style(classic): update black to 24.10.0 and reformat

Update black version to match pre-commit hook (24.10.0) and reformat
all files with the new version.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

.github/workflows/classic-autogpt-ci.yml

@@ -6,11 +6,15 @@ on:
     paths:
       - '.github/workflows/classic-autogpt-ci.yml'
       - 'classic/original_autogpt/**'
+      - 'classic/direct_benchmark/**'
+      - 'classic/forge/**'
   pull_request:
     branches: [ master, dev, release-* ]
     paths:
       - '.github/workflows/classic-autogpt-ci.yml'
       - 'classic/original_autogpt/**'
+      - 'classic/direct_benchmark/**'
+      - 'classic/forge/**'
 
 concurrency:
   group: ${{ format('classic-autogpt-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
@@ -19,47 +23,22 @@ concurrency:
 defaults:
   run:
     shell: bash
-    working-directory: classic/original_autogpt
+    working-directory: classic
 
 jobs:
   test:
     permissions:
       contents: read
     timeout-minutes: 30
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ["3.10"]
-        platform-os: [ubuntu, macos, macos-arm64, windows]
-    runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
+    runs-on: ubuntu-latest
 
     steps:
-      # Quite slow on macOS (2~4 minutes to set up Docker)
-      # - name: Set up Docker (macOS)
-      #   if: runner.os == 'macOS'
-      #   uses: crazy-max/ghaction-setup-docker@v3
-
-      - name: Start MinIO service (Linux)
-        if: runner.os == 'Linux'
+      - name: Start MinIO service
         working-directory: '.'
         run: |
           docker pull minio/minio:edge-cicd
           docker run -d -p 9000:9000 minio/minio:edge-cicd
 
-      - name: Start MinIO service (macOS)
-        if: runner.os == 'macOS'
-        working-directory: ${{ runner.temp }}
-        run: |
-          brew install minio/stable/minio
-          mkdir data
-          minio server ./data &
-
-      # No MinIO on Windows:
-      # - Windows doesn't support running Linux Docker containers
-      # - It doesn't seem possible to start background processes on Windows. They are
-      #   killed after the step returns.
-      #   See: https://github.com/actions/runner/issues/598#issuecomment-2011890429
-
       - name: Checkout repository
         uses: actions/checkout@v4
         with:
@@ -71,41 +50,23 @@ jobs:
           git config --global user.name "Auto-GPT-Bot"
           git config --global user.email "github-bot@agpt.co"
 
-      - name: Set up Python ${{ matrix.python-version }}
+      - name: Set up Python 3.12
         uses: actions/setup-python@v5
         with:
-          python-version: ${{ matrix.python-version }}
+          python-version: "3.12"
 
       - id: get_date
         name: Get date
         run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
 
       - name: Set up Python dependency cache
-        # On Windows, unpacking cached dependencies takes longer than just installing them
-        if: runner.os != 'Windows'
         uses: actions/cache@v4
         with:
-          path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
-          key: poetry-${{ runner.os }}-${{ hashFiles('classic/original_autogpt/poetry.lock') }}
+          path: ~/.cache/pypoetry
+          key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
 
-      - name: Install Poetry (Unix)
-        if: runner.os != 'Windows'
-        run: |
-          curl -sSL https://install.python-poetry.org | python3 -
-
-          if [ "${{ runner.os }}" = "macOS" ]; then
-            PATH="$HOME/.local/bin:$PATH"
-            echo "$HOME/.local/bin" >> $GITHUB_PATH
-          fi
-
-      - name: Install Poetry (Windows)
-        if: runner.os == 'Windows'
-        shell: pwsh
-        run: |
-          (Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
-
-          $env:PATH += ";$env:APPDATA\Python\Scripts"
-          echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
+      - name: Install Poetry
+        run: curl -sSL https://install.python-poetry.org | python3 -
 
       - name: Install Python dependencies
         run: poetry install
@@ -116,12 +77,12 @@ jobs:
             --cov=autogpt --cov-branch --cov-report term-missing --cov-report xml \
             --numprocesses=logical --durations=10 \
             --junitxml=junit.xml -o junit_family=legacy \
-            tests/unit tests/integration
+            original_autogpt/tests/unit original_autogpt/tests/integration
         env:
           CI: true
           PLAIN_OUTPUT: True
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-          S3_ENDPOINT_URL: ${{ runner.os != 'Windows' && 'http://127.0.0.1:9000' || '' }}
+          S3_ENDPOINT_URL: http://127.0.0.1:9000
           AWS_ACCESS_KEY_ID: minioadmin
           AWS_SECRET_ACCESS_KEY: minioadmin
 
@@ -135,11 +96,11 @@ jobs:
         uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
-          flags: autogpt-agent,${{ runner.os }}
+          flags: autogpt-agent
 
       - name: Upload logs to artifact
         if: always()
         uses: actions/upload-artifact@v4
         with:
           name: test-logs
-          path: classic/original_autogpt/logs/
+          path: classic/logs/

.github/workflows/classic-autogpts-ci.yml

@@ -11,9 +11,6 @@ on:
       - 'classic/original_autogpt/**'
       - 'classic/forge/**'
       - 'classic/benchmark/**'
-      - 'classic/run'
-      - 'classic/cli.py'
-      - 'classic/setup.py'
       - '!**/*.md'
   pull_request:
     branches: [ master, dev, release-* ]
@@ -22,9 +19,6 @@ on:
       - 'classic/original_autogpt/**'
       - 'classic/forge/**'
       - 'classic/benchmark/**'
-      - 'classic/run'
-      - 'classic/cli.py'
-      - 'classic/setup.py'
       - '!**/*.md'
 
 defaults:
@@ -35,13 +29,9 @@ defaults:
 jobs:
   serve-agent-protocol:
     runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        agent-name: [ original_autogpt ]
-      fail-fast: false
     timeout-minutes: 20
     env:
-      min-python-version: '3.10'
+      min-python-version: '3.12'
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
@@ -55,22 +45,22 @@ jobs:
           python-version: ${{ env.min-python-version }}
 
       - name: Install Poetry
-        working-directory: ./classic/${{ matrix.agent-name }}/
         run: |
           curl -sSL https://install.python-poetry.org | python -
 
-      - name: Run regression tests
+      - name: Install dependencies
+        run: poetry install
+
+      - name: Run smoke tests with direct-benchmark
         run: |
-          ./run agent start ${{ matrix.agent-name }}
-          cd ${{ matrix.agent-name }}
-          poetry run agbenchmark --mock --test=BasicRetrieval --test=Battleship --test=WebArenaTask_0
-          poetry run agbenchmark --test=WriteFile
+          poetry run direct-benchmark run \
+            --strategies one_shot \
+            --models claude \
+            --tests ReadFile,WriteFile \
+            --json
         env:
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-          AGENT_NAME: ${{ matrix.agent-name }}
+          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
           REQUESTS_CA_BUNDLE: /etc/ssl/certs/ca-certificates.crt
-          HELICONE_CACHE_ENABLED: false
-          HELICONE_PROPERTY_AGENT: ${{ matrix.agent-name }}
-          REPORTS_FOLDER: ${{ format('../../reports/{0}', matrix.agent-name) }}
-          TELEMETRY_ENVIRONMENT: autogpt-ci
-          TELEMETRY_OPT_IN: ${{ github.ref_name == 'master' }}
+          NONINTERACTIVE_MODE: "true"
+          CI: true

.github/workflows/classic-benchmark-ci.yml

@@ -1,17 +1,21 @@
-name: Classic - AGBenchmark CI
+name: Classic - Direct Benchmark CI
 
 on:
   push:
     branches: [ master, dev, ci-test* ]
     paths:
-      - 'classic/benchmark/**'
-      - '!classic/benchmark/reports/**'
+      - 'classic/direct_benchmark/**'
+      - 'classic/benchmark/agbenchmark/challenges/**'
+      - 'classic/original_autogpt/**'
+      - 'classic/forge/**'
       - .github/workflows/classic-benchmark-ci.yml
   pull_request:
     branches: [ master, dev, release-* ]
     paths:
-      - 'classic/benchmark/**'
-      - '!classic/benchmark/reports/**'
+      - 'classic/direct_benchmark/**'
+      - 'classic/benchmark/agbenchmark/challenges/**'
+      - 'classic/original_autogpt/**'
+      - 'classic/forge/**'
       - .github/workflows/classic-benchmark-ci.yml
 
 concurrency:
@@ -23,23 +27,16 @@ defaults:
     shell: bash
 
 env:
-  min-python-version: '3.10'
+  min-python-version: '3.12'
 
 jobs:
-  test:
-    permissions:
-      contents: read
+  benchmark-tests:
+    runs-on: ubuntu-latest
     timeout-minutes: 30
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ["3.10"]
-        platform-os: [ubuntu, macos, macos-arm64, windows]
-    runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
     defaults:
       run:
         shell: bash
-        working-directory: classic/benchmark
+        working-directory: classic
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
@@ -47,71 +44,84 @@ jobs:
           fetch-depth: 0
           submodules: true
 
-      - name: Set up Python ${{ matrix.python-version }}
+      - name: Set up Python ${{ env.min-python-version }}
         uses: actions/setup-python@v5
         with:
-          python-version: ${{ matrix.python-version }}
+          python-version: ${{ env.min-python-version }}
 
       - name: Set up Python dependency cache
-        # On Windows, unpacking cached dependencies takes longer than just installing them
-        if: runner.os != 'Windows'
         uses: actions/cache@v4
         with:
-          path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
-          key: poetry-${{ runner.os }}-${{ hashFiles('classic/benchmark/poetry.lock') }}
+          path: ~/.cache/pypoetry
+          key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
 
-      - name: Install Poetry (Unix)
-        if: runner.os != 'Windows'
+      - name: Install Poetry
         run: |
           curl -sSL https://install.python-poetry.org | python3 -
 
-          if [ "${{ runner.os }}" = "macOS" ]; then
-            PATH="$HOME/.local/bin:$PATH"
-            echo "$HOME/.local/bin" >> $GITHUB_PATH
-          fi
-
-      - name: Install Poetry (Windows)
-        if: runner.os == 'Windows'
-        shell: pwsh
-        run: |
-          (Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
-
-          $env:PATH += ";$env:APPDATA\Python\Scripts"
-          echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
-
-      - name: Install Python dependencies
+      - name: Install dependencies
         run: poetry install
 
-      - name: Run pytest with coverage
+      - name: Run basic benchmark tests
         run: |
-          poetry run pytest -vv \
-            --cov=agbenchmark --cov-branch --cov-report term-missing --cov-report xml \
-            --durations=10 \
-            --junitxml=junit.xml -o junit_family=legacy \
-            tests
+          echo "Testing ReadFile challenge with one_shot strategy..."
+          poetry run direct-benchmark run \
+            --strategies one_shot \
+            --models claude \
+            --tests ReadFile \
+            --json
+
+          echo "Testing WriteFile challenge..."
+          poetry run direct-benchmark run \
+            --strategies one_shot \
+            --models claude \
+            --tests WriteFile \
+            --json
         env:
           CI: true
+          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          NONINTERACTIVE_MODE: "true"
 
-      - name: Upload test results to Codecov
-        if: ${{ !cancelled() }}  # Run even if tests fail
-        uses: codecov/test-results-action@v1
-        with:
-          token: ${{ secrets.CODECOV_TOKEN }}
+      - name: Test category filtering
+        run: |
+          echo "Testing coding category..."
+          poetry run direct-benchmark run \
+            --strategies one_shot \
+            --models claude \
+            --categories coding \
+            --tests ReadFile,WriteFile \
+            --json
+        env:
+          CI: true
+          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          NONINTERACTIVE_MODE: "true"
 
-      - name: Upload coverage reports to Codecov
-        uses: codecov/codecov-action@v5
-        with:
-          token: ${{ secrets.CODECOV_TOKEN }}
-          flags: agbenchmark,${{ runner.os }}
+      - name: Test multiple strategies
+        run: |
+          echo "Testing multiple strategies..."
+          poetry run direct-benchmark run \
+            --strategies one_shot,plan_execute \
+            --models claude \
+            --tests ReadFile \
+            --parallel 2 \
+            --json
+        env:
+          CI: true
+          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          NONINTERACTIVE_MODE: "true"
 
-  self-test-with-agent:
+  # Run regression tests on maintain challenges
+  regression-tests:
     runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        agent-name: [forge]
-      fail-fast: false
-    timeout-minutes: 20
+    timeout-minutes: 45
+    if: github.ref == 'refs/heads/master' || github.ref == 'refs/heads/dev'
+    defaults:
+      run:
+        shell: bash
+        working-directory: classic
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
@@ -126,51 +136,22 @@ jobs:
 
       - name: Install Poetry
         run: |
-          curl -sSL https://install.python-poetry.org | python -
+          curl -sSL https://install.python-poetry.org | python3 -
+
+      - name: Install dependencies
+        run: poetry install
 
       - name: Run regression tests
-        working-directory: classic
         run: |
-          ./run agent start ${{ matrix.agent-name }}
-          cd ${{ matrix.agent-name }}
-
-          set +e # Ignore non-zero exit codes and continue execution
-          echo "Running the following command: poetry run agbenchmark --maintain --mock"
-          poetry run agbenchmark --maintain --mock
-          EXIT_CODE=$?
-          set -e  # Stop ignoring non-zero exit codes
-          # Check if the exit code was 5, and if so, exit with 0 instead
-          if [ $EXIT_CODE -eq 5 ]; then
-            echo "regression_tests.json is empty."
-          fi
-
-          echo "Running the following command: poetry run agbenchmark --mock"
-          poetry run agbenchmark --mock
-
-          echo "Running the following command: poetry run agbenchmark --mock --category=data"
-          poetry run agbenchmark --mock --category=data
-
-          echo "Running the following command: poetry run agbenchmark --mock --category=coding"
-          poetry run agbenchmark --mock --category=coding
-
-          # echo "Running the following command: poetry run agbenchmark --test=WriteFile"
-          # poetry run agbenchmark --test=WriteFile
-          cd ../benchmark
-          poetry install
-          echo "Adding the BUILD_SKILL_TREE environment variable. This will attempt to add new elements in the skill tree. If new elements are added, the CI fails because they should have been pushed"
-          export BUILD_SKILL_TREE=true
-
-          # poetry run agbenchmark --mock
-
-          # CHANGED=$(git diff --name-only | grep -E '(agbenchmark/challenges)|(../classic/frontend/assets)') || echo "No diffs"
-          # if [ ! -z "$CHANGED" ]; then
-          #   echo "There are unstaged changes please run agbenchmark and commit those changes since they are needed."
-          #   echo "$CHANGED"
-          #   exit 1
-          # else
-          #   echo "No unstaged changes."
-          # fi
+          echo "Running regression tests (previously beaten challenges)..."
+          poetry run direct-benchmark run \
+            --strategies one_shot \
+            --models claude \
+            --maintain \
+            --parallel 4 \
+            --json
         env:
+          CI: true
+          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-          TELEMETRY_ENVIRONMENT: autogpt-benchmark-ci
-          TELEMETRY_OPT_IN: ${{ github.ref_name == 'master' }}
+          NONINTERACTIVE_MODE: "true"

.github/workflows/classic-forge-ci.yml

@@ -6,13 +6,11 @@ on:
     paths:
       - '.github/workflows/classic-forge-ci.yml'
       - 'classic/forge/**'
-      - '!classic/forge/tests/vcr_cassettes'
   pull_request:
     branches: [ master, dev, release-* ]
     paths:
       - '.github/workflows/classic-forge-ci.yml'
       - 'classic/forge/**'
-      - '!classic/forge/tests/vcr_cassettes'
 
 concurrency:
   group: ${{ format('forge-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
@@ -21,115 +19,38 @@ concurrency:
 defaults:
   run:
     shell: bash
-    working-directory: classic/forge
+    working-directory: classic
 
 jobs:
   test:
     permissions:
       contents: read
     timeout-minutes: 30
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ["3.10"]
-        platform-os: [ubuntu, macos, macos-arm64, windows]
-    runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
+    runs-on: ubuntu-latest
 
     steps:
-      # Quite slow on macOS (2~4 minutes to set up Docker)
-      # - name: Set up Docker (macOS)
-      #   if: runner.os == 'macOS'
-      #   uses: crazy-max/ghaction-setup-docker@v3
-
-      - name: Start MinIO service (Linux)
-        if: runner.os == 'Linux'
+      - name: Start MinIO service
         working-directory: '.'
         run: |
           docker pull minio/minio:edge-cicd
           docker run -d -p 9000:9000 minio/minio:edge-cicd
 
-      - name: Start MinIO service (macOS)
-        if: runner.os == 'macOS'
-        working-directory: ${{ runner.temp }}
-        run: |
-          brew install minio/stable/minio
-          mkdir data
-          minio server ./data &
-
-      # No MinIO on Windows:
-      # - Windows doesn't support running Linux Docker containers
-      # - It doesn't seem possible to start background processes on Windows. They are
-      #   killed after the step returns.
-      #   See: https://github.com/actions/runner/issues/598#issuecomment-2011890429
-
       - name: Checkout repository
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          submodules: true
 
-      - name: Checkout cassettes
-        if: ${{ startsWith(github.event_name, 'pull_request') }}
-        env:
-          PR_BASE: ${{ github.event.pull_request.base.ref }}
-          PR_BRANCH: ${{ github.event.pull_request.head.ref }}
-          PR_AUTHOR: ${{ github.event.pull_request.user.login }}
-        run: |
-          cassette_branch="${PR_AUTHOR}-${PR_BRANCH}"
-          cassette_base_branch="${PR_BASE}"
-          cd tests/vcr_cassettes
-
-          if ! git ls-remote --exit-code --heads origin $cassette_base_branch ; then
-            cassette_base_branch="master"
-          fi
-
-          if git ls-remote --exit-code --heads origin $cassette_branch ; then
-            git fetch origin $cassette_branch
-            git fetch origin $cassette_base_branch
-
-            git checkout $cassette_branch
-
-            # Pick non-conflicting cassette updates from the base branch
-            git merge --no-commit --strategy-option=ours origin/$cassette_base_branch
-            echo "Using cassettes from mirror branch '$cassette_branch'," \
-              "synced to upstream branch '$cassette_base_branch'."
-          else
-            git checkout -b $cassette_branch
-            echo "Branch '$cassette_branch' does not exist in cassette submodule." \
-              "Using cassettes from '$cassette_base_branch'."
-          fi
-
-      - name: Set up Python ${{ matrix.python-version }}
+      - name: Set up Python 3.12
         uses: actions/setup-python@v5
         with:
-          python-version: ${{ matrix.python-version }}
+          python-version: "3.12"
 
       - name: Set up Python dependency cache
-        # On Windows, unpacking cached dependencies takes longer than just installing them
-        if: runner.os != 'Windows'
         uses: actions/cache@v4
         with:
-          path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
-          key: poetry-${{ runner.os }}-${{ hashFiles('classic/forge/poetry.lock') }}
+          path: ~/.cache/pypoetry
+          key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
 
-      - name: Install Poetry (Unix)
-        if: runner.os != 'Windows'
-        run: |
-          curl -sSL https://install.python-poetry.org | python3 -
-
-          if [ "${{ runner.os }}" = "macOS" ]; then
-            PATH="$HOME/.local/bin:$PATH"
-            echo "$HOME/.local/bin" >> $GITHUB_PATH
-          fi
-
-      - name: Install Poetry (Windows)
-        if: runner.os == 'Windows'
-        shell: pwsh
-        run: |
-          (Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
-
-          $env:PATH += ";$env:APPDATA\Python\Scripts"
-          echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
+      - name: Install Poetry
+        run: curl -sSL https://install.python-poetry.org | python3 -
 
       - name: Install Python dependencies
         run: poetry install
@@ -140,12 +61,15 @@ jobs:
             --cov=forge --cov-branch --cov-report term-missing --cov-report xml \
             --durations=10 \
             --junitxml=junit.xml -o junit_family=legacy \
-            forge
+            forge/forge forge/tests
         env:
           CI: true
           PLAIN_OUTPUT: True
+          # API keys - tests that need these will skip if not available
+          # Secrets are not available to fork PRs (GitHub security feature)
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-          S3_ENDPOINT_URL: ${{ runner.os != 'Windows' && 'http://127.0.0.1:9000' || '' }}
+          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
+          S3_ENDPOINT_URL: http://127.0.0.1:9000
           AWS_ACCESS_KEY_ID: minioadmin
           AWS_SECRET_ACCESS_KEY: minioadmin
 
@@ -159,85 +83,11 @@ jobs:
         uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
-          flags: forge,${{ runner.os }}
-
-      - id: setup_git_auth
-        name: Set up git token authentication
-        # Cassettes may be pushed even when tests fail
-        if: success() || failure()
-        run: |
-          config_key="http.${{ github.server_url }}/.extraheader"
-          if [ "${{ runner.os }}" = 'macOS' ]; then
-            base64_pat=$(echo -n "pat:${{ secrets.PAT_REVIEW }}" | base64)
-          else
-            base64_pat=$(echo -n "pat:${{ secrets.PAT_REVIEW }}" | base64 -w0)
-          fi
-
-          git config "$config_key" \
-            "Authorization: Basic $base64_pat"
-
-          cd tests/vcr_cassettes
-          git config "$config_key" \
-            "Authorization: Basic $base64_pat"
-
-          echo "config_key=$config_key" >> $GITHUB_OUTPUT
-
-      - id: push_cassettes
-        name: Push updated cassettes
-        # For pull requests, push updated cassettes even when tests fail
-        if: github.event_name == 'push' || (! github.event.pull_request.head.repo.fork && (success() || failure()))
-        env:
-          PR_BRANCH: ${{ github.event.pull_request.head.ref }}
-          PR_AUTHOR: ${{ github.event.pull_request.user.login }}
-        run: |
-          if [ "${{ startsWith(github.event_name, 'pull_request') }}" = "true" ]; then
-            is_pull_request=true
-            cassette_branch="${PR_AUTHOR}-${PR_BRANCH}"
-          else
-            cassette_branch="${{ github.ref_name }}"
-          fi
-
-          cd tests/vcr_cassettes
-          # Commit & push changes to cassettes if any
-          if ! git diff --quiet; then
-            git add .
-            git commit -m "Auto-update cassettes"
-            git push origin HEAD:$cassette_branch
-            if [ ! $is_pull_request ]; then
-              cd ../..
-              git add tests/vcr_cassettes
-              git commit -m "Update cassette submodule"
-              git push origin HEAD:$cassette_branch
-            fi
-            echo "updated=true" >> $GITHUB_OUTPUT
-          else
-            echo "updated=false" >> $GITHUB_OUTPUT
-            echo "No cassette changes to commit"
-          fi
-
-      - name: Post Set up git token auth
-        if: steps.setup_git_auth.outcome == 'success'
-        run: |
-          git config --unset-all '${{ steps.setup_git_auth.outputs.config_key }}'
-          git submodule foreach git config --unset-all '${{ steps.setup_git_auth.outputs.config_key }}'
-
-      - name: Apply "behaviour change" label and comment on PR
-        if: ${{ startsWith(github.event_name, 'pull_request') }}
-        run: |
-          PR_NUMBER="${{ github.event.pull_request.number }}"
-          TOKEN="${{ secrets.PAT_REVIEW }}"
-          REPO="${{ github.repository }}"
-
-          if [[ "${{ steps.push_cassettes.outputs.updated }}" == "true" ]]; then
-            echo "Adding label and comment..."
-            echo $TOKEN | gh auth login --with-token
-            gh issue edit $PR_NUMBER --add-label "behaviour change"
-            gh issue comment $PR_NUMBER --body "You changed AutoGPT's behaviour on ${{ runner.os }}. The cassettes have been updated and will be merged to the submodule when this Pull Request gets merged."
-          fi
+          flags: forge
 
       - name: Upload logs to artifact
         if: always()
         uses: actions/upload-artifact@v4
         with:
           name: test-logs
-          path: classic/forge/logs/
+          path: classic/logs/

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

@@ -1,60 +0,0 @@
-name: Classic - Frontend CI/CD
-
-on:
-  push:
-    branches:
-      - master
-      - dev
-      - 'ci-test*' # This will match any branch that starts with "ci-test"
-    paths:
-      - 'classic/frontend/**'
-      - '.github/workflows/classic-frontend-ci.yml'
-  pull_request:
-    paths:
-      - 'classic/frontend/**'
-      - '.github/workflows/classic-frontend-ci.yml'
-
-jobs:
-  build:
-    permissions:
-      contents: write
-      pull-requests: write
-    runs-on: ubuntu-latest
-    env:
-      BUILD_BRANCH: ${{ format('classic-frontend-build/{0}', github.ref_name) }}
-
-    steps:
-      - name: Checkout Repo
-        uses: actions/checkout@v4
-
-      - name: Setup Flutter
-        uses: subosito/flutter-action@v2
-        with:
-          flutter-version: '3.13.2'
-
-      - name: Build Flutter to Web
-        run: |
-          cd classic/frontend
-          flutter build web --base-href /app/
-
-      # - name: Commit and Push to ${{ env.BUILD_BRANCH }}
-      #   if: github.event_name == 'push'
-      #   run: |
-      #     git config --local user.email "action@github.com"
-      #     git config --local user.name "GitHub Action"
-      #     git add classic/frontend/build/web
-      #     git checkout -B ${{ env.BUILD_BRANCH }}
-      #     git commit -m "Update frontend build to ${GITHUB_SHA:0:7}" -a
-      #     git push -f origin ${{ env.BUILD_BRANCH }}
-
-      - name: Create PR ${{ env.BUILD_BRANCH }} -> ${{ github.ref_name }}
-        if: github.event_name == 'push'
-        uses: peter-evans/create-pull-request@v7
-        with:
-          add-paths: classic/frontend/build/web
-          base: ${{ github.ref_name }}
-          branch: ${{ env.BUILD_BRANCH }}
-          delete-branch: true
-          title: "Update frontend build in `${{ github.ref_name }}`"
-          body: "This PR updates the frontend build based on commit ${{ github.sha }}."
-          commit-message: "Update frontend build based on commit ${{ github.sha }}"

.github/workflows/classic-python-checks.yml

@@ -7,7 +7,9 @@ on:
       - '.github/workflows/classic-python-checks-ci.yml'
       - 'classic/original_autogpt/**'
       - 'classic/forge/**'
-      - 'classic/benchmark/**'
+      - 'classic/direct_benchmark/**'
+      - 'classic/pyproject.toml'
+      - 'classic/poetry.lock'
       - '**.py'
       - '!classic/forge/tests/vcr_cassettes'
   pull_request:
@@ -16,7 +18,9 @@ on:
       - '.github/workflows/classic-python-checks-ci.yml'
       - 'classic/original_autogpt/**'
       - 'classic/forge/**'
-      - 'classic/benchmark/**'
+      - 'classic/direct_benchmark/**'
+      - 'classic/pyproject.toml'
+      - 'classic/poetry.lock'
       - '**.py'
       - '!classic/forge/tests/vcr_cassettes'
 
@@ -27,44 +31,13 @@ concurrency:
 defaults:
   run:
     shell: bash
+    working-directory: classic
 
 jobs:
-  get-changed-parts:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v4
-
-      - id: changes-in
-        name: Determine affected subprojects
-        uses: dorny/paths-filter@v3
-        with:
-          filters: |
-            original_autogpt:
-              - classic/original_autogpt/autogpt/**
-              - classic/original_autogpt/tests/**
-              - classic/original_autogpt/poetry.lock
-            forge:
-              - classic/forge/forge/**
-              - classic/forge/tests/**
-              - classic/forge/poetry.lock
-            benchmark:
-              - classic/benchmark/agbenchmark/**
-              - classic/benchmark/tests/**
-              - classic/benchmark/poetry.lock
-    outputs:
-      changed-parts: ${{ steps.changes-in.outputs.changes }}
-
   lint:
-    needs: get-changed-parts
     runs-on: ubuntu-latest
     env:
-      min-python-version: "3.10"
-
-    strategy:
-      matrix:
-        sub-package: ${{ fromJson(needs.get-changed-parts.outputs.changed-parts) }}
-      fail-fast: false
+      min-python-version: "3.12"
 
     steps:
       - name: Checkout repository
@@ -81,42 +54,31 @@ jobs:
         uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
-          key: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
+          key: ${{ runner.os }}-poetry-${{ hashFiles('classic/poetry.lock') }}
 
       - name: Install Poetry
         run: curl -sSL https://install.python-poetry.org | python3 -
 
-      # Install dependencies
-
       - name: Install Python dependencies
-        run: poetry -C classic/${{ matrix.sub-package }} install
+        run: poetry install
 
       # Lint
 
       - name: Lint (isort)
         run: poetry run isort --check .
-        working-directory: classic/${{ matrix.sub-package }}
 
       - name: Lint (Black)
         if: success() || failure()
         run: poetry run black --check .
-        working-directory: classic/${{ matrix.sub-package }}
 
       - name: Lint (Flake8)
         if: success() || failure()
         run: poetry run flake8 .
-        working-directory: classic/${{ matrix.sub-package }}
 
   types:
-    needs: get-changed-parts
     runs-on: ubuntu-latest
     env:
-      min-python-version: "3.10"
-
-    strategy:
-      matrix:
-        sub-package: ${{ fromJson(needs.get-changed-parts.outputs.changed-parts) }}
-      fail-fast: false
+      min-python-version: "3.12"
 
     steps:
       - name: Checkout repository
@@ -133,19 +95,16 @@ jobs:
         uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
-          key: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
+          key: ${{ runner.os }}-poetry-${{ hashFiles('classic/poetry.lock') }}
 
       - name: Install Poetry
         run: curl -sSL https://install.python-poetry.org | python3 -
 
-      # Install dependencies
-
       - name: Install Python dependencies
-        run: poetry -C classic/${{ matrix.sub-package }} install
+        run: poetry install
 
       # Typecheck
 
       - name: Typecheck
         if: success() || failure()
         run: poetry run pyright
-        working-directory: classic/${{ matrix.sub-package }}

.gitignore

@@ -3,6 +3,7 @@
 classic/original_autogpt/keys.py
 classic/original_autogpt/*.json
 auto_gpt_workspace/*
+.autogpt/
 *.mpeg
 .env
 # Root .env files
@@ -159,6 +160,10 @@ CURRENT_BULLETIN.md
 
 # AgBenchmark
 classic/benchmark/agbenchmark/reports/
+classic/reports/
+classic/direct_benchmark/reports/
+classic/.benchmark_workspaces/
+classic/direct_benchmark/.benchmark_workspaces/
 
 # Nodejs
 package-lock.json
@@ -177,5 +182,8 @@ autogpt_platform/backend/settings.py
 
 *.ign.*
 .test-contents
-.claude/settings.local.json
+**/.claude/settings.local.json
 /autogpt_platform/backend/logs
+
+# Test database
+test.db

.gitmodules

@@ -1,3 +0,0 @@
-[submodule "classic/forge/tests/vcr_cassettes"]
-	path = classic/forge/tests/vcr_cassettes
-	url = https://github.com/Significant-Gravitas/Auto-GPT-test-cassettes

.pre-commit-config.yaml

@@ -43,29 +43,10 @@ repos:
         pass_filenames: false
 
       - id: poetry-install
-        name: Check & Install dependencies - Classic - AutoGPT
-        alias: poetry-install-classic-autogpt
-        entry: poetry -C classic/original_autogpt install
-        # include forge source (since it's a path dependency)
-        files: ^classic/(original_autogpt|forge)/poetry\.lock$
-        types: [file]
-        language: system
-        pass_filenames: false
-
-      - id: poetry-install
-        name: Check & Install dependencies - Classic - Forge
-        alias: poetry-install-classic-forge
-        entry: poetry -C classic/forge install
-        files: ^classic/forge/poetry\.lock$
-        types: [file]
-        language: system
-        pass_filenames: false
-
-      - id: poetry-install
-        name: Check & Install dependencies - Classic - Benchmark
-        alias: poetry-install-classic-benchmark
-        entry: poetry -C classic/benchmark install
-        files: ^classic/benchmark/poetry\.lock$
+        name: Check & Install dependencies - Classic
+        alias: poetry-install-classic
+        entry: poetry -C classic install
+        files: ^classic/poetry\.lock$
         types: [file]
         language: system
         pass_filenames: false
@@ -116,26 +97,10 @@ repos:
         language: system
 
       - id: isort
-        name: Lint (isort) - Classic - AutoGPT
-        alias: isort-classic-autogpt
-        entry: poetry -P classic/original_autogpt run isort -p autogpt
-        files: ^classic/original_autogpt/
-        types: [file, python]
-        language: system
-
-      - id: isort
-        name: Lint (isort) - Classic - Forge
-        alias: isort-classic-forge
-        entry: poetry -P classic/forge run isort -p forge
-        files: ^classic/forge/
-        types: [file, python]
-        language: system
-
-      - id: isort
-        name: Lint (isort) - Classic - Benchmark
-        alias: isort-classic-benchmark
-        entry: poetry -P classic/benchmark run isort -p agbenchmark
-        files: ^classic/benchmark/
+        name: Lint (isort) - Classic
+        alias: isort-classic
+        entry: bash -c 'cd classic && poetry run isort $(echo "$@" | sed "s|classic/||g")' --
+        files: ^classic/(original_autogpt|forge|direct_benchmark)/
         types: [file, python]
         language: system
 
@@ -149,26 +114,13 @@ repos:
 
   - repo: https://github.com/PyCQA/flake8
     rev: 7.0.0
-    # To have flake8 load the config of the individual subprojects, we have to call
-    # them separately.
+    # Use consolidated flake8 config at classic/.flake8
     hooks:
       - id: flake8
-        name: Lint (Flake8) - Classic - AutoGPT
-        alias: flake8-classic-autogpt
-        files: ^classic/original_autogpt/(autogpt|scripts|tests)/
-        args: [--config=classic/original_autogpt/.flake8]
-
-      - id: flake8
-        name: Lint (Flake8) - Classic - Forge
-        alias: flake8-classic-forge
-        files: ^classic/forge/(forge|tests)/
-        args: [--config=classic/forge/.flake8]
-
-      - id: flake8
-        name: Lint (Flake8) - Classic - Benchmark
-        alias: flake8-classic-benchmark
-        files: ^classic/benchmark/(agbenchmark|tests)/((?!reports).)*[/.]
-        args: [--config=classic/benchmark/.flake8]
+        name: Lint (Flake8) - Classic
+        alias: flake8-classic
+        files: ^classic/(original_autogpt|forge|direct_benchmark)/
+        args: [--config=classic/.flake8]
 
   - repo: local
     hooks:
@@ -204,29 +156,10 @@ repos:
         pass_filenames: false
 
       - id: pyright
-        name: Typecheck - Classic - AutoGPT
-        alias: pyright-classic-autogpt
-        entry: poetry -C classic/original_autogpt run pyright
-        # include forge source (since it's a path dependency) but exclude *_test.py files:
-        files: ^(classic/original_autogpt/((autogpt|scripts|tests)/|poetry\.lock$)|classic/forge/(forge/.*(?<!_test)\.py|poetry\.lock)$)
-        types: [file]
-        language: system
-        pass_filenames: false
-
-      - id: pyright
-        name: Typecheck - Classic - Forge
-        alias: pyright-classic-forge
-        entry: poetry -C classic/forge run pyright
-        files: ^classic/forge/(forge/|poetry\.lock$)
-        types: [file]
-        language: system
-        pass_filenames: false
-
-      - id: pyright
-        name: Typecheck - Classic - Benchmark
-        alias: pyright-classic-benchmark
-        entry: poetry -C classic/benchmark run pyright
-        files: ^classic/benchmark/(agbenchmark/|tests/|poetry\.lock$)
+        name: Typecheck - Classic
+        alias: pyright-classic
+        entry: poetry -C classic run pyright
+        files: ^classic/(original_autogpt|forge|direct_benchmark)/.*\.py$|^classic/poetry\.lock$
         types: [file]
         language: system
         pass_filenames: false

autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/core.py

@@ -218,7 +218,6 @@ async def save_agent_to_library(
     library_agents = await library_db.create_library_agent(
         graph=created_graph,
         user_id=user_id,
-        sensitive_action_safe_mode=True,
         create_library_agents_for_sub_graphs=False,
     )
 

autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py

@@ -33,7 +33,7 @@ from .models import (
     UserReadiness,
 )
 from .utils import (
-    build_missing_credentials_from_graph,
+    check_user_has_required_credentials,
     extract_credentials_from_schema,
     fetch_graph_from_store_slug,
     get_or_create_library_agent,
@@ -237,13 +237,15 @@ class RunAgentTool(BaseTool):
                 # Return credentials needed response with input data info
                 # The UI handles credential setup automatically, so the message
                 # focuses on asking about input data
-                requirements_creds_dict = build_missing_credentials_from_graph(
-                    graph, None
+                credentials = extract_credentials_from_schema(
+                    graph.credentials_input_schema
                 )
-                missing_credentials_dict = build_missing_credentials_from_graph(
-                    graph, graph_credentials
+                missing_creds_check = await check_user_has_required_credentials(
+                    user_id, credentials
                 )
-                requirements_creds_list = list(requirements_creds_dict.values())
+                missing_credentials_dict = {
+                    c.id: c.model_dump() for c in missing_creds_check
+                }
 
                 return SetupRequirementsResponse(
                     message=self._build_inputs_message(graph, MSG_WHAT_VALUES_TO_USE),
@@ -257,7 +259,7 @@ class RunAgentTool(BaseTool):
                             ready_to_run=False,
                         ),
                         requirements={
-                            "credentials": requirements_creds_list,
+                            "credentials": [c.model_dump() for c in credentials],
                             "inputs": self._get_inputs_list(graph.input_schema),
                             "execution_modes": self._get_execution_modes(graph),
                         },

autogpt_platform/backend/backend/api/features/chat/tools/run_block.py

@@ -22,7 +22,6 @@ from .models import (
     ToolResponseBase,
     UserReadiness,
 )
-from .utils import build_missing_credentials_from_field_info
 
 logger = logging.getLogger(__name__)
 
@@ -190,11 +189,7 @@ class RunBlockTool(BaseTool):
 
         if missing_credentials:
             # Return setup requirements response with missing credentials
-            credentials_fields_info = block.input_schema.get_credentials_fields_info()
-            missing_creds_dict = build_missing_credentials_from_field_info(
-                credentials_fields_info, set(matched_credentials.keys())
-            )
-            missing_creds_list = list(missing_creds_dict.values())
+            missing_creds_dict = {c.id: c.model_dump() for c in missing_credentials}
 
             return SetupRequirementsResponse(
                 message=(
@@ -211,7 +206,7 @@ class RunBlockTool(BaseTool):
                         ready_to_run=False,
                     ),
                     requirements={
-                        "credentials": missing_creds_list,
+                        "credentials": [c.model_dump() for c in missing_credentials],
                         "inputs": self._get_inputs_list(block),
                         "execution_modes": ["immediate"],
                     },

autogpt_platform/backend/backend/api/features/chat/tools/utils.py

@@ -8,7 +8,7 @@ from backend.api.features.library import model as library_model
 from backend.api.features.store import db as store_db
 from backend.data import graph as graph_db
 from backend.data.graph import GraphModel
-from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
+from backend.data.model import CredentialsMetaInput
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import NotFoundError
 
@@ -89,59 +89,6 @@ def extract_credentials_from_schema(
     return credentials
 
 
-def _serialize_missing_credential(
-    field_key: str, field_info: CredentialsFieldInfo
-) -> dict[str, Any]:
-    """
-    Convert credential field info into a serializable dict that preserves all supported
-    credential types (e.g., api_key + oauth2) so the UI can offer multiple options.
-    """
-    supported_types = sorted(field_info.supported_types)
-    provider = next(iter(field_info.provider), "unknown")
-    scopes = sorted(field_info.required_scopes or [])
-
-    return {
-        "id": field_key,
-        "title": field_key.replace("_", " ").title(),
-        "provider": provider,
-        "provider_name": provider.replace("_", " ").title(),
-        "type": supported_types[0] if supported_types else "api_key",
-        "types": supported_types,
-        "scopes": scopes,
-    }
-
-
-def build_missing_credentials_from_graph(
-    graph: GraphModel, matched_credentials: dict[str, CredentialsMetaInput] | None
-) -> dict[str, Any]:
-    """
-    Build a missing_credentials mapping from a graph's aggregated credentials inputs,
-    preserving all supported credential types for each field.
-    """
-    matched_keys = set(matched_credentials.keys()) if matched_credentials else set()
-    aggregated_fields = graph.aggregate_credentials_inputs()
-
-    return {
-        field_key: _serialize_missing_credential(field_key, field_info)
-        for field_key, (field_info, _node_fields) in aggregated_fields.items()
-        if field_key not in matched_keys
-    }
-
-
-def build_missing_credentials_from_field_info(
-    credential_fields: dict[str, CredentialsFieldInfo],
-    matched_keys: set[str],
-) -> dict[str, Any]:
-    """
-    Build missing_credentials mapping from a simple credentials field info dictionary.
-    """
-    return {
-        field_key: _serialize_missing_credential(field_key, field_info)
-        for field_key, field_info in credential_fields.items()
-        if field_key not in matched_keys
-    }
-
-
 def extract_credentials_as_dict(
     credentials_input_schema: dict[str, Any] | None,
 ) -> dict[str, CredentialsMetaInput]:

autogpt_platform/backend/backend/api/features/library/db.py

@@ -401,11 +401,27 @@ async def add_generated_agent_image(
     )
 
 
+def _initialize_graph_settings(graph: graph_db.GraphModel) -> GraphSettings:
+    """
+    Initialize GraphSettings based on graph content.
+
+    Args:
+        graph: The graph to analyze
+
+    Returns:
+        GraphSettings with appropriate human_in_the_loop_safe_mode value
+    """
+    if graph.has_human_in_the_loop:
+        # Graph has HITL blocks - set safe mode to True by default
+        return GraphSettings(human_in_the_loop_safe_mode=True)
+    else:
+        # Graph has no HITL blocks - keep None
+        return GraphSettings(human_in_the_loop_safe_mode=None)
+
+
 async def create_library_agent(
     graph: graph_db.GraphModel,
     user_id: str,
-    hitl_safe_mode: bool = True,
-    sensitive_action_safe_mode: bool = False,
     create_library_agents_for_sub_graphs: bool = True,
 ) -> list[library_model.LibraryAgent]:
     """
@@ -414,8 +430,6 @@ async def create_library_agent(
     Args:
         agent: The agent/Graph to add to the library.
         user_id: The user to whom the agent will be added.
-        hitl_safe_mode: Whether HITL blocks require manual review (default True).
-        sensitive_action_safe_mode: Whether sensitive action blocks require review.
         create_library_agents_for_sub_graphs: If True, creates LibraryAgent records for sub-graphs as well.
 
     Returns:
@@ -451,11 +465,7 @@ async def create_library_agent(
                             }
                         },
                         settings=SafeJson(
-                            GraphSettings.from_graph(
-                                graph_entry,
-                                hitl_safe_mode=hitl_safe_mode,
-                                sensitive_action_safe_mode=sensitive_action_safe_mode,
-                            ).model_dump()
+                            _initialize_graph_settings(graph_entry).model_dump()
                         ),
                     ),
                     include=library_agent_include(
@@ -617,6 +627,33 @@ async def update_library_agent(
         raise DatabaseError("Failed to update library agent") from e
 
 
+async def update_library_agent_settings(
+    user_id: str,
+    agent_id: str,
+    settings: GraphSettings,
+) -> library_model.LibraryAgent:
+    """
+    Updates the settings for a specific LibraryAgent.
+
+    Args:
+        user_id: The owner of the LibraryAgent.
+        agent_id: The ID of the LibraryAgent to update.
+        settings: New GraphSettings to apply.
+
+    Returns:
+        The updated LibraryAgent.
+
+    Raises:
+        NotFoundError: If the specified LibraryAgent does not exist.
+        DatabaseError: If there's an error in the update operation.
+    """
+    return await update_library_agent(
+        library_agent_id=agent_id,
+        user_id=user_id,
+        settings=settings,
+    )
+
+
 async def delete_library_agent(
     library_agent_id: str, user_id: str, soft_delete: bool = True
 ) -> None:
@@ -801,7 +838,7 @@ async def add_store_agent_to_library(
                 "isCreatedByUser": False,
                 "useGraphIsActiveVersion": False,
                 "settings": SafeJson(
-                    GraphSettings.from_graph(graph_model).model_dump()
+                    _initialize_graph_settings(graph_model).model_dump()
                 ),
             },
             include=library_agent_include(
@@ -1191,15 +1228,8 @@ async def fork_library_agent(
         )
         new_graph = await on_graph_activate(new_graph, user_id=user_id)
 
-        # Create a library agent for the new graph, preserving safe mode settings
-        return (
-            await create_library_agent(
-                new_graph,
-                user_id,
-                hitl_safe_mode=original_agent.settings.human_in_the_loop_safe_mode,
-                sensitive_action_safe_mode=original_agent.settings.sensitive_action_safe_mode,
-            )
-        )[0]
+        # Create a library agent for the new graph
+        return (await create_library_agent(new_graph, user_id))[0]
     except prisma.errors.PrismaError as e:
         logger.error(f"Database error cloning library agent: {e}")
         raise DatabaseError("Failed to fork library agent") from e

autogpt_platform/backend/backend/api/features/library/model.py

@@ -73,12 +73,6 @@ class LibraryAgent(pydantic.BaseModel):
     has_external_trigger: bool = pydantic.Field(
         description="Whether the agent has an external trigger (e.g. webhook) node"
     )
-    has_human_in_the_loop: bool = pydantic.Field(
-        description="Whether the agent has human-in-the-loop blocks"
-    )
-    has_sensitive_action: bool = pydantic.Field(
-        description="Whether the agent has sensitive action blocks"
-    )
     trigger_setup_info: Optional[GraphTriggerInfo] = None
 
     # Indicates whether there's a new output (based on recent runs)
@@ -186,8 +180,6 @@ class LibraryAgent(pydantic.BaseModel):
                 graph.credentials_input_schema if sub_graphs is not None else None
             ),
             has_external_trigger=graph.has_external_trigger,
-            has_human_in_the_loop=graph.has_human_in_the_loop,
-            has_sensitive_action=graph.has_sensitive_action,
             trigger_setup_info=graph.trigger_setup_info,
             new_output=new_output,
             can_access_graph=can_access_graph,

autogpt_platform/backend/backend/api/features/library/routes_test.py

@@ -52,8 +52,6 @@ async def test_get_library_agents_success(
                 output_schema={"type": "object", "properties": {}},
                 credentials_input_schema={"type": "object", "properties": {}},
                 has_external_trigger=False,
-                has_human_in_the_loop=False,
-                has_sensitive_action=False,
                 status=library_model.LibraryAgentStatus.COMPLETED,
                 recommended_schedule_cron=None,
                 new_output=False,
@@ -77,8 +75,6 @@ async def test_get_library_agents_success(
                 output_schema={"type": "object", "properties": {}},
                 credentials_input_schema={"type": "object", "properties": {}},
                 has_external_trigger=False,
-                has_human_in_the_loop=False,
-                has_sensitive_action=False,
                 status=library_model.LibraryAgentStatus.COMPLETED,
                 recommended_schedule_cron=None,
                 new_output=False,
@@ -154,8 +150,6 @@ async def test_get_favorite_library_agents_success(
                 output_schema={"type": "object", "properties": {}},
                 credentials_input_schema={"type": "object", "properties": {}},
                 has_external_trigger=False,
-                has_human_in_the_loop=False,
-                has_sensitive_action=False,
                 status=library_model.LibraryAgentStatus.COMPLETED,
                 recommended_schedule_cron=None,
                 new_output=False,
@@ -224,8 +218,6 @@ def test_add_agent_to_library_success(
         output_schema={"type": "object", "properties": {}},
         credentials_input_schema={"type": "object", "properties": {}},
         has_external_trigger=False,
-        has_human_in_the_loop=False,
-        has_sensitive_action=False,
         status=library_model.LibraryAgentStatus.COMPLETED,
         new_output=False,
         can_access_graph=True,

autogpt_platform/backend/backend/api/features/store/embeddings.py

@@ -154,16 +154,15 @@ async def store_content_embedding(
 
         # Upsert the embedding
         # WHERE clause in DO UPDATE prevents PostgreSQL 15 bug with NULLS NOT DISTINCT
-        # Use {pgvector_schema}.vector for explicit pgvector type qualification
         await execute_raw_with_schema(
             """
             INSERT INTO {schema_prefix}"UnifiedContentEmbedding" (
                 "id", "contentType", "contentId", "userId", "embedding", "searchableText", "metadata", "createdAt", "updatedAt"
             )
-            VALUES (gen_random_uuid()::text, $1::{schema_prefix}"ContentType", $2, $3, $4::{pgvector_schema}.vector, $5, $6::jsonb, NOW(), NOW())
+            VALUES (gen_random_uuid()::text, $1::{schema_prefix}"ContentType", $2, $3, $4::vector, $5, $6::jsonb, NOW(), NOW())
             ON CONFLICT ("contentType", "contentId", "userId")
             DO UPDATE SET
-                "embedding" = $4::{pgvector_schema}.vector,
+                "embedding" = $4::vector,
                 "searchableText" = $5,
                 "metadata" = $6::jsonb,
                 "updatedAt" = NOW()
@@ -178,6 +177,7 @@ async def store_content_embedding(
             searchable_text,
             metadata_json,
             client=client,
+            set_public_search_path=True,
         )
 
         logger.info(f"Stored embedding for {content_type}:{content_id}")
@@ -236,6 +236,7 @@ async def get_content_embedding(
             content_type,
             content_id,
             user_id,
+            set_public_search_path=True,
         )
 
         if result and len(result) > 0:
@@ -870,46 +871,31 @@ async def semantic_search(
         # Add content type parameters and build placeholders dynamically
         content_type_start_idx = len(params) + 1
         content_type_placeholders = ", ".join(
-            "$" + str(content_type_start_idx + i) + '::{schema_prefix}"ContentType"'
+            f'${content_type_start_idx + i}::{{{{schema_prefix}}}}"ContentType"'
             for i in range(len(content_types))
         )
         params.extend([ct.value for ct in content_types])
 
-        # Build min_similarity param index before appending
-        min_similarity_idx = len(params) + 1
-        params.append(min_similarity)
-
-        # Use regular string (not f-string) for template to preserve {schema_prefix} and {schema} placeholders
-        # Use OPERATOR({pgvector_schema}.<=>) for explicit operator schema qualification
-        sql = (
-            """
+        sql = f"""
             SELECT
                 "contentId" as content_id,
                 "contentType" as content_type,
                 "searchableText" as searchable_text,
                 metadata,
-                1 - (embedding OPERATOR({pgvector_schema}.<=>) '"""
-            + embedding_str
-            + """'::{pgvector_schema}.vector) as similarity
-            FROM {schema_prefix}"UnifiedContentEmbedding"
-            WHERE "contentType" IN ("""
-            + content_type_placeholders
-            + """)
-            """
-            + user_filter
-            + """
-            AND 1 - (embedding OPERATOR({pgvector_schema}.<=>) '"""
-            + embedding_str
-            + """'::{pgvector_schema}.vector) >= $"""
-            + str(min_similarity_idx)
-            + """
+                1 - (embedding <=> '{embedding_str}'::vector) as similarity
+            FROM {{{{schema_prefix}}}}"UnifiedContentEmbedding"
+            WHERE "contentType" IN ({content_type_placeholders})
+            {user_filter}
+            AND 1 - (embedding <=> '{embedding_str}'::vector) >= ${len(params) + 1}
             ORDER BY similarity DESC
             LIMIT $1
         """
-        )
+        params.append(min_similarity)
 
         try:
-            results = await query_raw_with_schema(sql, *params)
+            results = await query_raw_with_schema(
+                sql, *params, set_public_search_path=True
+            )
             return [
                 {
                     "content_id": row["content_id"],
@@ -936,41 +922,31 @@ async def semantic_search(
     # Add content type parameters and build placeholders dynamically
     content_type_start_idx = len(params_lexical) + 1
     content_type_placeholders_lexical = ", ".join(
-        "$" + str(content_type_start_idx + i) + '::{schema_prefix}"ContentType"'
+        f'${content_type_start_idx + i}::{{{{schema_prefix}}}}"ContentType"'
         for i in range(len(content_types))
     )
     params_lexical.extend([ct.value for ct in content_types])
 
-    # Build query param index before appending
-    query_param_idx = len(params_lexical) + 1
-    params_lexical.append(f"%{query}%")
-
-    # Use regular string (not f-string) for template to preserve {schema_prefix} placeholders
-    sql_lexical = (
-        """
+    sql_lexical = f"""
         SELECT
             "contentId" as content_id,
             "contentType" as content_type,
             "searchableText" as searchable_text,
             metadata,
             0.0 as similarity
-        FROM {schema_prefix}"UnifiedContentEmbedding"
-        WHERE "contentType" IN ("""
-        + content_type_placeholders_lexical
-        + """)
-        """
-        + user_filter
-        + """
-        AND "searchableText" ILIKE $"""
-        + str(query_param_idx)
-        + """
+        FROM {{{{schema_prefix}}}}"UnifiedContentEmbedding"
+        WHERE "contentType" IN ({content_type_placeholders_lexical})
+        {user_filter}
+        AND "searchableText" ILIKE ${len(params_lexical) + 1}
         ORDER BY "updatedAt" DESC
         LIMIT $1
     """
-    )
+    params_lexical.append(f"%{query}%")
 
     try:
-        results = await query_raw_with_schema(sql_lexical, *params_lexical)
+        results = await query_raw_with_schema(
+            sql_lexical, *params_lexical, set_public_search_path=True
+        )
         return [
             {
                 "content_id": row["content_id"],

autogpt_platform/backend/backend/api/features/store/embeddings_test.py

@@ -155,14 +155,18 @@ async def test_store_embedding_success(mocker):
     )
 
     assert result is True
-    # execute_raw is called once for INSERT (no separate SET search_path needed)
-    assert mock_client.execute_raw.call_count == 1
+    # execute_raw is called twice: once for SET search_path, once for INSERT
+    assert mock_client.execute_raw.call_count == 2
 
-    # Verify the INSERT query with the actual data
-    call_args = mock_client.execute_raw.call_args_list[0][0]
-    assert "test-version-id" in call_args
-    assert "[0.1,0.2,0.3]" in call_args
-    assert None in call_args  # userId should be None for store agents
+    # First call: SET search_path
+    first_call_args = mock_client.execute_raw.call_args_list[0][0]
+    assert "SET search_path" in first_call_args[0]
+
+    # Second call: INSERT query with the actual data
+    second_call_args = mock_client.execute_raw.call_args_list[1][0]
+    assert "test-version-id" in second_call_args
+    assert "[0.1,0.2,0.3]" in second_call_args
+    assert None in second_call_args  # userId should be None for store agents
 
 
 @pytest.mark.asyncio(loop_scope="session")

autogpt_platform/backend/backend/api/features/store/hybrid_search.py

@@ -12,7 +12,7 @@ from dataclasses import dataclass
 from typing import Any, Literal
 
 from prisma.enums import ContentType
-from rank_bm25 import BM25Okapi  # type: ignore[import-untyped]
+from rank_bm25 import BM25Okapi
 
 from backend.api.features.store.embeddings import (
     EMBEDDING_DIM,
@@ -295,7 +295,7 @@ async def unified_hybrid_search(
                 FROM {{schema_prefix}}"UnifiedContentEmbedding" uce
                 WHERE uce."contentType" = ANY({content_types_param}::{{schema_prefix}}"ContentType"[])
                 {user_filter}
-                ORDER BY uce.embedding OPERATOR({{pgvector_schema}}.<=>)  {embedding_param}::{{pgvector_schema}}.vector
+                ORDER BY uce.embedding <=> {embedding_param}::vector
                 LIMIT 200
             )
         ),
@@ -307,7 +307,7 @@ async def unified_hybrid_search(
                 uce.metadata,
                 uce."updatedAt" as updated_at,
                 -- Semantic score: cosine similarity (1 - distance)
-                COALESCE(1 - (uce.embedding OPERATOR({{pgvector_schema}}.<=>)  {embedding_param}::{{pgvector_schema}}.vector), 0) as semantic_score,
+                COALESCE(1 - (uce.embedding <=> {embedding_param}::vector), 0) as semantic_score,
                 -- Lexical score: ts_rank_cd
                 COALESCE(ts_rank_cd(uce.search, plainto_tsquery('english', {query_param})), 0) as lexical_raw,
                 -- Category match from metadata
@@ -363,7 +363,9 @@ async def unified_hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(sql_query, *params)
+    results = await query_raw_with_schema(
+        sql_query, *params, set_public_search_path=True
+    )
 
     total = results[0]["total_count"] if results else 0
     # Apply BM25 reranking
@@ -583,7 +585,7 @@ async def hybrid_search(
                 WHERE uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
                 AND uce."userId" IS NULL
                 AND {where_clause}
-                ORDER BY uce.embedding OPERATOR({{pgvector_schema}}.<=>)  {embedding_param}::{{pgvector_schema}}.vector
+                ORDER BY uce.embedding <=> {embedding_param}::vector
                 LIMIT 200
             ) uce
         ),
@@ -605,7 +607,7 @@ async def hybrid_search(
                 -- Searchable text for BM25 reranking
                 COALESCE(sa.agent_name, '') || ' ' || COALESCE(sa.sub_heading, '') || ' ' || COALESCE(sa.description, '') as searchable_text,
                 -- Semantic score
-                COALESCE(1 - (uce.embedding OPERATOR({{pgvector_schema}}.<=>)  {embedding_param}::{{pgvector_schema}}.vector), 0) as semantic_score,
+                COALESCE(1 - (uce.embedding <=> {embedding_param}::vector), 0) as semantic_score,
                 -- Lexical score (raw, will normalize)
                 COALESCE(ts_rank_cd(uce.search, plainto_tsquery('english', {query_param})), 0) as lexical_raw,
                 -- Category match
@@ -686,7 +688,9 @@ async def hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(sql_query, *params)
+    results = await query_raw_with_schema(
+        sql_query, *params, set_public_search_path=True
+    )
 
     total = results[0]["total_count"] if results else 0
 

autogpt_platform/backend/backend/api/features/v1.py

@@ -761,8 +761,10 @@ async def create_new_graph(
     graph.reassign_ids(user_id=user_id, reassign_graph_id=True)
     graph.validate_graph(for_run=False)
 
+    # The return value of the create graph & library function is intentionally not used here,
+    # as the graph already valid and no sub-graphs are returned back.
     await graph_db.create_graph(graph, user_id=user_id)
-    await library_db.create_library_agent(graph, user_id)
+    await library_db.create_library_agent(graph, user_id=user_id)
     activated_graph = await on_graph_activate(graph, user_id=user_id)
 
     if create_graph.source == "builder":
@@ -886,19 +888,21 @@ async def set_graph_active_version(
 async def _update_library_agent_version_and_settings(
     user_id: str, agent_graph: graph_db.GraphModel
 ) -> library_model.LibraryAgent:
+    # Keep the library agent up to date with the new active version
     library = await library_db.update_agent_version_in_library(
         user_id, agent_graph.id, agent_graph.version
     )
-    updated_settings = GraphSettings.from_graph(
-        graph=agent_graph,
-        hitl_safe_mode=library.settings.human_in_the_loop_safe_mode,
-        sensitive_action_safe_mode=library.settings.sensitive_action_safe_mode,
-    )
-    if updated_settings != library.settings:
-        library = await library_db.update_library_agent(
-            library_agent_id=library.id,
+    # If the graph has HITL node, initialize the setting if it's not already set.
+    if (
+        agent_graph.has_human_in_the_loop
+        and library.settings.human_in_the_loop_safe_mode is None
+    ):
+        await library_db.update_library_agent_settings(
             user_id=user_id,
-            settings=updated_settings,
+            agent_id=library.id,
+            settings=library.settings.model_copy(
+                update={"human_in_the_loop_safe_mode": True}
+            ),
         )
     return library
 
@@ -915,18 +919,21 @@ async def update_graph_settings(
     user_id: Annotated[str, Security(get_user_id)],
 ) -> GraphSettings:
     """Update graph settings for the user's library agent."""
+    # Get the library agent for this graph
     library_agent = await library_db.get_library_agent_by_graph_id(
         graph_id=graph_id, user_id=user_id
     )
     if not library_agent:
         raise HTTPException(404, f"Graph #{graph_id} not found in user's library")
 
-    updated_agent = await library_db.update_library_agent(
-        library_agent_id=library_agent.id,
+    # Update the library agent settings
+    updated_agent = await library_db.update_library_agent_settings(
         user_id=user_id,
+        agent_id=library_agent.id,
         settings=settings,
     )
 
+    # Return the updated settings
     return GraphSettings.model_validate(updated_agent.settings)
 
 

autogpt_platform/backend/backend/blocks/data_manipulation.py

@@ -680,58 +680,3 @@ class ListIsEmptyBlock(Block):
 
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         yield "is_empty", len(input_data.list) == 0
-
-
-class ConcatenateListsBlock(Block):
-    class Input(BlockSchemaInput):
-        lists: List[List[Any]] = SchemaField(
-            description="A list of lists to concatenate together. All lists will be combined in order into a single list.",
-            placeholder="e.g., [[1, 2], [3, 4], [5, 6]]",
-        )
-
-    class Output(BlockSchemaOutput):
-        concatenated_list: List[Any] = SchemaField(
-            description="The concatenated list containing all elements from all input lists in order."
-        )
-        error: str = SchemaField(
-            description="Error message if concatenation failed due to invalid input types."
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="3cf9298b-5817-4141-9d80-7c2cc5199c8e",
-            description="Concatenates multiple lists into a single list. All elements from all input lists are combined in order.",
-            categories={BlockCategory.BASIC},
-            input_schema=ConcatenateListsBlock.Input,
-            output_schema=ConcatenateListsBlock.Output,
-            test_input=[
-                {"lists": [[1, 2, 3], [4, 5, 6]]},
-                {"lists": [["a", "b"], ["c"], ["d", "e", "f"]]},
-                {"lists": [[1, 2], []]},
-                {"lists": []},
-            ],
-            test_output=[
-                ("concatenated_list", [1, 2, 3, 4, 5, 6]),
-                ("concatenated_list", ["a", "b", "c", "d", "e", "f"]),
-                ("concatenated_list", [1, 2]),
-                ("concatenated_list", []),
-            ],
-        )
-
-    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        concatenated = []
-        for idx, lst in enumerate(input_data.lists):
-            if lst is None:
-                # Skip None values to avoid errors
-                continue
-            if not isinstance(lst, list):
-                # Type validation: each item must be a list
-                # Strings are iterable and would cause extend() to iterate character-by-character
-                # Non-iterable types would raise TypeError
-                yield "error", (
-                    f"Invalid input at index {idx}: expected a list, got {type(lst).__name__}. "
-                    f"All items in 'lists' must be lists (e.g., [[1, 2], [3, 4]])."
-                )
-                return
-            concatenated.extend(lst)
-        yield "concatenated_list", concatenated

autogpt_platform/backend/backend/blocks/helpers/review.py

@@ -84,7 +84,7 @@ class HITLReviewHelper:
             Exception: If review creation or status update fails
         """
         # Skip review if safe mode is disabled - return auto-approved result
-        if not execution_context.human_in_the_loop_safe_mode:
+        if not execution_context.safe_mode:
             logger.info(
                 f"Block {block_name} skipping review for node {node_exec_id} - safe mode disabled"
             )

autogpt_platform/backend/backend/blocks/human_in_the_loop.py

@@ -104,7 +104,7 @@ class HumanInTheLoopBlock(Block):
         execution_context: ExecutionContext,
         **_kwargs,
     ) -> BlockOutput:
-        if not execution_context.human_in_the_loop_safe_mode:
+        if not execution_context.safe_mode:
             logger.info(
                 f"HITL block skipping review for node {node_exec_id} - safe mode disabled"
             )

autogpt_platform/backend/backend/blocks/llm.py

@@ -79,10 +79,6 @@ class ModelMetadata(NamedTuple):
     provider: str
     context_window: int
     max_output_tokens: int | None
-    display_name: str
-    provider_name: str
-    creator_name: str
-    price_tier: Literal[1, 2, 3]
 
 
 class LlmModelMeta(EnumMeta):
@@ -175,26 +171,6 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     V0_1_5_LG = "v0-1.5-lg"
     V0_1_0_MD = "v0-1.0-md"
 
-    @classmethod
-    def __get_pydantic_json_schema__(cls, schema, handler):
-        json_schema = handler(schema)
-        llm_model_metadata = {}
-        for model in cls:
-            model_name = model.value
-            metadata = model.metadata
-            llm_model_metadata[model_name] = {
-                "creator": metadata.creator_name,
-                "creator_name": metadata.creator_name,
-                "title": metadata.display_name,
-                "provider": metadata.provider,
-                "provider_name": metadata.provider_name,
-                "name": model_name,
-                "price_tier": metadata.price_tier,
-            }
-        json_schema["llm_model"] = True
-        json_schema["llm_model_metadata"] = llm_model_metadata
-        return json_schema
-
     @property
     def metadata(self) -> ModelMetadata:
         return MODEL_METADATA[self]
@@ -214,291 +190,119 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
 
 MODEL_METADATA = {
     # https://platform.openai.com/docs/models
-    LlmModel.O3: ModelMetadata("openai", 200000, 100000, "O3", "OpenAI", "OpenAI", 2),
-    LlmModel.O3_MINI: ModelMetadata(
-        "openai", 200000, 100000, "O3 Mini", "OpenAI", "OpenAI", 1
-    ),  # o3-mini-2025-01-31
-    LlmModel.O1: ModelMetadata(
-        "openai", 200000, 100000, "O1", "OpenAI", "OpenAI", 3
-    ),  # o1-2024-12-17
-    LlmModel.O1_MINI: ModelMetadata(
-        "openai", 128000, 65536, "O1 Mini", "OpenAI", "OpenAI", 2
-    ),  # o1-mini-2024-09-12
+    LlmModel.O3: ModelMetadata("openai", 200000, 100000),
+    LlmModel.O3_MINI: ModelMetadata("openai", 200000, 100000),  # o3-mini-2025-01-31
+    LlmModel.O1: ModelMetadata("openai", 200000, 100000),  # o1-2024-12-17
+    LlmModel.O1_MINI: ModelMetadata("openai", 128000, 65536),  # o1-mini-2024-09-12
     # GPT-5 models
-    LlmModel.GPT5_2: ModelMetadata(
-        "openai", 400000, 128000, "GPT-5.2", "OpenAI", "OpenAI", 3
-    ),
-    LlmModel.GPT5_1: ModelMetadata(
-        "openai", 400000, 128000, "GPT-5.1", "OpenAI", "OpenAI", 2
-    ),
-    LlmModel.GPT5: ModelMetadata(
-        "openai", 400000, 128000, "GPT-5", "OpenAI", "OpenAI", 1
-    ),
-    LlmModel.GPT5_MINI: ModelMetadata(
-        "openai", 400000, 128000, "GPT-5 Mini", "OpenAI", "OpenAI", 1
-    ),
-    LlmModel.GPT5_NANO: ModelMetadata(
-        "openai", 400000, 128000, "GPT-5 Nano", "OpenAI", "OpenAI", 1
-    ),
-    LlmModel.GPT5_CHAT: ModelMetadata(
-        "openai", 400000, 16384, "GPT-5 Chat Latest", "OpenAI", "OpenAI", 2
-    ),
-    LlmModel.GPT41: ModelMetadata(
-        "openai", 1047576, 32768, "GPT-4.1", "OpenAI", "OpenAI", 1
-    ),
-    LlmModel.GPT41_MINI: ModelMetadata(
-        "openai", 1047576, 32768, "GPT-4.1 Mini", "OpenAI", "OpenAI", 1
-    ),
+    LlmModel.GPT5_2: ModelMetadata("openai", 400000, 128000),
+    LlmModel.GPT5_1: ModelMetadata("openai", 400000, 128000),
+    LlmModel.GPT5: ModelMetadata("openai", 400000, 128000),
+    LlmModel.GPT5_MINI: ModelMetadata("openai", 400000, 128000),
+    LlmModel.GPT5_NANO: ModelMetadata("openai", 400000, 128000),
+    LlmModel.GPT5_CHAT: ModelMetadata("openai", 400000, 16384),
+    LlmModel.GPT41: ModelMetadata("openai", 1047576, 32768),
+    LlmModel.GPT41_MINI: ModelMetadata("openai", 1047576, 32768),
     LlmModel.GPT4O_MINI: ModelMetadata(
-        "openai", 128000, 16384, "GPT-4o Mini", "OpenAI", "OpenAI", 1
+        "openai", 128000, 16384
     ),  # gpt-4o-mini-2024-07-18
-    LlmModel.GPT4O: ModelMetadata(
-        "openai", 128000, 16384, "GPT-4o", "OpenAI", "OpenAI", 2
-    ),  # gpt-4o-2024-08-06
+    LlmModel.GPT4O: ModelMetadata("openai", 128000, 16384),  # gpt-4o-2024-08-06
     LlmModel.GPT4_TURBO: ModelMetadata(
-        "openai", 128000, 4096, "GPT-4 Turbo", "OpenAI", "OpenAI", 3
+        "openai", 128000, 4096
     ),  # gpt-4-turbo-2024-04-09
-    LlmModel.GPT3_5_TURBO: ModelMetadata(
-        "openai", 16385, 4096, "GPT-3.5 Turbo", "OpenAI", "OpenAI", 1
-    ),  # gpt-3.5-turbo-0125
+    LlmModel.GPT3_5_TURBO: ModelMetadata("openai", 16385, 4096),  # gpt-3.5-turbo-0125
     # https://docs.anthropic.com/en/docs/about-claude/models
     LlmModel.CLAUDE_4_1_OPUS: ModelMetadata(
-        "anthropic", 200000, 32000, "Claude Opus 4.1", "Anthropic", "Anthropic", 3
+        "anthropic", 200000, 32000
     ),  # claude-opus-4-1-20250805
     LlmModel.CLAUDE_4_OPUS: ModelMetadata(
-        "anthropic", 200000, 32000, "Claude Opus 4", "Anthropic", "Anthropic", 3
+        "anthropic", 200000, 32000
     ),  # claude-4-opus-20250514
     LlmModel.CLAUDE_4_SONNET: ModelMetadata(
-        "anthropic", 200000, 64000, "Claude Sonnet 4", "Anthropic", "Anthropic", 2
+        "anthropic", 200000, 64000
     ),  # claude-4-sonnet-20250514
     LlmModel.CLAUDE_4_5_OPUS: ModelMetadata(
-        "anthropic", 200000, 64000, "Claude Opus 4.5", "Anthropic", "Anthropic", 3
+        "anthropic", 200000, 64000
     ),  # claude-opus-4-5-20251101
     LlmModel.CLAUDE_4_5_SONNET: ModelMetadata(
-        "anthropic", 200000, 64000, "Claude Sonnet 4.5", "Anthropic", "Anthropic", 3
+        "anthropic", 200000, 64000
     ),  # claude-sonnet-4-5-20250929
     LlmModel.CLAUDE_4_5_HAIKU: ModelMetadata(
-        "anthropic", 200000, 64000, "Claude Haiku 4.5", "Anthropic", "Anthropic", 2
+        "anthropic", 200000, 64000
     ),  # claude-haiku-4-5-20251001
     LlmModel.CLAUDE_3_7_SONNET: ModelMetadata(
-        "anthropic", 200000, 64000, "Claude 3.7 Sonnet", "Anthropic", "Anthropic", 2
+        "anthropic", 200000, 64000
     ),  # claude-3-7-sonnet-20250219
     LlmModel.CLAUDE_3_HAIKU: ModelMetadata(
-        "anthropic", 200000, 4096, "Claude 3 Haiku", "Anthropic", "Anthropic", 1
+        "anthropic", 200000, 4096
     ),  # claude-3-haiku-20240307
     # https://docs.aimlapi.com/api-overview/model-database/text-models
-    LlmModel.AIML_API_QWEN2_5_72B: ModelMetadata(
-        "aiml_api", 32000, 8000, "Qwen 2.5 72B Instruct Turbo", "AI/ML", "Qwen", 1
-    ),
-    LlmModel.AIML_API_LLAMA3_1_70B: ModelMetadata(
-        "aiml_api",
-        128000,
-        40000,
-        "Llama 3.1 Nemotron 70B Instruct",
-        "AI/ML",
-        "Nvidia",
-        1,
-    ),
-    LlmModel.AIML_API_LLAMA3_3_70B: ModelMetadata(
-        "aiml_api", 128000, None, "Llama 3.3 70B Instruct Turbo", "AI/ML", "Meta", 1
-    ),
-    LlmModel.AIML_API_META_LLAMA_3_1_70B: ModelMetadata(
-        "aiml_api", 131000, 2000, "Llama 3.1 70B Instruct Turbo", "AI/ML", "Meta", 1
-    ),
-    LlmModel.AIML_API_LLAMA_3_2_3B: ModelMetadata(
-        "aiml_api", 128000, None, "Llama 3.2 3B Instruct Turbo", "AI/ML", "Meta", 1
-    ),
+    LlmModel.AIML_API_QWEN2_5_72B: ModelMetadata("aiml_api", 32000, 8000),
+    LlmModel.AIML_API_LLAMA3_1_70B: ModelMetadata("aiml_api", 128000, 40000),
+    LlmModel.AIML_API_LLAMA3_3_70B: ModelMetadata("aiml_api", 128000, None),
+    LlmModel.AIML_API_META_LLAMA_3_1_70B: ModelMetadata("aiml_api", 131000, 2000),
+    LlmModel.AIML_API_LLAMA_3_2_3B: ModelMetadata("aiml_api", 128000, None),
     # https://console.groq.com/docs/models
-    LlmModel.LLAMA3_3_70B: ModelMetadata(
-        "groq", 128000, 32768, "Llama 3.3 70B Versatile", "Groq", "Meta", 1
-    ),
-    LlmModel.LLAMA3_1_8B: ModelMetadata(
-        "groq", 128000, 8192, "Llama 3.1 8B Instant", "Groq", "Meta", 1
-    ),
+    LlmModel.LLAMA3_3_70B: ModelMetadata("groq", 128000, 32768),
+    LlmModel.LLAMA3_1_8B: ModelMetadata("groq", 128000, 8192),
     # https://ollama.com/library
-    LlmModel.OLLAMA_LLAMA3_3: ModelMetadata(
-        "ollama", 8192, None, "Llama 3.3", "Ollama", "Meta", 1
-    ),
-    LlmModel.OLLAMA_LLAMA3_2: ModelMetadata(
-        "ollama", 8192, None, "Llama 3.2", "Ollama", "Meta", 1
-    ),
-    LlmModel.OLLAMA_LLAMA3_8B: ModelMetadata(
-        "ollama", 8192, None, "Llama 3", "Ollama", "Meta", 1
-    ),
-    LlmModel.OLLAMA_LLAMA3_405B: ModelMetadata(
-        "ollama", 8192, None, "Llama 3.1 405B", "Ollama", "Meta", 1
-    ),
-    LlmModel.OLLAMA_DOLPHIN: ModelMetadata(
-        "ollama", 32768, None, "Dolphin Mistral Latest", "Ollama", "Mistral AI", 1
-    ),
+    LlmModel.OLLAMA_LLAMA3_3: ModelMetadata("ollama", 8192, None),
+    LlmModel.OLLAMA_LLAMA3_2: ModelMetadata("ollama", 8192, None),
+    LlmModel.OLLAMA_LLAMA3_8B: ModelMetadata("ollama", 8192, None),
+    LlmModel.OLLAMA_LLAMA3_405B: ModelMetadata("ollama", 8192, None),
+    LlmModel.OLLAMA_DOLPHIN: ModelMetadata("ollama", 32768, None),
     # https://openrouter.ai/models
-    LlmModel.GEMINI_2_5_PRO: ModelMetadata(
-        "open_router",
-        1050000,
-        8192,
-        "Gemini 2.5 Pro Preview 03.25",
-        "OpenRouter",
-        "Google",
-        2,
-    ),
-    LlmModel.GEMINI_3_PRO_PREVIEW: ModelMetadata(
-        "open_router", 1048576, 65535, "Gemini 3 Pro Preview", "OpenRouter", "Google", 2
-    ),
-    LlmModel.GEMINI_2_5_FLASH: ModelMetadata(
-        "open_router", 1048576, 65535, "Gemini 2.5 Flash", "OpenRouter", "Google", 1
-    ),
-    LlmModel.GEMINI_2_0_FLASH: ModelMetadata(
-        "open_router", 1048576, 8192, "Gemini 2.0 Flash 001", "OpenRouter", "Google", 1
-    ),
+    LlmModel.GEMINI_2_5_PRO: ModelMetadata("open_router", 1050000, 8192),
+    LlmModel.GEMINI_3_PRO_PREVIEW: ModelMetadata("open_router", 1048576, 65535),
+    LlmModel.GEMINI_2_5_FLASH: ModelMetadata("open_router", 1048576, 65535),
+    LlmModel.GEMINI_2_0_FLASH: ModelMetadata("open_router", 1048576, 8192),
     LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: ModelMetadata(
-        "open_router",
-        1048576,
-        65535,
-        "Gemini 2.5 Flash Lite Preview 06.17",
-        "OpenRouter",
-        "Google",
-        1,
-    ),
-    LlmModel.GEMINI_2_0_FLASH_LITE: ModelMetadata(
-        "open_router",
-        1048576,
-        8192,
-        "Gemini 2.0 Flash Lite 001",
-        "OpenRouter",
-        "Google",
-        1,
-    ),
-    LlmModel.MISTRAL_NEMO: ModelMetadata(
-        "open_router", 128000, 4096, "Mistral Nemo", "OpenRouter", "Mistral AI", 1
-    ),
-    LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata(
-        "open_router", 128000, 4096, "Command R 08.2024", "OpenRouter", "Cohere", 1
-    ),
-    LlmModel.COHERE_COMMAND_R_PLUS_08_2024: ModelMetadata(
-        "open_router", 128000, 4096, "Command R Plus 08.2024", "OpenRouter", "Cohere", 2
-    ),
-    LlmModel.DEEPSEEK_CHAT: ModelMetadata(
-        "open_router", 64000, 2048, "DeepSeek Chat", "OpenRouter", "DeepSeek", 1
-    ),
-    LlmModel.DEEPSEEK_R1_0528: ModelMetadata(
-        "open_router", 163840, 163840, "DeepSeek R1 0528", "OpenRouter", "DeepSeek", 1
-    ),
-    LlmModel.PERPLEXITY_SONAR: ModelMetadata(
-        "open_router", 127000, 8000, "Sonar", "OpenRouter", "Perplexity", 1
-    ),
-    LlmModel.PERPLEXITY_SONAR_PRO: ModelMetadata(
-        "open_router", 200000, 8000, "Sonar Pro", "OpenRouter", "Perplexity", 2
+        "open_router", 1048576, 65535
     ),
+    LlmModel.GEMINI_2_0_FLASH_LITE: ModelMetadata("open_router", 1048576, 8192),
+    LlmModel.MISTRAL_NEMO: ModelMetadata("open_router", 128000, 4096),
+    LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata("open_router", 128000, 4096),
+    LlmModel.COHERE_COMMAND_R_PLUS_08_2024: ModelMetadata("open_router", 128000, 4096),
+    LlmModel.DEEPSEEK_CHAT: ModelMetadata("open_router", 64000, 2048),
+    LlmModel.DEEPSEEK_R1_0528: ModelMetadata("open_router", 163840, 163840),
+    LlmModel.PERPLEXITY_SONAR: ModelMetadata("open_router", 127000, 8000),
+    LlmModel.PERPLEXITY_SONAR_PRO: ModelMetadata("open_router", 200000, 8000),
     LlmModel.PERPLEXITY_SONAR_DEEP_RESEARCH: ModelMetadata(
         "open_router",
         128000,
         16000,
-        "Sonar Deep Research",
-        "OpenRouter",
-        "Perplexity",
-        3,
     ),
     LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B: ModelMetadata(
-        "open_router",
-        131000,
-        4096,
-        "Hermes 3 Llama 3.1 405B",
-        "OpenRouter",
-        "Nous Research",
-        1,
+        "open_router", 131000, 4096
     ),
     LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B: ModelMetadata(
-        "open_router",
-        12288,
-        12288,
-        "Hermes 3 Llama 3.1 70B",
-        "OpenRouter",
-        "Nous Research",
-        1,
-    ),
-    LlmModel.OPENAI_GPT_OSS_120B: ModelMetadata(
-        "open_router", 131072, 131072, "GPT-OSS 120B", "OpenRouter", "OpenAI", 1
-    ),
-    LlmModel.OPENAI_GPT_OSS_20B: ModelMetadata(
-        "open_router", 131072, 32768, "GPT-OSS 20B", "OpenRouter", "OpenAI", 1
-    ),
-    LlmModel.AMAZON_NOVA_LITE_V1: ModelMetadata(
-        "open_router", 300000, 5120, "Nova Lite V1", "OpenRouter", "Amazon", 1
-    ),
-    LlmModel.AMAZON_NOVA_MICRO_V1: ModelMetadata(
-        "open_router", 128000, 5120, "Nova Micro V1", "OpenRouter", "Amazon", 1
-    ),
-    LlmModel.AMAZON_NOVA_PRO_V1: ModelMetadata(
-        "open_router", 300000, 5120, "Nova Pro V1", "OpenRouter", "Amazon", 1
-    ),
-    LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata(
-        "open_router", 65536, 4096, "WizardLM 2 8x22B", "OpenRouter", "Microsoft", 1
-    ),
-    LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata(
-        "open_router", 4096, 4096, "MythoMax L2 13B", "OpenRouter", "Gryphe", 1
-    ),
-    LlmModel.META_LLAMA_4_SCOUT: ModelMetadata(
-        "open_router", 131072, 131072, "Llama 4 Scout", "OpenRouter", "Meta", 1
-    ),
-    LlmModel.META_LLAMA_4_MAVERICK: ModelMetadata(
-        "open_router", 1048576, 1000000, "Llama 4 Maverick", "OpenRouter", "Meta", 1
-    ),
-    LlmModel.GROK_4: ModelMetadata(
-        "open_router", 256000, 256000, "Grok 4", "OpenRouter", "xAI", 3
-    ),
-    LlmModel.GROK_4_FAST: ModelMetadata(
-        "open_router", 2000000, 30000, "Grok 4 Fast", "OpenRouter", "xAI", 1
-    ),
-    LlmModel.GROK_4_1_FAST: ModelMetadata(
-        "open_router", 2000000, 30000, "Grok 4.1 Fast", "OpenRouter", "xAI", 1
-    ),
-    LlmModel.GROK_CODE_FAST_1: ModelMetadata(
-        "open_router", 256000, 10000, "Grok Code Fast 1", "OpenRouter", "xAI", 1
-    ),
-    LlmModel.KIMI_K2: ModelMetadata(
-        "open_router", 131000, 131000, "Kimi K2", "OpenRouter", "Moonshot AI", 1
-    ),
-    LlmModel.QWEN3_235B_A22B_THINKING: ModelMetadata(
-        "open_router",
-        262144,
-        262144,
-        "Qwen 3 235B A22B Thinking 2507",
-        "OpenRouter",
-        "Qwen",
-        1,
-    ),
-    LlmModel.QWEN3_CODER: ModelMetadata(
-        "open_router", 262144, 262144, "Qwen 3 Coder", "OpenRouter", "Qwen", 3
+        "open_router", 12288, 12288
     ),
+    LlmModel.OPENAI_GPT_OSS_120B: ModelMetadata("open_router", 131072, 131072),
+    LlmModel.OPENAI_GPT_OSS_20B: ModelMetadata("open_router", 131072, 32768),
+    LlmModel.AMAZON_NOVA_LITE_V1: ModelMetadata("open_router", 300000, 5120),
+    LlmModel.AMAZON_NOVA_MICRO_V1: ModelMetadata("open_router", 128000, 5120),
+    LlmModel.AMAZON_NOVA_PRO_V1: ModelMetadata("open_router", 300000, 5120),
+    LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata("open_router", 65536, 4096),
+    LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata("open_router", 4096, 4096),
+    LlmModel.META_LLAMA_4_SCOUT: ModelMetadata("open_router", 131072, 131072),
+    LlmModel.META_LLAMA_4_MAVERICK: ModelMetadata("open_router", 1048576, 1000000),
+    LlmModel.GROK_4: ModelMetadata("open_router", 256000, 256000),
+    LlmModel.GROK_4_FAST: ModelMetadata("open_router", 2000000, 30000),
+    LlmModel.GROK_4_1_FAST: ModelMetadata("open_router", 2000000, 30000),
+    LlmModel.GROK_CODE_FAST_1: ModelMetadata("open_router", 256000, 10000),
+    LlmModel.KIMI_K2: ModelMetadata("open_router", 131000, 131000),
+    LlmModel.QWEN3_235B_A22B_THINKING: ModelMetadata("open_router", 262144, 262144),
+    LlmModel.QWEN3_CODER: ModelMetadata("open_router", 262144, 262144),
     # Llama API models
-    LlmModel.LLAMA_API_LLAMA_4_SCOUT: ModelMetadata(
-        "llama_api",
-        128000,
-        4028,
-        "Llama 4 Scout 17B 16E Instruct FP8",
-        "Llama API",
-        "Meta",
-        1,
-    ),
-    LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata(
-        "llama_api",
-        128000,
-        4028,
-        "Llama 4 Maverick 17B 128E Instruct FP8",
-        "Llama API",
-        "Meta",
-        1,
-    ),
-    LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata(
-        "llama_api", 128000, 4028, "Llama 3.3 8B Instruct", "Llama API", "Meta", 1
-    ),
-    LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata(
-        "llama_api", 128000, 4028, "Llama 3.3 70B Instruct", "Llama API", "Meta", 1
-    ),
+    LlmModel.LLAMA_API_LLAMA_4_SCOUT: ModelMetadata("llama_api", 128000, 4028),
+    LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata("llama_api", 128000, 4028),
+    LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata("llama_api", 128000, 4028),
+    LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata("llama_api", 128000, 4028),
     # v0 by Vercel models
-    LlmModel.V0_1_5_MD: ModelMetadata("v0", 128000, 64000, "v0 1.5 MD", "V0", "V0", 1),
-    LlmModel.V0_1_5_LG: ModelMetadata("v0", 512000, 64000, "v0 1.5 LG", "V0", "V0", 1),
-    LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000, "v0 1.0 MD", "V0", "V0", 1),
+    LlmModel.V0_1_5_MD: ModelMetadata("v0", 128000, 64000),
+    LlmModel.V0_1_5_LG: ModelMetadata("v0", 512000, 64000),
+    LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000),
 }
 
 DEFAULT_LLM_MODEL = LlmModel.GPT5_2

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

@@ -242,7 +242,7 @@ async def test_smart_decision_maker_tracks_llm_stats():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
+        mock_execution_context = ExecutionContext(safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -343,7 +343,7 @@ async def test_smart_decision_maker_parameter_validation():
 
         # Create execution context
 
-        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
+        mock_execution_context = ExecutionContext(safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -409,7 +409,7 @@ async def test_smart_decision_maker_parameter_validation():
 
         # Create execution context
 
-        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
+        mock_execution_context = ExecutionContext(safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -471,7 +471,7 @@ async def test_smart_decision_maker_parameter_validation():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
+        mock_execution_context = ExecutionContext(safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -535,7 +535,7 @@ async def test_smart_decision_maker_parameter_validation():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
+        mock_execution_context = ExecutionContext(safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -658,7 +658,7 @@ async def test_smart_decision_maker_raw_response_conversion():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
+        mock_execution_context = ExecutionContext(safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -730,7 +730,7 @@ async def test_smart_decision_maker_raw_response_conversion():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
+        mock_execution_context = ExecutionContext(safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -786,7 +786,7 @@ async def test_smart_decision_maker_raw_response_conversion():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
+        mock_execution_context = ExecutionContext(safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -905,7 +905,7 @@ async def test_smart_decision_maker_agent_mode():
         # Create a mock execution context
 
         mock_execution_context = ExecutionContext(
-            human_in_the_loop_safe_mode=False,
+            safe_mode=False,
         )
 
         # Create a mock execution processor for agent mode tests
@@ -1027,7 +1027,7 @@ async def test_smart_decision_maker_traditional_mode_default():
 
         # Create execution context
 
-        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
+        mock_execution_context = ExecutionContext(safe_mode=False)
 
         # Create a mock execution processor for tests
 

autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dynamic_fields.py

@@ -386,7 +386,7 @@ async def test_output_yielding_with_dynamic_fields():
             outputs = {}
             from backend.data.execution import ExecutionContext
 
-            mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
+            mock_execution_context = ExecutionContext(safe_mode=False)
             mock_execution_processor = MagicMock()
 
             async for output_name, output_value in block.run(
@@ -609,9 +609,7 @@ async def test_validation_errors_dont_pollute_conversation():
                 outputs = {}
                 from backend.data.execution import ExecutionContext
 
-                mock_execution_context = ExecutionContext(
-                    human_in_the_loop_safe_mode=False
-                )
+                mock_execution_context = ExecutionContext(safe_mode=False)
 
                 # Create a proper mock execution processor for agent mode
                 from collections import defaultdict

autogpt_platform/backend/backend/data/block.py

@@ -474,7 +474,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
         self.block_type = block_type
         self.webhook_config = webhook_config
         self.execution_stats: NodeExecutionStats = NodeExecutionStats()
-        self.is_sensitive_action: bool = False
+        self.requires_human_review: bool = False
 
         if self.webhook_config:
             if isinstance(self.webhook_config, BlockWebhookConfig):
@@ -637,9 +637,8 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
             - should_pause: True if execution should be paused for review
             - input_data_to_use: The input data to use (may be modified by reviewer)
         """
-        if not (
-            self.is_sensitive_action and execution_context.sensitive_action_safe_mode
-        ):
+        # Skip review if not required or safe mode is disabled
+        if not self.requires_human_review or not execution_context.safe_mode:
             return False, input_data
 
         from backend.blocks.helpers.review import HITLReviewHelper

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -99,15 +99,10 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.OPENAI_GPT_OSS_20B: 1,
     LlmModel.GEMINI_2_5_PRO: 4,
     LlmModel.GEMINI_3_PRO_PREVIEW: 5,
-    LlmModel.GEMINI_2_5_FLASH: 1,
-    LlmModel.GEMINI_2_0_FLASH: 1,
-    LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: 1,
-    LlmModel.GEMINI_2_0_FLASH_LITE: 1,
     LlmModel.MISTRAL_NEMO: 1,
     LlmModel.COHERE_COMMAND_R_08_2024: 1,
     LlmModel.COHERE_COMMAND_R_PLUS_08_2024: 3,
     LlmModel.DEEPSEEK_CHAT: 2,
-    LlmModel.DEEPSEEK_R1_0528: 1,
     LlmModel.PERPLEXITY_SONAR: 1,
     LlmModel.PERPLEXITY_SONAR_PRO: 5,
     LlmModel.PERPLEXITY_SONAR_DEEP_RESEARCH: 10,
@@ -131,6 +126,11 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.KIMI_K2: 1,
     LlmModel.QWEN3_235B_A22B_THINKING: 1,
     LlmModel.QWEN3_CODER: 9,
+    LlmModel.GEMINI_2_5_FLASH: 1,
+    LlmModel.GEMINI_2_0_FLASH: 1,
+    LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: 1,
+    LlmModel.GEMINI_2_0_FLASH_LITE: 1,
+    LlmModel.DEEPSEEK_R1_0528: 1,
     # v0 by Vercel models
     LlmModel.V0_1_5_MD: 1,
     LlmModel.V0_1_5_LG: 2,

autogpt_platform/backend/backend/data/db.py

@@ -38,6 +38,20 @@ POOL_TIMEOUT = os.getenv("DB_POOL_TIMEOUT")
 if POOL_TIMEOUT:
     DATABASE_URL = add_param(DATABASE_URL, "pool_timeout", POOL_TIMEOUT)
 
+# Add public schema to search_path for pgvector type access
+# The vector extension is in public schema, but search_path is determined by schema parameter
+# Extract the schema from DATABASE_URL or default to 'public' (matching get_database_schema())
+parsed_url = urlparse(DATABASE_URL)
+url_params = dict(parse_qsl(parsed_url.query))
+db_schema = url_params.get("schema", "public")
+# Build search_path, avoiding duplicates if db_schema is already 'public'
+search_path_schemas = list(
+    dict.fromkeys([db_schema, "public"])
+)  # Preserves order, removes duplicates
+search_path = ",".join(search_path_schemas)
+# This allows using ::vector without schema qualification
+DATABASE_URL = add_param(DATABASE_URL, "options", f"-c search_path={search_path}")
+
 HTTP_TIMEOUT = int(POOL_TIMEOUT) if POOL_TIMEOUT else None
 
 prisma = Prisma(
@@ -113,48 +127,38 @@ async def _raw_with_schema(
     *args,
     execute: bool = False,
     client: Prisma | None = None,
+    set_public_search_path: bool = False,
 ) -> list[dict] | int:
     """Internal: Execute raw SQL with proper schema handling.
 
     Use query_raw_with_schema() or execute_raw_with_schema() instead.
 
-    Supports placeholders:
-        - {schema_prefix}: Table/type prefix (e.g., "platform".)
-        - {schema}: Raw schema name for application tables (e.g., platform)
-        - {pgvector_schema}: Schema where pgvector is installed (defaults to "public")
-
     Args:
-        query_template: SQL query with {schema_prefix}, {schema}, and/or {pgvector_schema} placeholders
+        query_template: SQL query with {schema_prefix} placeholder
         *args: Query parameters
         execute: If False, executes SELECT query. If True, executes INSERT/UPDATE/DELETE.
         client: Optional Prisma client for transactions (only used when execute=True).
+        set_public_search_path: If True, sets search_path to include public schema.
+                                Needed for pgvector types and other public schema objects.
 
     Returns:
         - list[dict] if execute=False (query results)
         - int if execute=True (number of affected rows)
-
-    Example with vector type:
-        await execute_raw_with_schema(
-            'INSERT INTO {schema_prefix}"Embedding" (vec) VALUES ($1::{pgvector_schema}.vector)',
-            embedding_data
-        )
     """
     schema = get_database_schema()
     schema_prefix = f'"{schema}".' if schema != "public" else ""
-    # pgvector extension is typically installed in "public" schema
-    # On Supabase it may be in "extensions" but "public" is the common default
-    pgvector_schema = "public"
-
-    formatted_query = query_template.format(
-        schema_prefix=schema_prefix,
-        schema=schema,
-        pgvector_schema=pgvector_schema,
-    )
+    formatted_query = query_template.format(schema_prefix=schema_prefix)
 
     import prisma as prisma_module
 
     db_client = client if client else prisma_module.get_client()
 
+    # Set search_path to include public schema if requested
+    # Prisma doesn't support the 'options' connection parameter, so we set it per-session
+    # This is idempotent and safe to call multiple times
+    if set_public_search_path:
+        await db_client.execute_raw(f"SET search_path = {schema}, public")  # type: ignore
+
     if execute:
         result = await db_client.execute_raw(formatted_query, *args)  # type: ignore
     else:
@@ -163,12 +167,16 @@ async def _raw_with_schema(
     return result
 
 
-async def query_raw_with_schema(query_template: str, *args) -> list[dict]:
+async def query_raw_with_schema(
+    query_template: str, *args, set_public_search_path: bool = False
+) -> list[dict]:
     """Execute raw SQL SELECT query with proper schema handling.
 
     Args:
-        query_template: SQL query with {schema_prefix} and/or {schema} placeholders
+        query_template: SQL query with {schema_prefix} placeholder
         *args: Query parameters
+        set_public_search_path: If True, sets search_path to include public schema.
+                                Needed for pgvector types and other public schema objects.
 
     Returns:
         List of result rows as dictionaries
@@ -179,20 +187,23 @@ async def query_raw_with_schema(query_template: str, *args) -> list[dict]:
             user_id
         )
     """
-    return await _raw_with_schema(query_template, *args, execute=False)  # type: ignore
+    return await _raw_with_schema(query_template, *args, execute=False, set_public_search_path=set_public_search_path)  # type: ignore
 
 
 async def execute_raw_with_schema(
     query_template: str,
     *args,
     client: Prisma | None = None,
+    set_public_search_path: bool = False,
 ) -> int:
     """Execute raw SQL command (INSERT/UPDATE/DELETE) with proper schema handling.
 
     Args:
-        query_template: SQL query with {schema_prefix} and/or {schema} placeholders
+        query_template: SQL query with {schema_prefix} placeholder
         *args: Query parameters
         client: Optional Prisma client for transactions
+        set_public_search_path: If True, sets search_path to include public schema.
+                                Needed for pgvector types and other public schema objects.
 
     Returns:
         Number of affected rows
@@ -204,7 +215,7 @@ async def execute_raw_with_schema(
             client=tx  # Optional transaction client
         )
     """
-    return await _raw_with_schema(query_template, *args, execute=True, client=client)  # type: ignore
+    return await _raw_with_schema(query_template, *args, execute=True, client=client, set_public_search_path=set_public_search_path)  # type: ignore
 
 
 class BaseDbModel(BaseModel):

autogpt_platform/backend/backend/data/execution.py

@@ -81,8 +81,7 @@ class ExecutionContext(BaseModel):
     This includes information needed by blocks, sub-graphs, and execution management.
     """
 
-    human_in_the_loop_safe_mode: bool = True
-    sensitive_action_safe_mode: bool = False
+    safe_mode: bool = True
     user_timezone: str = "UTC"
     root_execution_id: Optional[str] = None
     parent_execution_id: Optional[str] = None

autogpt_platform/backend/backend/data/graph.py

@@ -3,7 +3,7 @@ import logging
 import uuid
 from collections import defaultdict
 from datetime import datetime, timezone
-from typing import TYPE_CHECKING, Annotated, Any, Literal, Optional, cast
+from typing import TYPE_CHECKING, Any, Literal, Optional, cast
 
 from prisma.enums import SubmissionStatus
 from prisma.models import (
@@ -20,7 +20,7 @@ from prisma.types import (
     AgentNodeLinkCreateInput,
     StoreListingVersionWhereInput,
 )
-from pydantic import BaseModel, BeforeValidator, Field, create_model
+from pydantic import BaseModel, Field, create_model
 from pydantic.fields import computed_field
 
 from backend.blocks.agent import AgentExecutorBlock
@@ -62,29 +62,7 @@ logger = logging.getLogger(__name__)
 
 
 class GraphSettings(BaseModel):
-    # Use Annotated with BeforeValidator to coerce None to default values.
-    # This handles cases where the database has null values for these fields.
-    human_in_the_loop_safe_mode: Annotated[
-        bool, BeforeValidator(lambda v: v if v is not None else True)
-    ] = True
-    sensitive_action_safe_mode: Annotated[
-        bool, BeforeValidator(lambda v: v if v is not None else False)
-    ] = False
-
-    @classmethod
-    def from_graph(
-        cls,
-        graph: "GraphModel",
-        hitl_safe_mode: bool | None = None,
-        sensitive_action_safe_mode: bool = False,
-    ) -> "GraphSettings":
-        # Default to True if not explicitly set
-        if hitl_safe_mode is None:
-            hitl_safe_mode = True
-        return cls(
-            human_in_the_loop_safe_mode=hitl_safe_mode,
-            sensitive_action_safe_mode=sensitive_action_safe_mode,
-        )
+    human_in_the_loop_safe_mode: bool | None = None
 
 
 class Link(BaseDbModel):
@@ -266,14 +244,10 @@ class BaseGraph(BaseDbModel):
         return any(
             node.block_id
             for node in self.nodes
-            if node.block.block_type == BlockType.HUMAN_IN_THE_LOOP
-        )
-
-    @computed_field
-    @property
-    def has_sensitive_action(self) -> bool:
-        return any(
-            node.block_id for node in self.nodes if node.block.is_sensitive_action
+            if (
+                node.block.block_type == BlockType.HUMAN_IN_THE_LOOP
+                or node.block.requires_human_review
+            )
         )
 
     @property

autogpt_platform/backend/backend/executor/scheduler.py

@@ -309,7 +309,7 @@ def ensure_embeddings_coverage():
 
         # Process in batches until no more missing embeddings
         while True:
-            result = db_client.backfill_missing_embeddings(batch_size=100)
+            result = db_client.backfill_missing_embeddings(batch_size=10)
 
             total_processed += result["processed"]
             total_success += result["success"]

autogpt_platform/backend/backend/executor/utils.py

@@ -873,8 +873,11 @@ async def add_graph_execution(
         settings = await gdb.get_graph_settings(user_id=user_id, graph_id=graph_id)
 
         execution_context = ExecutionContext(
-            human_in_the_loop_safe_mode=settings.human_in_the_loop_safe_mode,
-            sensitive_action_safe_mode=settings.sensitive_action_safe_mode,
+            safe_mode=(
+                settings.human_in_the_loop_safe_mode
+                if settings.human_in_the_loop_safe_mode is not None
+                else True
+            ),
             user_timezone=(
                 user.timezone if user.timezone != USER_TIMEZONE_NOT_SET else "UTC"
             ),

autogpt_platform/backend/backend/executor/utils_test.py

@@ -386,7 +386,6 @@ async def test_add_graph_execution_is_repeatable(mocker: MockerFixture):
     mock_user.timezone = "UTC"
     mock_settings = mocker.MagicMock()
     mock_settings.human_in_the_loop_safe_mode = True
-    mock_settings.sensitive_action_safe_mode = False
 
     mock_udb.get_user_by_id = mocker.AsyncMock(return_value=mock_user)
     mock_gdb.get_graph_settings = mocker.AsyncMock(return_value=mock_settings)
@@ -652,7 +651,6 @@ async def test_add_graph_execution_with_nodes_to_skip(mocker: MockerFixture):
     mock_user.timezone = "UTC"
     mock_settings = mocker.MagicMock()
     mock_settings.human_in_the_loop_safe_mode = True
-    mock_settings.sensitive_action_safe_mode = False
 
     mock_udb.get_user_by_id = mocker.AsyncMock(return_value=mock_user)
     mock_gdb.get_graph_settings = mocker.AsyncMock(return_value=mock_settings)

autogpt_platform/backend/snapshots/grph_single

@@ -11,7 +11,6 @@
   "forked_from_version": null,
   "has_external_trigger": false,
   "has_human_in_the_loop": false,
-  "has_sensitive_action": false,
   "id": "graph-123",
   "input_schema": {
     "properties": {},

autogpt_platform/backend/snapshots/grphs_all

@@ -11,7 +11,6 @@
     "forked_from_version": null,
     "has_external_trigger": false,
     "has_human_in_the_loop": false,
-    "has_sensitive_action": false,
     "id": "graph-123",
     "input_schema": {
       "properties": {},

autogpt_platform/backend/snapshots/lib_agts_search

@@ -27,8 +27,6 @@
         "properties": {}
       },
       "has_external_trigger": false,
-      "has_human_in_the_loop": false,
-      "has_sensitive_action": false,
       "trigger_setup_info": null,
       "new_output": false,
       "can_access_graph": true,
@@ -36,8 +34,7 @@
       "is_favorite": false,
       "recommended_schedule_cron": null,
       "settings": {
-        "human_in_the_loop_safe_mode": true,
-        "sensitive_action_safe_mode": false
+        "human_in_the_loop_safe_mode": null
       },
       "marketplace_listing": null
     },
@@ -68,8 +65,6 @@
         "properties": {}
       },
       "has_external_trigger": false,
-      "has_human_in_the_loop": false,
-      "has_sensitive_action": false,
       "trigger_setup_info": null,
       "new_output": false,
       "can_access_graph": false,
@@ -77,8 +72,7 @@
       "is_favorite": false,
       "recommended_schedule_cron": null,
       "settings": {
-        "human_in_the_loop_safe_mode": true,
-        "sensitive_action_safe_mode": false
+        "human_in_the_loop_safe_mode": null
       },
       "marketplace_listing": null
     }

autogpt_platform/frontend/.env.default

@@ -29,4 +29,4 @@ NEXT_PUBLIC_CLOUDFLARE_TURNSTILE_SITE_KEY=
 NEXT_PUBLIC_TURNSTILE=disabled
 
 # PR previews
-NEXT_PUBLIC_PREVIEW_STEALING_DEV=
+NEXT_PUBLIC_PREVIEW_STEALING_DEV=

autogpt_platform/frontend/orval.config.ts

@@ -16,12 +16,6 @@ export default defineConfig({
       client: "react-query",
       httpClient: "fetch",
       indexFiles: false,
-      mock: {
-        type: "msw",
-        baseUrl: "http://localhost:3000/api/proxy",
-        generateEachHttpStatus: true,
-        delay: 0,
-      },
       override: {
         mutator: {
           path: "./mutators/custom-mutator.ts",

autogpt_platform/frontend/package.json

@@ -15,8 +15,6 @@
     "types": "tsc --noEmit",
     "test": "NEXT_PUBLIC_PW_TEST=true next build --turbo && playwright test",
     "test-ui": "NEXT_PUBLIC_PW_TEST=true next build --turbo && playwright test --ui",
-    "test:unit": "vitest run",
-    "test:unit:watch": "vitest",
     "test:no-build": "playwright test",
     "gentests": "playwright codegen http://localhost:3000",
     "storybook": "storybook dev -p 6006",
@@ -120,7 +118,6 @@
   },
   "devDependencies": {
     "@chromatic-com/storybook": "4.1.2",
-    "happy-dom": "20.3.4",
     "@opentelemetry/instrumentation": "0.209.0",
     "@playwright/test": "1.56.1",
     "@storybook/addon-a11y": "9.1.5",
@@ -130,8 +127,6 @@
     "@storybook/nextjs": "9.1.5",
     "@tanstack/eslint-plugin-query": "5.91.2",
     "@tanstack/react-query-devtools": "5.90.2",
-    "@testing-library/dom": "10.4.1",
-    "@testing-library/react": "16.3.2",
     "@types/canvas-confetti": "1.9.0",
     "@types/lodash": "4.17.20",
     "@types/negotiator": "0.6.4",
@@ -140,7 +135,6 @@
     "@types/react-dom": "18.3.5",
     "@types/react-modal": "3.16.3",
     "@types/react-window": "1.8.8",
-    "@vitejs/plugin-react": "5.1.2",
     "axe-playwright": "2.2.2",
     "chromatic": "13.3.3",
     "concurrently": "9.2.1",
@@ -159,9 +153,7 @@
     "require-in-the-middle": "8.0.1",
     "storybook": "9.1.5",
     "tailwindcss": "3.4.17",
-    "typescript": "5.9.3",
-    "vite-tsconfig-paths": "6.0.4",
-    "vitest": "4.0.17"
+    "typescript": "5.9.3"
   },
   "msw": {
     "workerDirectory": [

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunGraph/RunGraph.tsx

@@ -5,11 +5,10 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/atoms/Tooltip/BaseTooltip";
-import { CircleNotchIcon, PlayIcon, StopIcon } from "@phosphor-icons/react";
+import { PlayIcon, StopIcon } from "@phosphor-icons/react";
 import { useShallow } from "zustand/react/shallow";
 import { RunInputDialog } from "../RunInputDialog/RunInputDialog";
 import { useRunGraph } from "./useRunGraph";
-import { cn } from "@/lib/utils";
 
 export const RunGraph = ({ flowID }: { flowID: string | null }) => {
   const {
@@ -25,31 +24,6 @@ export const RunGraph = ({ flowID }: { flowID: string | null }) => {
     useShallow((state) => state.isGraphRunning),
   );
 
-  const isLoading = isExecutingGraph || isTerminatingGraph || isSaving;
-
-  // Determine which icon to show with proper animation
-  const renderIcon = () => {
-    const iconClass = cn(
-      "size-4 transition-transform duration-200 ease-out",
-      !isLoading && "group-hover:scale-110",
-    );
-
-    if (isLoading) {
-      return (
-        <CircleNotchIcon
-          className={cn(iconClass, "animate-spin")}
-          weight="bold"
-        />
-      );
-    }
-
-    if (isGraphRunning) {
-      return <StopIcon className={iconClass} weight="fill" />;
-    }
-
-    return <PlayIcon className={iconClass} weight="fill" />;
-  };
-
   return (
     <>
       <Tooltip>
@@ -59,18 +33,18 @@ export const RunGraph = ({ flowID }: { flowID: string | null }) => {
             variant={isGraphRunning ? "destructive" : "primary"}
             data-id={isGraphRunning ? "stop-graph-button" : "run-graph-button"}
             onClick={isGraphRunning ? handleStopGraph : handleRunGraph}
-            disabled={!flowID || isLoading}
-            className="group"
+            disabled={!flowID || isExecutingGraph || isTerminatingGraph}
+            loading={isExecutingGraph || isTerminatingGraph || isSaving}
           >
-            {renderIcon()}
+            {!isGraphRunning ? (
+              <PlayIcon className="size-4" />
+            ) : (
+              <StopIcon className="size-4" />
+            )}
           </Button>
         </TooltipTrigger>
         <TooltipContent>
-          {isLoading
-            ? "Processing..."
-            : isGraphRunning
-              ? "Stop agent"
-              : "Run agent"}
+          {isGraphRunning ? "Stop agent" : "Run agent"}
         </TooltipContent>
       </Tooltip>
       <RunInputDialog

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunInputDialog/RunInputDialog.tsx

@@ -10,7 +10,6 @@ import { useRunInputDialog } from "./useRunInputDialog";
 import { CronSchedulerDialog } from "../CronSchedulerDialog/CronSchedulerDialog";
 import { useTutorialStore } from "@/app/(platform)/build/stores/tutorialStore";
 import { useEffect } from "react";
-import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
 
 export const RunInputDialog = ({
   isOpen,
@@ -24,17 +23,19 @@ export const RunInputDialog = ({
   const hasInputs = useGraphStore((state) => state.hasInputs);
   const hasCredentials = useGraphStore((state) => state.hasCredentials);
   const inputSchema = useGraphStore((state) => state.inputSchema);
+  const credentialsSchema = useGraphStore(
+    (state) => state.credentialsInputSchema,
+  );
 
   const {
-    credentialFields,
-    requiredCredentials,
+    credentialsUiSchema,
     handleManualRun,
     handleInputChange,
     openCronSchedulerDialog,
     setOpenCronSchedulerDialog,
     inputValues,
     credentialValues,
-    handleCredentialFieldChange,
+    handleCredentialChange,
     isExecutingGraph,
   } = useRunInputDialog({ setIsOpen });
 
@@ -61,67 +62,67 @@ export const RunInputDialog = ({
           isOpen,
           set: setIsOpen,
         }}
-        styling={{ maxWidth: "700px", minWidth: "700px" }}
+        styling={{ maxWidth: "600px", minWidth: "600px" }}
       >
         <Dialog.Content>
-          <div
-            className="grid grid-cols-[1fr_auto] gap-10 p-1"
-            data-id="run-input-dialog-content"
-          >
-            <div className="space-y-6">
-              {/* Credentials Section */}
-              {hasCredentials() && credentialFields.length > 0 && (
-                <div data-id="run-input-credentials-section">
-                  <div className="mb-4">
-                    <Text variant="h4" className="text-gray-900">
-                      Credentials
-                    </Text>
-                  </div>
-                  <div className="px-2" data-id="run-input-credentials-form">
-                    <CredentialsGroupedView
-                      credentialFields={credentialFields}
-                      requiredCredentials={requiredCredentials}
-                      inputCredentials={credentialValues}
-                      inputValues={inputValues}
-                      onCredentialChange={handleCredentialFieldChange}
-                    />
-                  </div>
+          <div className="space-y-6 p-1" data-id="run-input-dialog-content">
+            {/* Credentials Section */}
+            {hasCredentials() && (
+              <div data-id="run-input-credentials-section">
+                <div className="mb-4">
+                  <Text variant="h4" className="text-gray-900">
+                    Credentials
+                  </Text>
                 </div>
-              )}
-
-              {/* Inputs Section */}
-              {hasInputs() && (
-                <div data-id="run-input-inputs-section">
-                  <div className="mb-4">
-                    <Text variant="h4" className="text-gray-900">
-                      Inputs
-                    </Text>
-                  </div>
-                  <div data-id="run-input-inputs-form">
-                    <FormRenderer
-                      jsonSchema={inputSchema as RJSFSchema}
-                      handleChange={(v) => handleInputChange(v.formData)}
-                      uiSchema={uiSchema}
-                      initialValues={{}}
-                      formContext={{
-                        showHandles: false,
-                        size: "large",
-                      }}
-                    />
-                  </div>
+                <div className="px-2" data-id="run-input-credentials-form">
+                  <FormRenderer
+                    jsonSchema={credentialsSchema as RJSFSchema}
+                    handleChange={(v) => handleCredentialChange(v.formData)}
+                    uiSchema={credentialsUiSchema}
+                    initialValues={{}}
+                    formContext={{
+                      showHandles: false,
+                      size: "large",
+                      showOptionalToggle: false,
+                    }}
+                  />
                 </div>
-              )}
-            </div>
+              </div>
+            )}
 
+            {/* Inputs Section */}
+            {hasInputs() && (
+              <div data-id="run-input-inputs-section">
+                <div className="mb-4">
+                  <Text variant="h4" className="text-gray-900">
+                    Inputs
+                  </Text>
+                </div>
+                <div data-id="run-input-inputs-form">
+                  <FormRenderer
+                    jsonSchema={inputSchema as RJSFSchema}
+                    handleChange={(v) => handleInputChange(v.formData)}
+                    uiSchema={uiSchema}
+                    initialValues={{}}
+                    formContext={{
+                      showHandles: false,
+                      size: "large",
+                    }}
+                  />
+                </div>
+              </div>
+            )}
+
+            {/* Action Button */}
             <div
-              className="flex flex-col items-end justify-start"
+              className="flex justify-end pt-2"
               data-id="run-input-actions-section"
             >
               {purpose === "run" && (
                 <Button
                   variant="primary"
                   size="large"
-                  className="group h-fit min-w-0 gap-2 px-10"
+                  className="group h-fit min-w-0 gap-2"
                   onClick={handleManualRun}
                   loading={isExecutingGraph}
                   data-id="run-input-manual-run-button"
@@ -136,7 +137,7 @@ export const RunInputDialog = ({
                 <Button
                   variant="primary"
                   size="large"
-                  className="group h-fit min-w-0 gap-2 px-10"
+                  className="group h-fit min-w-0 gap-2"
                   onClick={() => setOpenCronSchedulerDialog(true)}
                   data-id="run-input-schedule-button"
                 >

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunInputDialog/useRunInputDialog.ts

@@ -7,11 +7,12 @@ import {
   GraphExecutionMeta,
 } from "@/lib/autogpt-server-api";
 import { parseAsInteger, parseAsString, useQueryStates } from "nuqs";
-import { useCallback, useMemo, useState } from "react";
+import { useMemo, useState } from "react";
+import { uiSchema } from "../../../FlowEditor/nodes/uiSchema";
+import { isCredentialFieldSchema } from "@/components/renderers/InputRenderer/custom/CredentialField/helpers";
 import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { useReactFlow } from "@xyflow/react";
-import type { CredentialField } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers";
 
 export const useRunInputDialog = ({
   setIsOpen,
@@ -119,32 +120,27 @@ export const useRunInputDialog = ({
       },
     });
 
-  // Convert credentials schema to credential fields array for CredentialsGroupedView
-  const credentialFields: CredentialField[] = useMemo(() => {
-    if (!credentialsSchema?.properties) return [];
-    return Object.entries(credentialsSchema.properties);
-  }, [credentialsSchema]);
+  // We are rendering the credentials field differently compared to other fields.
+  // In the node, we have the field name as "credential" - so our library catches it and renders it differently.
+  // But here we have a different name, something like `Firecrawl credentials`, so here we are telling the library that this field is a credential field type.
 
-  // Get required credentials as a Set
-  const requiredCredentials = useMemo(() => {
-    return new Set<string>(credentialsSchema?.required || []);
-  }, [credentialsSchema]);
+  const credentialsUiSchema = useMemo(() => {
+    const dynamicUiSchema: any = { ...uiSchema };
 
-  // Handler for individual credential changes
-  const handleCredentialFieldChange = useCallback(
-    (key: string, value?: CredentialsMetaInput) => {
-      setCredentialValues((prev) => {
-        if (value) {
-          return { ...prev, [key]: value };
-        } else {
-          const next = { ...prev };
-          delete next[key];
-          return next;
+    if (credentialsSchema?.properties) {
+      Object.keys(credentialsSchema.properties).forEach((fieldName) => {
+        const fieldSchema = credentialsSchema.properties[fieldName];
+        if (isCredentialFieldSchema(fieldSchema)) {
+          dynamicUiSchema[fieldName] = {
+            ...dynamicUiSchema[fieldName],
+            "ui:field": "custom/credential_field",
+          };
         }
       });
-    },
-    [],
-  );
+    }
+
+    return dynamicUiSchema;
+  }, [credentialsSchema]);
 
   const handleManualRun = async () => {
     // Filter out incomplete credentials (those without a valid id)
@@ -177,14 +173,12 @@ export const useRunInputDialog = ({
   };
 
   return {
-    credentialFields,
-    requiredCredentials,
+    credentialsUiSchema,
     inputValues,
     credentialValues,
     isExecutingGraph,
     handleInputChange,
     handleCredentialChange,
-    handleCredentialFieldChange,
     handleManualRun,
     openCronSchedulerDialog,
     setOpenCronSchedulerDialog,

autogpt_platform/frontend/src/app/(platform)/build/components/FloatingSafeModeToogle.tsx

@@ -18,118 +18,69 @@ interface Props {
   fullWidth?: boolean;
 }
 
-interface SafeModeButtonProps {
-  isEnabled: boolean;
-  label: string;
-  tooltipEnabled: string;
-  tooltipDisabled: string;
-  onToggle: () => void;
-  isPending: boolean;
-  fullWidth?: boolean;
-}
-
-function SafeModeButton({
-  isEnabled,
-  label,
-  tooltipEnabled,
-  tooltipDisabled,
-  onToggle,
-  isPending,
-  fullWidth = false,
-}: SafeModeButtonProps) {
-  return (
-    <Tooltip delayDuration={100}>
-      <TooltipTrigger asChild>
-        <Button
-          variant={isEnabled ? "primary" : "outline"}
-          size="small"
-          onClick={onToggle}
-          disabled={isPending}
-          className={cn("justify-start", fullWidth ? "w-full" : "")}
-        >
-          {isEnabled ? (
-            <>
-              <ShieldCheckIcon weight="bold" size={16} />
-              <Text variant="body" className="text-zinc-200">
-                {label}: ON
-              </Text>
-            </>
-          ) : (
-            <>
-              <ShieldIcon weight="bold" size={16} />
-              <Text variant="body" className="text-zinc-600">
-                {label}: OFF
-              </Text>
-            </>
-          )}
-        </Button>
-      </TooltipTrigger>
-      <TooltipContent>
-        <div className="text-center">
-          <div className="font-medium">
-            {label}: {isEnabled ? "ON" : "OFF"}
-          </div>
-          <div className="mt-1 text-xs text-muted-foreground">
-            {isEnabled ? tooltipEnabled : tooltipDisabled}
-          </div>
-        </div>
-      </TooltipContent>
-    </Tooltip>
-  );
-}
-
 export function FloatingSafeModeToggle({
   graph,
   className,
   fullWidth = false,
 }: Props) {
   const {
-    currentHITLSafeMode,
-    showHITLToggle,
-    isHITLStateUndetermined,
-    handleHITLToggle,
-    currentSensitiveActionSafeMode,
-    showSensitiveActionToggle,
-    handleSensitiveActionToggle,
+    currentSafeMode,
     isPending,
     shouldShowToggle,
+    isStateUndetermined,
+    handleToggle,
   } = useAgentSafeMode(graph);
 
-  if (!shouldShowToggle || isPending) {
-    return null;
-  }
-
-  const showHITL = showHITLToggle && !isHITLStateUndetermined;
-  const showSensitive = showSensitiveActionToggle;
-
-  if (!showHITL && !showSensitive) {
+  if (!shouldShowToggle || isStateUndetermined || isPending) {
     return null;
   }
 
   return (
-    <div className={cn("fixed z-50 flex flex-col gap-2", className)}>
-      {showHITL && (
-        <SafeModeButton
-          isEnabled={currentHITLSafeMode}
-          label="Human in the loop block approval"
-          tooltipEnabled="The agent will pause at human-in-the-loop blocks and wait for your approval"
-          tooltipDisabled="Human in the loop blocks will proceed automatically"
-          onToggle={handleHITLToggle}
-          isPending={isPending}
-          fullWidth={fullWidth}
-        />
-      )}
-      {showSensitive && (
-        <SafeModeButton
-          isEnabled={currentSensitiveActionSafeMode}
-          label="Sensitive actions blocks approval"
-          tooltipEnabled="The agent will pause at sensitive action blocks and wait for your approval"
-          tooltipDisabled="Sensitive action blocks will proceed automatically"
-          onToggle={handleSensitiveActionToggle}
-          isPending={isPending}
-          fullWidth={fullWidth}
-        />
-      )}
+    <div className={cn("fixed z-50", className)}>
+      <Tooltip delayDuration={100}>
+        <TooltipTrigger asChild>
+          <Button
+            variant={currentSafeMode! ? "primary" : "outline"}
+            key={graph.id}
+            size="small"
+            title={
+              currentSafeMode!
+                ? "Safe Mode: ON. Human in the loop blocks require manual review"
+                : "Safe Mode: OFF. Human in the loop blocks proceed automatically"
+            }
+            onClick={handleToggle}
+            className={cn(fullWidth ? "w-full" : "")}
+          >
+            {currentSafeMode! ? (
+              <>
+                <ShieldCheckIcon weight="bold" size={16} />
+                <Text variant="body" className="text-zinc-200">
+                  Safe Mode: ON
+                </Text>
+              </>
+            ) : (
+              <>
+                <ShieldIcon weight="bold" size={16} />
+                <Text variant="body" className="text-zinc-600">
+                  Safe Mode: OFF
+                </Text>
+              </>
+            )}
+          </Button>
+        </TooltipTrigger>
+        <TooltipContent>
+          <div className="text-center">
+            <div className="font-medium">
+              Safe Mode: {currentSafeMode! ? "ON" : "OFF"}
+            </div>
+            <div className="mt-1 text-xs text-muted-foreground">
+              {currentSafeMode!
+                ? "Human in the loop blocks require manual review"
+                : "Human in the loop blocks proceed automatically"}
+            </div>
+          </div>
+        </TooltipContent>
+      </Tooltip>
     </div>
   );
 }

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/components/CustomControl.tsx

@@ -53,14 +53,14 @@ export const CustomControls = memo(
     const controls = [
       {
         id: "zoom-in-button",
-        icon: <PlusIcon className="size-3.5 text-zinc-600" />,
+        icon: <PlusIcon className="size-4" />,
         label: "Zoom In",
         onClick: () => zoomIn(),
         className: "h-10 w-10 border-none",
       },
       {
         id: "zoom-out-button",
-        icon: <MinusIcon className="size-3.5 text-zinc-600" />,
+        icon: <MinusIcon className="size-4" />,
         label: "Zoom Out",
         onClick: () => zoomOut(),
         className: "h-10 w-10 border-none",
@@ -68,9 +68,9 @@ export const CustomControls = memo(
       {
         id: "tutorial-button",
         icon: isTutorialLoading ? (
-          <CircleNotchIcon className="size-3.5 animate-spin text-zinc-600" />
+          <CircleNotchIcon className="size-4 animate-spin" />
         ) : (
-          <ChalkboardIcon className="size-3.5 text-zinc-600" />
+          <ChalkboardIcon className="size-4" />
         ),
         label: isTutorialLoading ? "Loading Tutorial..." : "Start Tutorial",
         onClick: handleTutorialClick,
@@ -79,7 +79,7 @@ export const CustomControls = memo(
       },
       {
         id: "fit-view-button",
-        icon: <FrameCornersIcon className="size-3.5 text-zinc-600" />,
+        icon: <FrameCornersIcon className="size-4" />,
         label: "Fit View",
         onClick: () => fitView({ padding: 0.2, duration: 800, maxZoom: 1 }),
         className: "h-10 w-10 border-none",
@@ -87,9 +87,9 @@ export const CustomControls = memo(
       {
         id: "lock-button",
         icon: !isLocked ? (
-          <LockOpenIcon className="size-3.5 text-zinc-600" />
+          <LockOpenIcon className="size-4" />
         ) : (
-          <LockIcon className="size-3.5 text-zinc-600" />
+          <LockIcon className="size-4" />
         ),
         label: "Toggle Lock",
         onClick: () => setIsLocked(!isLocked),

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/useFlow.ts

@@ -139,6 +139,14 @@ export const useFlow = () => {
       useNodeStore.getState().setNodes([]);
       useNodeStore.getState().clearResolutionState();
       addNodes(customNodes);
+
+      // Sync hardcoded values with handle IDs.
+      // If a key–value field has a key without a value, the backend omits it from hardcoded values.
+      // But if a handleId exists for that key, it causes inconsistency.
+      // This ensures hardcoded values stay in sync with handle IDs.
+      customNodes.forEach((node) => {
+        useNodeStore.getState().syncHardcodedValuesWithHandleIds(node.id);
+      });
     }
   }, [customNodes, addNodes]);
 
@@ -150,14 +158,6 @@ export const useFlow = () => {
     }
   }, [graph?.links, addLinks]);
 
-  useEffect(() => {
-    if (customNodes.length > 0 && graph?.links) {
-      customNodes.forEach((node) => {
-        useNodeStore.getState().syncHardcodedValuesWithHandleIds(node.id);
-      });
-    }
-  }, [customNodes, graph?.links]);
-
   // update node execution status in nodes
   useEffect(() => {
     if (

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/edges/CustomEdge.tsx

@@ -19,8 +19,6 @@ export type CustomEdgeData = {
   beadUp?: number;
   beadDown?: number;
   beadData?: Map<string, NodeExecutionResult["status"]>;
-  edgeColorClass?: string;
-  edgeHexColor?: string;
 };
 
 export type CustomEdge = XYEdge<CustomEdgeData, "custom">;
@@ -38,6 +36,7 @@ const CustomEdge = ({
   selected,
 }: EdgeProps<CustomEdge>) => {
   const removeConnection = useEdgeStore((state) => state.removeEdge);
+  // Subscribe to the brokenEdgeIDs map and check if this edge is broken across any node
   const isBroken = useNodeStore((state) => state.isEdgeBroken(id));
   const [isHovered, setIsHovered] = useState(false);
 
@@ -53,7 +52,6 @@ const CustomEdge = ({
   const isStatic = data?.isStatic ?? false;
   const beadUp = data?.beadUp ?? 0;
   const beadDown = data?.beadDown ?? 0;
-  const edgeColorClass = data?.edgeColorClass;
 
   const handleRemoveEdge = () => {
     removeConnection(id);
@@ -72,9 +70,7 @@ const CustomEdge = ({
             ? "!stroke-red-500 !stroke-[2px] [stroke-dasharray:4]"
             : selected
               ? "stroke-zinc-800"
-              : edgeColorClass
-                ? cn(edgeColorClass, "opacity-70 hover:opacity-100")
-                : "stroke-zinc-500/50 hover:stroke-zinc-500",
+              : "stroke-zinc-500/50 hover:stroke-zinc-500",
         )}
       />
       <JSBeads

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/edges/useCustomEdge.ts

@@ -8,7 +8,6 @@ import { useCallback } from "react";
 import { useNodeStore } from "../../../stores/nodeStore";
 import { useHistoryStore } from "../../../stores/historyStore";
 import { CustomEdge } from "./CustomEdge";
-import { getEdgeColorFromOutputType } from "../nodes/helpers";
 
 export const useCustomEdge = () => {
   const edges = useEdgeStore((s) => s.edges);
@@ -35,13 +34,8 @@ export const useCustomEdge = () => {
       if (exists) return;
 
       const nodes = useNodeStore.getState().nodes;
-      const sourceNode = nodes.find((n) => n.id === conn.source);
-      const isStatic = sourceNode?.data?.staticOutput;
-
-      const { colorClass, hexColor } = getEdgeColorFromOutputType(
-        sourceNode?.data?.outputSchema,
-        conn.sourceHandle,
-      );
+      const isStatic = nodes.find((n) => n.id === conn.source)?.data
+        ?.staticOutput;
 
       addEdge({
         source: conn.source,
@@ -50,8 +44,6 @@ export const useCustomEdge = () => {
         targetHandle: conn.targetHandle,
         data: {
           isStatic,
-          edgeColorClass: colorClass,
-          edgeHexColor: hexColor,
         },
       });
     },

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/NodeOutput.tsx

@@ -1,21 +1,22 @@
 import { Button } from "@/components/atoms/Button/Button";
 import { Text } from "@/components/atoms/Text/Text";
-import {
-  Accordion,
-  AccordionContent,
-  AccordionItem,
-  AccordionTrigger,
-} from "@/components/molecules/Accordion/Accordion";
 import { beautifyString, cn } from "@/lib/utils";
-import { CopyIcon, CheckIcon } from "@phosphor-icons/react";
+import { CaretDownIcon, CopyIcon, CheckIcon } from "@phosphor-icons/react";
 import { NodeDataViewer } from "./components/NodeDataViewer/NodeDataViewer";
 import { ContentRenderer } from "./components/ContentRenderer";
 import { useNodeOutput } from "./useNodeOutput";
 import { ViewMoreData } from "./components/ViewMoreData";
 
 export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
-  const { outputData, copiedKey, handleCopy, executionResultId, inputData } =
-    useNodeOutput(nodeId);
+  const {
+    outputData,
+    isExpanded,
+    setIsExpanded,
+    copiedKey,
+    handleCopy,
+    executionResultId,
+    inputData,
+  } = useNodeOutput(nodeId);
 
   if (Object.keys(outputData).length === 0) {
     return null;
@@ -24,117 +25,122 @@ export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
   return (
     <div
       data-tutorial-id={`node-output`}
-      className="rounded-b-xl border-t border-zinc-200 px-4 py-2"
+      className="flex flex-col gap-3 rounded-b-xl border-t border-zinc-200 px-4 py-4"
     >
-      <Accordion type="single" collapsible defaultValue="node-output">
-        <AccordionItem value="node-output" className="border-none">
-          <AccordionTrigger className="py-2 hover:no-underline">
-            <Text
-              variant="body-medium"
-              className="!font-semibold text-slate-700"
-            >
-              Node Output
-            </Text>
-          </AccordionTrigger>
-          <AccordionContent className="pt-2">
-            <div className="flex max-w-[350px] flex-col gap-4">
-              <div className="space-y-2">
-                <Text variant="small-medium">Input</Text>
+      <div className="flex items-center justify-between">
+        <Text variant="body-medium" className="!font-semibold text-slate-700">
+          Node Output
+        </Text>
+        <Button
+          variant="ghost"
+          size="small"
+          onClick={() => setIsExpanded(!isExpanded)}
+          className="h-fit min-w-0 p-1 text-slate-600 hover:text-slate-900"
+        >
+          <CaretDownIcon
+            size={16}
+            weight="bold"
+            className={`transition-transform ${isExpanded ? "rotate-180" : ""}`}
+          />
+        </Button>
+      </div>
 
-                <ContentRenderer value={inputData} shortContent={false} />
+      {isExpanded && (
+        <>
+          <div className="flex max-w-[350px] flex-col gap-4">
+            <div className="space-y-2">
+              <Text variant="small-medium">Input</Text>
 
-                <div className="mt-1 flex justify-end gap-1">
-                  <NodeDataViewer
-                    data={inputData}
-                    pinName="Input"
-                    execId={executionResultId}
-                  />
-                  <Button
-                    variant="secondary"
-                    size="small"
-                    onClick={() => handleCopy("input", inputData)}
-                    className={cn(
-                      "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
-                      copiedKey === "input" &&
-                        "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
-                    )}
-                  >
-                    {copiedKey === "input" ? (
-                      <CheckIcon size={12} className="text-green-600" />
-                    ) : (
-                      <CopyIcon size={12} />
-                    )}
-                  </Button>
-                </div>
+              <ContentRenderer value={inputData} shortContent={false} />
+
+              <div className="mt-1 flex justify-end gap-1">
+                <NodeDataViewer
+                  data={inputData}
+                  pinName="Input"
+                  execId={executionResultId}
+                />
+                <Button
+                  variant="secondary"
+                  size="small"
+                  onClick={() => handleCopy("input", inputData)}
+                  className={cn(
+                    "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
+                    copiedKey === "input" &&
+                      "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
+                  )}
+                >
+                  {copiedKey === "input" ? (
+                    <CheckIcon size={12} className="text-green-600" />
+                  ) : (
+                    <CopyIcon size={12} />
+                  )}
+                </Button>
               </div>
+            </div>
 
-              {Object.entries(outputData)
-                .slice(0, 2)
-                .map(([key, value]) => (
-                  <div key={key} className="flex flex-col gap-2">
-                    <div className="flex items-center gap-2">
-                      <Text
-                        variant="small-medium"
-                        className="!font-semibold text-slate-600"
-                      >
-                        Pin:
-                      </Text>
-                      <Text variant="small" className="text-slate-700">
-                        {beautifyString(key)}
-                      </Text>
-                    </div>
-                    <div className="w-full space-y-2">
-                      <Text
-                        variant="small"
-                        className="!font-semibold text-slate-600"
-                      >
-                        Data:
-                      </Text>
-                      <div className="relative space-y-2">
-                        {value.map((item, index) => (
-                          <div key={index}>
-                            <ContentRenderer value={item} shortContent={true} />
-                          </div>
-                        ))}
-
-                        <div className="mt-1 flex justify-end gap-1">
-                          <NodeDataViewer
-                            data={value}
-                            pinName={key}
-                            execId={executionResultId}
-                          />
-                          <Button
-                            variant="secondary"
-                            size="small"
-                            onClick={() => handleCopy(key, value)}
-                            className={cn(
-                              "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
-                              copiedKey === key &&
-                                "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
-                            )}
-                          >
-                            {copiedKey === key ? (
-                              <CheckIcon size={12} className="text-green-600" />
-                            ) : (
-                              <CopyIcon size={12} />
-                            )}
-                          </Button>
+            {Object.entries(outputData)
+              .slice(0, 2)
+              .map(([key, value]) => (
+                <div key={key} className="flex flex-col gap-2">
+                  <div className="flex items-center gap-2">
+                    <Text
+                      variant="small-medium"
+                      className="!font-semibold text-slate-600"
+                    >
+                      Pin:
+                    </Text>
+                    <Text variant="small" className="text-slate-700">
+                      {beautifyString(key)}
+                    </Text>
+                  </div>
+                  <div className="w-full space-y-2">
+                    <Text
+                      variant="small"
+                      className="!font-semibold text-slate-600"
+                    >
+                      Data:
+                    </Text>
+                    <div className="relative space-y-2">
+                      {value.map((item, index) => (
+                        <div key={index}>
+                          <ContentRenderer value={item} shortContent={true} />
                         </div>
+                      ))}
+
+                      <div className="mt-1 flex justify-end gap-1">
+                        <NodeDataViewer
+                          data={value}
+                          pinName={key}
+                          execId={executionResultId}
+                        />
+                        <Button
+                          variant="secondary"
+                          size="small"
+                          onClick={() => handleCopy(key, value)}
+                          className={cn(
+                            "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
+                            copiedKey === key &&
+                              "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
+                          )}
+                        >
+                          {copiedKey === key ? (
+                            <CheckIcon size={12} className="text-green-600" />
+                          ) : (
+                            <CopyIcon size={12} />
+                          )}
+                        </Button>
                       </div>
                     </div>
                   </div>
-                ))}
-            </div>
+                </div>
+              ))}
+          </div>
 
-            {Object.keys(outputData).length > 2 && (
-              <ViewMoreData
-                outputData={outputData}
-                execId={executionResultId}
-              />
-            )}
-          </AccordionContent>
-        </AccordionItem>
-      </Accordion>
+          {Object.keys(outputData).length > 2 && (
+            <ViewMoreData outputData={outputData} execId={executionResultId} />
+          )}
+        </>
+      )}
     </div>
   );
 };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/useNodeOutput.tsx

@@ -4,6 +4,7 @@ import { useShallow } from "zustand/react/shallow";
 import { useState } from "react";
 
 export const useNodeOutput = (nodeId: string) => {
+  const [isExpanded, setIsExpanded] = useState(true);
   const [copiedKey, setCopiedKey] = useState<string | null>(null);
   const { toast } = useToast();
 
@@ -36,10 +37,13 @@ export const useNodeOutput = (nodeId: string) => {
     }
   };
   return {
-    outputData,
-    inputData,
-    copiedKey,
-    handleCopy,
+    outputData: outputData,
+    inputData: inputData,
+    isExpanded: isExpanded,
+    setIsExpanded: setIsExpanded,
+    copiedKey: copiedKey,
+    setCopiedKey: setCopiedKey,
+    handleCopy: handleCopy,
     executionResultId: nodeExecutionResult?.node_exec_id,
   };
 };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/helpers.ts

@@ -187,38 +187,3 @@ export const getTypeDisplayInfo = (schema: any) => {
     hexColor,
   };
 };
-
-export function getEdgeColorFromOutputType(
-  outputSchema: RJSFSchema | undefined,
-  sourceHandle: string,
-): { colorClass: string; hexColor: string } {
-  const defaultColor = {
-    colorClass: "stroke-zinc-500/50",
-    hexColor: "#6b7280",
-  };
-
-  if (!outputSchema?.properties) return defaultColor;
-
-  const properties = outputSchema.properties as Record<string, unknown>;
-  const handleParts = sourceHandle.split("_#_");
-  let currentSchema: Record<string, unknown> = properties;
-
-  for (let i = 0; i < handleParts.length; i++) {
-    const part = handleParts[i];
-    const fieldSchema = currentSchema[part] as Record<string, unknown>;
-    if (!fieldSchema) return defaultColor;
-
-    if (i === handleParts.length - 1) {
-      const { hexColor, colorClass } = getTypeDisplayInfo(fieldSchema);
-      return { colorClass: colorClass.replace("!text-", "stroke-"), hexColor };
-    }
-
-    if (fieldSchema.properties) {
-      currentSchema = fieldSchema.properties as Record<string, unknown>;
-    } else {
-      return defaultColor;
-    }
-  }
-
-  return defaultColor;
-}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/tutorial/icons.ts

@@ -1,32 +1,7 @@
-type IconOptions = {
-  size?: number;
-  color?: string;
-};
-
-const DEFAULT_SIZE = 16;
-const DEFAULT_COLOR = "#52525b"; // zinc-600
-
-const iconPaths = {
-  ClickIcon: `M88,24V16a8,8,0,0,1,16,0v8a8,8,0,0,1-16,0ZM16,104h8a8,8,0,0,0,0-16H16a8,8,0,0,0,0,16ZM124.42,39.16a8,8,0,0,0,10.74-3.58l8-16a8,8,0,0,0-14.31-7.16l-8,16A8,8,0,0,0,124.42,39.16Zm-96,81.69-16,8a8,8,0,0,0,7.16,14.31l16-8a8,8,0,1,0-7.16-14.31ZM219.31,184a16,16,0,0,1,0,22.63l-12.68,12.68a16,16,0,0,1-22.63,0L132.7,168,115,214.09c0,.1-.08.21-.13.32a15.83,15.83,0,0,1-14.6,9.59l-.79,0a15.83,15.83,0,0,1-14.41-11L32.8,52.92A16,16,0,0,1,52.92,32.8L213,85.07a16,16,0,0,1,1.41,29.8l-.32.13L168,132.69ZM208,195.31,156.69,144h0a16,16,0,0,1,4.93-26l.32-.14,45.95-17.64L48,48l52.2,159.86,17.65-46c0-.11.08-.22.13-.33a16,16,0,0,1,11.69-9.34,16.72,16.72,0,0,1,3-.28,16,16,0,0,1,11.3,4.69L195.31,208Z`,
-  Keyboard: `M224,48H32A16,16,0,0,0,16,64V192a16,16,0,0,0,16,16H224a16,16,0,0,0,16-16V64A16,16,0,0,0,224,48Zm0,144H32V64H224V192Zm-16-64a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,128Zm0-32a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,96ZM72,160a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16h8A8,8,0,0,1,72,160Zm96,0a8,8,0,0,1-8,8H96a8,8,0,0,1,0-16h64A8,8,0,0,1,168,160Zm40,0a8,8,0,0,1-8,8h-8a8,8,0,0,1,0-16h8A8,8,0,0,1,208,160Z`,
-  Drag: `M188,80a27.79,27.79,0,0,0-13.36,3.4,28,28,0,0,0-46.64-11A28,28,0,0,0,80,92v20H68a28,28,0,0,0-28,28v12a88,88,0,0,0,176,0V108A28,28,0,0,0,188,80Zm12,72a72,72,0,0,1-144,0V140a12,12,0,0,1,12-12H80v24a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V108a12,12,0,0,1,24,0Z`,
-};
-
-function createIcon(path: string, options: IconOptions = {}): string {
-  const size = options.size ?? DEFAULT_SIZE;
-  const color = options.color ?? DEFAULT_COLOR;
-  return `<svg xmlns="http://www.w3.org/2000/svg" width="${size}" height="${size}" fill="${color}" viewBox="0 0 256 256"><path d="${path}"></path></svg>`;
-}
+// These are SVG Phosphor icons
 
 export const ICONS = {
-  ClickIcon: createIcon(iconPaths.ClickIcon),
-  Keyboard: createIcon(iconPaths.Keyboard),
-  Drag: createIcon(iconPaths.Drag),
+  ClickIcon: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="#000000" viewBox="0 0 256 256"><path d="M88,24V16a8,8,0,0,1,16,0v8a8,8,0,0,1-16,0ZM16,104h8a8,8,0,0,0,0-16H16a8,8,0,0,0,0,16ZM124.42,39.16a8,8,0,0,0,10.74-3.58l8-16a8,8,0,0,0-14.31-7.16l-8,16A8,8,0,0,0,124.42,39.16Zm-96,81.69-16,8a8,8,0,0,0,7.16,14.31l16-8a8,8,0,1,0-7.16-14.31ZM219.31,184a16,16,0,0,1,0,22.63l-12.68,12.68a16,16,0,0,1-22.63,0L132.7,168,115,214.09c0,.1-.08.21-.13.32a15.83,15.83,0,0,1-14.6,9.59l-.79,0a15.83,15.83,0,0,1-14.41-11L32.8,52.92A16,16,0,0,1,52.92,32.8L213,85.07a16,16,0,0,1,1.41,29.8l-.32.13L168,132.69ZM208,195.31,156.69,144h0a16,16,0,0,1,4.93-26l.32-.14,45.95-17.64L48,48l52.2,159.86,17.65-46c0-.11.08-.22.13-.33a16,16,0,0,1,11.69-9.34,16.72,16.72,0,0,1,3-.28,16,16,0,0,1,11.3,4.69L195.31,208Z"></path></svg>`,
+  Keyboard: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="#000000" viewBox="0 0 256 256"><path d="M224,48H32A16,16,0,0,0,16,64V192a16,16,0,0,0,16,16H224a16,16,0,0,0,16-16V64A16,16,0,0,0,224,48Zm0,144H32V64H224V192Zm-16-64a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,128Zm0-32a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,96ZM72,160a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16h8A8,8,0,0,1,72,160Zm96,0a8,8,0,0,1-8,8H96a8,8,0,0,1,0-16h64A8,8,0,0,1,168,160Zm40,0a8,8,0,0,1-8,8h-8a8,8,0,0,1,0-16h8A8,8,0,0,1,208,160Z"></path></svg>`,
+  Drag: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="#000000" viewBox="0 0 256 256"><path d="M188,80a27.79,27.79,0,0,0-13.36,3.4,28,28,0,0,0-46.64-11A28,28,0,0,0,80,92v20H68a28,28,0,0,0-28,28v12a88,88,0,0,0,176,0V108A28,28,0,0,0,188,80Zm12,72a72,72,0,0,1-144,0V140a12,12,0,0,1,12-12H80v24a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V108a12,12,0,0,1,24,0Z"></path></svg>`,
 };
-
-export function getIcon(
-  name: keyof typeof iconPaths,
-  options?: IconOptions,
-): string {
-  return createIcon(iconPaths[name], options);
-}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/tutorial/index.ts

@@ -11,7 +11,6 @@ import {
 } from "./helpers";
 import { useNodeStore } from "../../../stores/nodeStore";
 import { useEdgeStore } from "../../../stores/edgeStore";
-import { useTutorialStore } from "../../../stores/tutorialStore";
 
 let isTutorialLoading = false;
 let tutorialLoadingCallback: ((loading: boolean) => void) | null = null;
@@ -61,14 +60,12 @@ export const startTutorial = async () => {
     handleTutorialComplete();
     removeTutorialStyles();
     clearPrefetchedBlocks();
-    useTutorialStore.getState().setIsTutorialRunning(false);
   });
 
   tour.on("cancel", () => {
     handleTutorialCancel(tour);
     removeTutorialStyles();
     clearPrefetchedBlocks();
-    useTutorialStore.getState().setIsTutorialRunning(false);
   });
 
   for (const step of tour.steps) {

autogpt_platform/frontend/src/app/(platform)/build/components/helper.ts

@@ -61,18 +61,12 @@ export const convertNodesPlusBlockInfoIntoCustomNodes = (
   return customNode;
 };
 
-const isToolSourceName = (sourceName: string): boolean =>
-  sourceName.startsWith("tools_^_");
-
-const cleanupSourceName = (sourceName: string): string =>
-  isToolSourceName(sourceName) ? "tools" : sourceName;
-
 export const linkToCustomEdge = (link: Link): CustomEdge => ({
   id: link.id ?? "",
   type: "custom" as const,
   source: link.source_id,
   target: link.sink_id,
-  sourceHandle: cleanupSourceName(link.source_name),
+  sourceHandle: link.source_name,
   targetHandle: link.sink_name,
   data: {
     isStatic: link.is_static,

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatContainer/helpers.ts

@@ -267,34 +267,23 @@ export function extractCredentialsNeeded(
       | undefined;
     if (missingCreds && Object.keys(missingCreds).length > 0) {
       const agentName = (setupInfo?.agent_name as string) || "this block";
-      const credentials = Object.values(missingCreds).map((credInfo) => {
-        // Normalize to array at boundary - prefer 'types' array, fall back to single 'type'
-        const typesArray = credInfo.types as
-          | Array<"api_key" | "oauth2" | "user_password" | "host_scoped">
-          | undefined;
-        const singleType =
+      const credentials = Object.values(missingCreds).map((credInfo) => ({
+        provider: (credInfo.provider as string) || "unknown",
+        providerName:
+          (credInfo.provider_name as string) ||
+          (credInfo.provider as string) ||
+          "Unknown Provider",
+        credentialType:
           (credInfo.type as
             | "api_key"
             | "oauth2"
             | "user_password"
-            | "host_scoped"
-            | undefined) || "api_key";
-        const credentialTypes =
-          typesArray && typesArray.length > 0 ? typesArray : [singleType];
-
-        return {
-          provider: (credInfo.provider as string) || "unknown",
-          providerName:
-            (credInfo.provider_name as string) ||
-            (credInfo.provider as string) ||
-            "Unknown Provider",
-          credentialTypes,
-          title:
-            (credInfo.title as string) ||
-            `${(credInfo.provider_name as string) || (credInfo.provider as string)} credentials`,
-          scopes: credInfo.scopes as string[] | undefined,
-        };
-      });
+            | "host_scoped") || "api_key",
+        title:
+          (credInfo.title as string) ||
+          `${(credInfo.provider_name as string) || (credInfo.provider as string)} credentials`,
+        scopes: credInfo.scopes as string[] | undefined,
+      }));
       return {
         type: "credentials_needed",
         toolName,
@@ -369,14 +358,11 @@ export function extractInputsNeeded(
       credentials.forEach((cred) => {
         const id = cred.id as string;
         if (id) {
-          const credentialTypes = Array.isArray(cred.types)
-            ? cred.types
-            : [(cred.type as string) || "api_key"];
           credentialsSchema[id] = {
             type: "object",
             properties: {},
             credentials_provider: [cred.provider as string],
-            credentials_types: credentialTypes,
+            credentials_types: [(cred.type as string) || "api_key"],
             credentials_scopes: cred.scopes as string[] | undefined,
           };
         }

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatCredentialsSetup/ChatCredentialsSetup.tsx

@@ -9,9 +9,7 @@ import { useChatCredentialsSetup } from "./useChatCredentialsSetup";
 export interface CredentialInfo {
   provider: string;
   providerName: string;
-  credentialTypes: Array<
-    "api_key" | "oauth2" | "user_password" | "host_scoped"
-  >;
+  credentialType: "api_key" | "oauth2" | "user_password" | "host_scoped";
   title: string;
   scopes?: string[];
 }
@@ -32,7 +30,7 @@ function createSchemaFromCredentialInfo(
     type: "object",
     properties: {},
     credentials_provider: [credential.provider],
-    credentials_types: credential.credentialTypes,
+    credentials_types: [credential.credentialType],
     credentials_scopes: credential.scopes,
     discriminator: undefined,
     discriminator_mapping: undefined,

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatMessage/useChatMessage.ts

@@ -41,9 +41,7 @@ export type ChatMessageData =
       credentials: Array<{
         provider: string;
         providerName: string;
-        credentialTypes: Array<
-          "api_key" | "oauth2" | "user_password" | "host_scoped"
-        >;
+        credentialType: "api_key" | "oauth2" | "user_password" | "host_scoped";
         title: string;
         scopes?: string[];
       }>;

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

@@ -31,18 +31,10 @@ export function AgentSettingsModal({
     }
   }
 
-  const {
-    currentHITLSafeMode,
-    showHITLToggle,
-    handleHITLToggle,
-    currentSensitiveActionSafeMode,
-    showSensitiveActionToggle,
-    handleSensitiveActionToggle,
-    isPending,
-    shouldShowToggle,
-  } = useAgentSafeMode(agent);
+  const { currentSafeMode, isPending, hasHITLBlocks, handleToggle } =
+    useAgentSafeMode(agent);
 
-  if (!shouldShowToggle) return null;
+  if (!hasHITLBlocks) return null;
 
   return (
     <Dialog
@@ -65,48 +57,23 @@ export function AgentSettingsModal({
       )}
       <Dialog.Content>
         <div className="space-y-6">
-          {showHITLToggle && (
-            <div className="flex w-full flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
-              <div className="flex w-full items-start justify-between gap-4">
-                <div className="flex-1">
-                  <Text variant="large-semibold">
-                    Human-in-the-loop approval
-                  </Text>
-                  <Text variant="large" className="mt-1 text-zinc-900">
-                    The agent will pause at human-in-the-loop blocks and wait
-                    for your review before continuing
-                  </Text>
-                </div>
-                <Switch
-                  checked={currentHITLSafeMode || false}
-                  onCheckedChange={handleHITLToggle}
-                  disabled={isPending}
-                  className="mt-1"
-                />
+          <div className="flex w-full flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
+            <div className="flex w-full items-start justify-between gap-4">
+              <div className="flex-1">
+                <Text variant="large-semibold">Require human approval</Text>
+                <Text variant="large" className="mt-1 text-zinc-900">
+                  The agent will pause and wait for your review before
+                  continuing
+                </Text>
               </div>
+              <Switch
+                checked={currentSafeMode || false}
+                onCheckedChange={handleToggle}
+                disabled={isPending}
+                className="mt-1"
+              />
             </div>
-          )}
-          {showSensitiveActionToggle && (
-            <div className="flex w-full flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
-              <div className="flex w-full items-start justify-between gap-4">
-                <div className="flex-1">
-                  <Text variant="large-semibold">
-                    Sensitive action approval
-                  </Text>
-                  <Text variant="large" className="mt-1 text-zinc-900">
-                    The agent will pause at sensitive action blocks and wait for
-                    your review before continuing
-                  </Text>
-                </div>
-                <Switch
-                  checked={currentSensitiveActionSafeMode}
-                  onCheckedChange={handleSensitiveActionToggle}
-                  disabled={isPending}
-                  className="mt-1"
-                />
-              </div>
-            </div>
-          )}
+          </div>
         </div>
       </Dialog.Content>
     </Dialog>

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/CredentialsGroupedView/CredentialsGroupedView.tsx

@@ -5,37 +5,30 @@ import {
   AccordionItem,
   AccordionTrigger,
 } from "@/components/molecules/Accordion/Accordion";
-import {
-  CredentialsMetaInput,
-  CredentialsType,
-} from "@/lib/autogpt-server-api/types";
 import { CredentialsProvidersContext } from "@/providers/agent-credentials/credentials-provider";
-import { SlidersHorizontalIcon } from "@phosphor-icons/react";
+import { SlidersHorizontal } from "@phosphor-icons/react";
 import { useContext, useEffect, useMemo, useRef } from "react";
+import { useRunAgentModalContext } from "../../context";
 import {
   areSystemCredentialProvidersLoading,
   CredentialField,
   findSavedCredentialByProviderAndType,
   hasMissingRequiredSystemCredentials,
   splitCredentialFieldsBySystem,
-} from "./helpers";
+} from "../helpers";
 
 type Props = {
   credentialFields: CredentialField[];
   requiredCredentials: Set<string>;
-  inputCredentials: Record<string, CredentialsMetaInput | undefined>;
-  inputValues: Record<string, any>;
-  onCredentialChange: (key: string, value?: CredentialsMetaInput) => void;
 };
 
 export function CredentialsGroupedView({
   credentialFields,
   requiredCredentials,
-  inputCredentials,
-  inputValues,
-  onCredentialChange,
 }: Props) {
   const allProviders = useContext(CredentialsProvidersContext);
+  const { inputCredentials, setInputCredentialsValue, inputValues } =
+    useRunAgentModalContext();
 
   const { userCredentialFields, systemCredentialFields } = useMemo(
     () =>
@@ -94,11 +87,11 @@ export function CredentialsGroupedView({
       );
 
       if (savedCredential) {
-        onCredentialChange(key, {
+        setInputCredentialsValue(key, {
           id: savedCredential.id,
           provider: savedCredential.provider,
-          type: savedCredential.type as CredentialsType,
-          title: savedCredential.title,
+          type: savedCredential.type,
+          title: (savedCredential as { title?: string }).title,
         });
       }
     }
@@ -110,7 +103,7 @@ export function CredentialsGroupedView({
     systemCredentialFields,
     requiredCredentials,
     inputCredentials,
-    onCredentialChange,
+    setInputCredentialsValue,
     isLoadingProviders,
   ]);
 
@@ -130,7 +123,7 @@ export function CredentialsGroupedView({
                   }
                   selectedCredentials={selectedCred}
                   onSelectCredentials={(value) => {
-                    onCredentialChange(key, value);
+                    setInputCredentialsValue(key, value);
                   }}
                   siblingInputs={inputValues}
                   isOptional={!requiredCredentials.has(key)}
@@ -150,8 +143,7 @@ export function CredentialsGroupedView({
           <AccordionItem value="system-credentials" className="border-none">
             <AccordionTrigger className="py-2 text-sm text-muted-foreground hover:no-underline">
               <div className="flex items-center gap-1">
-                <SlidersHorizontalIcon size={16} weight="bold" /> System
-                credentials
+                <SlidersHorizontal size={16} weight="bold" /> System credentials
                 {hasMissingSystemCredentials && (
                   <span className="text-destructive">(missing)</span>
                 )}
@@ -171,7 +163,7 @@ export function CredentialsGroupedView({
                         }
                         selectedCredentials={selectedCred}
                         onSelectCredentials={(value) => {
-                          onCredentialChange(key, value);
+                          setInputCredentialsValue(key, value);
                         }}
                         siblingInputs={inputValues}
                         isOptional={!requiredCredentials.has(key)}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/ModalRunSection.tsx

@@ -1,9 +1,9 @@
 import { Input } from "@/components/atoms/Input/Input";
-import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
 import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
 import { useMemo } from "react";
 import { RunAgentInputs } from "../../../RunAgentInputs/RunAgentInputs";
 import { useRunAgentModalContext } from "../../context";
+import { CredentialsGroupedView } from "../CredentialsGroupedView/CredentialsGroupedView";
 import { ModalSection } from "../ModalSection/ModalSection";
 import { WebhookTriggerBanner } from "../WebhookTriggerBanner/WebhookTriggerBanner";
 
@@ -19,8 +19,6 @@ export function ModalRunSection() {
     setInputValue,
     agentInputFields,
     agentCredentialsInputFields,
-    inputCredentials,
-    setInputCredentialsValue,
   } = useRunAgentModalContext();
 
   const inputFields = Object.entries(agentInputFields || {});
@@ -104,9 +102,6 @@ export function ModalRunSection() {
           <CredentialsGroupedView
             credentialFields={credentialFields}
             requiredCredentials={requiredCredentials}
-            inputCredentials={inputCredentials}
-            inputValues={inputValues}
-            onCredentialChange={setInputCredentialsValue}
           />
         </ModalSection>
       ) : null}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/helpers.ts

@@ -1,5 +1,5 @@
 import { CredentialsProvidersContextType } from "@/providers/agent-credentials/credentials-provider";
-import { filterSystemCredentials, getSystemCredentials } from "../../helpers";
+import { getSystemCredentials } from "../../../../../../../../../../../components/contextual/CredentialsInput/helpers";
 
 export type CredentialField = [string, any];
 
@@ -208,42 +208,3 @@ export function findSavedCredentialByProviderAndType(
 
   return undefined;
 }
-
-export function findSavedUserCredentialByProviderAndType(
-  providerNames: string[],
-  credentialTypes: string[],
-  requiredScopes: string[] | undefined,
-  allProviders: CredentialsProvidersContextType | null,
-): SavedCredential | undefined {
-  for (const providerName of providerNames) {
-    const providerData = allProviders?.[providerName];
-    if (!providerData) continue;
-
-    const userCredentials = filterSystemCredentials(
-      providerData.savedCredentials ?? [],
-    );
-
-    const matchingCredentials: SavedCredential[] = [];
-
-    for (const credential of userCredentials) {
-      const typeMatches =
-        credentialTypes.length === 0 ||
-        credentialTypes.includes(credential.type);
-      const scopesMatch = hasRequiredScopes(credential, requiredScopes);
-
-      if (!typeMatches) continue;
-      if (!scopesMatch) continue;
-
-      matchingCredentials.push(credential as SavedCredential);
-    }
-
-    if (matchingCredentials.length === 1) {
-      return matchingCredentials[0];
-    }
-    if (matchingCredentials.length > 1) {
-      return undefined;
-    }
-  }
-
-  return undefined;
-}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedRunView/components/SafeModeToggle.tsx

@@ -5,112 +5,48 @@ import { Graph } from "@/lib/autogpt-server-api/types";
 import { cn } from "@/lib/utils";
 import { ShieldCheckIcon, ShieldIcon } from "@phosphor-icons/react";
 import { useAgentSafeMode } from "@/hooks/useAgentSafeMode";
-import {
-  Tooltip,
-  TooltipContent,
-  TooltipTrigger,
-} from "@/components/atoms/Tooltip/BaseTooltip";
 
 interface Props {
   graph: GraphModel | LibraryAgent | Graph;
   className?: string;
+  fullWidth?: boolean;
 }
 
-interface SafeModeIconButtonProps {
-  isEnabled: boolean;
-  label: string;
-  tooltipEnabled: string;
-  tooltipDisabled: string;
-  onToggle: () => void;
-  isPending: boolean;
-}
-
-function SafeModeIconButton({
-  isEnabled,
-  label,
-  tooltipEnabled,
-  tooltipDisabled,
-  onToggle,
-  isPending,
-}: SafeModeIconButtonProps) {
-  return (
-    <Tooltip delayDuration={100}>
-      <TooltipTrigger asChild>
-        <Button
-          variant="icon"
-          size="icon"
-          aria-label={`${label}: ${isEnabled ? "ON" : "OFF"}. ${isEnabled ? tooltipEnabled : tooltipDisabled}`}
-          onClick={onToggle}
-          disabled={isPending}
-          className={cn(isPending ? "opacity-0" : "opacity-100")}
-        >
-          {isEnabled ? (
-            <ShieldCheckIcon weight="bold" size={16} />
-          ) : (
-            <ShieldIcon weight="bold" size={16} />
-          )}
-        </Button>
-      </TooltipTrigger>
-      <TooltipContent>
-        <div className="text-center">
-          <div className="font-medium">
-            {label}: {isEnabled ? "ON" : "OFF"}
-          </div>
-          <div className="mt-1 text-xs text-muted-foreground">
-            {isEnabled ? tooltipEnabled : tooltipDisabled}
-          </div>
-        </div>
-      </TooltipContent>
-    </Tooltip>
-  );
-}
-
-export function SafeModeToggle({ graph, className }: Props) {
+export function SafeModeToggle({ graph }: Props) {
   const {
-    currentHITLSafeMode,
-    showHITLToggle,
-    isHITLStateUndetermined,
-    handleHITLToggle,
-    currentSensitiveActionSafeMode,
-    showSensitiveActionToggle,
-    handleSensitiveActionToggle,
+    currentSafeMode,
     isPending,
     shouldShowToggle,
+    isStateUndetermined,
+    handleToggle,
   } = useAgentSafeMode(graph);
 
-  if (!shouldShowToggle || isHITLStateUndetermined) {
-    return null;
-  }
-
-  const showHITL = showHITLToggle && !isHITLStateUndetermined;
-  const showSensitive = showSensitiveActionToggle;
-
-  if (!showHITL && !showSensitive) {
+  if (!shouldShowToggle || isStateUndetermined) {
     return null;
   }
 
   return (
-    <div className={cn("flex gap-1", className)}>
-      {showHITL && (
-        <SafeModeIconButton
-          isEnabled={currentHITLSafeMode}
-          label="Human-in-the-loop"
-          tooltipEnabled="The agent will pause at human-in-the-loop blocks and wait for your approval"
-          tooltipDisabled="Human-in-the-loop blocks will proceed automatically"
-          onToggle={handleHITLToggle}
-          isPending={isPending}
-        />
+    <Button
+      variant="icon"
+      key={graph.id}
+      size="icon"
+      aria-label={
+        currentSafeMode!
+          ? "Safe Mode: ON. Human in the loop blocks require manual review"
+          : "Safe Mode: OFF. Human in the loop blocks proceed automatically"
+      }
+      onClick={handleToggle}
+      className={cn(isPending ? "opacity-0" : "opacity-100")}
+    >
+      {currentSafeMode! ? (
+        <>
+          <ShieldCheckIcon weight="bold" size={16} />
+        </>
+      ) : (
+        <>
+          <ShieldIcon weight="bold" size={16} />
+        </>
       )}
-      {showSensitive && (
-        <SafeModeIconButton
-          isEnabled={currentSensitiveActionSafeMode}
-          label="Sensitive actions"
-          tooltipEnabled="The agent will pause at sensitive action blocks and wait for your approval"
-          tooltipDisabled="Sensitive action blocks will proceed automatically"
-          onToggle={handleSensitiveActionToggle}
-          isPending={isPending}
-        />
-      )}
-    </div>
+    </Button>
   );
 }

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedSettingsView/SelectedSettingsView.tsx

@@ -13,16 +13,8 @@ interface Props {
 }
 
 export function SelectedSettingsView({ agent, onClearSelectedRun }: Props) {
-  const {
-    currentHITLSafeMode,
-    showHITLToggle,
-    handleHITLToggle,
-    currentSensitiveActionSafeMode,
-    showSensitiveActionToggle,
-    handleSensitiveActionToggle,
-    isPending,
-    shouldShowToggle,
-  } = useAgentSafeMode(agent);
+  const { currentSafeMode, isPending, hasHITLBlocks, handleToggle } =
+    useAgentSafeMode(agent);
 
   return (
     <SelectedViewLayout agent={agent}>
@@ -42,51 +34,24 @@ export function SelectedSettingsView({ agent, onClearSelectedRun }: Props) {
         </div>
 
         <div className={`${AGENT_LIBRARY_SECTION_PADDING_X} space-y-6`}>
-          {shouldShowToggle ? (
-            <>
-              {showHITLToggle && (
-                <div className="flex w-full max-w-2xl flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
-                  <div className="flex w-full items-start justify-between gap-4">
-                    <div className="flex-1">
-                      <Text variant="large-semibold">
-                        Human-in-the-loop approval
-                      </Text>
-                      <Text variant="large" className="mt-1 text-zinc-900">
-                        The agent will pause at human-in-the-loop blocks and
-                        wait for your review before continuing
-                      </Text>
-                    </div>
-                    <Switch
-                      checked={currentHITLSafeMode || false}
-                      onCheckedChange={handleHITLToggle}
-                      disabled={isPending}
-                      className="mt-1"
-                    />
-                  </div>
+          {hasHITLBlocks ? (
+            <div className="flex w-full max-w-2xl flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
+              <div className="flex w-full items-start justify-between gap-4">
+                <div className="flex-1">
+                  <Text variant="large-semibold">Require human approval</Text>
+                  <Text variant="large" className="mt-1 text-zinc-900">
+                    The agent will pause and wait for your review before
+                    continuing
+                  </Text>
                 </div>
-              )}
-              {showSensitiveActionToggle && (
-                <div className="flex w-full max-w-2xl flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
-                  <div className="flex w-full items-start justify-between gap-4">
-                    <div className="flex-1">
-                      <Text variant="large-semibold">
-                        Sensitive action approval
-                      </Text>
-                      <Text variant="large" className="mt-1 text-zinc-900">
-                        The agent will pause at sensitive action blocks and wait
-                        for your review before continuing
-                      </Text>
-                    </div>
-                    <Switch
-                      checked={currentSensitiveActionSafeMode}
-                      onCheckedChange={handleSensitiveActionToggle}
-                      disabled={isPending}
-                      className="mt-1"
-                    />
-                  </div>
-                </div>
-              )}
-            </>
+                <Switch
+                  checked={currentSafeMode || false}
+                  onCheckedChange={handleToggle}
+                  disabled={isPending}
+                  className="mt-1"
+                />
+              </div>
+            </div>
           ) : (
             <div className="rounded-xl border border-zinc-100 bg-white p-6">
               <Text variant="body" className="text-muted-foreground">

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

@@ -1,15 +1,8 @@
 "use client";
-import React, {
-  useCallback,
-  useContext,
-  useEffect,
-  useMemo,
-  useState,
-} from "react";
+import React, { useCallback, useEffect, useMemo, useState } from "react";
 
 import {
   CredentialsMetaInput,
-  CredentialsType,
   GraphExecutionID,
   GraphMeta,
   LibraryAgentPreset,
@@ -36,11 +29,7 @@ import {
 } from "@/components/__legacy__/ui/icons";
 import { Input } from "@/components/__legacy__/ui/input";
 import { Button } from "@/components/atoms/Button/Button";
-import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
-import {
-  findSavedCredentialByProviderAndType,
-  findSavedUserCredentialByProviderAndType,
-} from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers";
+import { CredentialsInput } from "@/components/contextual/CredentialsInput/CredentialsInput";
 import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
 import {
   useToast,
@@ -48,7 +37,6 @@ import {
 } from "@/components/molecules/Toast/use-toast";
 import { humanizeCronExpression } from "@/lib/cron-expression-utils";
 import { cn, isEmpty } from "@/lib/utils";
-import { CredentialsProvidersContext } from "@/providers/agent-credentials/credentials-provider";
 import { ClockIcon, CopyIcon, InfoIcon } from "@phosphor-icons/react";
 import { CalendarClockIcon, Trash2Icon } from "lucide-react";
 
@@ -102,7 +90,6 @@ export function AgentRunDraftView({
   const api = useBackendAPI();
   const { toast } = useToast();
   const toastOnFail = useToastOnFail();
-  const allProviders = useContext(CredentialsProvidersContext);
 
   const [inputValues, setInputValues] = useState<Record<string, any>>({});
   const [inputCredentials, setInputCredentials] = useState<
@@ -141,77 +128,6 @@ export function AgentRunDraftView({
     () => graph.credentials_input_schema.properties,
     [graph],
   );
-  const credentialFields = useMemo(
-    function getCredentialFields() {
-      return Object.entries(agentCredentialsInputFields);
-    },
-    [agentCredentialsInputFields],
-  );
-  const requiredCredentials = useMemo(
-    function getRequiredCredentials() {
-      return new Set(
-        (graph.credentials_input_schema?.required as string[]) || [],
-      );
-    },
-    [graph.credentials_input_schema?.required],
-  );
-
-  useEffect(
-    function initializeDefaultCredentials() {
-      if (!allProviders) return;
-      if (!graph.credentials_input_schema?.properties) return;
-      if (requiredCredentials.size === 0) return;
-
-      setInputCredentials(function updateCredentials(currentCreds) {
-        const next = { ...currentCreds };
-        let didAdd = false;
-
-        for (const key of requiredCredentials) {
-          if (next[key]) continue;
-          const schema = graph.credentials_input_schema.properties[key];
-          if (!schema) continue;
-
-          const providerNames = schema.credentials_provider || [];
-          const credentialTypes = schema.credentials_types || [];
-          const requiredScopes = schema.credentials_scopes;
-
-          const userCredential = findSavedUserCredentialByProviderAndType(
-            providerNames,
-            credentialTypes,
-            requiredScopes,
-            allProviders,
-          );
-
-          const savedCredential =
-            userCredential ||
-            findSavedCredentialByProviderAndType(
-              providerNames,
-              credentialTypes,
-              requiredScopes,
-              allProviders,
-            );
-
-          if (!savedCredential) continue;
-
-          next[key] = {
-            id: savedCredential.id,
-            provider: savedCredential.provider,
-            type: savedCredential.type as CredentialsType,
-            title: savedCredential.title,
-          };
-          didAdd = true;
-        }
-
-        if (!didAdd) return currentCreds;
-        return next;
-      });
-    },
-    [
-      allProviders,
-      graph.credentials_input_schema?.properties,
-      requiredCredentials,
-    ],
-  );
 
   const [allRequiredInputsAreSet, missingInputs] = useMemo(() => {
     const nonEmptyInputs = new Set(
@@ -229,35 +145,18 @@ export function AgentRunDraftView({
     );
     return [isSuperset, difference];
   }, [agentInputSchema.required, inputValues]);
-  const [allCredentialsAreSet, missingCredentials] = useMemo(
-    function getCredentialStatus() {
-      const missing = Array.from(requiredCredentials).filter((key) => {
-        const cred = inputCredentials[key];
-        return !cred || !cred.id;
-      });
-      return [missing.length === 0, missing];
-    },
-    [requiredCredentials, inputCredentials],
-  );
-  function addChangedCredentials(prev: Set<keyof LibraryAgentPresetUpdatable>) {
-    const next = new Set(prev);
-    next.add("credentials");
-    return next;
-  }
-
-  function handleCredentialChange(key: string, value?: CredentialsMetaInput) {
-    setInputCredentials(function updateInputCredentials(currentCreds) {
-      const next = { ...currentCreds };
-      if (value === undefined) {
-        delete next[key];
-        return next;
-      }
-      next[key] = value;
-      return next;
-    });
-    setChangedPresetAttributes(addChangedCredentials);
-  }
-
+  const [allCredentialsAreSet, missingCredentials] = useMemo(() => {
+    const availableCredentials = new Set(Object.keys(inputCredentials));
+    const allCredentials = new Set(Object.keys(agentCredentialsInputFields));
+    // Backwards-compatible implementation of isSupersetOf and difference
+    const isSuperset = Array.from(allCredentials).every((item) =>
+      availableCredentials.has(item),
+    );
+    const difference = Array.from(allCredentials).filter(
+      (item) => !availableCredentials.has(item),
+    );
+    return [isSuperset, difference];
+  }, [agentCredentialsInputFields, inputCredentials]);
   const notifyMissingInputs = useCallback(
     (needPresetName: boolean = true) => {
       const allMissingFields = (
@@ -750,6 +649,35 @@ export function AgentRunDraftView({
               </>
             )}
 
+            {/* Credentials inputs */}
+            {Object.entries(agentCredentialsInputFields).map(
+              ([key, inputSubSchema]) => (
+                <CredentialsInput
+                  key={key}
+                  schema={{ ...inputSubSchema, discriminator: undefined }}
+                  selectedCredentials={
+                    inputCredentials[key] ?? inputSubSchema.default
+                  }
+                  onSelectCredentials={(value) => {
+                    setInputCredentials((obj) => {
+                      const newObj = { ...obj };
+                      if (value === undefined) {
+                        delete newObj[key];
+                        return newObj;
+                      }
+                      return {
+                        ...obj,
+                        [key]: value,
+                      };
+                    });
+                    setChangedPresetAttributes((prev) =>
+                      prev.add("credentials"),
+                    );
+                  }}
+                />
+              ),
+            )}
+
             {/* Regular inputs */}
             {Object.entries(agentInputFields).map(([key, inputSubSchema]) => (
               <RunAgentInputs
@@ -767,17 +695,6 @@ export function AgentRunDraftView({
                 data-testid={`agent-input-${key}`}
               />
             ))}
-
-            {/* Credentials inputs */}
-            {credentialFields.length > 0 && (
-              <CredentialsGroupedView
-                credentialFields={credentialFields}
-                requiredCredentials={requiredCredentials}
-                inputCredentials={inputCredentials}
-                inputValues={inputValues}
-                onCredentialChange={handleCredentialChange}
-              />
-            )}
           </CardContent>
         </Card>
       </div>

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

@@ -2,7 +2,6 @@
 import { Button } from "@/components/atoms/Button/Button";
 import { FileInput } from "@/components/atoms/FileInput/FileInput";
 import { Input } from "@/components/atoms/Input/Input";
-import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import {
   Form,
@@ -121,7 +120,7 @@ export default function LibraryUploadAgentDialog() {
           >
             {isUploading ? (
               <div className="flex items-center gap-2">
-                <LoadingSpinner size="small" className="text-white" />
+                <div className="h-4 w-4 animate-spin rounded-full border-b-2 border-t-2 border-white"></div>
                 <span>Uploading...</span>
               </div>
             ) : (

autogpt_platform/frontend/src/app/api/openapi.json

@@ -6383,11 +6383,6 @@
             "title": "Has Human In The Loop",
             "readOnly": true
           },
-          "has_sensitive_action": {
-            "type": "boolean",
-            "title": "Has Sensitive Action",
-            "readOnly": true
-          },
           "trigger_setup_info": {
             "anyOf": [
               { "$ref": "#/components/schemas/GraphTriggerInfo" },
@@ -6404,7 +6399,6 @@
           "output_schema",
           "has_external_trigger",
           "has_human_in_the_loop",
-          "has_sensitive_action",
           "trigger_setup_info"
         ],
         "title": "BaseGraph"
@@ -7635,11 +7629,6 @@
             "title": "Has Human In The Loop",
             "readOnly": true
           },
-          "has_sensitive_action": {
-            "type": "boolean",
-            "title": "Has Sensitive Action",
-            "readOnly": true
-          },
           "trigger_setup_info": {
             "anyOf": [
               { "$ref": "#/components/schemas/GraphTriggerInfo" },
@@ -7663,7 +7652,6 @@
           "output_schema",
           "has_external_trigger",
           "has_human_in_the_loop",
-          "has_sensitive_action",
           "trigger_setup_info",
           "credentials_input_schema"
         ],
@@ -7742,11 +7730,6 @@
             "title": "Has Human In The Loop",
             "readOnly": true
           },
-          "has_sensitive_action": {
-            "type": "boolean",
-            "title": "Has Sensitive Action",
-            "readOnly": true
-          },
           "trigger_setup_info": {
             "anyOf": [
               { "$ref": "#/components/schemas/GraphTriggerInfo" },
@@ -7771,7 +7754,6 @@
           "output_schema",
           "has_external_trigger",
           "has_human_in_the_loop",
-          "has_sensitive_action",
           "trigger_setup_info",
           "credentials_input_schema"
         ],
@@ -7780,14 +7762,8 @@
       "GraphSettings": {
         "properties": {
           "human_in_the_loop_safe_mode": {
-            "type": "boolean",
-            "title": "Human In The Loop Safe Mode",
-            "default": true
-          },
-          "sensitive_action_safe_mode": {
-            "type": "boolean",
-            "title": "Sensitive Action Safe Mode",
-            "default": false
+            "anyOf": [{ "type": "boolean" }, { "type": "null" }],
+            "title": "Human In The Loop Safe Mode"
           }
         },
         "type": "object",
@@ -7945,16 +7921,6 @@
             "title": "Has External Trigger",
             "description": "Whether the agent has an external trigger (e.g. webhook) node"
           },
-          "has_human_in_the_loop": {
-            "type": "boolean",
-            "title": "Has Human In The Loop",
-            "description": "Whether the agent has human-in-the-loop blocks"
-          },
-          "has_sensitive_action": {
-            "type": "boolean",
-            "title": "Has Sensitive Action",
-            "description": "Whether the agent has sensitive action blocks"
-          },
           "trigger_setup_info": {
             "anyOf": [
               { "$ref": "#/components/schemas/GraphTriggerInfo" },
@@ -8001,8 +7967,6 @@
           "output_schema",
           "credentials_input_schema",
           "has_external_trigger",
-          "has_human_in_the_loop",
-          "has_sensitive_action",
           "new_output",
           "can_access_graph",
           "is_latest_version",

autogpt_platform/frontend/src/components/atoms/Badge/Badge.test.tsx

@@ -0,0 +1,81 @@
+// import { render, screen } from "@testing-library/react";
+// import { describe, expect, it } from "vitest";
+// import { Badge } from "./Badge";
+
+// describe("Badge Component", () => {
+//   it("renders badge with content", () => {
+//     render(<Badge variant="success">Success</Badge>);
+
+//     expect(screen.getByText("Success")).toBeInTheDocument();
+//   });
+
+//   it("applies correct variant styles", () => {
+//     const { rerender } = render(<Badge variant="success">Success</Badge>);
+//     let badge = screen.getByText("Success");
+//     expect(badge).toHaveClass("bg-green-100", "text-green-800");
+
+//     rerender(<Badge variant="error">Error</Badge>);
+//     badge = screen.getByText("Error");
+//     expect(badge).toHaveClass("bg-red-100", "text-red-800");
+
+//     rerender(<Badge variant="info">Info</Badge>);
+//     badge = screen.getByText("Info");
+//     expect(badge).toHaveClass("bg-slate-100", "text-slate-800");
+//   });
+
+//   it("applies custom className", () => {
+//     render(
+//       <Badge variant="success" className="custom-class">
+//         Success
+//       </Badge>,
+//     );
+
+//     const badge = screen.getByText("Success");
+//     expect(badge).toHaveClass("custom-class");
+//   });
+
+//   it("renders as span element", () => {
+//     render(<Badge variant="success">Success</Badge>);
+
+//     const badge = screen.getByText("Success");
+//     expect(badge.tagName).toBe("SPAN");
+//   });
+
+//   it("renders children correctly", () => {
+//     render(
+//       <Badge variant="success">
+//         <span>Custom</span> Content
+//       </Badge>,
+//     );
+
+//     expect(screen.getByText("Custom")).toBeInTheDocument();
+//     expect(screen.getByText("Content")).toBeInTheDocument();
+//   });
+
+//   it("supports all badge variants", () => {
+//     const variants = ["success", "error", "info"] as const;
+
+//     variants.forEach((variant) => {
+//       const { unmount } = render(
+//         <Badge variant={variant} data-testid={`badge-${variant}`}>
+//           {variant}
+//         </Badge>,
+//       );
+
+//       expect(screen.getByTestId(`badge-${variant}`)).toBeInTheDocument();
+//       unmount();
+//     });
+//   });
+
+//   it("handles long text content", () => {
+//     render(
+//       <Badge variant="info">
+//         Very long text that should be handled properly by the component
+//       </Badge>,
+//     );
+
+//     const badge = screen.getByText(/Very long text/);
+//     expect(badge).toBeInTheDocument();
+//     expect(badge).toHaveClass("overflow-hidden", "text-ellipsis");
+//   });
+// });

autogpt_platform/frontend/src/components/contextual/CredentialsInput/useCredentialsInput.ts

@@ -98,20 +98,24 @@ export function useCredentialsInput({
 
   // Auto-select the first available credential on initial mount
   // Once a user has made a selection, we don't override it
-  useEffect(
-    function autoSelectCredential() {
-      if (readOnly) return;
-      if (!credentials || !("savedCredentials" in credentials)) return;
-      if (selectedCredential?.id) return;
+  useEffect(() => {
+    if (readOnly) return;
+    if (!credentials || !("savedCredentials" in credentials)) return;
 
-      const savedCreds = credentials.savedCredentials;
-      if (savedCreds.length === 0) return;
+    // If already selected, don't auto-select
+    if (selectedCredential?.id) return;
 
-      if (hasAttemptedAutoSelect.current) return;
-      hasAttemptedAutoSelect.current = true;
+    // Only attempt auto-selection once
+    if (hasAttemptedAutoSelect.current) return;
+    hasAttemptedAutoSelect.current = true;
 
-      if (isOptional) return;
+    // If optional, don't auto-select (user can choose "None")
+    if (isOptional) return;
 
+    const savedCreds = credentials.savedCredentials;
+
+    // Auto-select the first credential if any are available
+    if (savedCreds.length > 0) {
       const cred = savedCreds[0];
       onSelectCredential({
         id: cred.id,
@@ -119,15 +123,14 @@ export function useCredentialsInput({
         provider: credentials.provider,
         title: (cred as any).title,
       });
-    },
-    [
-      credentials,
-      selectedCredential?.id,
-      readOnly,
-      isOptional,
-      onSelectCredential,
-    ],
-  );
+    }
+  }, [
+    credentials,
+    selectedCredential?.id,
+    readOnly,
+    isOptional,
+    onSelectCredential,
+  ]);
 
   if (
     !credentials ||

autogpt_platform/frontend/src/components/molecules/Popover/Popover.tsx

@@ -1,33 +0,0 @@
-"use client";
-
-import * as PopoverPrimitive from "@radix-ui/react-popover";
-import * as React from "react";
-
-import { cn } from "@/lib/utils";
-
-const Popover = PopoverPrimitive.Root;
-
-const PopoverTrigger = PopoverPrimitive.Trigger;
-
-const PopoverAnchor = PopoverPrimitive.Anchor;
-
-const PopoverContent = React.forwardRef<
-  React.ElementRef<typeof PopoverPrimitive.Content>,
-  React.ComponentPropsWithoutRef<typeof PopoverPrimitive.Content>
->(({ className, align = "center", sideOffset = 4, ...props }, ref) => (
-  <PopoverPrimitive.Portal>
-    <PopoverPrimitive.Content
-      ref={ref}
-      align={align}
-      sideOffset={sideOffset}
-      className={cn(
-        "z-50 w-72 rounded-lg border border-zinc-200 bg-white p-4 text-zinc-900 shadow-md outline-none data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2",
-        className,
-      )}
-      {...props}
-    />
-  </PopoverPrimitive.Portal>
-));
-PopoverContent.displayName = PopoverPrimitive.Content.displayName;
-
-export { Popover, PopoverAnchor, PopoverContent, PopoverTrigger };

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/CredentialField/components/CredentialFieldTitle.tsx

@@ -35,13 +35,12 @@ export const CredentialFieldTitle = (props: {
     uiOptions,
   );
 
-  const provider = getCredentialProviderFromSchema(
-    useNodeStore.getState().getHardCodedValues(nodeId),
-    schema as BlockIOCredentialsSubSchema,
+  const credentialProvider = toDisplayName(
+    getCredentialProviderFromSchema(
+      useNodeStore.getState().getHardCodedValues(nodeId),
+      schema as BlockIOCredentialsSubSchema,
+    ) ?? "",
   );
-  const credentialProvider = provider
-    ? `${toDisplayName(provider)} credential`
-    : "credential";
 
   const updatedUiSchema = updateUiOption(uiSchema, {
     showHandles: false,

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/LlmModelField.tsx

@@ -1,92 +0,0 @@
-"use client";
-
-import {
-  descriptionId,
-  FieldProps,
-  getTemplate,
-  RJSFSchema,
-  titleId,
-} from "@rjsf/utils";
-import { useMemo } from "react";
-import { LlmModelPicker } from "./components/LlmModelPicker";
-import { LlmModelMetadataMap } from "./types";
-import { updateUiOption } from "../../helpers";
-
-type LlmModelSchema = RJSFSchema & {
-  llm_model_metadata?: LlmModelMetadataMap;
-};
-
-export function LlmModelField(props: FieldProps) {
-  const { schema, formData, onChange, disabled, readonly, fieldPathId } = props;
-
-  const metadata = useMemo(() => {
-    return (schema as LlmModelSchema)?.llm_model_metadata ?? {};
-  }, [schema]);
-
-  const models = useMemo(() => {
-    return Object.values(metadata);
-  }, [metadata]);
-
-  const selectedName =
-    typeof formData === "string"
-      ? formData
-      : typeof schema.default === "string"
-        ? schema.default
-        : "";
-
-  const selectedModel = selectedName
-    ? (metadata[selectedName] ??
-      models.find((model) => model.name === selectedName))
-    : undefined;
-
-  const recommendedName =
-    typeof schema.default === "string" ? schema.default : models[0]?.name;
-
-  const recommendedModel =
-    recommendedName && metadata[recommendedName]
-      ? metadata[recommendedName]
-      : undefined;
-
-  if (models.length === 0) {
-    return null;
-  }
-
-  const TitleFieldTemplate = getTemplate("TitleFieldTemplate", props.registry);
-  const DescriptionFieldTemplate = getTemplate(
-    "DescriptionFieldTemplate",
-    props.registry,
-  );
-
-  const updatedUiSchema = updateUiOption(props.uiSchema, {
-    showHandles: false,
-  });
-
-  return (
-    <>
-      <div className="flex items-center gap-2">
-        <TitleFieldTemplate
-          id={titleId(fieldPathId)}
-          title={schema.title || ""}
-          required={true}
-          schema={schema}
-          uiSchema={updatedUiSchema}
-          registry={props.registry}
-        />
-        <DescriptionFieldTemplate
-          id={descriptionId(fieldPathId)}
-          description={schema.description || ""}
-          schema={schema}
-          registry={props.registry}
-        />
-      </div>
-
-      <LlmModelPicker
-        models={models}
-        selectedModel={selectedModel}
-        recommendedModel={recommendedModel}
-        onSelect={(value) => onChange(value, fieldPathId?.path)}
-        disabled={disabled || readonly}
-      />
-    </>
-  );
-}

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/components/LlmIcon.tsx

@@ -1,66 +0,0 @@
-"use client";
-
-import Image from "next/image";
-import { Text } from "@/components/atoms/Text/Text";
-
-const creatorIconMap: Record<string, string> = {
-  anthropic: "/integrations/anthropic-color.png",
-  openai: "/integrations/openai.png",
-  google: "/integrations/gemini.png",
-  nvidia: "/integrations/nvidia.png",
-  groq: "/integrations/groq.png",
-  ollama: "/integrations/ollama.png",
-  openrouter: "/integrations/open_router.png",
-  v0: "/integrations/v0.png",
-  xai: "/integrations/xai.webp",
-  meta: "/integrations/llama_api.png",
-  amazon: "/integrations/amazon.png",
-  cohere: "/integrations/cohere.png",
-  deepseek: "/integrations/deepseek.png",
-  gryphe: "/integrations/gryphe.png",
-  microsoft: "/integrations/microsoft.webp",
-  moonshotai: "/integrations/moonshot.png",
-  mistral: "/integrations/mistral.png",
-  mistralai: "/integrations/mistral.png",
-  nousresearch: "/integrations/nousresearch.avif",
-  perplexity: "/integrations/perplexity.webp",
-  qwen: "/integrations/qwen.png",
-};
-
-type Props = {
-  value: string;
-  size?: number;
-};
-
-export function LlmIcon({ value, size = 20 }: Props) {
-  const normalized = value.trim().toLowerCase().replace(/\s+/g, "");
-  const src = creatorIconMap[normalized];
-  if (src) {
-    return (
-      <div
-        className="flex items-center justify-center overflow-hidden rounded-xsmall"
-        style={{ width: size, height: size }}
-      >
-        <Image
-          src={src}
-          alt={value}
-          width={size}
-          height={size}
-          className="h-full w-full object-cover"
-        />
-      </div>
-    );
-  }
-
-  const fallback = value?.trim().slice(0, 1).toUpperCase() || "?";
-  return (
-    <div
-      className="flex items-center justify-center rounded-xsmall bg-zinc-100"
-      style={{ width: size, height: size }}
-    >
-      <Text variant="small" className="text-zinc-500">
-        {fallback}
-      </Text>
-    </div>
-  );
-}

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/components/LlmMenuHeader.tsx

@@ -1,24 +0,0 @@
-"use client";
-
-import { ArrowLeftIcon } from "@phosphor-icons/react";
-import { Text } from "@/components/atoms/Text/Text";
-
-type Props = {
-  label: string;
-  onBack: () => void;
-};
-
-export function LlmMenuHeader({ label, onBack }: Props) {
-  return (
-    <button
-      type="button"
-      onClick={onBack}
-      className="flex w-full items-center gap-2 px-2 py-2 text-left hover:bg-zinc-100"
-    >
-      <ArrowLeftIcon className="h-4 w-4 text-zinc-800" weight="bold" />
-      <Text variant="body" className="text-zinc-900">
-        {label}
-      </Text>
-    </button>
-  );
-}

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/components/LlmMenuItem.tsx

@@ -1,61 +0,0 @@
-"use client";
-
-import { CaretRightIcon, CheckIcon } from "@phosphor-icons/react";
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-
-type Props = {
-  title: string;
-  subtitle?: string;
-  icon?: React.ReactNode;
-  showChevron?: boolean;
-  rightSlot?: React.ReactNode;
-  onClick: () => void;
-  isActive?: boolean;
-};
-
-export function LlmMenuItem({
-  title,
-  subtitle,
-  icon,
-  showChevron,
-  rightSlot,
-  onClick,
-  isActive,
-}: Props) {
-  const hasIcon = Boolean(icon);
-
-  return (
-    <button
-      type="button"
-      onClick={onClick}
-      className={cn("w-full py-1 pl-2 pr-4 text-left hover:bg-zinc-100")}
-    >
-      <div className="flex items-center justify-between gap-3">
-        <div className="flex items-center gap-2">
-          {icon}
-          <Text variant="body" className="text-zinc-900">
-            {title}
-          </Text>
-        </div>
-        <div className="flex items-center gap-2">
-          {isActive && (
-            <CheckIcon className="h-4 w-4 text-emerald-600" weight="bold" />
-          )}
-          {rightSlot}
-          {showChevron && (
-            <CaretRightIcon className="h-4 w-4 text-zinc-900" weight="bold" />
-          )}
-        </div>
-      </div>
-      {subtitle && (
-        <Text
-          variant="small"
-          className={cn("mb-1 text-zinc-500", hasIcon && "pl-0")}
-        >
-          {subtitle}
-        </Text>
-      )}
-    </button>
-  );
-}

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/components/LlmModelPicker.tsx

@@ -1,235 +0,0 @@
-"use client";
-
-import { useCallback, useEffect, useMemo, useState } from "react";
-import { CaretDownIcon } from "@phosphor-icons/react";
-import {
-  Popover,
-  PopoverContent,
-  PopoverTrigger,
-} from "@/components/molecules/Popover/Popover";
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import {
-  getCreatorDisplayName,
-  getModelDisplayName,
-  getProviderDisplayName,
-  groupByCreator,
-  groupByTitle,
-} from "../helpers";
-import { LlmModelMetadata } from "../types";
-import { LlmIcon } from "./LlmIcon";
-import { LlmMenuHeader } from "./LlmMenuHeader";
-import { LlmMenuItem } from "./LlmMenuItem";
-import { LlmPriceTier } from "./LlmPriceTier";
-
-type MenuView = "creator" | "model" | "provider";
-
-type Props = {
-  models: LlmModelMetadata[];
-  selectedModel?: LlmModelMetadata;
-  recommendedModel?: LlmModelMetadata;
-  onSelect: (value: string) => void;
-  disabled?: boolean;
-};
-
-export function LlmModelPicker({
-  models,
-  selectedModel,
-  recommendedModel,
-  onSelect,
-  disabled,
-}: Props) {
-  const [open, setOpen] = useState(false);
-  const [view, setView] = useState<MenuView>("creator");
-  const [activeCreator, setActiveCreator] = useState<string | null>(null);
-  const [activeTitle, setActiveTitle] = useState<string | null>(null);
-
-  const modelsByCreator = useMemo(() => groupByCreator(models), [models]);
-
-  const creators = useMemo(() => {
-    return Array.from(modelsByCreator.keys()).sort((a, b) =>
-      a.localeCompare(b),
-    );
-  }, [modelsByCreator]);
-
-  const creatorIconValues = useMemo(() => {
-    const map = new Map<string, string>();
-    for (const [creator, entries] of modelsByCreator.entries()) {
-      map.set(creator, entries[0]?.creator ?? creator);
-    }
-    return map;
-  }, [modelsByCreator]);
-
-  useEffect(() => {
-    if (!open) {
-      return;
-    }
-    setView("creator");
-    setActiveCreator(
-      selectedModel
-        ? getCreatorDisplayName(selectedModel)
-        : (creators[0] ?? null),
-    );
-    setActiveTitle(selectedModel ? getModelDisplayName(selectedModel) : null);
-  }, [open, selectedModel, creators]);
-
-  const currentCreator = activeCreator ?? creators[0] ?? null;
-
-  const currentModels = useMemo(() => {
-    return currentCreator ? (modelsByCreator.get(currentCreator) ?? []) : [];
-  }, [currentCreator, modelsByCreator]);
-
-  const currentCreatorIcon = useMemo(() => {
-    return currentModels[0]?.creator ?? currentCreator;
-  }, [currentModels, currentCreator]);
-
-  const modelsByTitle = useMemo(
-    () => groupByTitle(currentModels),
-    [currentModels],
-  );
-
-  const modelEntries = useMemo(() => {
-    return Array.from(modelsByTitle.entries())
-      .map(([title, entries]) => {
-        const providers = new Set(entries.map((entry) => entry.provider));
-        return {
-          title,
-          entries,
-          providerCount: providers.size,
-        };
-      })
-      .sort((a, b) => a.title.localeCompare(b.title));
-  }, [modelsByTitle]);
-
-  const providerEntries = useMemo(() => {
-    if (!activeTitle) {
-      return [];
-    }
-    return modelsByTitle.get(activeTitle) ?? [];
-  }, [activeTitle, modelsByTitle]);
-
-  const handleSelectModel = useCallback(
-    (modelName: string) => {
-      onSelect(modelName);
-      setOpen(false);
-    },
-    [onSelect],
-  );
-
-  const triggerModel = selectedModel ?? recommendedModel ?? models[0];
-  const triggerTitle = triggerModel
-    ? getModelDisplayName(triggerModel)
-    : "Select model";
-  const triggerCreator = triggerModel?.creator ?? "";
-
-  return (
-    <Popover open={open} onOpenChange={setOpen}>
-      <PopoverTrigger asChild>
-        <button
-          type="button"
-          disabled={disabled}
-          className={cn(
-            "flex w-full min-w-[15rem] items-center rounded-lg border border-zinc-200 bg-white px-3 py-2 text-left",
-            "hover:border-zinc-300 focus:outline-none focus:ring-2 focus:ring-zinc-200",
-            disabled && "cursor-not-allowed opacity-60",
-          )}
-        >
-          <LlmIcon value={triggerCreator} />
-          <Text variant="body" className="ml-1 flex-1 text-zinc-900">
-            {triggerTitle}
-          </Text>
-          <CaretDownIcon className="h-3 w-3 text-zinc-900" weight="bold" />
-        </button>
-      </PopoverTrigger>
-      <PopoverContent
-        align="start"
-        sideOffset={4}
-        className="max-h-[45vh] w-[--radix-popover-trigger-width] min-w-[16rem] overflow-y-auto rounded-md border border-zinc-200 bg-white p-0 shadow-[0px_1px_4px_rgba(12,12,13,0.12)]"
-      >
-        {view === "creator" && (
-          <div className="flex flex-col">
-            {recommendedModel && (
-              <>
-                <LlmMenuItem
-                  title={getModelDisplayName(recommendedModel)}
-                  subtitle="Recommended"
-                  icon={<LlmIcon value={recommendedModel.creator} />}
-                  onClick={() => handleSelectModel(recommendedModel.name)}
-                />
-                <div className="border-b border-zinc-200" />
-              </>
-            )}
-            {creators.map((creator) => (
-              <LlmMenuItem
-                key={creator}
-                title={creator}
-                icon={
-                  <LlmIcon value={creatorIconValues.get(creator) ?? creator} />
-                }
-                showChevron={true}
-                isActive={
-                  selectedModel
-                    ? getCreatorDisplayName(selectedModel) === creator
-                    : false
-                }
-                onClick={() => {
-                  setActiveCreator(creator);
-                  setView("model");
-                }}
-              />
-            ))}
-          </div>
-        )}
-        {view === "model" && currentCreator && (
-          <div className="flex flex-col">
-            <LlmMenuHeader
-              label={currentCreator}
-              onBack={() => setView("creator")}
-            />
-            <div className="border-b border-zinc-200" />
-            {modelEntries.map((entry) => (
-              <LlmMenuItem
-                key={entry.title}
-                title={entry.title}
-                icon={<LlmIcon value={currentCreatorIcon} />}
-                rightSlot={<LlmPriceTier tier={entry.entries[0]?.price_tier} />}
-                showChevron={entry.providerCount > 1}
-                isActive={
-                  selectedModel
-                    ? getModelDisplayName(selectedModel) === entry.title
-                    : false
-                }
-                onClick={() => {
-                  if (entry.providerCount > 1) {
-                    setActiveTitle(entry.title);
-                    setView("provider");
-                    return;
-                  }
-                  handleSelectModel(entry.entries[0].name);
-                }}
-              />
-            ))}
-          </div>
-        )}
-        {view === "provider" && activeTitle && (
-          <div className="flex flex-col">
-            <LlmMenuHeader
-              label={activeTitle}
-              onBack={() => setView("model")}
-            />
-            <div className="border-b border-zinc-200" />
-            {providerEntries.map((entry) => (
-              <LlmMenuItem
-                key={`${entry.title}-${entry.provider}`}
-                title={getProviderDisplayName(entry)}
-                icon={<LlmIcon value={entry.provider} />}
-                isActive={selectedModel?.provider === entry.provider}
-                onClick={() => handleSelectModel(entry.name)}
-              />
-            ))}
-          </div>
-        )}
-      </PopoverContent>
-    </Popover>
-  );
-}

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/components/LlmPriceTier.tsx

@@ -1,25 +0,0 @@
-"use client";
-
-import { CurrencyDollarSimpleIcon } from "@phosphor-icons/react";
-
-type Props = {
-  tier?: number;
-};
-
-export function LlmPriceTier({ tier }: Props) {
-  if (!tier || tier <= 0) {
-    return null;
-  }
-  const clamped = Math.min(3, Math.max(1, tier));
-  return (
-    <div className="flex items-center text-zinc-900">
-      {Array.from({ length: clamped }).map((_, index) => (
-        <CurrencyDollarSimpleIcon
-          key={`price-${index}`}
-          className="-mr-0.5 h-3 w-3"
-          weight="bold"
-        />
-      ))}
-    </div>
-  );
-}

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/helpers.ts

@@ -1,35 +0,0 @@
-import { LlmModelMetadata } from "./types";
-
-export function groupByCreator(models: LlmModelMetadata[]) {
-  const map = new Map<string, LlmModelMetadata[]>();
-  for (const model of models) {
-    const key = getCreatorDisplayName(model);
-    const existing = map.get(key) ?? [];
-    existing.push(model);
-    map.set(key, existing);
-  }
-  return map;
-}
-
-export function groupByTitle(models: LlmModelMetadata[]) {
-  const map = new Map<string, LlmModelMetadata[]>();
-  for (const model of models) {
-    const displayName = getModelDisplayName(model);
-    const existing = map.get(displayName) ?? [];
-    existing.push(model);
-    map.set(displayName, existing);
-  }
-  return map;
-}
-
-export function getCreatorDisplayName(model: LlmModelMetadata): string {
-  return model.creator_name || model.creator || "";
-}
-
-export function getModelDisplayName(model: LlmModelMetadata): string {
-  return model.title || model.name || "";
-}
-
-export function getProviderDisplayName(model: LlmModelMetadata): string {
-  return model.provider_name || model.provider || "";
-}

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/types.ts

@@ -1,11 +0,0 @@
-export type LlmModelMetadata = {
-  creator: string;
-  creator_name: string;
-  title: string;
-  provider: string;
-  provider_name: string;
-  name: string;
-  price_tier?: number;
-};
-
-export type LlmModelMetadataMap = Record<string, LlmModelMetadata>;

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/custom-registry.ts

@@ -8,7 +8,6 @@ import {
   isMultiSelectSchema,
 } from "../utils/schema-utils";
 import { TableField } from "./TableField/TableField";
-import { LlmModelField } from "./LlmModelField/LlmModelField";
 
 export interface CustomFieldDefinition {
   id: string;
@@ -58,15 +57,6 @@ export const CUSTOM_FIELDS: CustomFieldDefinition[] = [
     },
     component: TableField,
   },
-  {
-    id: "custom/llm_model_field",
-    matcher: (schema: any) => {
-      return (
-        typeof schema === "object" && schema !== null && "llm_model" in schema
-      );
-    },
-    component: LlmModelField,
-  },
 ];
 
 export function findCustomFieldId(schema: any): string | null {

autogpt_platform/frontend/src/hooks/useAgentSafeMode.ts

@@ -20,15 +20,11 @@ function hasHITLBlocks(graph: GraphModel | LibraryAgent | Graph): boolean {
   if ("has_human_in_the_loop" in graph) {
     return !!graph.has_human_in_the_loop;
   }
-  return false;
-}
 
-function hasSensitiveActionBlocks(
-  graph: GraphModel | LibraryAgent | Graph,
-): boolean {
-  if ("has_sensitive_action" in graph) {
-    return !!graph.has_sensitive_action;
+  if (isLibraryAgent(graph)) {
+    return graph.settings?.human_in_the_loop_safe_mode !== null;
   }
+
   return false;
 }
 
@@ -44,9 +40,7 @@ export function useAgentSafeMode(graph: GraphModel | LibraryAgent | Graph) {
 
   const graphId = getGraphId(graph);
   const isAgent = isLibraryAgent(graph);
-  const showHITLToggle = hasHITLBlocks(graph);
-  const showSensitiveActionToggle = hasSensitiveActionBlocks(graph);
-  const shouldShowToggle = showHITLToggle || showSensitiveActionToggle;
+  const shouldShowToggle = hasHITLBlocks(graph);
 
   const { mutateAsync: updateGraphSettings, isPending } =
     usePatchV1UpdateGraphSettings();
@@ -62,37 +56,27 @@ export function useAgentSafeMode(graph: GraphModel | LibraryAgent | Graph) {
     },
   );
 
-  const [localHITLSafeMode, setLocalHITLSafeMode] = useState<boolean>(true);
-  const [localSensitiveActionSafeMode, setLocalSensitiveActionSafeMode] =
-    useState<boolean>(false);
-  const [isLocalStateLoaded, setIsLocalStateLoaded] = useState<boolean>(false);
+  const [localSafeMode, setLocalSafeMode] = useState<boolean | null>(null);
 
   useEffect(() => {
     if (!isAgent && libraryAgent) {
-      setLocalHITLSafeMode(
-        libraryAgent.settings?.human_in_the_loop_safe_mode ?? true,
-      );
-      setLocalSensitiveActionSafeMode(
-        libraryAgent.settings?.sensitive_action_safe_mode ?? false,
-      );
-      setIsLocalStateLoaded(true);
+      const backendValue = libraryAgent.settings?.human_in_the_loop_safe_mode;
+      if (backendValue !== undefined) {
+        setLocalSafeMode(backendValue);
+      }
     }
   }, [isAgent, libraryAgent]);
 
-  const currentHITLSafeMode = isAgent
-    ? (graph.settings?.human_in_the_loop_safe_mode ?? true)
-    : localHITLSafeMode;
+  const currentSafeMode = isAgent
+    ? graph.settings?.human_in_the_loop_safe_mode
+    : localSafeMode;
 
-  const currentSensitiveActionSafeMode = isAgent
-    ? (graph.settings?.sensitive_action_safe_mode ?? false)
-    : localSensitiveActionSafeMode;
+  const isStateUndetermined = isAgent
+    ? graph.settings?.human_in_the_loop_safe_mode == null
+    : isLoading || localSafeMode === null;
 
-  const isHITLStateUndetermined = isAgent
-    ? false
-    : isLoading || !isLocalStateLoaded;
-
-  const handleHITLToggle = useCallback(async () => {
-    const newSafeMode = !currentHITLSafeMode;
+  const handleToggle = useCallback(async () => {
+    const newSafeMode = !currentSafeMode;
 
     try {
       await updateGraphSettings({
@@ -101,7 +85,7 @@ export function useAgentSafeMode(graph: GraphModel | LibraryAgent | Graph) {
       });
 
       if (!isAgent) {
-        setLocalHITLSafeMode(newSafeMode);
+        setLocalSafeMode(newSafeMode);
       }
 
       if (isAgent) {
@@ -117,62 +101,37 @@ export function useAgentSafeMode(graph: GraphModel | LibraryAgent | Graph) {
       queryClient.invalidateQueries({ queryKey: ["v2", "executions"] });
 
       toast({
-        title: `HITL safe mode ${newSafeMode ? "enabled" : "disabled"}`,
+        title: `Safe mode ${newSafeMode ? "enabled" : "disabled"}`,
         description: newSafeMode
           ? "Human-in-the-loop blocks will require manual review"
           : "Human-in-the-loop blocks will proceed automatically",
         duration: 2000,
       });
     } catch (error) {
-      handleToggleError(error, isAgent, toast);
-    }
-  }, [
-    currentHITLSafeMode,
-    graphId,
-    isAgent,
-    graph.id,
-    updateGraphSettings,
-    queryClient,
-    toast,
-  ]);
+      const isNotFoundError =
+        error instanceof Error &&
+        (error.message.includes("404") || error.message.includes("not found"));
 
-  const handleSensitiveActionToggle = useCallback(async () => {
-    const newSafeMode = !currentSensitiveActionSafeMode;
-
-    try {
-      await updateGraphSettings({
-        graphId,
-        data: { sensitive_action_safe_mode: newSafeMode },
-      });
-
-      if (!isAgent) {
-        setLocalSensitiveActionSafeMode(newSafeMode);
-      }
-
-      if (isAgent) {
-        queryClient.invalidateQueries({
-          queryKey: getGetV2GetLibraryAgentQueryOptions(graph.id.toString())
-            .queryKey,
+      if (!isAgent && isNotFoundError) {
+        toast({
+          title: "Safe mode not available",
+          description:
+            "To configure safe mode, please save this graph to your library first.",
+          variant: "destructive",
+        });
+      } else {
+        toast({
+          title: "Failed to update safe mode",
+          description:
+            error instanceof Error
+              ? error.message
+              : "An unexpected error occurred.",
+          variant: "destructive",
         });
       }
-
-      queryClient.invalidateQueries({
-        queryKey: ["v1", "graphs", graphId, "executions"],
-      });
-      queryClient.invalidateQueries({ queryKey: ["v2", "executions"] });
-
-      toast({
-        title: `Sensitive action safe mode ${newSafeMode ? "enabled" : "disabled"}`,
-        description: newSafeMode
-          ? "Sensitive action blocks will require manual review"
-          : "Sensitive action blocks will proceed automatically",
-        duration: 2000,
-      });
-    } catch (error) {
-      handleToggleError(error, isAgent, toast);
     }
   }, [
-    currentSensitiveActionSafeMode,
+    currentSafeMode,
     graphId,
     isAgent,
     graph.id,
@@ -182,53 +141,11 @@ export function useAgentSafeMode(graph: GraphModel | LibraryAgent | Graph) {
   ]);
 
   return {
-    // HITL safe mode
-    currentHITLSafeMode,
-    showHITLToggle,
-    isHITLStateUndetermined,
-    handleHITLToggle,
-
-    // Sensitive action safe mode
-    currentSensitiveActionSafeMode,
-    showSensitiveActionToggle,
-    handleSensitiveActionToggle,
-
-    // General
+    currentSafeMode,
     isPending,
     shouldShowToggle,
-
-    // Backwards compatibility
-    currentSafeMode: currentHITLSafeMode,
-    isStateUndetermined: isHITLStateUndetermined,
-    handleToggle: handleHITLToggle,
-    hasHITLBlocks: showHITLToggle,
+    isStateUndetermined,
+    handleToggle,
+    hasHITLBlocks: shouldShowToggle,
   };
 }
-
-function handleToggleError(
-  error: unknown,
-  isAgent: boolean,
-  toast: ReturnType<typeof useToast>["toast"],
-) {
-  const isNotFoundError =
-    error instanceof Error &&
-    (error.message.includes("404") || error.message.includes("not found"));
-
-  if (!isAgent && isNotFoundError) {
-    toast({
-      title: "Safe mode not available",
-      description:
-        "To configure safe mode, please save this graph to your library first.",
-      variant: "destructive",
-    });
-  } else {
-    toast({
-      title: "Failed to update safe mode",
-      description:
-        error instanceof Error
-          ? error.message
-          : "An unexpected error occurred.",
-      variant: "destructive",
-    });
-  }
-}

autogpt_platform/frontend/src/lib/dexie/draft-utils.ts

@@ -5,7 +5,7 @@ import isEqual from "lodash/isEqual";
 export function cleanNode(node: CustomNode) {
   return {
     id: node.id,
-    // Note: position is intentionally excluded to prevent draft saves when dragging nodes
+    position: node.position,
     data: {
       hardcodedValues: node.data.hardcodedValues,
       title: node.data.title,

autogpt_platform/frontend/src/lib/timezone-utils.ts

@@ -106,14 +106,9 @@ export function getTimezoneDisplayName(timezone: string): string {
     const parts = timezone.split("/");
     const city = parts[parts.length - 1].replace(/_/g, " ");
     const abbr = getTimezoneAbbreviation(timezone);
-    if (abbr && abbr !== timezone) {
-      return `${city} (${abbr})`;
-    }
-    // If abbreviation is same as timezone or not found, show timezone with underscores replaced
-    const timezoneDisplay = timezone.replace(/_/g, " ");
-    return `${city} (${timezoneDisplay})`;
+    return abbr ? `${city} (${abbr})` : city;
   } catch {
-    return timezone.replace(/_/g, " ");
+    return timezone;
   }
 }
 

autogpt_platform/frontend/src/mocks/index.ts

@@ -1,13 +0,0 @@
-// We are not using this for tests because Vitest runs our tests in a Node.js environment.
-// However, we can use it for development purposes to test our UI in the browser with fake data.
-export async function initMocks() {
-  if (typeof window === "undefined") {
-    const { server } = await import("./mock-server");
-    server.listen({ onUnhandledRequest: "bypass" });
-    console.log("[MSW] Server mock initialized");
-  } else {
-    const { worker } = await import("./mock-browser");
-    await worker.start({ onUnhandledRequest: "bypass" });
-    console.log("[MSW] Browser mock initialized");
-  }
-}

autogpt_platform/frontend/src/mocks/mock-browser.ts

@@ -1,4 +0,0 @@
-import { setupWorker } from "msw/browser";
-import { mockHandlers } from "./mock-handlers";
-
-export const worker = setupWorker(...mockHandlers);

autogpt_platform/frontend/src/mocks/mock-handlers.ts

@@ -1,48 +0,0 @@
-import { getAdminMock } from "@/app/api/__generated__/endpoints/admin/admin.msw";
-import { getAnalyticsMock } from "@/app/api/__generated__/endpoints/analytics/analytics.msw";
-import { getApiKeysMock } from "@/app/api/__generated__/endpoints/api-keys/api-keys.msw";
-import { getAuthMock } from "@/app/api/__generated__/endpoints/auth/auth.msw";
-import { getBlocksMock } from "@/app/api/__generated__/endpoints/blocks/blocks.msw";
-import { getChatMock } from "@/app/api/__generated__/endpoints/chat/chat.msw";
-import { getCreditsMock } from "@/app/api/__generated__/endpoints/credits/credits.msw";
-import { getDefaultMock } from "@/app/api/__generated__/endpoints/default/default.msw";
-import { getEmailMock } from "@/app/api/__generated__/endpoints/email/email.msw";
-import { getExecutionsMock } from "@/app/api/__generated__/endpoints/executions/executions.msw";
-import { getFilesMock } from "@/app/api/__generated__/endpoints/files/files.msw";
-import { getGraphsMock } from "@/app/api/__generated__/endpoints/graphs/graphs.msw";
-import { getHealthMock } from "@/app/api/__generated__/endpoints/health/health.msw";
-import { getIntegrationsMock } from "@/app/api/__generated__/endpoints/integrations/integrations.msw";
-import { getLibraryMock } from "@/app/api/__generated__/endpoints/library/library.msw";
-import { getMetricsMock } from "@/app/api/__generated__/endpoints/metrics/metrics.msw";
-import { getOauthMock } from "@/app/api/__generated__/endpoints/oauth/oauth.msw";
-import { getOnboardingMock } from "@/app/api/__generated__/endpoints/onboarding/onboarding.msw";
-import { getOttoMock } from "@/app/api/__generated__/endpoints/otto/otto.msw";
-import { getPresetsMock } from "@/app/api/__generated__/endpoints/presets/presets.msw";
-import { getSchedulesMock } from "@/app/api/__generated__/endpoints/schedules/schedules.msw";
-import { getStoreMock } from "@/app/api/__generated__/endpoints/store/store.msw";
-
-// Pass hard-coded data to individual handler functions to override faker-generated data.
-export const mockHandlers = [
-  ...getAdminMock(),
-  ...getAnalyticsMock(),
-  ...getApiKeysMock(),
-  ...getAuthMock(),
-  ...getBlocksMock(),
-  ...getChatMock(),
-  ...getCreditsMock(),
-  ...getDefaultMock(),
-  ...getEmailMock(),
-  ...getExecutionsMock(),
-  ...getFilesMock(),
-  ...getGraphsMock(),
-  ...getHealthMock(),
-  ...getIntegrationsMock(),
-  ...getLibraryMock(),
-  ...getMetricsMock(),
-  ...getOauthMock(),
-  ...getOnboardingMock(),
-  ...getOttoMock(),
-  ...getPresetsMock(),
-  ...getSchedulesMock(),
-  ...getStoreMock(),
-];

autogpt_platform/frontend/src/mocks/mock-server.ts

@@ -1,4 +0,0 @@
-import { setupServer } from "msw/node";
-import { mockHandlers } from "./mock-handlers";
-
-export const server = setupServer(...mockHandlers);