_key,
-        )
-
-        # Skip if flag is True (treat missing/None as False)
-        if kv_value is True:
-            skip_reasons.append(f"KV flag '{conditions.kv_flag}' is true")
-            conditions_met.append(True)
-        else:
-            conditions_met.append(False)
-
-    # Apply logical operator
-    if not conditions_met:
-        return False, ""
-
-    if conditions.operator == "and":
-        should_skip = all(conditions_met)
-    else:  # OR
-        should_skip = any(conditions_met)
-
-    skip_message = optional_config.skip_message or "; ".join(skip_reasons)
-    return should_skip, skip_message
-
-
 async def execute_node(
     node: Node,
     creds_manager: IntegrationCredentialsManager,
     data: NodeExecutionEntry,
     execution_stats: NodeExecutionStats | None = None,
-    nodes_input_masks: Optional[NodesInputMasks] = None,
+    nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
 ) -> BlockOutput:
     """
     Execute a node in the graph. This will trigger a block execution on a node,
@@ -319,12 +237,12 @@ async def execute_node(
 async def _enqueue_next_nodes(
     db_client: "DatabaseManagerAsyncClient",
     node: Node,
-    output: BlockOutputEntry,
+    output: BlockData,
     user_id: str,
     graph_exec_id: str,
     graph_id: str,
     log_metadata: LogMetadata,
-    nodes_input_masks: Optional[NodesInputMasks],
+    nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]],
     user_context: UserContext,
 ) -> list[NodeExecutionEntry]:
     async def add_enqueued_execution(
@@ -501,7 +419,7 @@ class ExecutionProcessor:
         self,
         node_exec: NodeExecutionEntry,
         node_exec_progress: NodeExecutionProgress,
-        nodes_input_masks: Optional[NodesInputMasks],
+        nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]],
         graph_stats_pair: tuple[GraphExecutionStats, threading.Lock],
     ) -> NodeExecutionStats:
         log_metadata = LogMetadata(
@@ -569,7 +487,7 @@ class ExecutionProcessor:
         stats: NodeExecutionStats,
         db_client: "DatabaseManagerAsyncClient",
         log_metadata: LogMetadata,
-        nodes_input_masks: Optional[NodesInputMasks] = None,
+        nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
     ) -> ExecutionStatus:
         status = ExecutionStatus.RUNNING
 
@@ -593,28 +511,6 @@ class ExecutionProcessor:
             )
 
         try:
-            # Check if node should be skipped
-            should_skip, skip_reason = await should_skip_node(
-                node=node,
-                creds_manager=self.creds_manager,
-                user_id=node_exec.user_id,
-                user_context=node_exec.user_context,
-                input_data=node_exec.inputs,
-                graph_id=node_exec.graph_id,
-            )
-
-            if should_skip:
-                log_metadata.info(
-                    f"Skipping node execution {node_exec.node_exec_id}: {skip_reason}"
-                )
-                await async_update_node_execution_status(
-                    db_client=db_client,
-                    exec_id=node_exec.node_exec_id,
-                    status=ExecutionStatus.SKIPPED,
-                    stats={"skip_reason": skip_reason},
-                )
-                return ExecutionStatus.SKIPPED
-
             log_metadata.info(f"Start node execution {node_exec.node_exec_id}")
             await async_update_node_execution_status(
                 db_client=db_client,
@@ -709,7 +605,7 @@ class ExecutionProcessor:
             )
             return
 
-        if exec_meta.status in [ExecutionStatus.QUEUED, ExecutionStatus.INCOMPLETE]:
+        if exec_meta.status == ExecutionStatus.QUEUED:
             log_metadata.info(f"⚙️ Starting graph execution #{graph_exec.graph_exec_id}")
             exec_meta.status = ExecutionStatus.RUNNING
             send_execution_update(
@@ -1157,7 +1053,7 @@ class ExecutionProcessor:
         node_id: str,
         graph_exec: GraphExecutionEntry,
         log_metadata: LogMetadata,
-        nodes_input_masks: Optional[NodesInputMasks],
+        nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]],
         execution_queue: ExecutionQueue[NodeExecutionEntry],
     ) -> None:
         """Process a node's output, update its status, and enqueue next nodes.
@@ -1498,14 +1394,14 @@ class ExecutionManager(AppProcess):
         delivery_tag = method.delivery_tag
 
         @func_retry
-        def _ack_message(reject: bool, requeue: bool):
+        def _ack_message(reject: bool = False):
             """Acknowledge or reject the message based on execution status."""
 
             # Connection can be lost, so always get a fresh channel
             channel = self.run_client.get_channel()
             if reject:
                 channel.connection.add_callback_threadsafe(
-                    lambda: channel.basic_nack(delivery_tag, requeue=requeue)
+                    lambda: channel.basic_nack(delivery_tag, requeue=True)
                 )
             else:
                 channel.connection.add_callback_threadsafe(
@@ -1517,13 +1413,13 @@ class ExecutionManager(AppProcess):
             logger.info(
                 f"[{self.service_name}] Rejecting new execution during shutdown"
             )
-            _ack_message(reject=True, requeue=True)
+            _ack_message(reject=True)
             return
 
         # Check if we can accept more runs
         self._cleanup_completed_runs()
         if len(self.active_graph_runs) >= self.pool_size:
-            _ack_message(reject=True, requeue=True)
+            _ack_message(reject=True)
             return
 
         try:
@@ -1532,7 +1428,7 @@ class ExecutionManager(AppProcess):
             logger.error(
                 f"[{self.service_name}] Could not parse run message: {e}, body={body}"
             )
-            _ack_message(reject=True, requeue=False)
+            _ack_message(reject=True)
             return
 
         graph_exec_id = graph_exec_entry.graph_exec_id
@@ -1544,7 +1440,7 @@ class ExecutionManager(AppProcess):
             logger.error(
                 f"[{self.service_name}] Graph {graph_exec_id} already running; rejecting duplicate run."
             )
-            _ack_message(reject=True, requeue=False)
+            _ack_message(reject=True)
             return
 
         cancel_event = threading.Event()
@@ -1560,9 +1456,9 @@ class ExecutionManager(AppProcess):
                     logger.error(
                         f"[{self.service_name}] Execution for {graph_exec_id} failed: {type(exec_error)} {exec_error}"
                     )
-                    _ack_message(reject=True, requeue=True)
+                    _ack_message(reject=True)
                 else:
-                    _ack_message(reject=False, requeue=False)
+                    _ack_message(reject=False)
             except BaseException as e:
                 logger.exception(
                     f"[{self.service_name}] Error in run completion callback: {e}"

autogpt_platform/backend/backend/executor/manager_test.py

@@ -1,5 +1,6 @@
 import logging
 
+import autogpt_libs.auth.models
 import fastapi.responses
 import pytest
 
@@ -35,20 +36,21 @@ async def execute_graph(
     logger.info(f"Input data: {input_data}")
 
     # --- Test adding new executions --- #
-    graph_exec = await agent_server.test_execute_graph(
+    response = await agent_server.test_execute_graph(
         user_id=test_user.id,
         graph_id=test_graph.id,
         graph_version=test_graph.version,
         node_input=input_data,
     )
-    logger.info(f"Created execution with ID: {graph_exec.id}")
+    graph_exec_id = response.graph_exec_id
+    logger.info(f"Created execution with ID: {graph_exec_id}")
 
     # Execution queue should be empty
     logger.info("Waiting for execution to complete...")
-    result = await wait_execution(test_user.id, graph_exec.id, 30)
+    result = await wait_execution(test_user.id, graph_exec_id, 30)
     logger.info(f"Execution completed with {len(result)} results")
     assert len(result) == num_execs
-    return graph_exec.id
+    return graph_exec_id
 
 
 async def assert_sample_graph_executions(
@@ -378,7 +380,7 @@ async def test_execute_preset(server: SpinTestServer):
 
     # Verify execution
     assert result is not None
-    graph_exec_id = result.id
+    graph_exec_id = result["id"]
 
     # Wait for execution to complete
     executions = await wait_execution(test_user.id, graph_exec_id)
@@ -467,7 +469,7 @@ async def test_execute_preset_with_clash(server: SpinTestServer):
 
     # Verify execution
     assert result is not None, "Result must not be None"
-    graph_exec_id = result.id
+    graph_exec_id = result["id"]
 
     # Wait for execution to complete
     executions = await wait_execution(test_user.id, graph_exec_id)
@@ -519,7 +521,12 @@ async def test_store_listing_graph(server: SpinTestServer):
             is_approved=True,
             comments="Test comments",
         ),
-        user_id=admin_user.id,
+        autogpt_libs.auth.models.User(
+            user_id=admin_user.id,
+            role="admin",
+            email=admin_user.email,
+            phone_number="1234567890",
+        ),
     )
     alt_test_user = admin_user
 

autogpt_platform/backend/backend/executor/scheduler.py

@@ -191,22 +191,15 @@ class GraphExecutionJobInfo(GraphExecutionJobArgs):
     id: str
     name: str
     next_run_time: str
-    timezone: str = Field(default="UTC", description="Timezone used for scheduling")
 
     @staticmethod
     def from_db(
         job_args: GraphExecutionJobArgs, job_obj: JobObj
     ) -> "GraphExecutionJobInfo":
-        # Extract timezone from the trigger if it's a CronTrigger
-        timezone_str = "UTC"
-        if hasattr(job_obj.trigger, "timezone"):
-            timezone_str = str(job_obj.trigger.timezone)
-
         return GraphExecutionJobInfo(
             id=job_obj.id,
             name=job_obj.name,
             next_run_time=job_obj.next_run_time.isoformat(),
-            timezone=timezone_str,
             **job_args.model_dump(),
         )
 
@@ -402,7 +395,6 @@ class Scheduler(AppService):
         input_data: BlockInput,
         input_credentials: dict[str, CredentialsMetaInput],
         name: Optional[str] = None,
-        user_timezone: str | None = None,
     ) -> GraphExecutionJobInfo:
         # Validate the graph before scheduling to prevent runtime failures
         # We don't need the return value, just want the validation to run
@@ -416,18 +408,7 @@ class Scheduler(AppService):
             )
         )
 
-        # Use provided timezone or default to UTC
-        # Note: Timezone should be passed from the client to avoid database lookups
-        if not user_timezone:
-            user_timezone = "UTC"
-            logger.warning(
-                f"No timezone provided for user {user_id}, using UTC for scheduling. "
-                f"Client should pass user's timezone for correct scheduling."
-            )
-
-        logger.info(
-            f"Scheduling job for user {user_id} with timezone {user_timezone} (cron: {cron})"
-        )
+        logger.info(f"Scheduling job for user {user_id} in UTC (cron: {cron})")
 
         job_args = GraphExecutionJobArgs(
             user_id=user_id,
@@ -441,12 +422,12 @@ class Scheduler(AppService):
             execute_graph,
             kwargs=job_args.model_dump(),
             name=name,
-            trigger=CronTrigger.from_crontab(cron, timezone=user_timezone),
+            trigger=CronTrigger.from_crontab(cron, timezone="UTC"),
             jobstore=Jobstores.EXECUTION.value,
             replace_existing=True,
         )
         logger.info(
-            f"Added job {job.id} with cron schedule '{cron}' in timezone {user_timezone}, input data: {input_data}"
+            f"Added job {job.id} with cron schedule '{cron}' in UTC, input data: {input_data}"
         )
         return GraphExecutionJobInfo.from_db(job_args, job)
 

autogpt_platform/backend/backend/executor/util_test.py

@@ -1,7 +1,6 @@
 from typing import cast
 
 import pytest
-from pytest_mock import MockerFixture
 
 from backend.executor.utils import merge_execution_input, parse_execution_output
 from backend.util.mock import MockObject
@@ -277,147 +276,3 @@ def test_merge_execution_input():
     result = merge_execution_input(data)
     assert "mixed" in result
     assert result["mixed"].attr[0]["key"] == "value3"
-
-
-@pytest.mark.asyncio
-async def test_add_graph_execution_is_repeatable(mocker: MockerFixture):
-    """
-    Verify that calling the function with its own output creates the same execution again.
-    """
-    from backend.data.execution import GraphExecutionWithNodes
-    from backend.data.model import CredentialsMetaInput
-    from backend.executor.utils import add_graph_execution
-    from backend.integrations.providers import ProviderName
-
-    # Mock data
-    graph_id = "test-graph-id"
-    user_id = "test-user-id"
-    inputs = {"test_input": "test_value"}
-    preset_id = "test-preset-id"
-    graph_version = 1
-    graph_credentials_inputs = {
-        "cred_key": CredentialsMetaInput(
-            id="cred-id", provider=ProviderName("test_provider"), type="oauth2"
-        )
-    }
-    nodes_input_masks = {"node1": {"input1": "masked_value"}}
-
-    # Mock the graph object returned by validate_and_construct_node_execution_input
-    mock_graph = mocker.MagicMock()
-    mock_graph.version = graph_version
-
-    # Mock the starting nodes input and compiled nodes input masks
-    starting_nodes_input = [
-        ("node1", {"input1": "value1"}),
-        ("node2", {"input1": "value2"}),
-    ]
-    compiled_nodes_input_masks = {"node1": {"input1": "compiled_mask"}}
-
-    # Mock the graph execution object
-    mock_graph_exec = mocker.MagicMock(spec=GraphExecutionWithNodes)
-    mock_graph_exec.id = "execution-id-123"
-    mock_graph_exec.node_executions = []  # Add this to avoid AttributeError
-    mock_graph_exec.to_graph_execution_entry.return_value = mocker.MagicMock()
-
-    # Mock user context
-    mock_user_context = {"user_id": user_id, "context": "test_context"}
-
-    # Mock the queue and event bus
-    mock_queue = mocker.AsyncMock()
-    mock_event_bus = mocker.MagicMock()
-    mock_event_bus.publish = mocker.AsyncMock()
-
-    # Setup mocks
-    mock_validate = mocker.patch(
-        "backend.executor.utils.validate_and_construct_node_execution_input"
-    )
-    mock_edb = mocker.patch("backend.executor.utils.execution_db")
-    mock_prisma = mocker.patch("backend.executor.utils.prisma")
-    mock_get_user_context = mocker.patch("backend.executor.utils.get_user_context")
-    mock_get_queue = mocker.patch("backend.executor.utils.get_async_execution_queue")
-    mock_get_event_bus = mocker.patch(
-        "backend.executor.utils.get_async_execution_event_bus"
-    )
-
-    # Setup mock returns
-    mock_validate.return_value = (
-        mock_graph,
-        starting_nodes_input,
-        compiled_nodes_input_masks,
-    )
-    mock_prisma.is_connected.return_value = True
-    mock_edb.create_graph_execution = mocker.AsyncMock(return_value=mock_graph_exec)
-    mock_edb.update_graph_execution_stats = mocker.AsyncMock(
-        return_value=mock_graph_exec
-    )
-    mock_edb.update_node_execution_status_batch = mocker.AsyncMock()
-    mock_get_user_context.return_value = mock_user_context
-    mock_get_queue.return_value = mock_queue
-    mock_get_event_bus.return_value = mock_event_bus
-
-    # Call the function - first execution
-    result1 = await add_graph_execution(
-        graph_id=graph_id,
-        user_id=user_id,
-        inputs=inputs,
-        preset_id=preset_id,
-        graph_version=graph_version,
-        graph_credentials_inputs=graph_credentials_inputs,
-        nodes_input_masks=nodes_input_masks,
-    )
-
-    # Store the parameters used in the first call to create_graph_execution
-    first_call_kwargs = mock_edb.create_graph_execution.call_args[1]
-
-    # Verify the create_graph_execution was called with correct parameters
-    mock_edb.create_graph_execution.assert_called_once_with(
-        user_id=user_id,
-        graph_id=graph_id,
-        graph_version=mock_graph.version,
-        inputs=inputs,
-        credential_inputs=graph_credentials_inputs,
-        nodes_input_masks=nodes_input_masks,
-        starting_nodes_input=starting_nodes_input,
-        preset_id=preset_id,
-    )
-
-    # Set up the graph execution mock to have properties we can extract
-    mock_graph_exec.graph_id = graph_id
-    mock_graph_exec.user_id = user_id
-    mock_graph_exec.graph_version = graph_version
-    mock_graph_exec.inputs = inputs
-    mock_graph_exec.credential_inputs = graph_credentials_inputs
-    mock_graph_exec.nodes_input_masks = nodes_input_masks
-    mock_graph_exec.preset_id = preset_id
-
-    # Create a second mock execution for the sanity check
-    mock_graph_exec_2 = mocker.MagicMock(spec=GraphExecutionWithNodes)
-    mock_graph_exec_2.id = "execution-id-456"
-    mock_graph_exec_2.to_graph_execution_entry.return_value = mocker.MagicMock()
-
-    # Reset mocks and set up for second call
-    mock_edb.create_graph_execution.reset_mock()
-    mock_edb.create_graph_execution.return_value = mock_graph_exec_2
-    mock_validate.reset_mock()
-
-    # Sanity check: call add_graph_execution with properties from first result
-    # This should create the same execution parameters
-    result2 = await add_graph_execution(
-        graph_id=mock_graph_exec.graph_id,
-        user_id=mock_graph_exec.user_id,
-        inputs=mock_graph_exec.inputs,
-        preset_id=mock_graph_exec.preset_id,
-        graph_version=mock_graph_exec.graph_version,
-        graph_credentials_inputs=mock_graph_exec.credential_inputs,
-        nodes_input_masks=mock_graph_exec.nodes_input_masks,
-    )
-
-    # Verify that create_graph_execution was called with identical parameters
-    second_call_kwargs = mock_edb.create_graph_execution.call_args[1]
-
-    # The sanity check: both calls should use identical parameters
-    assert first_call_kwargs == second_call_kwargs
-
-    # Both executions should succeed (though they create different objects)
-    assert result1 == mock_graph_exec
-    assert result2 == mock_graph_exec_2

autogpt_platform/backend/backend/executor/utils.py

@@ -4,27 +4,20 @@ import threading
 import time
 from collections import defaultdict
 from concurrent.futures import Future
-from typing import Any, Mapping, Optional, cast
+from typing import Any, Optional
 
 from pydantic import BaseModel, JsonValue, ValidationError
 
 from backend.data import execution as execution_db
 from backend.data import graph as graph_db
-from backend.data.block import (
-    Block,
-    BlockCostType,
-    BlockInput,
-    BlockOutputEntry,
-    BlockType,
-    get_block,
-)
+from backend.data.block import Block, BlockData, BlockInput, BlockType, get_block
 from backend.data.block_cost_config import BLOCK_COSTS
+from backend.data.cost import BlockCostType
 from backend.data.db import prisma
 from backend.data.execution import (
     ExecutionStatus,
     GraphExecutionStats,
     GraphExecutionWithNodes,
-    NodesInputMasks,
     UserContext,
 )
 from backend.data.graph import GraphModel, Node
@@ -246,7 +239,7 @@ def _tokenise(path: str) -> list[tuple[str, str]] | None:
 # --------------------------------------------------------------------------- #
 
 
-def parse_execution_output(output: BlockOutputEntry, name: str) -> JsonValue | None:
+def parse_execution_output(output: BlockData, name: str) -> Any | None:
     """
     Retrieve a nested value out of `output` using the flattened *name*.
 
@@ -270,7 +263,7 @@ def parse_execution_output(output: BlockOutputEntry, name: str) -> JsonValue | N
     if tokens is None:
         return None
 
-    cur: JsonValue = data
+    cur: Any = data
     for delim, ident in tokens:
         if delim == LIST_SPLIT:
             # list[index]
@@ -435,7 +428,7 @@ def validate_exec(
 async def _validate_node_input_credentials(
     graph: GraphModel,
     user_id: str,
-    nodes_input_masks: Optional[NodesInputMasks] = None,
+    nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
 ) -> dict[str, dict[str, str]]:
     """
     Checks all credentials for all nodes of the graph and returns structured errors.
@@ -515,8 +508,8 @@ async def _validate_node_input_credentials(
 
 def make_node_credentials_input_map(
     graph: GraphModel,
-    graph_credentials_input: Mapping[str, CredentialsMetaInput],
-) -> NodesInputMasks:
+    graph_credentials_input: dict[str, CredentialsMetaInput],
+) -> dict[str, dict[str, JsonValue]]:
     """
     Maps credentials for an execution to the correct nodes.
 
@@ -551,8 +544,8 @@ def make_node_credentials_input_map(
 async def validate_graph_with_credentials(
     graph: GraphModel,
     user_id: str,
-    nodes_input_masks: Optional[NodesInputMasks] = None,
-) -> Mapping[str, Mapping[str, str]]:
+    nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
+) -> dict[str, dict[str, str]]:
     """
     Validate graph including credentials and return structured errors per node.
 
@@ -582,7 +575,7 @@ async def _construct_starting_node_execution_input(
     graph: GraphModel,
     user_id: str,
     graph_inputs: BlockInput,
-    nodes_input_masks: Optional[NodesInputMasks] = None,
+    nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
 ) -> list[tuple[str, BlockInput]]:
     """
     Validates and prepares the input data for executing a graph.
@@ -623,7 +616,7 @@ async def _construct_starting_node_execution_input(
 
         # Extract request input data, and assign it to the input pin.
         if block.block_type == BlockType.INPUT:
-            input_name = cast(str | None, node.input_default.get("name"))
+            input_name = node.input_default.get("name")
             if input_name and input_name in graph_inputs:
                 input_data = {"value": graph_inputs[input_name]}
 
@@ -650,9 +643,9 @@ async def validate_and_construct_node_execution_input(
     user_id: str,
     graph_inputs: BlockInput,
     graph_version: Optional[int] = None,
-    graph_credentials_inputs: Optional[Mapping[str, CredentialsMetaInput]] = None,
-    nodes_input_masks: Optional[NodesInputMasks] = None,
-) -> tuple[GraphModel, list[tuple[str, BlockInput]], NodesInputMasks]:
+    graph_credentials_inputs: Optional[dict[str, CredentialsMetaInput]] = None,
+    nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
+) -> tuple[GraphModel, list[tuple[str, BlockInput]], dict[str, dict[str, JsonValue]]]:
     """
     Public wrapper that handles graph fetching, credential mapping, and validation+construction.
     This centralizes the logic used by both scheduler validation and actual execution.
@@ -666,9 +659,7 @@ async def validate_and_construct_node_execution_input(
         nodes_input_masks: Node inputs to use.
 
     Returns:
-        GraphModel: Full graph object for the given `graph_id`.
-        list[tuple[node_id, BlockInput]]: Starting node IDs with corresponding inputs.
-        dict[str, BlockInput]: Node input masks including all passed-in credentials.
+        tuple[GraphModel, list[tuple[str, BlockInput]]]: Graph model and list of tuples for node execution input.
 
     Raises:
         NotFoundError: If the graph is not found.
@@ -709,11 +700,11 @@ async def validate_and_construct_node_execution_input(
 
 
 def _merge_nodes_input_masks(
-    overrides_map_1: NodesInputMasks,
-    overrides_map_2: NodesInputMasks,
-) -> NodesInputMasks:
+    overrides_map_1: dict[str, dict[str, JsonValue]],
+    overrides_map_2: dict[str, dict[str, JsonValue]],
+) -> dict[str, dict[str, JsonValue]]:
     """Perform a per-node merge of input overrides"""
-    result = dict(overrides_map_1).copy()
+    result = overrides_map_1.copy()
     for node_id, overrides2 in overrides_map_2.items():
         if node_id in result:
             result[node_id] = {**result[node_id], **overrides2}
@@ -863,8 +854,8 @@ async def add_graph_execution(
     inputs: Optional[BlockInput] = None,
     preset_id: Optional[str] = None,
     graph_version: Optional[int] = None,
-    graph_credentials_inputs: Optional[Mapping[str, CredentialsMetaInput]] = None,
-    nodes_input_masks: Optional[NodesInputMasks] = None,
+    graph_credentials_inputs: Optional[dict[str, CredentialsMetaInput]] = None,
+    nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
 ) -> GraphExecutionWithNodes:
     """
     Adds a graph execution to the queue and returns the execution entry.
@@ -888,7 +879,7 @@ async def add_graph_execution(
     else:
         edb = get_database_manager_async_client()
 
-    graph, starting_nodes_input, compiled_nodes_input_masks = (
+    graph, starting_nodes_input, nodes_input_masks = (
         await validate_and_construct_node_execution_input(
             graph_id=graph_id,
             user_id=user_id,
@@ -901,43 +892,37 @@ async def add_graph_execution(
     graph_exec = None
 
     try:
-        # Sanity check: running add_graph_execution with the properties of
-        # the graph_exec created here should create the same execution again.
         graph_exec = await edb.create_graph_execution(
             user_id=user_id,
             graph_id=graph_id,
             graph_version=graph.version,
-            inputs=inputs or {},
-            credential_inputs=graph_credentials_inputs,
-            nodes_input_masks=nodes_input_masks,
             starting_nodes_input=starting_nodes_input,
             preset_id=preset_id,
         )
 
-        graph_exec_entry = graph_exec.to_graph_execution_entry(
-            user_context=await get_user_context(user_id),
-            compiled_nodes_input_masks=compiled_nodes_input_masks,
-        )
+        # Fetch user context for the graph execution
+        user_context = await get_user_context(user_id)
+
+        queue = await get_async_execution_queue()
+        graph_exec_entry = graph_exec.to_graph_execution_entry(user_context)
+        if nodes_input_masks:
+            graph_exec_entry.nodes_input_masks = nodes_input_masks
+
         logger.info(
             f"Created graph execution #{graph_exec.id} for graph "
             f"#{graph_id} with {len(starting_nodes_input)} starting nodes. "
             f"Now publishing to execution queue."
         )
 
-        exec_queue = await get_async_execution_queue()
-        await exec_queue.publish_message(
+        await queue.publish_message(
             routing_key=GRAPH_EXECUTION_ROUTING_KEY,
             message=graph_exec_entry.model_dump_json(),
             exchange=GRAPH_EXECUTION_EXCHANGE,
         )
         logger.info(f"Published execution {graph_exec.id} to RabbitMQ queue")
 
-        graph_exec.status = ExecutionStatus.QUEUED
-        await edb.update_graph_execution_stats(
-            graph_exec_id=graph_exec.id,
-            status=graph_exec.status,
-        )
-        await get_async_execution_event_bus().publish(graph_exec)
+        bus = get_async_execution_event_bus()
+        await bus.publish(graph_exec)
 
         return graph_exec
     except BaseException as e:
@@ -967,7 +952,7 @@ async def add_graph_execution(
 class ExecutionOutputEntry(BaseModel):
     node: Node
     node_exec_id: str
-    data: BlockOutputEntry
+    data: BlockData
 
 
 class NodeExecutionProgress:

autogpt_platform/backend/backend/integrations/webhooks/__init__.py

@@ -1,14 +1,13 @@
+import functools
 from typing import TYPE_CHECKING
 
-from autogpt_libs.utils.cache import cached
-
 if TYPE_CHECKING:
     from ..providers import ProviderName
     from ._base import BaseWebhooksManager
 
 
 # --8<-- [start:load_webhook_managers]
-@cached()
+@functools.cache
 def load_webhook_managers() -> dict["ProviderName", type["BaseWebhooksManager"]]:
     webhook_managers = {}
 

autogpt_platform/backend/backend/integrations/webhooks/graph_lifecycle_hooks.py

@@ -7,9 +7,10 @@ from backend.data.graph import set_node_webhook
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 
 from . import get_webhook_manager, supports_webhooks
+from .utils import setup_webhook_for_block
 
 if TYPE_CHECKING:
-    from backend.data.graph import BaseGraph, GraphModel, NodeModel
+    from backend.data.graph import BaseGraph, GraphModel, Node, NodeModel
     from backend.data.model import Credentials
 
     from ._base import BaseWebhooksManager
@@ -42,19 +43,32 @@ async def _on_graph_activate(graph: "BaseGraph", user_id: str) -> "BaseGraph": .
 
 async def _on_graph_activate(graph: "BaseGraph | GraphModel", user_id: str):
     get_credentials = credentials_manager.cached_getter(user_id)
+    updated_nodes = []
     for new_node in graph.nodes:
         block_input_schema = cast(BlockSchema, new_node.block.input_schema)
 
-        for creds_field_name in block_input_schema.get_credentials_fields().keys():
-            # Prevent saving graph with non-existent credentials
-            if (
-                creds_meta := new_node.input_default.get(creds_field_name)
-            ) and not await get_credentials(creds_meta["id"]):
-                raise ValueError(
-                    f"Node #{new_node.id} input '{creds_field_name}' updated with "
-                    f"non-existent credentials #{creds_meta['id']}"
+        node_credentials = None
+        if (
+            # Webhook-triggered blocks are only allowed to have 1 credentials input
+            (
+                creds_field_name := next(
+                    iter(block_input_schema.get_credentials_fields()), None
                 )
+            )
+            and (creds_meta := new_node.input_default.get(creds_field_name))
+            and not (node_credentials := await get_credentials(creds_meta["id"]))
+        ):
+            raise ValueError(
+                f"Node #{new_node.id} input '{creds_field_name}' updated with "
+                f"non-existent credentials #{creds_meta['id']}"
+            )
 
+        updated_node = await on_node_activate(
+            user_id, graph.id, new_node, credentials=node_credentials
+        )
+        updated_nodes.append(updated_node)
+
+    graph.nodes = updated_nodes
     return graph
 
 
@@ -71,14 +85,20 @@ async def on_graph_deactivate(graph: "GraphModel", user_id: str):
         block_input_schema = cast(BlockSchema, node.block.input_schema)
 
         node_credentials = None
-        for creds_field_name in block_input_schema.get_credentials_fields().keys():
-            if (creds_meta := node.input_default.get(creds_field_name)) and not (
-                node_credentials := await get_credentials(creds_meta["id"])
-            ):
-                logger.warning(
-                    f"Node #{node.id} input '{creds_field_name}' referenced "
-                    f"non-existent credentials #{creds_meta['id']}"
+        if (
+            # Webhook-triggered blocks are only allowed to have 1 credentials input
+            (
+                creds_field_name := next(
+                    iter(block_input_schema.get_credentials_fields()), None
                 )
+            )
+            and (creds_meta := node.input_default.get(creds_field_name))
+            and not (node_credentials := await get_credentials(creds_meta["id"]))
+        ):
+            logger.error(
+                f"Node #{node.id} input '{creds_field_name}' referenced non-existent "
+                f"credentials #{creds_meta['id']}"
+            )
 
         updated_node = await on_node_deactivate(
             user_id, node, credentials=node_credentials
@@ -89,6 +109,32 @@ async def on_graph_deactivate(graph: "GraphModel", user_id: str):
     return graph
 
 
+async def on_node_activate(
+    user_id: str,
+    graph_id: str,
+    node: "Node",
+    *,
+    credentials: Optional["Credentials"] = None,
+) -> "Node":
+    """Hook to be called when the node is activated/created"""
+
+    if node.block.webhook_config:
+        new_webhook, feedback = await setup_webhook_for_block(
+            user_id=user_id,
+            trigger_block=node.block,
+            trigger_config=node.input_default,
+            for_graph_id=graph_id,
+        )
+        if new_webhook:
+            node = await set_node_webhook(node.id, new_webhook.id)
+        else:
+            logger.debug(
+                f"Node #{node.id} does not have everything for a webhook: {feedback}"
+            )
+
+    return node
+
+
 async def on_node_deactivate(
     user_id: str,
     node: "NodeModel",

autogpt_platform/backend/backend/integrations/webhooks/utils.py

@@ -4,6 +4,7 @@ from typing import TYPE_CHECKING, Optional, cast
 from pydantic import JsonValue
 
 from backend.integrations.creds_manager import IntegrationCredentialsManager
+from backend.integrations.providers import ProviderName
 from backend.util.settings import Config
 
 from . import get_webhook_manager, supports_webhooks
@@ -12,7 +13,6 @@ if TYPE_CHECKING:
     from backend.data.block import Block, BlockSchema
     from backend.data.integrations import Webhook
     from backend.data.model import Credentials
-    from backend.integrations.providers import ProviderName
 
 logger = logging.getLogger(__name__)
 app_config = Config()
@@ -20,7 +20,7 @@ credentials_manager = IntegrationCredentialsManager()
 
 
 # TODO: add test to assert this matches the actual API route
-def webhook_ingress_url(provider_name: "ProviderName", webhook_id: str) -> str:
+def webhook_ingress_url(provider_name: ProviderName, webhook_id: str) -> str:
     return (
         f"{app_config.platform_base_url}/api/integrations/{provider_name.value}"
         f"/webhooks/{webhook_id}/ingress"
@@ -144,69 +144,3 @@ async def setup_webhook_for_block(
         )
     logger.debug(f"Acquired webhook: {webhook}")
     return webhook, None
-
-
-async def migrate_legacy_triggered_graphs():
-    from prisma.models import AgentGraph
-
-    from backend.data.graph import AGENT_GRAPH_INCLUDE, GraphModel, set_node_webhook
-    from backend.data.model import is_credentials_field_name
-    from backend.server.v2.library.db import create_preset
-    from backend.server.v2.library.model import LibraryAgentPresetCreatable
-
-    triggered_graphs = [
-        GraphModel.from_db(_graph)
-        for _graph in await AgentGraph.prisma().find_many(
-            where={
-                "isActive": True,
-                "Nodes": {"some": {"NOT": [{"webhookId": None}]}},
-            },
-            include=AGENT_GRAPH_INCLUDE,
-        )
-    ]
-
-    n_migrated_webhooks = 0
-
-    for graph in triggered_graphs:
-        try:
-            if not (
-                (trigger_node := graph.webhook_input_node) and trigger_node.webhook_id
-            ):
-                continue
-
-            # Use trigger node's inputs for the preset
-            preset_credentials = {
-                field_name: creds_meta
-                for field_name, creds_meta in trigger_node.input_default.items()
-                if is_credentials_field_name(field_name)
-            }
-            preset_inputs = {
-                field_name: value
-                for field_name, value in trigger_node.input_default.items()
-                if not is_credentials_field_name(field_name)
-            }
-
-            # Create a triggered preset for the graph
-            await create_preset(
-                graph.user_id,
-                LibraryAgentPresetCreatable(
-                    graph_id=graph.id,
-                    graph_version=graph.version,
-                    inputs=preset_inputs,
-                    credentials=preset_credentials,
-                    name=graph.name,
-                    description=graph.description,
-                    webhook_id=trigger_node.webhook_id,
-                    is_active=True,
-                ),
-            )
-
-            # Detach webhook from the graph node
-            await set_node_webhook(trigger_node.id, None)
-
-            n_migrated_webhooks += 1
-        except Exception as e:
-            logger.error(f"Failed to migrate graph #{graph.id} trigger to preset: {e}")
-            continue
-
-    logger.info(f"Migrated {n_migrated_webhooks} node triggers to triggered presets")

autogpt_platform/backend/backend/monitoring/instrumentation.py

@@ -1,287 +0,0 @@
-"""
-Prometheus instrumentation for FastAPI services.
-
-This module provides centralized metrics collection and instrumentation
-for all FastAPI services in the AutoGPT platform.
-"""
-
-import logging
-from typing import Optional
-
-from fastapi import FastAPI
-from prometheus_client import Counter, Gauge, Histogram, Info
-from prometheus_fastapi_instrumentator import Instrumentator, metrics
-
-logger = logging.getLogger(__name__)
-
-# Custom business metrics with controlled cardinality
-GRAPH_EXECUTIONS = Counter(
-    "autogpt_graph_executions_total",
-    "Total number of graph executions",
-    labelnames=[
-        "status"
-    ],  # Removed graph_id and user_id to prevent cardinality explosion
-)
-
-GRAPH_EXECUTIONS_BY_USER = Counter(
-    "autogpt_graph_executions_by_user_total",
-    "Total number of graph executions by user (sampled)",
-    labelnames=["status"],  # Only status, user_id tracked separately when needed
-)
-
-BLOCK_EXECUTIONS = Counter(
-    "autogpt_block_executions_total",
-    "Total number of block executions",
-    labelnames=["block_type", "status"],  # block_type is bounded
-)
-
-BLOCK_DURATION = Histogram(
-    "autogpt_block_duration_seconds",
-    "Duration of block executions in seconds",
-    labelnames=["block_type"],
-    buckets=[0.1, 0.25, 0.5, 1, 2.5, 5, 10, 30, 60],
-)
-
-WEBSOCKET_CONNECTIONS = Gauge(
-    "autogpt_websocket_connections_total",
-    "Total number of active WebSocket connections",
-    # Removed user_id label - track total only to prevent cardinality explosion
-)
-
-SCHEDULER_JOBS = Gauge(
-    "autogpt_scheduler_jobs",
-    "Current number of scheduled jobs",
-    labelnames=["job_type", "status"],
-)
-
-DATABASE_QUERIES = Histogram(
-    "autogpt_database_query_duration_seconds",
-    "Duration of database queries in seconds",
-    labelnames=["operation", "table"],
-    buckets=[0.01, 0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
-)
-
-RABBITMQ_MESSAGES = Counter(
-    "autogpt_rabbitmq_messages_total",
-    "Total number of RabbitMQ messages",
-    labelnames=["queue", "status"],
-)
-
-AUTHENTICATION_ATTEMPTS = Counter(
-    "autogpt_auth_attempts_total",
-    "Total number of authentication attempts",
-    labelnames=["method", "status"],
-)
-
-API_KEY_USAGE = Counter(
-    "autogpt_api_key_usage_total",
-    "API key usage by provider",
-    labelnames=["provider", "block_type", "status"],
-)
-
-# Function/operation level metrics with controlled cardinality
-GRAPH_OPERATIONS = Counter(
-    "autogpt_graph_operations_total",
-    "Graph operations by type",
-    labelnames=["operation", "status"],  # create, update, delete, execute, etc.
-)
-
-USER_OPERATIONS = Counter(
-    "autogpt_user_operations_total",
-    "User operations by type",
-    labelnames=["operation", "status"],  # login, register, update_profile, etc.
-)
-
-RATE_LIMIT_HITS = Counter(
-    "autogpt_rate_limit_hits_total",
-    "Number of rate limit hits",
-    labelnames=["endpoint"],  # Removed user_id to prevent cardinality explosion
-)
-
-SERVICE_INFO = Info(
-    "autogpt_service",
-    "Service information",
-)
-
-
-def instrument_fastapi(
-    app: FastAPI,
-    service_name: str,
-    expose_endpoint: bool = True,
-    endpoint: str = "/metrics",
-    include_in_schema: bool = False,
-    excluded_handlers: Optional[list] = None,
-) -> Instrumentator:
-    """
-    Instrument a FastAPI application with Prometheus metrics.
-
-    Args:
-        app: FastAPI application instance
-        service_name: Name of the service for metrics labeling
-        expose_endpoint: Whether to expose /metrics endpoint
-        endpoint: Path for metrics endpoint
-        include_in_schema: Whether to include metrics endpoint in OpenAPI schema
-        excluded_handlers: List of paths to exclude from metrics
-
-    Returns:
-        Configured Instrumentator instance
-    """
-
-    # Set service info
-    try:
-        from importlib.metadata import version
-
-        service_version = version("autogpt-platform-backend")
-    except Exception:
-        service_version = "unknown"
-
-    SERVICE_INFO.info(
-        {
-            "service": service_name,
-            "version": service_version,
-        }
-    )
-
-    # Create instrumentator with default metrics
-    instrumentator = Instrumentator(
-        should_group_status_codes=True,
-        should_ignore_untemplated=True,
-        should_respect_env_var=True,
-        should_instrument_requests_inprogress=True,
-        excluded_handlers=excluded_handlers or ["/health", "/readiness"],
-        env_var_name="ENABLE_METRICS",
-        inprogress_name="autogpt_http_requests_inprogress",
-        inprogress_labels=True,
-    )
-
-    # Add default HTTP metrics
-    instrumentator.add(
-        metrics.default(
-            metric_namespace="autogpt",
-            metric_subsystem=service_name.replace("-", "_"),
-        )
-    )
-
-    # Add request size metrics
-    instrumentator.add(
-        metrics.request_size(
-            metric_namespace="autogpt",
-            metric_subsystem=service_name.replace("-", "_"),
-        )
-    )
-
-    # Add response size metrics
-    instrumentator.add(
-        metrics.response_size(
-            metric_namespace="autogpt",
-            metric_subsystem=service_name.replace("-", "_"),
-        )
-    )
-
-    # Add latency metrics with custom buckets for better granularity
-    instrumentator.add(
-        metrics.latency(
-            metric_namespace="autogpt",
-            metric_subsystem=service_name.replace("-", "_"),
-            buckets=[0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1, 2.5, 5, 10, 30, 60],
-        )
-    )
-
-    # Add combined metrics (requests by method and status)
-    instrumentator.add(
-        metrics.combined_size(
-            metric_namespace="autogpt",
-            metric_subsystem=service_name.replace("-", "_"),
-        )
-    )
-
-    # Instrument the app
-    instrumentator.instrument(app)
-
-    # Expose metrics endpoint if requested
-    if expose_endpoint:
-        instrumentator.expose(
-            app,
-            endpoint=endpoint,
-            include_in_schema=include_in_schema,
-            tags=["monitoring"] if include_in_schema else None,
-        )
-        logger.info(f"Metrics endpoint exposed at {endpoint} for {service_name}")
-
-    return instrumentator
-
-
-def record_graph_execution(graph_id: str, status: str, user_id: str):
-    """Record a graph execution event.
-
-    Args:
-        graph_id: Graph identifier (kept for future sampling/debugging)
-        status: Execution status (success/error/validation_error)
-        user_id: User identifier (kept for future sampling/debugging)
-    """
-    # Track overall executions without high-cardinality labels
-    GRAPH_EXECUTIONS.labels(status=status).inc()
-
-    # Optionally track per-user executions (implement sampling if needed)
-    # For now, just track status to avoid cardinality explosion
-    GRAPH_EXECUTIONS_BY_USER.labels(status=status).inc()
-
-
-def record_block_execution(block_type: str, status: str, duration: float):
-    """Record a block execution event with duration."""
-    BLOCK_EXECUTIONS.labels(block_type=block_type, status=status).inc()
-    BLOCK_DURATION.labels(block_type=block_type).observe(duration)
-
-
-def update_websocket_connections(user_id: str, delta: int):
-    """Update the number of active WebSocket connections.
-
-    Args:
-        user_id: User identifier (kept for future sampling/debugging)
-        delta: Change in connection count (+1 for connect, -1 for disconnect)
-    """
-    # Track total connections without user_id to prevent cardinality explosion
-    if delta > 0:
-        WEBSOCKET_CONNECTIONS.inc(delta)
-    else:
-        WEBSOCKET_CONNECTIONS.dec(abs(delta))
-
-
-def record_database_query(operation: str, table: str, duration: float):
-    """Record a database query with duration."""
-    DATABASE_QUERIES.labels(operation=operation, table=table).observe(duration)
-
-
-def record_rabbitmq_message(queue: str, status: str):
-    """Record a RabbitMQ message event."""
-    RABBITMQ_MESSAGES.labels(queue=queue, status=status).inc()
-
-
-def record_authentication_attempt(method: str, status: str):
-    """Record an authentication attempt."""
-    AUTHENTICATION_ATTEMPTS.labels(method=method, status=status).inc()
-
-
-def record_api_key_usage(provider: str, block_type: str, status: str):
-    """Record API key usage by provider and block."""
-    API_KEY_USAGE.labels(provider=provider, block_type=block_type, status=status).inc()
-
-
-def record_rate_limit_hit(endpoint: str, user_id: str):
-    """Record a rate limit hit.
-
-    Args:
-        endpoint: API endpoint that was rate limited
-        user_id: User identifier (kept for future sampling/debugging)
-    """
-    RATE_LIMIT_HITS.labels(endpoint=endpoint).inc()
-
-
-def record_graph_operation(operation: str, status: str):
-    """Record a graph operation (create, update, delete, execute, etc.)."""
-    GRAPH_OPERATIONS.labels(operation=operation, status=status).inc()
-
-
-def record_user_operation(operation: str, status: str):
-    """Record a user operation (login, register, etc.)."""
-    USER_OPERATIONS.labels(operation=operation, status=status).inc()

autogpt_platform/backend/backend/sdk/__init__.py

@@ -63,7 +63,7 @@ except ImportError:
 
 # Cost System
 try:
-    from backend.data.block import BlockCost, BlockCostType
+    from backend.data.cost import BlockCost, BlockCostType
 except ImportError:
     from backend.data.block_cost_config import BlockCost, BlockCostType
 

autogpt_platform/backend/backend/sdk/builder.py

@@ -8,7 +8,7 @@ from typing import Callable, List, Optional, Type
 
 from pydantic import SecretStr
 
-from backend.data.block import BlockCost, BlockCostType
+from backend.data.cost import BlockCost, BlockCostType
 from backend.data.model import (
     APIKeyCredentials,
     Credentials,

autogpt_platform/backend/backend/sdk/cost_integration.py

@@ -8,8 +8,9 @@ BLOCK_COSTS configuration used by the execution system.
 import logging
 from typing import List, Type
 
-from backend.data.block import Block, BlockCost
+from backend.data.block import Block
 from backend.data.block_cost_config import BLOCK_COSTS
+from backend.data.cost import BlockCost
 from backend.sdk.registry import AutoRegistry
 
 logger = logging.getLogger(__name__)

autogpt_platform/backend/backend/sdk/provider.py

@@ -7,7 +7,7 @@ from typing import Any, Callable, List, Optional, Set, Type
 
 from pydantic import BaseModel, SecretStr
 
-from backend.data.block import BlockCost
+from backend.data.cost import BlockCost
 from backend.data.model import (
     APIKeyCredentials,
     Credentials,

autogpt_platform/backend/backend/sdk/registry.py

@@ -6,10 +6,10 @@ import logging
 import threading
 from typing import TYPE_CHECKING, Any, Dict, List, Optional, Type
 
-from pydantic import BaseModel
+from pydantic import BaseModel, SecretStr
 
 from backend.blocks.basic import Block
-from backend.data.model import Credentials
+from backend.data.model import APIKeyCredentials, Credentials
 from backend.integrations.oauth.base import BaseOAuthHandler
 from backend.integrations.providers import ProviderName
 from backend.integrations.webhooks._base import BaseWebhooksManager
@@ -17,8 +17,6 @@ from backend.integrations.webhooks._base import BaseWebhooksManager
 if TYPE_CHECKING:
     from backend.sdk.provider import Provider
 
-logger = logging.getLogger(__name__)
-
 
 class SDKOAuthCredentials(BaseModel):
     """OAuth credentials configuration for SDK providers."""
@@ -104,8 +102,21 @@ class AutoRegistry:
         """Register an environment variable as an API key for a provider."""
         with cls._lock:
             cls._api_key_mappings[provider] = env_var_name
-            # Note: The credential itself is created by ProviderBuilder.with_api_key()
-            # We only store the mapping here to avoid duplication
+
+            # Dynamically check if the env var exists and create credential
+            import os
+
+            api_key = os.getenv(env_var_name)
+            if api_key:
+                credential = APIKeyCredentials(
+                    id=f"{provider}-default",
+                    provider=provider,
+                    api_key=SecretStr(api_key),
+                    title=f"Default {provider} credentials",
+                )
+                # Check if credential already exists to avoid duplicates
+                if not any(c.id == credential.id for c in cls._default_credentials):
+                    cls._default_credentials.append(credential)
 
     @classmethod
     def get_all_credentials(cls) -> List[Credentials]:
@@ -199,43 +210,3 @@ class AutoRegistry:
                 webhooks.load_webhook_managers = patched_load
         except Exception as e:
             logging.warning(f"Failed to patch webhook managers: {e}")
-
-        # Patch credentials store to include SDK-registered credentials
-        try:
-            import sys
-            from typing import Any
-
-            # Get the module from sys.modules to respect mocking
-            if "backend.integrations.credentials_store" in sys.modules:
-                creds_store: Any = sys.modules["backend.integrations.credentials_store"]
-            else:
-                import backend.integrations.credentials_store
-
-                creds_store: Any = backend.integrations.credentials_store
-
-            if hasattr(creds_store, "IntegrationCredentialsStore"):
-                store_class = creds_store.IntegrationCredentialsStore
-                if hasattr(store_class, "get_all_creds"):
-                    original_get_all_creds = store_class.get_all_creds
-
-                    async def patched_get_all_creds(self, user_id: str):
-                        # Get original credentials
-                        original_creds = await original_get_all_creds(self, user_id)
-
-                        # Add SDK-registered credentials
-                        sdk_creds = cls.get_all_credentials()
-
-                        # Combine credentials, avoiding duplicates by ID
-                        existing_ids = {c.id for c in original_creds}
-                        for cred in sdk_creds:
-                            if cred.id not in existing_ids:
-                                original_creds.append(cred)
-
-                        return original_creds
-
-                    store_class.get_all_creds = patched_get_all_creds
-                    logger.info(
-                        "Successfully patched IntegrationCredentialsStore.get_all_creds"
-                    )
-        except Exception as e:
-            logging.warning(f"Failed to patch credentials store: {e}")

autogpt_platform/backend/backend/server/conftest.py

@@ -11,45 +11,7 @@ def configured_snapshot(snapshot: Snapshot) -> Snapshot:
     return snapshot
 
 
-@pytest.fixture
-def test_user_id() -> str:
-    """Test user ID fixture."""
-    return "test-user-id"
-
-
-@pytest.fixture
-def admin_user_id() -> str:
-    """Admin user ID fixture."""
-    return "admin-user-id"
-
-
-@pytest.fixture
-def target_user_id() -> str:
-    """Target user ID fixture."""
-    return "target-user-id"
-
-
-@pytest.fixture
-def mock_jwt_user(test_user_id):
-    """Provide mock JWT payload for regular user testing."""
-    import fastapi
-
-    def override_get_jwt_payload(request: fastapi.Request) -> dict[str, str]:
-        return {"sub": test_user_id, "role": "user", "email": "test@example.com"}
-
-    return {"get_jwt_payload": override_get_jwt_payload, "user_id": test_user_id}
-
-
-@pytest.fixture
-def mock_jwt_admin(admin_user_id):
-    """Provide mock JWT payload for admin user testing."""
-    import fastapi
-
-    def override_get_jwt_payload(request: fastapi.Request) -> dict[str, str]:
-        return {
-            "sub": admin_user_id,
-            "role": "admin",
-            "email": "test-admin@example.com",
-        }
-
-    return {"get_jwt_payload": override_get_jwt_payload, "user_id": admin_user_id}
+# Test ID constants
+TEST_USER_ID = "test-user-id"
+ADMIN_USER_ID = "admin-user-id"
+TARGET_USER_ID = "target-user-id"

autogpt_platform/backend/backend/server/conn_manager_test.py

@@ -88,7 +88,6 @@ async def test_send_graph_execution_result(
         user_id="user-1",
         graph_id="test_graph",
         graph_version=1,
-        preset_id=None,
         status=ExecutionStatus.COMPLETED,
         started_at=datetime.now(tz=timezone.utc),
         ended_at=datetime.now(tz=timezone.utc),
@@ -102,8 +101,6 @@ async def test_send_graph_execution_result(
             "input_1": "some input value :)",
             "input_2": "some *other* input value",
         },
-        credential_inputs=None,
-        nodes_input_masks=None,
         outputs={
             "the_output": ["some output value"],
             "other_output": ["sike there was another output"],

autogpt_platform/backend/backend/server/external/api.py

@@ -1,6 +1,5 @@
 from fastapi import FastAPI
 
-from backend.monitoring.instrumentation import instrument_fastapi
 from backend.server.middleware.security import SecurityHeadersMiddleware
 
 from .routes.v1 import v1_router
@@ -14,12 +13,3 @@ external_app = FastAPI(
 
 external_app.add_middleware(SecurityHeadersMiddleware)
 external_app.include_router(v1_router, prefix="/v1")
-
-# Add Prometheus instrumentation
-instrument_fastapi(
-    external_app,
-    service_name="external-api",
-    expose_endpoint=True,
-    endpoint="/metrics",
-    include_in_schema=True,
-)

autogpt_platform/backend/backend/server/external/middleware.py

@@ -1,14 +1,16 @@
-from fastapi import HTTPException, Security
+from fastapi import Depends, HTTPException, Request
 from fastapi.security import APIKeyHeader
 from prisma.enums import APIKeyPermission
 
-from backend.data.api_key import APIKeyInfo, has_permission, validate_api_key
+from backend.data.api_key import has_permission, validate_api_key
 
-api_key_header = APIKeyHeader(name="X-API-Key", auto_error=False)
+api_key_header = APIKeyHeader(name="X-API-Key")
 
 
-async def require_api_key(api_key: str | None = Security(api_key_header)) -> APIKeyInfo:
+async def require_api_key(request: Request):
     """Base middleware for API key authentication"""
+    api_key = await api_key_header(request)
+
     if api_key is None:
         raise HTTPException(status_code=401, detail="Missing API key")
 
@@ -17,19 +19,18 @@ async def require_api_key(api_key: str | None = Security(api_key_header)) -> API
     if not api_key_obj:
         raise HTTPException(status_code=401, detail="Invalid API key")
 
+    request.state.api_key = api_key_obj
     return api_key_obj
 
 
 def require_permission(permission: APIKeyPermission):
     """Dependency function for checking specific permissions"""
 
-    async def check_permission(
-        api_key: APIKeyInfo = Security(require_api_key),
-    ) -> APIKeyInfo:
+    async def check_permission(api_key=Depends(require_api_key)):
         if not has_permission(api_key, permission):
             raise HTTPException(
                 status_code=403,
-                detail=f"API key lacks the required permission '{permission}'",
+                detail=f"API key missing required permission: {permission}",
             )
         return api_key