Merge branch 'main' into release/v1.0.0

(cherry picked from commit d46e20fa09bcd2f5916282f5553ddeb7183bd92c)

.github/workflows/build-uv-cache.yml

@@ -0,0 +1,46 @@
+name: Build uv cache
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - "uv.lock"
+      - "pyproject.toml"
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+jobs:
+  build-cache:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          version: "0.8.4"
+          python-version: ${{ matrix.python-version }}
+          enable-cache: false
+
+      - name: Install dependencies and populate cache
+        run: |
+          echo "Building global UV cache for Python ${{ matrix.python-version }}..."
+          uv sync --all-groups --all-extras --no-install-project
+          echo "Cache populated successfully"
+
+      - name: Save uv caches
+        uses: actions/cache/save@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}

.github/workflows/codeql.yml

@@ -0,0 +1,102 @@
+# For most projects, this workflow file will not need changing; you simply need
+# to commit it to your repository.
+#
+# You may wish to alter this file to override the set of languages analyzed,
+# or to provide custom queries or build logic.
+#
+# ******** NOTE ********
+# We have attempted to detect the languages in your repository. Please check
+# the `language` matrix defined below to confirm you have the correct set of
+# supported CodeQL languages.
+#
+name: "CodeQL Advanced"
+
+on:
+  push:
+    branches: [ "main" ]
+    paths-ignore:
+      - "lib/crewai/src/crewai/cli/templates/**"
+  pull_request:
+    branches: [ "main" ]
+    paths-ignore:
+      - "lib/crewai/src/crewai/cli/templates/**"
+
+jobs:
+  analyze:
+    name: Analyze (${{ matrix.language }})
+    # Runner size impacts CodeQL analysis time. To learn more, please see:
+    #   - https://gh.io/recommended-hardware-resources-for-running-codeql
+    #   - https://gh.io/supported-runners-and-hardware-resources
+    #   - https://gh.io/using-larger-runners (GitHub.com only)
+    # Consider using larger runners or machines with greater resources for possible analysis time improvements.
+    runs-on: ${{ (matrix.language == 'swift' && 'macos-latest') || 'ubuntu-latest' }}
+    permissions:
+      # required for all workflows
+      security-events: write
+
+      # required to fetch internal or private CodeQL packs
+      packages: read
+
+      # only required for workflows in private repositories
+      actions: read
+      contents: read
+
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+        - language: actions
+          build-mode: none
+        - language: python
+          build-mode: none
+        # CodeQL supports the following values keywords for 'language': 'actions', 'c-cpp', 'csharp', 'go', 'java-kotlin', 'javascript-typescript', 'python', 'ruby', 'rust', 'swift'
+        # Use `c-cpp` to analyze code written in C, C++ or both
+        # Use 'java-kotlin' to analyze code written in Java, Kotlin or both
+        # Use 'javascript-typescript' to analyze code written in JavaScript, TypeScript or both
+        # To learn more about changing the languages that are analyzed or customizing the build mode for your analysis,
+        # see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/customizing-your-advanced-setup-for-code-scanning.
+        # If you are analyzing a compiled language, you can modify the 'build-mode' for that language to customize how
+        # your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v4
+
+    # Add any setup steps before running the `github/codeql-action/init` action.
+    # This includes steps like installing compilers or runtimes (`actions/setup-node`
+    # or others). This is typically only required for manual builds.
+    # - name: Setup runtime (example)
+    #   uses: actions/setup-example@v1
+
+    # Initializes the CodeQL tools for scanning.
+    - name: Initialize CodeQL
+      uses: github/codeql-action/init@v3
+      with:
+        languages: ${{ matrix.language }}
+        build-mode: ${{ matrix.build-mode }}
+        # If you wish to specify custom queries, you can do so here or in a config file.
+        # By default, queries listed here will override any specified in a config file.
+        # Prefix the list here with "+" to use these queries and those in the config file.
+
+        # For more details on CodeQL's query packs, refer to: https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
+        # queries: security-extended,security-and-quality
+
+    # If the analyze step fails for one of the languages you are analyzing with
+    # "We were unable to automatically build your code", modify the matrix above
+    # to set the build mode to "manual" for that language. Then modify this step
+    # to build your code.
+    # ℹ️ Command-line programs to run using the OS shell.
+    # 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
+    - if: matrix.build-mode == 'manual'
+      shell: bash
+      run: |
+        echo 'If you are using a "manual" build mode for one or more of the' \
+          'languages you are analyzing, replace this with the commands to build' \
+          'your code, for example:'
+        echo '  make bootstrap'
+        echo '  make release'
+        exit 1
+
+    - name: Perform CodeQL Analysis
+      uses: github/codeql-action/analyze@v3
+      with:
+        category: "/language:${{matrix.language}}"

.github/workflows/linter.yml

@@ -2,6 +2,9 @@ name: Lint
 
 on: [pull_request]
 
+permissions:
+  contents: read
+
 jobs:
   lint:
     runs-on: ubuntu-latest
@@ -15,8 +18,27 @@ jobs:
       - name: Fetch Target Branch
         run: git fetch origin $TARGET_BRANCH --depth=1
 
-      - name: Install Ruff
-        run: pip install ruff
+      - name: Restore global uv cache
+        id: cache-restore
+        uses: actions/cache/restore@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py3.11-${{ hashFiles('uv.lock') }}
+          restore-keys: |
+            uv-main-py3.11-
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          version: "0.8.4"
+          python-version: "3.11"
+          enable-cache: false
+
+      - name: Install dependencies
+        run: uv sync --all-groups --all-extras --no-install-project
 
       - name: Get Changed Python Files
         id: changed-files
@@ -30,7 +52,17 @@ jobs:
       - name: Run Ruff on Changed Files
         if: ${{ steps.changed-files.outputs.files != '' }}
         run: |
-          echo "${{ steps.changed-files.outputs.files }}" \
-            | tr ' ' '\n' \
-            | grep -v 'src/crewai/cli/templates/' \
-            | xargs -I{} ruff check "{}"
+         echo "${{ steps.changed-files.outputs.files }}" \
+           | tr ' ' '\n' \
+           | grep -v 'src/crewai/cli/templates/' \
+           | xargs -I{} uv run ruff check "{}"
+
+      - name: Save uv caches
+        if: steps.cache-restore.outputs.cache-hit != 'true'
+        uses: actions/cache/save@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py3.11-${{ hashFiles('uv.lock') }}

.github/workflows/publish.yml

@@ -0,0 +1,71 @@
+name: Publish to PyPI
+
+on:
+  release:
+    types: [ published ]
+  workflow_dispatch:
+
+jobs:
+  build:
+    if: github.event.release.prerelease == true
+    name: Build packages
+    runs-on: ubuntu-latest
+    permissions:
+        contents: read
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+
+      - name: Build packages
+        run: |
+          uv build --all-packages
+          rm dist/.gitignore
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: dist
+          path: dist/
+
+  publish:
+    if: github.event.release.prerelease == true
+    name: Publish to PyPI
+    needs: build
+    runs-on: ubuntu-latest
+    environment:
+      name: pypi
+      url: https://pypi.org/p/crewai
+    permissions:
+      id-token: write
+      contents: read
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          version: "0.8.4"
+          python-version: "3.12"
+          enable-cache: false
+
+      - name: Download artifacts
+        uses: actions/download-artifact@v4
+        with:
+          name: dist
+          path: dist
+
+      - name: Publish to PyPI
+        env:
+          UV_PUBLISH_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
+        run: |
+          for package in dist/*; do
+            echo "Publishing $package"
+            uv publish "$package"
+          done

.github/workflows/security-checker.yml

@@ -1,23 +0,0 @@
-name: Security Checker
-
-on: [pull_request]
-
-jobs:
-  security-check:
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: "3.11.9"
-
-      - name: Install dependencies
-        run: pip install bandit
-
-      - name: Run Bandit
-        run: bandit -c pyproject.toml -r src/ -ll
-

.github/workflows/tests.yml

@@ -3,11 +3,19 @@ name: Run Tests
 on: [pull_request]
 
 permissions:
-  contents: write
+  contents: read
 
 env:
   OPENAI_API_KEY: fake-api-key
   PYTHONUNBUFFERED: 1
+  BRAVE_API_KEY: fake-brave-key
+  SNOWFLAKE_USER: fake-snowflake-user
+  SNOWFLAKE_PASSWORD: fake-snowflake-password
+  SNOWFLAKE_ACCOUNT: fake-snowflake-account
+  SNOWFLAKE_WAREHOUSE: fake-snowflake-warehouse
+  SNOWFLAKE_DATABASE: fake-snowflake-database
+  SNOWFLAKE_SCHEMA: fake-snowflake-schema
+  EMBEDCHAIN_DB_URI: sqlite:///test.db
 
 jobs:
   tests:
@@ -22,24 +30,73 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          fetch-depth: 0  # Fetch all history for proper diff
+
+      - name: Restore global uv cache
+        id: cache-restore
+        uses: actions/cache/restore@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
+          restore-keys: |
+            uv-main-py${{ matrix.python-version }}-
 
       - name: Install uv
-        uses: astral-sh/setup-uv@v3
+        uses: astral-sh/setup-uv@v6
         with:
-          enable-cache: true
-          cache-dependency-glob: |
-            **/pyproject.toml
-            **/uv.lock
-
-      - name: Set up Python ${{ matrix.python-version }}
-        run: uv python install ${{ matrix.python-version }}
+          version: "0.8.4"
+          python-version: ${{ matrix.python-version }}
+          enable-cache: false
 
       - name: Install the project
-        run: uv sync --dev --all-extras
+        run: uv sync --all-groups --all-extras
+
+      - name: Restore test durations
+        uses: actions/cache/restore@v4
+        with:
+          path: .test_durations_py*
+          key: test-durations-py${{ matrix.python-version }}
 
       - name: Run tests (group ${{ matrix.group }} of 8)
         run: |
-          uv run pytest \
+          PYTHON_VERSION_SAFE=$(echo "${{ matrix.python-version }}" | tr '.' '_')
+          DURATION_FILE="../../.test_durations_py${PYTHON_VERSION_SAFE}"
+
+          # Temporarily always skip cached durations to fix test splitting
+          # When durations don't match, pytest-split runs duplicate tests instead of splitting
+          echo "Using even test splitting (duration cache disabled until fix merged)"
+          DURATIONS_ARG=""
+
+          # Original logic (disabled temporarily):
+          # if [ ! -f "$DURATION_FILE" ]; then
+          #   echo "No cached durations found, tests will be split evenly"
+          #   DURATIONS_ARG=""
+          # elif git diff origin/${{ github.base_ref }}...HEAD --name-only 2>/dev/null | grep -q "^tests/.*\.py$"; then
+          #   echo "Test files have changed, skipping cached durations to avoid mismatches"
+          #   DURATIONS_ARG=""
+          # else
+          #   echo "No test changes detected, using cached test durations for optimal splitting"
+          #   DURATIONS_ARG="--durations-path=${DURATION_FILE}"
+          # fi
+
+          cd lib/crewai && uv run pytest \
+            --block-network \
+            --timeout=30 \
+            -vv \
+            --splits 8 \
+            --group ${{ matrix.group }} \
+            $DURATIONS_ARG \
+            --durations=10 \
+            -n auto \
+            --maxfail=3
+
+      - name: Run tool tests (group ${{ matrix.group }} of 8)
+        run: |
+          cd lib/crewai-tools && uv run pytest \
             --block-network \
             --timeout=30 \
             -vv \
@@ -48,3 +105,14 @@ jobs:
             --durations=10 \
             -n auto \
             --maxfail=3
+
+
+      - name: Save uv caches
+        if: steps.cache-restore.outputs.cache-hit != 'true'
+        uses: actions/cache/save@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}

.github/workflows/type-checker.yml

@@ -3,24 +3,99 @@ name: Run Type Checks
 on: [pull_request]
 
 permissions:
-  contents: write
+  contents: read
 
 jobs:
-  type-checker:
+  type-checker-matrix:
+    name: type-checker (${{ matrix.python-version }})
     runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
 
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-
-      - name: Setup Python
-        uses: actions/setup-python@v5
         with:
-          python-version: "3.11.9"
+          fetch-depth: 0 # Fetch all history for proper diff
 
-      - name: Install Requirements
+      - name: Restore global uv cache
+        id: cache-restore
+        uses: actions/cache/restore@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
+          restore-keys: |
+            uv-main-py${{ matrix.python-version }}-
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          version: "0.8.4"
+          python-version: ${{ matrix.python-version }}
+          enable-cache: false
+
+      - name: Install dependencies
+        run: uv sync --all-groups --all-extras
+
+      - name: Get changed Python files
+        id: changed-files
         run: |
-          pip install mypy
+          # Get the list of changed Python files compared to the base branch
+          echo "Fetching changed files..."
+          git diff --name-only --diff-filter=ACMRT origin/${{ github.base_ref }}...HEAD -- '*.py' > changed_files.txt
 
-      - name: Run type checks
-        run: mypy src
+          # Filter for files in src/ directory only (excluding tests/)
+          grep -E "^src/" changed_files.txt > filtered_changed_files.txt || true
+
+          # Check if there are any changed files
+          if [ -s filtered_changed_files.txt ]; then
+            echo "Changed Python files in src/:"
+            cat filtered_changed_files.txt
+            echo "has_changes=true" >> $GITHUB_OUTPUT
+            # Convert newlines to spaces for mypy command
+            echo "files=$(cat filtered_changed_files.txt | tr '\n' ' ')" >> $GITHUB_OUTPUT
+          else
+            echo "No Python files changed in src/"
+            echo "has_changes=false" >> $GITHUB_OUTPUT
+          fi
+
+      - name: Run type checks on changed files
+        if: steps.changed-files.outputs.has_changes == 'true'
+        run: |
+          echo "Running mypy on changed files with Python ${{ matrix.python-version }}..."
+          uv run mypy ${{ steps.changed-files.outputs.files }}
+
+      - name: No files to check
+        if: steps.changed-files.outputs.has_changes == 'false'
+        run: echo "No Python files in src/ were modified - skipping type checks"
+
+      - name: Save uv caches
+        if: steps.cache-restore.outputs.cache-hit != 'true'
+        uses: actions/cache/save@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
+
+  # Summary job to provide single status for branch protection
+  type-checker:
+    name: type-checker
+    runs-on: ubuntu-latest
+    needs: type-checker-matrix
+    if: always()
+    steps:
+      - name: Check matrix results
+        run: |
+          if [ "${{ needs.type-checker-matrix.result }}" == "success" ] || [ "${{ needs.type-checker-matrix.result }}" == "skipped" ]; then
+            echo "✅ All type checks passed"
+          else
+            echo "❌ Type checks failed"
+            exit 1
+          fi

.github/workflows/update-test-durations.yml

@@ -0,0 +1,71 @@
+name: Update Test Durations
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - 'tests/**/*.py'
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+jobs:
+  update-durations:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.10', '3.11', '3.12', '3.13']
+    env:
+      OPENAI_API_KEY: fake-api-key
+      PYTHONUNBUFFERED: 1
+    
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Restore global uv cache
+        id: cache-restore
+        uses: actions/cache/restore@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
+          restore-keys: |
+            uv-main-py${{ matrix.python-version }}-
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          version: "0.8.4"
+          python-version: ${{ matrix.python-version }}
+          enable-cache: false
+
+      - name: Install the project
+        run: uv sync --all-groups --all-extras
+
+      - name: Run all tests and store durations
+        run: |
+          PYTHON_VERSION_SAFE=$(echo "${{ matrix.python-version }}" | tr '.' '_')
+          uv run pytest --store-durations --durations-path=.test_durations_py${PYTHON_VERSION_SAFE} -n auto
+        continue-on-error: true
+
+      - name: Save durations to cache
+        if: always()
+        uses: actions/cache/save@v4
+        with:
+          path: .test_durations_py*
+          key: test-durations-py${{ matrix.python-version }}
+
+      - name: Save uv caches
+        if: steps.cache-restore.outputs.cache-hit != 'true'
+        uses: actions/cache/save@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}

.gitignore

@@ -2,7 +2,6 @@
 .pytest_cache
 __pycache__
 dist/
-lib/
 .env
 assets/*
 .idea

.pre-commit-config.yaml

@@ -1,7 +1,21 @@
 repos:
-  - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.2
+  - repo: local
     hooks:
       - id: ruff
-        args: ["--fix"]
+        name: ruff
+        entry: uv run ruff check
+        language: system
+        types: [python]
+        exclude: ^lib/crewai/
       - id: ruff-format
+        name: ruff-format
+        entry: uv run ruff format
+        language: system
+        types: [python]
+        exclude: ^lib/crewai/
+      - id: mypy
+        name: mypy
+        entry: uv run mypy
+        language: system
+        types: [python]
+        exclude: ^lib/crewai/

.ruff.toml

@@ -1,4 +0,0 @@
-exclude = [
-    "templates",
-    "__init__.py",
-]

README.md

@@ -418,10 +418,10 @@ Choose CrewAI to easily build powerful, adaptable, and production-ready AI autom
 
 You can test different real life examples of AI crews in the [CrewAI-examples repo](https://github.com/crewAIInc/crewAI-examples?tab=readme-ov-file):
 
-- [Landing Page Generator](https://github.com/crewAIInc/crewAI-examples/tree/main/landing_page_generator)
+- [Landing Page Generator](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/landing_page_generator)
 - [Having Human input on the execution](https://docs.crewai.com/how-to/Human-Input-on-Execution)
-- [Trip Planner](https://github.com/crewAIInc/crewAI-examples/tree/main/trip_planner)
-- [Stock Analysis](https://github.com/crewAIInc/crewAI-examples/tree/main/stock_analysis)
+- [Trip Planner](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/trip_planner)
+- [Stock Analysis](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/stock_analysis)
 
 ### Quick Tutorial
 
@@ -429,19 +429,19 @@ You can test different real life examples of AI crews in the [CrewAI-examples re
 
 ### Write Job Descriptions
 
-[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/job-posting) or watch a video below:
+[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/job-posting) or watch a video below:
 
 [![Jobs postings](https://img.youtube.com/vi/u98wEMz-9to/maxresdefault.jpg)](https://www.youtube.com/watch?v=u98wEMz-9to "Jobs postings")
 
 ### Trip Planner
 
-[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/trip_planner) or watch a video below:
+[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/trip_planner) or watch a video below:
 
 [![Trip Planner](https://img.youtube.com/vi/xis7rWp-hjs/maxresdefault.jpg)](https://www.youtube.com/watch?v=xis7rWp-hjs "Trip Planner")
 
 ### Stock Analysis
 
-[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/stock_analysis) or watch a video below:
+[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/stock_analysis) or watch a video below:
 
 [![Stock Analysis](https://img.youtube.com/vi/e0Uj4yWdaAg/maxresdefault.jpg)](https://www.youtube.com/watch?v=e0Uj4yWdaAg "Stock Analysis")
 

docs/docs.json

@@ -1,6 +1,6 @@
 {
   "$schema": "https://mintlify.com/docs.json",
-  "theme": "mint",
+  "theme": "aspen",
   "name": "CrewAI",
   "colors": {
     "primary": "#EB6658",
@@ -28,20 +28,31 @@
               "icon": "discourse"
             },
             {
-              "anchor": "Crew GPT",
-              "href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
-              "icon": "robot"
+              "anchor": "Blog",
+              "href": "https://blog.crewai.com",
+              "icon": "newspaper"
             },
             {
-              "anchor": "Releases",
-              "href": "https://github.com/crewAIInc/crewAI/releases",
-              "icon": "tag"
+              "anchor": "CrewGPT",
+              "href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
+              "icon": "robot"
             }
           ]
         },
         "tabs": [
+          {
+            "tab": "Home",
+            "icon": "house",
+            "groups": [
+              {
+                "group": "Welcome",
+                "pages": ["index"]
+              }
+            ]
+          },
           {
             "tab": "Documentation",
+            "icon": "book-open",
             "groups": [
               {
                 "group": "Get Started",
@@ -52,18 +63,22 @@
                 "pages": [
                   {
                     "group": "Strategy",
+                    "icon": "compass",
                     "pages": ["en/guides/concepts/evaluating-use-cases"]
                   },
                   {
                     "group": "Agents",
+                    "icon": "user",
                     "pages": ["en/guides/agents/crafting-effective-agents"]
                   },
                   {
                     "group": "Crews",
+                    "icon": "users",
                     "pages": ["en/guides/crews/first-crew"]
                   },
                   {
                     "group": "Flows",
+                    "icon": "code-branch",
                     "pages": [
                       "en/guides/flows/first-flow",
                       "en/guides/flows/mastering-flow-state"
@@ -71,6 +86,7 @@
                   },
                   {
                     "group": "Advanced",
+                    "icon": "gear",
                     "pages": [
                       "en/guides/advanced/customizing-prompts",
                       "en/guides/advanced/fingerprinting"
@@ -116,6 +132,7 @@
                   "en/tools/overview",
                   {
                     "group": "File & Document",
+                    "icon": "folder-open",
                     "pages": [
                       "en/tools/file-document/overview",
                       "en/tools/file-document/filereadtool",
@@ -135,6 +152,7 @@
                   },
                   {
                     "group": "Web Scraping & Browsing",
+                    "icon": "globe",
                     "pages": [
                       "en/tools/web-scraping/overview",
                       "en/tools/web-scraping/scrapewebsitetool",
@@ -154,6 +172,7 @@
                   },
                   {
                     "group": "Search & Research",
+                    "icon": "magnifying-glass",
                     "pages": [
                       "en/tools/search-research/overview",
                       "en/tools/search-research/serperdevtool",
@@ -175,6 +194,7 @@
                   },
                   {
                     "group": "Database & Data",
+                    "icon": "database",
                     "pages": [
                       "en/tools/database-data/overview",
                       "en/tools/database-data/mysqltool",
@@ -189,6 +209,7 @@
                   },
                   {
                     "group": "AI & Machine Learning",
+                    "icon": "brain",
                     "pages": [
                       "en/tools/ai-ml/overview",
                       "en/tools/ai-ml/dalletool",
@@ -202,16 +223,26 @@
                   },
                   {
                     "group": "Cloud & Storage",
+                    "icon": "cloud",
                     "pages": [
                       "en/tools/cloud-storage/overview",
                       "en/tools/cloud-storage/s3readertool",
                       "en/tools/cloud-storage/s3writertool",
-                      "en/tools/cloud-storage/bedrockinvokeagenttool",
                       "en/tools/cloud-storage/bedrockkbretriever"
                     ]
                   },
                   {
-                    "group": "Automation & Integration",
+                    "group": "Integrations",
+                    "icon": "plug",
+                    "pages": [
+                      "en/tools/integration/overview",
+                      "en/tools/integration/bedrockinvokeagenttool",
+                      "en/tools/integration/crewaiautomationtool"
+                    ]
+                  },
+                  {
+                    "group": "Automation",
+                    "icon": "bolt",
                     "pages": [
                       "en/tools/automation/overview",
                       "en/tools/automation/apifyactorstool",
@@ -273,21 +304,34 @@
           },
           {
             "tab": "Enterprise",
+            "icon": "briefcase",
             "groups": [
               {
                 "group": "Getting Started",
                 "pages": ["en/enterprise/introduction"]
               },
               {
-                "group": "Features",
+                "group": "Build",
+                "pages": [
+                  "en/enterprise/features/automations",
+                  "en/enterprise/features/crew-studio",
+                  "en/enterprise/features/marketplace",
+                  "en/enterprise/features/agent-repositories",
+                  "en/enterprise/features/tools-and-integrations"
+                ]
+              },
+              {
+                "group": "Operate",
                 "pages": [
-                  "en/enterprise/features/rbac",
-                  "en/enterprise/features/tool-repository",
-                  "en/enterprise/features/webhook-streaming",
                   "en/enterprise/features/traces",
-                  "en/enterprise/features/hallucination-guardrail",
-                  "en/enterprise/features/integrations",
-                  "en/enterprise/features/agent-repositories"
+                  "en/enterprise/features/webhook-streaming",
+                  "en/enterprise/features/hallucination-guardrail"
+                ]
+              },
+              {
+                "group": "Manage",
+                "pages": [
+                  "en/enterprise/features/rbac"
                 ]
               },
               {
@@ -311,6 +355,22 @@
                   "en/enterprise/integrations/zendesk"
                 ]
               },
+              {
+                "group": "Triggers",
+                "pages": [
+                  "en/enterprise/guides/automation-triggers",
+                  "en/enterprise/guides/gmail-trigger",
+                  "en/enterprise/guides/google-calendar-trigger",
+                  "en/enterprise/guides/google-drive-trigger",
+                  "en/enterprise/guides/outlook-trigger",
+                  "en/enterprise/guides/onedrive-trigger",
+                  "en/enterprise/guides/microsoft-teams-trigger",
+                  "en/enterprise/guides/slack-trigger",
+                  "en/enterprise/guides/hubspot-trigger",
+                  "en/enterprise/guides/salesforce-trigger",
+                  "en/enterprise/guides/zapier-trigger"
+                ]
+              },
               {
                 "group": "How-To Guides",
                 "pages": [
@@ -320,14 +380,11 @@
                   "en/enterprise/guides/update-crew",
                   "en/enterprise/guides/enable-crew-studio",
                   "en/enterprise/guides/azure-openai-setup",
-                  "en/enterprise/guides/hubspot-trigger",
+                  "en/enterprise/guides/tool-repository",
                   "en/enterprise/guides/react-component-export",
-                  "en/enterprise/guides/salesforce-trigger",
-                  "en/enterprise/guides/slack-trigger",
                   "en/enterprise/guides/team-management",
-                  "en/enterprise/guides/webhook-automation",
                   "en/enterprise/guides/human-in-the-loop",
-                  "en/enterprise/guides/zapier-trigger"
+                  "en/enterprise/guides/webhook-automation"
                 ]
               },
               {
@@ -338,25 +395,38 @@
           },
           {
             "tab": "API Reference",
+            "icon": "magnifying-glass",
             "groups": [
               {
                 "group": "Getting Started",
-                "pages": ["en/api-reference/introduction"]
-              },
-              {
-                "group": "Endpoints",
-                "openapi": "https://raw.githubusercontent.com/crewAIInc/crewAI/main/docs/enterprise-api.en.yaml"
+                "pages": [
+                  "en/api-reference/introduction",
+                  "en/api-reference/inputs",
+                  "en/api-reference/kickoff",
+                  "en/api-reference/status"
+                ]
               }
             ]
           },
           {
             "tab": "Examples",
+            "icon": "code",
             "groups": [
               {
                 "group": "Examples",
                 "pages": ["en/examples/example", "en/examples/cookbooks"]
               }
             ]
+          },
+          {
+            "tab": "Changelog",
+            "icon": "clock",
+            "groups": [
+              {
+                "group": "Release Notes",
+                "pages": ["en/changelog"]
+              }
+            ]
           }
         ]
       },
@@ -375,20 +445,31 @@
               "icon": "discourse"
             },
             {
-              "anchor": "Crew GPT",
-              "href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
-              "icon": "robot"
+              "anchor": "Blog",
+              "href": "https://blog.crewai.com",
+              "icon": "newspaper"
             },
             {
-              "anchor": "Lançamentos",
-              "href": "https://github.com/crewAIInc/crewAI/releases",
-              "icon": "tag"
+              "anchor": "CrewGPT",
+              "href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
+              "icon": "robot"
             }
           ]
         },
         "tabs": [
+          {
+            "tab": "Início",
+            "icon": "house",
+            "groups": [
+              {
+                "group": "Bem-vindo",
+                "pages": ["pt-BR/index"]
+              }
+            ]
+          },
           {
             "tab": "Documentação",
+            "icon": "book-open",
             "groups": [
               {
                 "group": "Começando",
@@ -403,18 +484,22 @@
                 "pages": [
                   {
                     "group": "Estratégia",
+                    "icon": "compass",
                     "pages": ["pt-BR/guides/concepts/evaluating-use-cases"]
                   },
                   {
                     "group": "Agentes",
+                    "icon": "user",
                     "pages": ["pt-BR/guides/agents/crafting-effective-agents"]
                   },
                   {
                     "group": "Crews",
+                    "icon": "users",
                     "pages": ["pt-BR/guides/crews/first-crew"]
                   },
                   {
                     "group": "Flows",
+                    "icon": "code-branch",
                     "pages": [
                       "pt-BR/guides/flows/first-flow",
                       "pt-BR/guides/flows/mastering-flow-state"
@@ -422,6 +507,7 @@
                   },
                   {
                     "group": "Avançado",
+                    "icon": "gear",
                     "pages": [
                       "pt-BR/guides/advanced/customizing-prompts",
                       "pt-BR/guides/advanced/fingerprinting"
@@ -467,6 +553,7 @@
                   "pt-BR/tools/overview",
                   {
                     "group": "Arquivo & Documento",
+                    "icon": "folder-open",
                     "pages": [
                       "pt-BR/tools/file-document/overview",
                       "pt-BR/tools/file-document/filereadtool",
@@ -484,6 +571,7 @@
                   },
                   {
                     "group": "Web Scraping & Navegação",
+                    "icon": "globe",
                     "pages": [
                       "pt-BR/tools/web-scraping/overview",
                       "pt-BR/tools/web-scraping/scrapewebsitetool",
@@ -502,6 +590,7 @@
                   },
                   {
                     "group": "Pesquisa",
+                    "icon": "magnifying-glass",
                     "pages": [
                       "pt-BR/tools/search-research/overview",
                       "pt-BR/tools/search-research/serperdevtool",
@@ -517,6 +606,7 @@
                   },
                   {
                     "group": "Dados",
+                    "icon": "database",
                     "pages": [
                       "pt-BR/tools/database-data/overview",
                       "pt-BR/tools/database-data/mysqltool",
@@ -529,6 +619,7 @@
                   },
                   {
                     "group": "IA & Machine Learning",
+                    "icon": "brain",
                     "pages": [
                       "pt-BR/tools/ai-ml/overview",
                       "pt-BR/tools/ai-ml/dalletool",
@@ -542,16 +633,26 @@
                   },
                   {
                     "group": "Cloud & Armazenamento",
+                    "icon": "cloud",
                     "pages": [
                       "pt-BR/tools/cloud-storage/overview",
                       "pt-BR/tools/cloud-storage/s3readertool",
                       "pt-BR/tools/cloud-storage/s3writertool",
-                      "pt-BR/tools/cloud-storage/bedrockinvokeagenttool",
                       "pt-BR/tools/cloud-storage/bedrockkbretriever"
                     ]
                   },
                   {
-                    "group": "Automação & Integração",
+                    "group": "Integrations",
+                    "icon": "plug",
+                    "pages": [
+                      "pt-BR/tools/integration/overview",
+                      "pt-BR/tools/integration/bedrockinvokeagenttool",
+                      "pt-BR/tools/integration/crewaiautomationtool"
+                    ]
+                  },
+                  {
+                    "group": "Automação",
+                    "icon": "bolt",
                     "pages": [
                       "pt-BR/tools/automation/overview",
                       "pt-BR/tools/automation/apifyactorstool",
@@ -611,20 +712,34 @@
           },
           {
             "tab": "Enterprise",
+            "icon": "briefcase",
             "groups": [
               {
                 "group": "Começando",
                 "pages": ["pt-BR/enterprise/introduction"]
               },
               {
-                "group": "Funcionalidades",
+                "group": "Construir",
+                "pages": [
+                  "pt-BR/enterprise/features/automations",
+                  "pt-BR/enterprise/features/crew-studio",
+                  "pt-BR/enterprise/features/marketplace",
+                  "pt-BR/enterprise/features/agent-repositories",
+                  "pt-BR/enterprise/features/tools-and-integrations"
+                ]
+              },
+              {
+                "group": "Operar",
                 "pages": [
-                  "pt-BR/enterprise/features/rbac",
-                  "pt-BR/enterprise/features/tool-repository",
-                  "pt-BR/enterprise/features/webhook-streaming",
                   "pt-BR/enterprise/features/traces",
-                  "pt-BR/enterprise/features/hallucination-guardrail",
-                  "pt-BR/enterprise/features/integrations"
+                  "pt-BR/enterprise/features/webhook-streaming",
+                  "pt-BR/enterprise/features/hallucination-guardrail"
+                ]
+              },
+              {
+                "group": "Gerenciar",
+                "pages": [
+                  "pt-BR/enterprise/features/rbac"
                 ]
               },
               {
@@ -657,13 +772,20 @@
                   "pt-BR/enterprise/guides/update-crew",
                   "pt-BR/enterprise/guides/enable-crew-studio",
                   "pt-BR/enterprise/guides/azure-openai-setup",
-                  "pt-BR/enterprise/guides/hubspot-trigger",
+                  "pt-BR/enterprise/guides/tool-repository",
                   "pt-BR/enterprise/guides/react-component-export",
-                  "pt-BR/enterprise/guides/salesforce-trigger",
-                  "pt-BR/enterprise/guides/slack-trigger",
                   "pt-BR/enterprise/guides/team-management",
-                  "pt-BR/enterprise/guides/webhook-automation",
                   "pt-BR/enterprise/guides/human-in-the-loop",
+                  "pt-BR/enterprise/guides/webhook-automation"
+                ]
+              },
+              {
+                "group": "Triggers",
+                "pages": [
+                  "pt-BR/enterprise/guides/automation-triggers",
+                  "pt-BR/enterprise/guides/slack-trigger",
+                  "pt-BR/enterprise/guides/hubspot-trigger",
+                  "pt-BR/enterprise/guides/salesforce-trigger",
                   "pt-BR/enterprise/guides/zapier-trigger"
                 ]
               },
@@ -677,25 +799,38 @@
           },
           {
             "tab": "Referência da API",
+            "icon": "magnifying-glass",
             "groups": [
               {
                 "group": "Começando",
-                "pages": ["pt-BR/api-reference/introduction"]
-              },
-              {
-                "group": "Endpoints",
-                "openapi": "https://raw.githubusercontent.com/crewAIInc/crewAI/main/docs/enterprise-api.pt-BR.yaml"
+                "pages": [
+                  "pt-BR/api-reference/introduction",
+                  "pt-BR/api-reference/inputs",
+                  "pt-BR/api-reference/kickoff",
+                  "pt-BR/api-reference/status"
+                ]
               }
             ]
           },
           {
             "tab": "Exemplos",
+            "icon": "code",
             "groups": [
               {
                 "group": "Exemplos",
                 "pages": ["pt-BR/examples/example", "pt-BR/examples/cookbooks"]
               }
             ]
+          },
+          {
+            "tab": "Notas de Versão",
+            "icon": "clock",
+            "groups": [
+              {
+                "group": "Notas de Versão",
+                "pages": ["pt-BR/changelog"]
+              }
+            ]
           }
         ]
       },
@@ -709,47 +844,62 @@
               "icon": "globe"
             },
             {
-              "anchor": "법정",
+              "anchor": "포럼",
               "href": "https://community.crewai.com",
               "icon": "discourse"
             },
             {
-              "anchor": "Crew GPT",
-              "href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
-              "icon": "robot"
+              "anchor": "블로그",
+              "href": "https://blog.crewai.com",
+              "icon": "newspaper"
             },
             {
-              "anchor": "출시",
-              "href": "https://github.com/crewAIInc/crewAI/releases",
-              "icon": "tag"
+              "anchor": "CrewGPT",
+              "href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
+              "icon": "robot"
             }
           ]
         },
         "tabs": [
+          {
+            "tab": "홈",
+            "icon": "house",
+            "groups": [
+              {
+                "group": "환영합니다",
+                "pages": ["ko/index"]
+              }
+            ]
+          },
           {
             "tab": "기술 문서",
+            "icon": "book-open",
             "groups": [
               {
                 "group": "시작 안내",
                 "pages": ["ko/introduction", "ko/installation", "ko/quickstart"]
               },
               {
-                "group": "안내서",
+                "group": "가이드",
                 "pages": [
                   {
                     "group": "전략",
+                    "icon": "compass",
                     "pages": ["ko/guides/concepts/evaluating-use-cases"]
                   },
                   {
-                    "group": "Agents",
+                    "group": "에이전트 (Agents)",
+                    "icon": "user",
                     "pages": ["ko/guides/agents/crafting-effective-agents"]
                   },
                   {
-                    "group": "Crews",
+                    "group": "크루 (Crews)",
+                    "icon": "users",
                     "pages": ["ko/guides/crews/first-crew"]
                   },
                   {
-                    "group": "Flows",
+                    "group": "플로우 (Flows)",
+                    "icon": "code-branch",
                     "pages": [
                       "ko/guides/flows/first-flow",
                       "ko/guides/flows/mastering-flow-state"
@@ -757,6 +907,7 @@
                   },
                   {
                     "group": "고급",
+                    "icon": "gear",
                     "pages": [
                       "ko/guides/advanced/customizing-prompts",
                       "ko/guides/advanced/fingerprinting"
@@ -797,11 +948,12 @@
                 ]
               },
               {
-                "group": "도구",
+                "group": "도구 (Tools)",
                 "pages": [
                   "ko/tools/overview",
                   {
                     "group": "파일 & 문서",
+                    "icon": "folder-open",
                     "pages": [
                       "ko/tools/file-document/overview",
                       "ko/tools/file-document/filereadtool",
@@ -821,6 +973,7 @@
                   },
                   {
                     "group": "웹 스크래핑 & 브라우징",
+                    "icon": "globe",
                     "pages": [
                       "ko/tools/web-scraping/overview",
                       "ko/tools/web-scraping/scrapewebsitetool",
@@ -840,6 +993,7 @@
                   },
                   {
                     "group": "검색 및 연구",
+                    "icon": "magnifying-glass",
                     "pages": [
                       "ko/tools/search-research/overview",
                       "ko/tools/search-research/serperdevtool",
@@ -861,6 +1015,7 @@
                   },
                   {
                     "group": "데이터베이스 & 데이터",
+                    "icon": "database",
                     "pages": [
                       "ko/tools/database-data/overview",
                       "ko/tools/database-data/mysqltool",
@@ -875,6 +1030,7 @@
                   },
                   {
                     "group": "인공지능 & 머신러닝",
+                    "icon": "brain",
                     "pages": [
                       "ko/tools/ai-ml/overview",
                       "ko/tools/ai-ml/dalletool",
@@ -887,7 +1043,8 @@
                     ]
                   },
                   {
-                    "group": "클라우드 & 저장",
+                    "group": "클라우드 & 스토리지",
+                    "icon": "cloud",
                     "pages": [
                       "ko/tools/cloud-storage/overview",
                       "ko/tools/cloud-storage/s3readertool",
@@ -897,7 +1054,17 @@
                     ]
                   },
                   {
-                    "group": "자동화 & 통합",
+                    "group": "Integrations",
+                    "icon": "plug",
+                    "pages": [
+                      "ko/tools/integration/overview",
+                      "ko/tools/integration/bedrockinvokeagenttool",
+                      "ko/tools/integration/crewaiautomationtool"
+                    ]
+                  },
+                  {
+                    "group": "자동화",
+                    "icon": "bolt",
                     "pages": [
                       "ko/tools/automation/overview",
                       "ko/tools/automation/apifyactorstool",
@@ -909,7 +1076,7 @@
                 ]
               },
               {
-                "group": "오브저버빌리티",
+                "group": "Observability",
                 "pages": [
                   "ko/observability/overview",
                   "ko/observability/arize-phoenix",
@@ -927,7 +1094,7 @@
                 ]
               },
               {
-                "group": "익히다",
+                "group": "학습",
                 "pages": [
                   "ko/learn/overview",
                   "ko/learn/llm-selection-guide",
@@ -951,28 +1118,41 @@
                 ]
               },
               {
-                "group": "원격측정",
+                "group": "Telemetry",
                 "pages": ["ko/telemetry"]
               }
             ]
           },
           {
-            "tab": "기업",
+            "tab": "엔터프라이즈",
+            "icon": "briefcase",
             "groups": [
               {
                 "group": "시작 안내",
                 "pages": ["ko/enterprise/introduction"]
               },
               {
-                "group": "특징",
+                "group": "빌드",
+                "pages": [
+                  "ko/enterprise/features/automations",
+                  "ko/enterprise/features/crew-studio",
+                  "ko/enterprise/features/marketplace",
+                  "ko/enterprise/features/agent-repositories",
+                  "ko/enterprise/features/tools-and-integrations"
+                ]
+              },
+              {
+                "group": "운영",
                 "pages": [
-                  "ko/enterprise/features/rbac",
-                  "ko/enterprise/features/tool-repository",
-                  "ko/enterprise/features/webhook-streaming",
                   "ko/enterprise/features/traces",
-                  "ko/enterprise/features/hallucination-guardrail",
-                  "ko/enterprise/features/integrations",
-                  "ko/enterprise/features/agent-repositories"
+                  "ko/enterprise/features/webhook-streaming",
+                  "ko/enterprise/features/hallucination-guardrail"
+                ]
+              },
+              {
+                "group": "관리",
+                "pages": [
+                  "ko/enterprise/features/rbac"
                 ]
               },
               {
@@ -997,7 +1177,7 @@
                 ]
               },
               {
-                "group": "사용 안내서",
+                "group": "How-To Guides",
                 "pages": [
                   "ko/enterprise/guides/build-crew",
                   "ko/enterprise/guides/deploy-crew",
@@ -1005,13 +1185,20 @@
                   "ko/enterprise/guides/update-crew",
                   "ko/enterprise/guides/enable-crew-studio",
                   "ko/enterprise/guides/azure-openai-setup",
-                  "ko/enterprise/guides/hubspot-trigger",
+                  "ko/enterprise/guides/tool-repository",
                   "ko/enterprise/guides/react-component-export",
-                  "ko/enterprise/guides/salesforce-trigger",
-                  "ko/enterprise/guides/slack-trigger",
                   "ko/enterprise/guides/team-management",
-                  "ko/enterprise/guides/webhook-automation",
                   "ko/enterprise/guides/human-in-the-loop",
+                  "ko/enterprise/guides/webhook-automation"
+                ]
+              },
+              {
+                "group": "트리거",
+                "pages": [
+                  "ko/enterprise/guides/automation-triggers",
+                  "ko/enterprise/guides/slack-trigger",
+                  "ko/enterprise/guides/hubspot-trigger",
+                  "ko/enterprise/guides/salesforce-trigger",
                   "ko/enterprise/guides/zapier-trigger"
                 ]
               },
@@ -1023,25 +1210,38 @@
           },
           {
             "tab": "API 레퍼런스",
+            "icon": "magnifying-glass",
             "groups": [
               {
                 "group": "시작 안내",
-                "pages": ["ko/api-reference/introduction"]
-              },
-              {
-                "group": "Endpoints",
-                "openapi": "https://raw.githubusercontent.com/crewAIInc/crewAI/main/docs/enterprise-api.ko.yaml"
+                "pages": [
+                  "ko/api-reference/introduction",
+                  "ko/api-reference/inputs",
+                  "ko/api-reference/kickoff",
+                  "ko/api-reference/status"
+                ]
               }
             ]
           },
           {
             "tab": "예시",
+            "icon": "code",
             "groups": [
               {
                 "group": "예시",
                 "pages": ["ko/examples/example", "ko/examples/cookbooks"]
               }
             ]
+          },
+          {
+            "tab": "변경 로그",
+            "icon": "clock",
+            "groups": [
+              {
+                "group": "릴리스 노트",
+                "pages": ["ko/changelog"]
+              }
+            ]
           }
         ]
       }
@@ -1051,15 +1251,23 @@
     "light": "/images/crew_only_logo.png",
     "dark": "/images/crew_only_logo.png"
   },
+  "fonts": {
+    "family": "Inter"
+  },
   "appearance": {
-    "default": "dark",
-    "strict": false
+    "default": "system",
+    "strict": false,
+    "layout": "sidenav"
+  },
+  "background": {
+    "decoration": "grid"
   },
   "navbar": {
     "links": [
       {
         "label": "Start Cloud Trial",
-        "href": "https://app.crewai.com"
+        "href": "https://app.crewai.com",
+        "icon": "arrow-up-right-from-square"
       }
     ],
     "primary": {
@@ -1078,9 +1286,26 @@
     }
   },
   "seo": {
-    "indexing": "all"
+    "indexing": "all",
+    "metatags": {
+      "og:type": "website",
+      "og:site_name": "CrewAI Documentation",
+      "og:image": "https://docs.crewai.com/images/crew_only_logo.png",
+      "twitter:card": "summary_large_image",
+      "twitter:site": "@crewAIInc",
+      "keywords": "AI agents, multi-agent systems, CrewAI, artificial intelligence, automation, Python framework, agent collaboration, AI workflows"
+    }
+  },
+  "feedback": {
+    "enabled": true,
+    "thumbsRating": true,
+    "suggestEdit": true
   },
   "redirects": [
+    {
+      "source": "/api-reference",
+      "destination": "/en/api-reference/introduction"
+    },
     {
       "source": "/introduction",
       "destination": "/en/introduction"
@@ -1095,7 +1320,7 @@
     },
     {
       "source": "/changelog",
-      "destination": "https://github.com/crewAIInc/crewAI/releases"
+      "destination": "/en/changelog"
     },
     {
       "source": "/telemetry",
@@ -1133,6 +1358,18 @@
       "source": "/api-reference/:path*",
       "destination": "/en/api-reference/:path*"
     },
+    {
+      "source": "/en/api-reference",
+      "destination": "/en/api-reference/introduction"
+    },
+    {
+      "source": "/pt-BR/api-reference",
+      "destination": "/pt-BR/api-reference/introduction"
+    },
+    {
+      "source": "/ko/api-reference",
+      "destination": "/ko/api-reference/introduction"
+    },
     {
       "source": "/examples/:path*",
       "destination": "/en/examples/:path*"

docs/en/api-reference/inputs.mdx

@@ -0,0 +1,8 @@
+---
+title: "GET /inputs"
+description: "Get required inputs for your crew"
+openapi: "/enterprise-api.en.yaml GET /inputs"
+mode: "wide"
+---
+
+

docs/en/api-reference/introduction.mdx

@@ -2,6 +2,7 @@
 title: "Introduction"
 description: "Complete reference for the CrewAI Enterprise REST API"
 icon: "code"
+mode: "wide"
 ---
 
 # CrewAI Enterprise API

docs/en/api-reference/kickoff.mdx

@@ -0,0 +1,8 @@
+---
+title: "POST /kickoff"
+description: "Start a crew execution"
+openapi: "/enterprise-api.en.yaml POST /kickoff"
+mode: "wide"
+---
+
+

docs/en/api-reference/status.mdx

@@ -0,0 +1,8 @@
+---
+title: "GET /status/{kickoff_id}"
+description: "Get execution status"
+openapi: "/enterprise-api.en.yaml GET /status/{kickoff_id}"
+mode: "wide"
+---
+
+

docs/en/concepts/agents.mdx

@@ -2,6 +2,7 @@
 title: Agents
 description: Detailed guide on creating and managing agents within the CrewAI framework.
 icon: robot
+mode: "wide"
 ---
 
 ## Overview of an Agent

docs/en/concepts/cli.mdx

@@ -2,6 +2,7 @@
 title: CLI
 description: Learn how to use the CrewAI CLI to interact with CrewAI.
 icon: terminal
+mode: "wide"
 ---
 
 <Warning>Since release 0.140.0, CrewAI Enterprise started a process of migrating their login provider. As such, the authentication flow via CLI was updated. Users that use Google to login, or that created their account after July 3rd, 2025 will be unable to log in with older versions of the `crewai` library.</Warning>
@@ -272,17 +273,33 @@ You must be authenticated to CrewAI Enterprise to use these organization managem
 Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI Enterprise](http://app.crewai.com) using the CLI.
 
 <iframe
-  width="100%"
-  height="400"
+  className="w-full aspect-video rounded-xl"
   src="https://www.youtube.com/embed/3EqSV-CYDZA"
   title="CrewAI Deployment Guide"
-  frameborder="0"
-  style={{ borderRadius: '10px' }}
+  frameBorder="0"
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-  allowfullscreen
+  allowFullScreen
 ></iframe>
 
-### 11. API Keys
+### 11. Login
+
+Authenticate with CrewAI Enterprise using a secure device code flow (no email entry required).
+
+```shell Terminal
+crewai login
+```
+
+What happens:
+- A verification URL and short code are displayed in your terminal
+- Your browser opens to the verification URL
+- Enter/confirm the code to complete authentication
+
+Notes:
+- The OAuth2 provider and domain are configured via `crewai config` (defaults use `login.crewai.com`)
+- After successful login, the CLI also attempts to authenticate to the Tool Repository automatically
+- If you reset your configuration, run `crewai login` again to re-authenticate
+
+### 12. API Keys
 
 When running ```crewai create crew``` command, the CLI will show you a list of available LLM providers to choose from, followed by model selection for your chosen provider.
 
@@ -310,7 +327,7 @@ See the following link for each provider's key name:
 
 * [LiteLLM Providers](https://docs.litellm.ai/docs/providers)
 
-### 12. Configuration Management
+### 13. Configuration Management
 
 Manage CLI configuration settings for CrewAI.
 
@@ -351,19 +368,15 @@ crewai config list
 ```
 
 Example output:
-```
-CrewAI CLI Configuration
-┏━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
-┃ Setting            ┃ Value                              ┃ Description                                                                                      ┃
-┡━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
-│ enterprise_base_url│ https://app.crewai.com             │ Base URL of the CrewAI Enterprise instance                                                       │
-│ org_name           │ Not set                            │ Name of the currently active organization                                                        │
-│ org_uuid           │ Not set                            │ UUID of the currently active organization                                                        │
-│ oauth2_provider    │ workos                             │ OAuth2 provider used for authentication (e.g., workos, okta, auth0).                             │
-│ oauth2_audience    │ client_01YYY                       │ OAuth2 audience value, typically used to identify the target API or resource.                    │
-│ oauth2_client_id   │ client_01XXX                       │ OAuth2 client ID issued by the provider, used during authentication requests.                    │
-│ oauth2_domain      │ login.crewai.com                   │ OAuth2 provider's domain (e.g., your-org.auth0.com) used for issuing tokens.                     │
-```
+| Setting             | Value                    | Description                                                 |
+| :------------------ | :----------------------- | :---------------------------------------------------------- |
+| enterprise_base_url | https://app.crewai.com   | Base URL of the CrewAI Enterprise instance                  |
+| org_name            | Not set                  | Name of the currently active organization                   |
+| org_uuid            | Not set                  | UUID of the currently active organization                   |
+| oauth2_provider     | workos                   | OAuth2 provider (e.g., workos, okta, auth0)                 |
+| oauth2_audience     | client_01YYY             | Audience identifying the target API/resource                |
+| oauth2_client_id    | client_01XXX             | OAuth2 client ID issued by the provider                     |
+| oauth2_domain       | login.crewai.com         | Provider domain (e.g., your-org.auth0.com)                  |
 
 Set the enterprise base URL:
 ```shell Terminal
@@ -385,6 +398,14 @@ Reset all configuration to defaults:
 crewai config reset
 ```
 
+<Tip>
+After resetting configuration, re-run `crewai login` to authenticate again.
+</Tip>
+
+<Tip>
+CrewAI CLI handles authentication to the Tool Repository automatically when adding packages to your project. Just append `crewai` before any `uv` command to use it. E.g. `crewai uv add requests`. For more information, see [Tool Repository](https://docs.crewai.com/enterprise/features/tool-repository) docs.
+</Tip>
+
 <Note>
 Configuration settings are stored in `~/.config/crewai/settings.json`. Some settings like organization name and UUID are read-only and managed through authentication and organization commands. Tool repository related settings are hidden and cannot be set directly by users.
 </Note>

docs/en/concepts/collaboration.mdx

@@ -2,6 +2,7 @@
 title: Collaboration
 description: How to enable agents to work together, delegate tasks, and communicate effectively within CrewAI teams.
 icon: screen-users
+mode: "wide"
 ---
 
 ## Overview

docs/en/concepts/crews.mdx

@@ -2,6 +2,7 @@
 title: Crews
 description: Understanding and utilizing crews in the crewAI framework with comprehensive attributes and functionalities.
 icon: people-group
+mode: "wide"
 ---
 
 ## Overview

docs/en/concepts/event-listener.mdx

@@ -2,6 +2,7 @@
 title: 'Event Listeners'
 description: 'Tap into CrewAI events to build custom integrations and monitoring'
 icon: spinner
+mode: "wide"
 ---
 
 ## Overview
@@ -44,12 +45,12 @@ To create a custom event listener, you need to:
 Here's a simple example of a custom event listener class:
 
 ```python
-from crewai.utilities.events import (
+from crewai.events import (
     CrewKickoffStartedEvent,
     CrewKickoffCompletedEvent,
     AgentExecutionCompletedEvent,
 )
-from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.events import BaseEventListener
 
 class MyCustomListener(BaseEventListener):
     def __init__(self):
@@ -146,7 +147,7 @@ my_project/
 
 ```python
 # my_custom_listener.py
-from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.events import BaseEventListener
 # ... import events ...
 
 class MyCustomListener(BaseEventListener):
@@ -279,7 +280,7 @@ Additional fields vary by event type. For example, `CrewKickoffCompletedEvent` i
 For temporary event handling (useful for testing or specific operations), you can use the `scoped_handlers` context manager:
 
 ```python
-from crewai.utilities.events import crewai_event_bus, CrewKickoffStartedEvent
+from crewai.events import crewai_event_bus, CrewKickoffStartedEvent
 
 with crewai_event_bus.scoped_handlers():
     @crewai_event_bus.on(CrewKickoffStartedEvent)

docs/en/concepts/flows.mdx

@@ -2,6 +2,7 @@
 title: Flows
 description: Learn how to create and manage AI workflows using CrewAI Flows.
 icon: arrow-progress
+mode: "wide"
 ---
 
 ## Overview
@@ -97,7 +98,13 @@ The state's unique ID and stored data can be useful for tracking flow executions
 
 ### @start()
 
-The `@start()` decorator is used to mark a method as the starting point of a Flow. When a Flow is started, all the methods decorated with `@start()` are executed in parallel. You can have multiple start methods in a Flow, and they will all be executed when the Flow is started.
+The `@start()` decorator marks entry points for a Flow. You can:
+
+- Declare multiple unconditional starts: `@start()`
+- Gate a start on a prior method or router label: `@start("method_or_label")`
+- Provide a callable condition to control when a start should fire
+
+All satisfied `@start()` methods will execute (often in parallel) when the Flow begins or resumes.
 
 ### @listen()
 
@@ -868,14 +875,13 @@ By exploring these examples, you can gain insights into how to leverage CrewAI F
 Also, check out our YouTube video on how to use flows in CrewAI below!
 
 <iframe
-  width="560"
-  height="315"
+  className="w-full aspect-video rounded-xl"
   src="https://www.youtube.com/embed/MTb5my6VOT8"
-  title="YouTube video player"
-  frameborder="0"
+  title="CrewAI Flows overview"
+  frameBorder="0"
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
-  referrerpolicy="strict-origin-when-cross-origin"
-  allowfullscreen
+  referrerPolicy="strict-origin-when-cross-origin"
+  allowFullScreen
 ></iframe>
 
 ## Running Flows

docs/en/concepts/knowledge.mdx

@@ -2,6 +2,7 @@
 title: Knowledge
 description: What is knowledge in CrewAI and how to use it.
 icon: book
+mode: "wide"
 ---
 
 ## Overview
@@ -24,6 +25,41 @@ For file-based Knowledge Sources, make sure to place your files in a `knowledge`
 Also, use relative paths from the `knowledge` directory when creating the source.
 </Tip>
 
+### Vector store (RAG) client configuration
+
+CrewAI exposes a provider-neutral RAG client abstraction for vector stores. The default provider is ChromaDB, and Qdrant is supported as well. You can switch providers using configuration utilities.
+
+Supported today:
+- ChromaDB (default)
+- Qdrant
+
+```python Code
+from crewai.rag.config.utils import set_rag_config, get_rag_client, clear_rag_config
+
+# ChromaDB (default)
+from crewai.rag.chromadb.config import ChromaDBConfig
+set_rag_config(ChromaDBConfig())
+chromadb_client = get_rag_client()
+
+# Qdrant
+from crewai.rag.qdrant.config import QdrantConfig
+set_rag_config(QdrantConfig())
+qdrant_client = get_rag_client()
+
+# Example operations (same API for any provider)
+client = qdrant_client  # or chromadb_client
+client.create_collection(collection_name="docs")
+client.add_documents(
+    collection_name="docs",
+    documents=[{"id": "1", "content": "CrewAI enables collaborative AI agents."}],
+)
+results = client.search(collection_name="docs", query="collaborative agents", limit=3)
+
+clear_rag_config()  # optional reset
+```
+
+This RAG client is separate from Knowledge’s built-in storage. Use it when you need direct vector-store control or custom retrieval pipelines.
+
 ### Basic String Knowledge Example
 
 ```python Code
@@ -681,11 +717,11 @@ CrewAI emits events during the knowledge retrieval process that you can listen f
 #### Example: Monitoring Knowledge Retrieval
 
 ```python
-from crewai.utilities.events import (
+from crewai.events import (
     KnowledgeRetrievalStartedEvent,
     KnowledgeRetrievalCompletedEvent,
+    BaseEventListener,
 )
-from crewai.utilities.events.base_event_listener import BaseEventListener
 
 class KnowledgeMonitorListener(BaseEventListener):
     def setup_listeners(self, crewai_event_bus):

docs/en/concepts/llms.mdx

@@ -2,6 +2,7 @@
 title: 'LLMs'
 description: 'A comprehensive guide to configuring and using Large Language Models (LLMs) in your CrewAI projects'
 icon: 'microchip-ai'
+mode: "wide"
 ---
 
 ## Overview
@@ -733,10 +734,10 @@ CrewAI supports streaming responses from LLMs, allowing your application to rece
     CrewAI emits events for each chunk received during streaming:
 
     ```python
-    from crewai.utilities.events import (
+    from crewai.events import (
       LLMStreamChunkEvent
     )
-    from crewai.utilities.events.base_event_listener import BaseEventListener
+    from crewai.events import BaseEventListener
 
     class MyCustomListener(BaseEventListener):
         def setup_listeners(self, crewai_event_bus):
@@ -758,8 +759,8 @@ CrewAI supports streaming responses from LLMs, allowing your application to rece
 
     ```python
     from crewai import LLM, Agent, Task, Crew
-    from crewai.utilities.events import LLMStreamChunkEvent
-    from crewai.utilities.events.base_event_listener import BaseEventListener
+    from crewai.events import LLMStreamChunkEvent
+    from crewai.events import BaseEventListener
 
     class MyCustomListener(BaseEventListener):
         def setup_listeners(self, crewai_event_bus):

docs/en/concepts/memory.mdx

@@ -2,11 +2,12 @@
 title: Memory
 description: Leveraging memory systems in the CrewAI framework to enhance agent capabilities.
 icon: database
+mode: "wide"
 ---
 
 ## Overview
 
-The CrewAI framework provides a sophisticated memory system designed to significantly enhance AI agent capabilities. CrewAI offers **three distinct memory approaches** that serve different use cases:
+The CrewAI framework provides a sophisticated memory system designed to significantly enhance AI agent capabilities. CrewAI offers **two distinct memory approaches** that serve different use cases:
 
 1. **Basic Memory System** - Built-in short-term, long-term, and entity memory
 2. **External Memory** - Standalone external memory providers
@@ -738,6 +739,17 @@ print(f"OpenAI: {openai_time:.2f}s")
 print(f"Ollama: {ollama_time:.2f}s")
 ```
 
+### Entity Memory batching behavior
+
+Entity Memory supports batching when saving multiple entities at once. When you pass a list of `EntityMemoryItem`, the system:
+
+- Emits a single MemorySaveStartedEvent with `entity_count`
+- Saves each entity internally, collecting any partial errors
+- Emits MemorySaveCompletedEvent with aggregate metadata (saved count, errors)
+- Raises a partial-save exception if some entities failed (includes counts)
+
+This improves performance and observability when writing many entities in one operation.
+
 ## 2. External Memory 
 External Memory provides a standalone memory system that operates independently from the crew's built-in memory. This is ideal for specialized memory providers or cross-application memory sharing.
 
@@ -1041,8 +1053,8 @@ CrewAI emits the following memory-related events:
 Track memory operation timing to optimize your application:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemoryQueryCompletedEvent,
     MemorySaveCompletedEvent
 )
@@ -1076,8 +1088,8 @@ memory_monitor = MemoryPerformanceMonitor()
 Log memory operations for debugging and insights:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemorySaveStartedEvent,
     MemoryQueryStartedEvent,
     MemoryRetrievalCompletedEvent
@@ -1117,8 +1129,8 @@ memory_logger = MemoryLogger()
 Capture and respond to memory errors:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemorySaveFailedEvent,
     MemoryQueryFailedEvent
 )
@@ -1167,8 +1179,8 @@ error_tracker = MemoryErrorTracker(notify_email="admin@example.com")
 Memory events can be forwarded to analytics and monitoring platforms to track performance metrics, detect anomalies, and visualize memory usage patterns:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemoryQueryCompletedEvent,
     MemorySaveCompletedEvent
 )

docs/en/concepts/planning.mdx

@@ -2,6 +2,7 @@
 title: Planning
 description: Learn how to add planning to your CrewAI Crew and improve their performance.
 icon: ruler-combined
+mode: "wide"
 ---
 
 ## Overview

docs/en/concepts/processes.mdx

@@ -2,6 +2,7 @@
 title: Processes
 description: Detailed guide on workflow management through processes in CrewAI, with updated implementation details.
 icon: bars-staggered
+mode: "wide"
 ---
 
 ## Overview

docs/en/concepts/reasoning.mdx

@@ -2,6 +2,7 @@
 title: Reasoning
 description: "Learn how to enable and use agent reasoning to improve task execution."
 icon: brain
+mode: "wide"
 ---
 
 ## Overview

docs/en/concepts/tasks.mdx

@@ -2,6 +2,7 @@
 title: Tasks
 description: Detailed guide on managing and creating tasks within the CrewAI framework.
 icon: list-check
+mode: "wide"
 ---
 
 ## Overview
@@ -59,6 +60,12 @@ crew = Crew(
 | **Output Pydantic** _(optional)_ | `output_pydantic` | `Optional[Type[BaseModel]]`   | A Pydantic model for task output.                                                                                    |
 | **Callback** _(optional)_        | `callback`        | `Optional[Any]`               | Function/object to be executed after task completion.                                                                |
 | **Guardrail** _(optional)_       | `guardrail`       | `Optional[Callable]`             | Function to validate task output before proceeding to next task.                                                  |
+| **Guardrail Max Retries** _(optional)_ | `guardrail_max_retries` | `Optional[int]`     | Maximum number of retries when guardrail validation fails. Defaults to 3.                                         |
+
+<Note type="warning" title="Deprecated: max_retries">
+  The task attribute `max_retries` is deprecated and will be removed in v1.0.0.
+  Use `guardrail_max_retries` instead to control retry attempts when a guardrail fails.
+</Note>
 
 ## Creating Tasks
 
@@ -431,7 +438,7 @@ When a guardrail returns `(False, error)`:
 2. The agent attempts to fix the issue
 3. The process repeats until:
    - The guardrail returns `(True, result)`
-   - Maximum retries are reached
+   - Maximum retries are reached (`guardrail_max_retries`)
 
 Example with retry handling:
 ```python Code
@@ -452,7 +459,7 @@ task = Task(
     expected_output="A valid JSON object",
     agent=analyst,
     guardrail=validate_json_output,
-    max_retries=3  # Limit retry attempts
+    guardrail_max_retries=3  # Limit retry attempts
 )
 ```
 
@@ -890,14 +897,13 @@ except RuntimeError as e:
 Check out the video below to see how to use structured outputs in CrewAI:
 
 <iframe
-  width="560"
-  height="315"
+  className="w-full aspect-video rounded-xl"
   src="https://www.youtube.com/embed/dNpKQk5uxHw"
-  title="YouTube video player"
-  frameborder="0"
+  title="Structured outputs in CrewAI"
+  frameBorder="0"
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
-  referrerpolicy="strict-origin-when-cross-origin"
-  allowfullscreen
+  referrerPolicy="strict-origin-when-cross-origin"
+  allowFullScreen
 ></iframe>
 
 ## Conclusion

docs/en/concepts/testing.mdx

@@ -2,6 +2,7 @@
 title: Testing
 description: Learn how to test your CrewAI Crew and evaluate their performance.
 icon: vial
+mode: "wide"
 ---
 
 ## Overview

docs/en/concepts/tools.mdx

@@ -2,6 +2,7 @@
 title: Tools
 description: Understanding and leveraging tools within the CrewAI framework for agent collaboration and task execution.
 icon: screwdriver-wrench
+mode: "wide"
 ---
 
 ## Overview

docs/en/concepts/training.mdx

@@ -2,6 +2,7 @@
 title: Training
 description: Learn how to train your CrewAI agents by giving them feedback early on and get consistent results.
 icon: dumbbell
+mode: "wide"
 ---
 
 ## Overview
@@ -21,13 +22,17 @@ To use the training feature, follow these steps:
 3. Run the following command:
 
 ```shell
-crewai train -n <n_iterations> <filename> (optional)
+crewai train -n <n_iterations> -f <filename.pkl>
 ```
 <Tip>
   Replace `<n_iterations>` with the desired number of training iterations and `<filename>` with the appropriate filename ending with `.pkl`.
 </Tip>
 
-### Training Your Crew Programmatically
+<Note>
+  If you omit `-f`, the output defaults to `trained_agents_data.pkl` in the current working directory. You can pass an absolute path to control where the file is written.
+</Note>
+
+### Training your Crew programmatically
 
 To train your crew programmatically, use the following steps:
 
@@ -51,19 +56,65 @@ except Exception as e:
     raise Exception(f"An error occurred while training the crew: {e}")
 ```
 
-### Key Points to Note
+## How trained data is used by agents
 
-- **Positive Integer Requirement:** Ensure that the number of iterations (`n_iterations`) is a positive integer. The code will raise a `ValueError` if this condition is not met.
-- **Filename Requirement:** Ensure that the filename ends with `.pkl`. The code will raise a `ValueError` if this condition is not met.
-- **Error Handling:** The code handles subprocess errors and unexpected exceptions, providing error messages to the user.
+CrewAI uses the training artifacts in two ways: during training to incorporate your human feedback, and after training to guide agents with consolidated suggestions.
 
-It is important to note that the training process may take some time, depending on the complexity of your agents and will also require your feedback on each iteration.
+### Training data flow
 
-Once the training is complete, your agents will be equipped with enhanced capabilities and knowledge, ready to tackle complex tasks and provide more consistent and valuable insights.
+```mermaid
+flowchart TD
+  A["Start training<br/>CLI: crewai train -n -f<br/>or Python: crew.train(...)"] --> B["Setup training mode<br/>- task.human_input = true<br/>- disable delegation<br/>- init training_data.pkl + trained file"]
 
-Remember to regularly update and retrain your agents to ensure they stay up-to-date with the latest information and advancements in the field.
+  subgraph "Iterations"
+    direction LR
+    C["Iteration i<br/>initial_output"] --> D["User human_feedback"]
+    D --> E["improved_output"]
+    E --> F["Append to training_data.pkl<br/>by agent_id and iteration"]
+  end
 
-Happy training with CrewAI! 🚀
+  B --> C
+  F --> G{"More iterations?"}
+  G -- "Yes" --> C
+  G -- "No" --> H["Evaluate per agent<br/>aggregate iterations"]
+
+  H --> I["Consolidate<br/>suggestions[] + quality + final_summary"]
+  I --> J["Save by agent role to trained file<br/>(default: trained_agents_data.pkl)"]
+
+  J --> K["Normal (non-training) runs"]
+  K --> L["Auto-load suggestions<br/>from trained_agents_data.pkl"]
+  L --> M["Append to prompt<br/>for consistent improvements"]
+```
+
+### During training runs
+
+- On each iteration, the system records for every agent:
+  - `initial_output`: the agent’s first answer
+  - `human_feedback`: your inline feedback when prompted
+  - `improved_output`: the agent’s follow-up answer after feedback
+- This data is stored in a working file named `training_data.pkl` keyed by the agent’s internal ID and iteration.
+- While training is active, the agent automatically appends your prior human feedback to its prompt to enforce those instructions on subsequent attempts within the training session.
+  Training is interactive: tasks set `human_input = true`, so running in a non-interactive environment will block on user input.
+
+### After training completes
+
+- When `train(...)` finishes, CrewAI evaluates the collected training data per agent and produces a consolidated result containing:
+  - `suggestions`: clear, actionable instructions distilled from your feedback and the difference between initial/improved outputs
+  - `quality`: a 0–10 score capturing improvement
+  - `final_summary`: a step-by-step set of action items for future tasks
+- These consolidated results are saved to the filename you pass to `train(...)` (default via CLI is `trained_agents_data.pkl`). Entries are keyed by the agent’s `role` so they can be applied across sessions.
+- During normal (non-training) execution, each agent automatically loads its consolidated `suggestions` and appends them to the task prompt as mandatory instructions. This gives you consistent improvements without changing your agent definitions.
+
+### File summary
+
+- `training_data.pkl` (ephemeral, per-session):
+  - Structure: `agent_id -> { iteration_number: { initial_output, human_feedback, improved_output } }`
+  - Purpose: capture raw data and human feedback during training
+  - Location: saved in the current working directory (CWD)
+- `trained_agents_data.pkl` (or your custom filename):
+  - Structure: `agent_role -> { suggestions: string[], quality: number, final_summary: string }`
+  - Purpose: persist consolidated guidance for future runs
+  - Location: written to the CWD by default; use `-f` to set a custom (including absolute) path
 
 ## Small Language Model Considerations
 
@@ -129,3 +180,18 @@ Happy training with CrewAI! 🚀
     </Warning>
   </Tab>
 </Tabs>
+
+### Key Points to Note
+
+- **Positive Integer Requirement:** Ensure that the number of iterations (`n_iterations`) is a positive integer. The code will raise a `ValueError` if this condition is not met.
+- **Filename Requirement:** Ensure that the filename ends with `.pkl`. The code will raise a `ValueError` if this condition is not met.
+- **Error Handling:** The code handles subprocess errors and unexpected exceptions, providing error messages to the user.
+- Trained guidance is applied at prompt time; it does not modify your Python/YAML agent configuration.
+- Agents automatically load trained suggestions from a file named `trained_agents_data.pkl` located in the current working directory. If you trained to a different filename, either rename it to `trained_agents_data.pkl` before running, or adjust the loader in code.
+- You can change the output filename when calling `crewai train` with `-f/--filename`. Absolute paths are supported if you want to save outside the CWD.
+
+It is important to note that the training process may take some time, depending on the complexity of your agents and will also require your feedback on each iteration.
+
+Once the training is complete, your agents will be equipped with enhanced capabilities and knowledge, ready to tackle complex tasks and provide more consistent and valuable insights.
+
+Remember to regularly update and retrain your agents to ensure they stay up-to-date with the latest information and advancements in the field.

docs/en/enterprise/features/agent-repositories.mdx

@@ -1,11 +1,16 @@
 ---
 title: 'Agent Repositories'
 description: 'Learn how to use Agent Repositories to share and reuse your agents across teams and projects'
-icon: 'database'
+icon: 'people-group'
+mode: "wide"
 ---
 
 Agent Repositories allow enterprise users to store, share, and reuse agent definitions across teams and projects. This feature enables organizations to maintain a centralized library of standardized agents, promoting consistency and reducing duplication of effort.
 
+<Frame>
+  ![Agent Repositories](/images/enterprise/agent-repositories.png)
+</Frame>
+
 ## Benefits of Agent Repositories
 
 - **Standardization**: Maintain consistent agent definitions across your organization
@@ -13,25 +18,21 @@ Agent Repositories allow enterprise users to store, share, and reuse agent defin
 - **Governance**: Implement organization-wide policies for agent configurations
 - **Collaboration**: Enable teams to share and build upon each other's work
 
-## Using Agent Repositories
-
-### Prerequisites
+## Creating and Use Agent Repositories
 
 1. You must have an account at CrewAI, try the [free plan](https://app.crewai.com).
-2. You need to be authenticated using the CrewAI CLI.
-3. If you have more than one organization, make sure you are switched to the correct organization using the CLI command:
+2. Create agents with specific roles and goals for your workflows.
+3. Configure tools and capabilities for each specialized assistant.
+4. Deploy agents across projects via visual interface or API integration.
 
-```bash
-crewai org switch <org_id>
-```
+<Frame>
+  ![Agent Repositories](/images/enterprise/create-agent-repository.png)
+</Frame>
 
-### Creating and Managing Agents in Repositories
-
-To create and manage agents in repositories,Enterprise Dashboard.
 
 ### Loading Agents from Repositories
 
-You can load agents from repositories in your code using the `from_repository` parameter:
+You can load agents from repositories in your code using the `from_repository` parameter to run locally:
 
 ```python
 from crewai import Agent
@@ -41,7 +42,6 @@ from crewai import Agent
 researcher = Agent(
     from_repository="market-research-agent"
 )
-
 ```
 
 ### Overriding Repository Settings

docs/en/enterprise/features/automations.mdx

@@ -0,0 +1,106 @@
+---
+title: Automations
+description: "Manage, deploy, and monitor your live crews (automations) in one place."
+icon: "rocket"
+mode: "wide"
+---
+
+## Overview
+
+Automations is the live operations hub for your deployed crews. Use it to deploy from GitHub or a ZIP file, manage environment variables, re‑deploy when needed, and monitor the status of each automation.
+
+<Frame>
+  ![Automations Overview](/images/enterprise/automations-overview.png)
+
+</Frame>
+
+## Deployment Methods
+
+### Deploy from GitHub
+
+Use this for version‑controlled projects and continuous deployment.
+
+<Steps>
+  <Step title="Connect GitHub">
+    Click <b>Configure GitHub</b> and authorize access.
+  </Step>
+  <Step title="Select Repository & Branch">
+    Choose the <b>Repository</b> and <b>Branch</b> you want to deploy from.
+  </Step>
+  <Step title="Enable Auto‑deploy (optional)">
+    Turn on <b>Automatically deploy new commits</b> to ship updates on every push.
+  </Step>
+  <Step title="Add Environment Variables">
+    Add secrets individually or use <b>Bulk View</b> for multiple variables.
+  </Step>
+  <Step title="Deploy">
+    Click <b>Deploy</b> to create your live automation.
+  </Step>
+</Steps>
+
+<Frame>
+  ![GitHub Deployment](/images/enterprise/deploy-from-github.png)
+</Frame>
+
+### Deploy from ZIP
+
+Ship quickly without Git—upload a compressed package of your project.
+
+<Steps>
+  <Step title="Choose File">
+    Select the ZIP archive from your computer.
+  </Step>
+  <Step title="Add Environment Variables">
+    Provide any required variables or keys.
+  </Step>
+  <Step title="Deploy">
+    Click <b>Deploy</b> to create your live automation.
+  </Step>
+</Steps>
+
+<Frame>
+  ![ZIP Deployment](/images/enterprise/deploy-from-zip.png)
+</Frame>
+
+## Automations Dashboard
+
+The table lists all live automations with key details:
+
+- **CREW**: Automation name
+- **STATUS**: Online / Failed / In Progress
+- **URL**: Endpoint for kickoff/status
+- **TOKEN**: Automation token
+- **ACTIONS**: Re‑deploy, delete, and more
+
+Use the top‑right controls to filter and search:
+
+- Search by name
+- Filter by <b>Status</b>
+- Filter by <b>Source</b> (GitHub / Studio / ZIP)
+
+Once deployed, you can view the automation details and have the **Options** dropdown menu to `chat with this crew`, `Export React Component` and `Export as MCP`.
+
+<Frame>
+  ![Automations Table](/images/enterprise/automations-table.png)
+</Frame>
+
+## Best Practices
+
+- Prefer GitHub deployments for version control and CI/CD
+- Use re‑deploy to roll forward after code or config updates or set it to auto-deploy on every push
+
+## Related
+
+<CardGroup cols={3}>
+  <Card title="Deploy a Crew" href="/en/enterprise/guides/deploy-crew" icon="rocket">
+    Deploy a Crew from GitHub or ZIP file.
+  </Card>
+  <Card title="Automation Triggers" href="/en/enterprise/guides/automation-triggers" icon="trigger">
+    Trigger automations via webhooks or API.
+  </Card>
+  <Card title="Webhook Automation" href="/en/enterprise/guides/webhook-automation" icon="webhook">
+    Stream real-time events and updates to your systems.
+  </Card>
+</CardGroup>
+
+

docs/en/enterprise/features/crew-studio.mdx

@@ -0,0 +1,90 @@
+---
+title: Crew Studio
+description: "Build new automations with AI assistance, a visual editor, and integrated testing."
+icon: "pencil"
+mode: "wide"
+---
+
+## Overview
+
+Crew Studio is an interactive, AI‑assisted workspace for creating new automations from scratch using natural language and a visual workflow editor.
+
+<Frame>
+  ![Crew Studio Overview](/images/enterprise/crew-studio-overview.png)
+</Frame>
+
+## Prompt‑based Creation
+
+- Describe the automation you want; the AI generates agents, tasks, and tools.
+- Use voice input via the microphone icon if preferred.
+- Start from built‑in prompts for common use cases.
+
+<Frame>
+  ![Prompt Builder](/images/enterprise/crew-studio-prompt.png)
+</Frame>
+
+## Visual Editor
+
+The canvas reflects the workflow as nodes and edges with three supporting panels that allow you to configure the workflow easily without writing code; a.k.a. "**vibe coding AI Agents**".
+
+You can use the drag-and-drop functionality to add agents, tasks, and tools to the canvas or you can use the chat section to build the agents. Both approaches share state and can be used interchangeably.
+
+- **AI Thoughts (left)**: streaming reasoning as the workflow is designed
+- **Canvas (center)**: agents and tasks as connected nodes
+- **Resources (right)**: drag‑and‑drop components (agents, tasks, tools)
+
+<Frame>
+  ![Visual Canvas](/images/enterprise/crew-studio-canvas.png)
+</Frame>
+
+## Execution & Debugging
+
+Switch to the <b>Execution</b> view to run and observe the workflow:
+
+- Event timeline
+- Detailed logs (Details, Messages, Raw Data)
+- Local test runs before publishing
+
+<Frame>
+  ![Execution View](/images/enterprise/crew-studio-execution.png)
+</Frame>
+
+## Publish & Export
+
+- <b>Publish</b> to deploy a live automation
+- <b>Download</b> source as a ZIP for local development or customization
+
+<Frame>
+  ![Publish & Download](/images/enterprise/crew-studio-publish.png)
+</Frame>
+
+Once published, you can view the automation details and have the **Options** dropdown menu to `chat with this crew`, `Export React Component` and `Export as MCP`.
+
+<Frame>
+  ![Published Automation](/images/enterprise/crew-studio-published.png)
+</Frame>
+
+## Best Practices
+
+- Iterate quickly in Studio; publish only when stable
+- Keep tools constrained to minimum permissions needed
+- Use Traces to validate behavior and performance
+
+## Related
+
+<CardGroup cols={4}>
+  <Card title="Enable Crew Studio" href="/en/enterprise/guides/enable-crew-studio" icon="palette">
+    Enable Crew Studio.
+  </Card>
+  <Card title="Build a Crew" href="/en/enterprise/guides/build-crew" icon="paintbrush">
+    Build a Crew.
+  </Card>
+  <Card title="Deploy a Crew" href="/en/enterprise/guides/deploy-crew" icon="rocket">
+    Deploy a Crew from GitHub or ZIP file.
+  </Card>
+  <Card title="Export a React Component" href="/en/enterprise/guides/react-component-export" icon="download">
+    Export a React Component.
+  </Card>
+</CardGroup>
+
+

docs/en/enterprise/features/hallucination-guardrail.mdx

@@ -2,6 +2,7 @@
 title: Hallucination Guardrail
 description: "Prevent and detect AI hallucinations in your CrewAI tasks"
 icon: "shield-check"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/features/integrations.mdx

@@ -1,185 +0,0 @@
----
-title: Integrations
-description: "Connected applications for your agents to take actions."
-icon: "plug"
----
-
-## Overview
-
-Enable your agents to authenticate with any OAuth enabled provider and take actions. From Salesforce and HubSpot to Google and GitHub, we've got you covered with 16+ integrated services.
-
-<Frame>
-  ![Integrations](/images/enterprise/crew_connectors.png)
-</Frame>
-
-## Supported Integrations
-
-### **Communication & Collaboration**
-- **Gmail** - Manage emails and drafts
-- **Slack** - Workspace notifications and alerts
-- **Microsoft** - Office 365 and Teams integration
-
-### **Project Management**
-- **Jira** - Issue tracking and project management
-- **ClickUp** - Task and productivity management
-- **Asana** - Team task and project coordination
-- **Notion** - Page and database management
-- **Linear** - Software project and bug tracking
-- **GitHub** - Repository and issue management
-
-### **Customer Relationship Management**
-- **Salesforce** - CRM account and opportunity management
-- **HubSpot** - Sales pipeline and contact management
-- **Zendesk** - Customer support ticket management
-
-### **Business & Finance**
-- **Stripe** - Payment processing and customer management
-- **Shopify** - E-commerce store and product management
-
-### **Productivity & Storage**
-- **Google Sheets** - Spreadsheet data synchronization
-- **Google Calendar** - Event and schedule management
-- **Box** - File storage and document management
-
-and more to come!
-
-## Prerequisites
-
-Before using Authentication Integrations, ensure you have:
-
-- A [CrewAI Enterprise](https://app.crewai.com) account. You can get started with a free trial.
-
-
-## Setting Up Integrations
-
-### 1. Connect Your Account
-
-1. Navigate to [CrewAI Enterprise](https://app.crewai.com)
-2. Go to **Integrations** tab - https://app.crewai.com/crewai_plus/connectors
-3. Click **Connect** on your desired service from the Authentication Integrations section
-4. Complete the OAuth authentication flow
-5. Grant necessary permissions for your use case
-6. Get your Enterprise Token from your [CrewAI Enterprise](https://app.crewai.com) account page - https://app.crewai.com/crewai_plus/settings/account
-
-<Frame>
-  ![Integrations](/images/enterprise/enterprise_action_auth_token.png)
-</Frame>
-
-### 2. Install Integration Tools
-
-All you need is the latest version of `crewai-tools` package.
-
-```bash
-uv add crewai-tools
-```
-
-## Usage Examples
-
-### Basic Usage
-<Tip>
-  All the services you are authenticated into will be available as tools. So all you need to do is add the `CrewaiEnterpriseTools` to your agent and you are good to go.
-</Tip>
-
-```python
-from crewai import Agent, Task, Crew
-from crewai_tools import CrewaiEnterpriseTools
-
-# Get enterprise tools (Gmail tool will be included)
-enterprise_tools = CrewaiEnterpriseTools(
-    enterprise_token="your_enterprise_token"
-)
-# print the tools
-print(enterprise_tools)
-
-# Create an agent with Gmail capabilities
-email_agent = Agent(
-    role="Email Manager",
-    goal="Manage and organize email communications",
-    backstory="An AI assistant specialized in email management and communication.",
-    tools=enterprise_tools
-)
-
-# Task to send an email
-email_task = Task(
-    description="Draft and send a follow-up email to john@example.com about the project update",
-    agent=email_agent,
-    expected_output="Confirmation that email was sent successfully"
-)
-
-# Run the task
-crew = Crew(
-    agents=[email_agent],
-    tasks=[email_task]
-)
-
-# Run the crew
-crew.kickoff()
-```
-
-### Filtering Tools
-
-```python
-from crewai_tools import CrewaiEnterpriseTools
-
-enterprise_tools = CrewaiEnterpriseTools(
-    actions_list=["gmail_find_email"] # only gmail_find_email tool will be available
-)
-gmail_tool = enterprise_tools["gmail_find_email"]
-
-gmail_agent = Agent(
-    role="Gmail Manager",
-    goal="Manage gmail communications and notifications",
-    backstory="An AI assistant that helps coordinate gmail communications.",
-    tools=[gmail_tool]
-)
-
-notification_task = Task(
-    description="Find the email from john@example.com",
-    agent=gmail_agent,
-    expected_output="Email found from john@example.com"
-)
-
-# Run the task
-crew = Crew(
-    agents=[slack_agent],
-    tasks=[notification_task]
-)
-```
-
-## Best Practices
-
-### Security
-- **Principle of Least Privilege**: Only grant the minimum permissions required for your agents' tasks
-- **Regular Audits**: Periodically review connected integrations and their permissions
-- **Secure Credentials**: Never hardcode credentials; use CrewAI's secure authentication flow
-
-
-### Filtering Tools
-On a deployed crew, you can specify which actions are avialbel for each integration from the settings page of the service you connected to.
-
-<Frame>
-  ![Integrations](/images/enterprise/filtering_enterprise_action_tools.png)
-</Frame>
-
-
-### Scoped Deployments for multi user organizations
-You can deploy your crew and scope each integration to a specific user. For example, a crew that connects to google can use a specific user's gmail account.
-
-<Tip>
-  This is useful for multi user organizations where you want to scope the integration to a specific user.
-</Tip>
-
-
-Use the `user_bearer_token` to scope the integration to a specific user so that when the crew is kicked off, it will use the user's bearer token to authenticate with the integration. If user is not logged in, then the crew will not use any connected integrations. Use the default bearer token to authenticate with the integrations thats deployed with the crew.
-
-<Frame>
-  ![Integrations](/images/enterprise/user_bearer_token.png)
-</Frame>
-
-
-
-### Getting Help
-
-<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with integration setup or troubleshooting.
-</Card>

docs/en/enterprise/features/marketplace.mdx

@@ -0,0 +1,48 @@
+---
+title: Marketplace
+description: "Discover, install, and govern reusable assets for your enterprise crews."
+icon: "store"
+mode: "wide"
+---
+
+## Overview
+
+The Marketplace provides a curated surface for discovering integrations, internal tools, and reusable assets that accelerate crew development.
+
+<Frame>
+  ![Marketplace Overview](/images/enterprise/marketplace-overview.png)
+</Frame>
+
+## Discoverability
+
+- Browse by category and capability
+- Search for assets by name or keyword
+
+## Install & Enable
+
+- One‑click install for approved assets
+- Enable or disable per crew as needed
+- Configure required environment variables and scopes
+
+<Frame>
+  ![Install & Configure](/images/enterprise/marketplace-install.png)
+</Frame>
+
+You can also download the templates directly from the marketplace by clicking on the `Download` button so 
+you can use them locally or refine them to your needs.
+
+## Related
+
+<CardGroup cols={3}>
+  <Card title="Tools & Integrations" href="/en/enterprise/features/tools-and-integrations" icon="wrench">
+    Connect external apps and manage internal tools your agents can use.
+  </Card>
+  <Card title="Tool Repository" href="/en/enterprise/features/tool-repository" icon="toolbox">
+    Publish and install tools to enhance your crews' capabilities.
+  </Card>
+  <Card title="Agents Repository" href="/en/enterprise/features/agent-repositories" icon="people-group">
+    Store, share, and reuse agent definitions across teams and projects.
+  </Card>
+</CardGroup>
+
+

docs/en/enterprise/features/rbac.mdx

@@ -2,6 +2,7 @@
 title: "Role-Based Access Control (RBAC)"
 description: "Control access to crews, tools, and data with roles, scopes, and granular permissions."
 icon: "shield"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/features/tools-and-integrations.mdx

@@ -0,0 +1,250 @@
+---
+title: Tools & Integrations
+description: "Connect external apps and manage internal tools your agents can use."
+icon: "wrench"
+mode: "wide"
+---
+
+## Overview
+
+Tools & Integrations is the central hub for connecting third‑party apps and managing internal tools that your agents can use at runtime.
+
+<Frame>
+  ![Tools & Integrations Overview](/images/enterprise/crew_connectors.png)
+</Frame>
+
+## Explore
+
+<Tabs>
+  <Tab title="Integrations" icon="plug">
+
+  ## Agent Apps (Integrations)
+
+  Connect enterprise‑grade applications (e.g., Gmail, Google Drive, HubSpot, Slack) via OAuth to enable agent actions.
+
+  <Steps>
+    <Step title="Connect">
+      Click <b>Connect</b> on an app and complete OAuth.
+    </Step>
+    <Step title="Configure">
+      Optionally adjust scopes, triggers, and action availability.
+    </Step>
+    <Step title="Use in Agents">
+      Connected services become available as tools for your agents.
+    </Step>
+  </Steps>
+
+  <Frame>
+    ![Integrations Grid](/images/enterprise/agent-apps.png)
+  </Frame>
+
+  ### Connect your Account
+
+  1. Go to <Link href="https://app.crewai.com/crewai_plus/connectors">Integrations</Link>
+  2. Click <b>Connect</b> on the desired service
+  3. Complete the OAuth flow and grant scopes
+  4. Copy your Enterprise Token from the <b>Integration</b> tab
+
+  <Frame>
+    ![Enterprise Token](/images/enterprise/enterprise_action_auth_token.png)
+  </Frame>
+
+  ### Install Integration Tools
+
+  To use the integrations locally, you need to install the latest `crewai-tools` package.
+
+  ```bash
+  uv add crewai-tools
+  ```
+
+  ### Usage Example
+
+  <Tip>
+    All services you have authenticated will be available as tools. Add `CrewaiEnterpriseTools` to your agent and you’re set.
+  </Tip>
+
+  ```python
+  from crewai import Agent, Task, Crew
+  from crewai_tools import CrewaiEnterpriseTools
+
+  # Get enterprise tools (Gmail tool will be included)
+  enterprise_tools = CrewaiEnterpriseTools(
+      enterprise_token="your_enterprise_token"
+  )
+  # print the tools
+  print(enterprise_tools)
+
+  # Create an agent with Gmail capabilities
+  email_agent = Agent(
+      role="Email Manager",
+      goal="Manage and organize email communications",
+      backstory="An AI assistant specialized in email management and communication.",
+      tools=enterprise_tools
+  )
+
+  # Task to send an email
+  email_task = Task(
+      description="Draft and send a follow-up email to john@example.com about the project update",
+      agent=email_agent,
+      expected_output="Confirmation that email was sent successfully"
+  )
+
+  # Run the task
+  crew = Crew(
+      agents=[email_agent],
+      tasks=[email_task]
+  )
+
+  # Run the crew
+  crew.kickoff()
+  ```
+
+  ### Filtering Tools
+
+  ```python
+  from crewai_tools import CrewaiEnterpriseTools
+
+  enterprise_tools = CrewaiEnterpriseTools(
+      actions_list=["gmail_find_email"]  # only gmail_find_email tool will be available
+  )
+
+
+  gmail_tool = enterprise_tools["gmail_find_email"]
+
+
+  gmail_agent = Agent(
+      role="Gmail Manager",
+      goal="Manage gmail communications and notifications",
+      backstory="An AI assistant that helps coordinate gmail communications.",
+      tools=[gmail_tool]
+  )
+
+  notification_task = Task(
+      description="Find the email from john@example.com",
+      agent=gmail_agent,
+      expected_output="Email found from john@example.com"
+  )
+
+  crew = Crew(
+      agents=[gmail_agent],
+      tasks=[notification_task]
+  )
+  ```
+
+  On a deployed crew, you can specify which actions are available for each integration from the service settings page.
+
+  <Frame>
+    ![Filter Actions](/images/enterprise/filtering_enterprise_action_tools.png)
+  </Frame>
+
+  ### Scoped Deployments (multi‑user orgs)
+
+  You can scope each integration to a specific user. For example, a crew that connects to Google can use a specific user’s Gmail account.
+
+  <Tip>
+    Useful when different teams/users must keep data access separated.
+  </Tip>
+
+  Use the `user_bearer_token` to scope authentication to the requesting user. If the user isn’t logged in, the crew won’t use connected integrations. Otherwise it falls back to the default bearer token configured for the deployment.
+
+  <Frame>
+    ![User Bearer Token](/images/enterprise/user_bearer_token.png)
+  </Frame>
+
+  <div id="catalog"></div>
+  ### Catalog
+
+  #### Communication & Collaboration
+  - Gmail — Manage emails and drafts
+  - Slack — Workspace notifications and alerts
+  - Microsoft — Office 365 and Teams integration
+
+  #### Project Management
+  - Jira — Issue tracking and project management
+  - ClickUp — Task and productivity management
+  - Asana — Team task and project coordination
+  - Notion — Page and database management
+  - Linear — Software project and bug tracking
+  - GitHub — Repository and issue management
+
+  #### Customer Relationship Management
+  - Salesforce — CRM account and opportunity management
+  - HubSpot — Sales pipeline and contact management
+  - Zendesk — Customer support ticket management
+
+  #### Business & Finance
+  - Stripe — Payment processing and customer management
+  - Shopify — E‑commerce store and product management
+
+  #### Productivity & Storage
+  - Google Sheets — Spreadsheet data synchronization
+  - Google Calendar — Event and schedule management
+  - Box — File storage and document management
+
+  …and more to come!
+
+  </Tab>
+  <Tab title="Internal Tools" icon="toolbox">
+
+  ## Internal Tools
+
+  Create custom tools locally, publish them on CrewAI Enterprise Tool Repository and use them in your agents. 
+
+  <Tip>
+  Before running the commands below, make sure you log in to your CrewAI Enterprise account by running this command: 
+    ```bash
+    crewai login
+    ```
+  </Tip>
+
+  <Frame>
+    ![Internal Tool Detail](/images/enterprise/tools-integrations-internal.png)
+  </Frame>
+
+  <Steps>
+    <Step title="Create">
+      Create a new tool locally.
+      ```bash
+      crewai tool create your-tool
+      ```
+    </Step>
+    <Step title="Publish">
+      Publish the tool to the CrewAI Enterprise Tool Repository.
+      ```bash
+      crewai tool publish
+      ```
+    </Step>
+    <Step title="Install">
+      Install the tool from the CrewAI Enterprise Tool Repository.
+      ```bash
+      crewai tool install your-tool
+      ```
+    </Step>
+  </Steps>
+
+  Manage:
+
+  - Name and description
+  - Visibility (Private / Public)
+  - Required environment variables
+  - Version history and downloads
+  - Team and role access
+
+  <Frame>
+    ![Internal Tool Detail](/images/enterprise/tool-configs.png)
+  </Frame>
+
+  </Tab>
+</Tabs>
+
+## Related
+
+<CardGroup cols={2}>
+  <Card title="Tool Repository" href="/en/enterprise/features/tool-repository" icon="toolbox">
+    Create, publish, and version custom tools for your organization.
+  </Card>
+  <Card title="Webhook Automation" href="/en/enterprise/guides/webhook-automation" icon="bolt">
+    Automate workflows and integrate with external platforms and services.
+  </Card>
+</CardGroup>
+

docs/en/enterprise/features/traces.mdx

@@ -2,6 +2,7 @@
 title: Traces
 description: "Using Traces to monitor your Crews"
 icon: "timeline"
+mode: "wide"
 ---
 
 ## Overview
@@ -141,6 +142,16 @@ Traces are invaluable for troubleshooting issues with your crews:
   </Step>
 </Steps>
 
+## Performance and batching
+
+CrewAI batches trace uploads to reduce overhead on high-volume runs:
+
+- A TraceBatchManager buffers events and sends them in batches via the Plus API client
+- Reduces network chatter and improves reliability on flaky connections
+- Automatically enabled in the default trace listener; no configuration needed
+
+This yields more stable tracing under load while preserving detailed task/agent telemetry.
+
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
   Contact our support team for assistance with trace analysis or any other CrewAI Enterprise features.
 </Card>

docs/en/enterprise/features/webhook-streaming.mdx

@@ -2,6 +2,7 @@
 title: Webhook Streaming
 description: "Using Webhook Streaming to stream events to your webhook"
 icon: "webhook"
+mode: "wide"
 ---
 
 ## Overview
@@ -62,21 +63,106 @@ As requests are sent over HTTP, the order of events can't be guaranteed. If you
 
 CrewAI supports both system events and custom events in Enterprise Event Streaming. These events are sent to your configured webhook endpoint during crew and flow execution.
 
-- `crew_kickoff_started`
-- `crew_step_started`
-- `crew_step_completed`
-- `crew_execution_completed`
-- `llm_call_started`
-- `llm_call_completed`
-- `tool_usage_started`
-- `tool_usage_completed`
-- `crew_test_failed`
-- *...and others*
+### Flow Events:
 
-Event names match the internal event bus. See [GitHub source](https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events) for the full list.
+  - `flow_created`
+  - `flow_started`
+  - `flow_finished`
+  - `flow_plot`
+  - `method_execution_started`
+  - `method_execution_finished`
+  - `method_execution_failed`
+
+### Agent Events:
+
+  - `agent_execution_started`
+  - `agent_execution_completed`
+  - `agent_execution_error`
+  - `lite_agent_execution_started`
+  - `lite_agent_execution_completed`
+  - `lite_agent_execution_error`
+  - `agent_logs_started`
+  - `agent_logs_execution`
+  - `agent_evaluation_started`
+  - `agent_evaluation_completed`
+  - `agent_evaluation_failed`
+
+### Crew Events:
+
+  - `crew_kickoff_started`
+  - `crew_kickoff_completed`
+  - `crew_kickoff_failed`
+  - `crew_train_started`
+  - `crew_train_completed`
+  - `crew_train_failed`
+  - `crew_test_started`
+  - `crew_test_completed`
+  - `crew_test_failed`
+  - `crew_test_result`
+
+### Task Events:
+
+  - `task_started`
+  - `task_completed`
+  - `task_failed`
+  - `task_evaluation`
+
+### Tool Usage Events:
+
+  - `tool_usage_started`
+  - `tool_usage_finished`
+  - `tool_usage_error`
+  - `tool_validate_input_error`
+  - `tool_selection_error`
+  - `tool_execution_error`
+
+### LLM Events:
+
+  - `llm_call_started`
+  - `llm_call_completed`
+  - `llm_call_failed`
+  - `llm_stream_chunk`
+
+### LLM Guardrail Events:
+
+  - `llm_guardrail_started`
+  - `llm_guardrail_completed`
+
+### Memory Events:
+
+  - `memory_query_started`
+  - `memory_query_completed`
+  - `memory_query_failed`
+  - `memory_save_started`
+  - `memory_save_completed`
+  - `memory_save_failed`
+  - `memory_retrieval_started`
+  - `memory_retrieval_completed`
+
+### Knowledge Events:
+
+  - `knowledge_search_query_started`
+  - `knowledge_search_query_completed`
+  - `knowledge_search_query_failed`
+  - `knowledge_query_started`
+  - `knowledge_query_completed`
+  - `knowledge_query_failed`
+
+### Reasoning Events:
+
+  - `agent_reasoning_started`
+  - `agent_reasoning_completed` 
+  - `agent_reasoning_failed`
+
+Event names match the internal event bus. See GitHub for the full list of events.
 
 You can emit your own custom events, and they will be delivered through the webhook stream alongside system events.
 
+<CardGroup>
+ <Card title="GitHub" icon="github" href="https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events">
+  Full list of events
+ </Card>
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
   Contact our support team for assistance with webhook integration or troubleshooting.
-</Card>
+</Card>
+</CardGroup>

docs/en/enterprise/guides/automation-triggers.mdx

@@ -0,0 +1,255 @@
+---
+title: "Triggers Overview"
+description: "Understand how CrewAI Enterprise triggers work, how to manage them, and where to find integration-specific playbooks"
+icon: "face-smile"
+mode: "wide"
+---
+
+CrewAI Enterprise triggers connect your automations to real-time events across the tools your teams already use. Instead of polling systems or relying on manual kickoffs, triggers listen for changes—new emails, calendar updates, CRM status changes—and immediately launch the crew or flow you specify.
+
+<Frame>
+  ![Automation Triggers Overview](/images/enterprise/crew_connectors.png)
+</Frame>
+
+### Integration Playbooks
+
+Deep-dive guides walk through setup and sample workflows for each integration:
+
+<CardGroup cols={2}>
+  <Card title="Gmail Trigger" icon="envelope">
+    <a href="/en/enterprise/guides/gmail-trigger">Enable crews when emails arrive or threads update.</a>
+  </Card>
+
+  <Card title="Google Calendar Trigger" icon="calendar-days">
+    <a href="/en/enterprise/guides/google-calendar-trigger">React to calendar events as they are created, updated, or cancelled.</a>
+  </Card>
+
+  <Card title="Google Drive Trigger" icon="folder-open">
+    <a href="/en/enterprise/guides/google-drive-trigger">Handle Drive file uploads, edits, and deletions.</a>
+  </Card>
+
+  <Card title="Outlook Trigger" icon="envelope-open">
+    <a href="/en/enterprise/guides/outlook-trigger">Automate responses to new Outlook messages and calendar updates.</a>
+  </Card>
+
+  <Card title="OneDrive Trigger" icon="cloud">
+    <a href="/en/enterprise/guides/onedrive-trigger">Audit file activity and sharing changes in OneDrive.</a>
+  </Card>
+
+  <Card title="Microsoft Teams Trigger" icon="comments">
+    <a href="/en/enterprise/guides/microsoft-teams-trigger">Kick off workflows when new Teams chats start.</a>
+  </Card>
+
+  <Card title="HubSpot Trigger" icon="hubspot">
+    <a href="/en/enterprise/guides/hubspot-trigger">Launch automations from HubSpot workflows and lifecycle events.</a>
+  </Card>
+
+  <Card title="Salesforce Trigger" icon="salesforce">
+    <a href="/en/enterprise/guides/salesforce-trigger">Connect Salesforce processes to CrewAI for CRM automation.</a>
+  </Card>
+
+  <Card title="Slack Trigger" icon="slack">
+    <a href="/en/enterprise/guides/slack-trigger">Start crews directly from Slack slash commands.</a>
+  </Card>
+
+  <Card title="Zapier Trigger" icon="bolt">
+    <a href="/en/enterprise/guides/zapier-trigger">Bridge CrewAI with thousands of Zapier-supported apps.</a>
+  </Card>
+</CardGroup>
+
+## Trigger Capabilities
+
+With triggers, you can:
+
+- **Respond to real-time events** - Automatically execute workflows when specific conditions are met
+- **Integrate with external systems** - Connect with platforms like Gmail, Outlook, OneDrive, JIRA, Slack, Stripe and more
+- **Scale your automation** - Handle high-volume events without manual intervention
+- **Maintain context** - Access trigger data within your crews and flows
+
+## Managing Triggers
+
+### Viewing Available Triggers
+
+To access and manage your automation triggers:
+
+1. Navigate to your deployment in the CrewAI dashboard
+2. Click on the **Triggers** tab to view all available trigger integrations
+
+<Frame caption="Example of available automation triggers for a Gmail deployment">
+  <img src="/images/enterprise/list-available-triggers.png" alt="List of available automation triggers" />
+</Frame>
+
+This view shows all the trigger integrations available for your deployment, along with their current connection status.
+
+### Enabling and Disabling Triggers
+
+Each trigger can be easily enabled or disabled using the toggle switch:
+
+<Frame caption="Enable or disable triggers with toggle">
+  <img src="/images/enterprise/trigger-selected.png" alt="Enable or disable triggers with toggle" />
+</Frame>
+
+- **Enabled (blue toggle)**: The trigger is active and will automatically execute your deployment when the specified events occur
+- **Disabled (gray toggle)**: The trigger is inactive and will not respond to events
+
+Simply click the toggle to change the trigger state. Changes take effect immediately.
+
+### Monitoring Trigger Executions
+
+Track the performance and history of your triggered executions:
+
+<Frame caption="List of executions triggered by automation">
+  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+</Frame>
+
+## Building Trigger-Driven Automations
+
+Before building your automation, it's helpful to understand the structure of trigger payloads that your crews and flows will receive.
+
+### Trigger Setup Checklist
+
+Before wiring a trigger into production, make sure you:
+
+- Connect the integration under **Tools & Integrations** and complete any OAuth or API key steps
+- Enable the trigger toggle on the deployment that should respond to events
+- Provide any required environment variables (API tokens, tenant IDs, shared secrets)
+- Create or update tasks that can parse the incoming payload within the first crew task or flow step
+- Decide whether to pass trigger context automatically using `allow_crewai_trigger_context`
+- Set up monitoring—webhook logs, CrewAI execution history, and optional external alerting
+
+### Payload & Crew Examples Repository
+
+We maintain a comprehensive repository with end-to-end trigger examples to help you build and test your automations:
+
+This repository contains:
+
+- **Realistic payload samples** for every supported trigger integration
+- **Ready-to-run crew implementations** that parse each payload and turn it into a business workflow
+- **Multiple scenarios per integration** (e.g., new events, updates, deletions) so you can match the shape of your data
+
+| Integration | When it fires | Payload Samples | Crew Examples |
+| :-- | :-- | :-- | :-- |
+| Gmail | New messages, thread updates | [New alerts, thread updates](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/gmail) | [`new-email-crew.py`, `gmail-alert-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/gmail) |
+| Google Calendar | Event created / updated / started / ended / cancelled | [Event lifecycle payloads](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_calendar) | [`calendar-event-crew.py`, `calendar-meeting-crew.py`, `calendar-working-location-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_calendar) |
+| Google Drive | File created / updated / deleted | [File lifecycle payloads](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_drive) | [`drive-file-crew.py`, `drive-file-deletion-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_drive) |
+| Outlook | New email, calendar event removed | [Outlook payloads](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/outlook) | [`outlook-message-crew.py`, `outlook-event-removal-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/outlook) |
+| OneDrive | File operations (create, update, share, delete) | [OneDrive payloads](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/onedrive) | [`onedrive-file-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/onedrive) |
+| HubSpot | Record created / updated (contacts, companies, deals) | [HubSpot payloads](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/hubspot) | [`hubspot-company-crew.py`, `hubspot-contact-crew.py`, `hubspot-record-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/hubspot) |
+| Microsoft Teams | Chat thread created | [Teams chat payload](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/microsoft-teams) | [`teams-chat-created-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/microsoft-teams) |
+
+Use these samples to understand payload shape, copy the matching crew, and then replace the test payload with your live trigger data.
+
+### Triggers with Crew
+
+Your existing crew definitions work seamlessly with triggers, you just need to have a task to parse the received payload:
+
+```python
+@CrewBase
+class MyAutomatedCrew:
+    @agent
+    def researcher(self) -> Agent:
+        return Agent(
+            config=self.agents_config['researcher'],
+        )
+
+    @task
+    def parse_trigger_payload(self) -> Task:
+        return Task(
+            config=self.tasks_config['parse_trigger_payload'],
+            agent=self.researcher(),
+        )
+
+    @task
+    def analyze_trigger_content(self) -> Task:
+        return Task(
+            config=self.tasks_config['analyze_trigger_data'],
+            agent=self.researcher(),
+        )
+```
+
+The crew will automatically receive and can access the trigger payload through the standard CrewAI context mechanisms.
+
+<Note>
+  Crew and Flow inputs can include `crewai_trigger_payload`. CrewAI automatically injects this payload:
+  - Tasks: appended to the first task's description by default ("Trigger Payload: {crewai_trigger_payload}")
+  - Control via `allow_crewai_trigger_context`: set `True` to always inject, `False` to never inject
+  - Flows: any `@start()` method that accepts a `crewai_trigger_payload` parameter will receive it
+</Note>
+
+### Integration with Flows
+
+For flows, you have more control over how trigger data is handled:
+
+#### Accessing Trigger Payload
+
+All `@start()` methods in your flows will accept an additional parameter called `crewai_trigger_payload`:
+
+```python
+from crewai.flow import Flow, start, listen
+
+class MyAutomatedFlow(Flow):
+    @start()
+    def handle_trigger(self, crewai_trigger_payload: dict = None):
+        """
+        This start method can receive trigger data
+        """
+        if crewai_trigger_payload:
+            # Process the trigger data
+            trigger_id = crewai_trigger_payload.get('id')
+            event_data = crewai_trigger_payload.get('payload', {})
+
+            # Store in flow state for use by other methods
+            self.state.trigger_id = trigger_id
+            self.state.trigger_type = event_data
+
+            return event_data
+
+        # Handle manual execution
+        return None
+
+    @listen(handle_trigger)
+    def process_data(self, trigger_data):
+        """
+        Process the data from the trigger
+        """
+        # ... process the trigger
+```
+
+#### Triggering Crews from Flows
+
+When kicking off a crew within a flow that was triggered, pass the trigger payload as it:
+
+```python
+@start()
+def delegate_to_crew(self, crewai_trigger_payload: dict = None):
+    """
+    Delegate processing to a specialized crew
+    """
+    crew = MySpecializedCrew()
+
+    # Pass the trigger payload to the crew
+    result = crew.crew().kickoff(
+        inputs={
+            'a_custom_parameter': "custom_value",
+            'crewai_trigger_payload': crewai_trigger_payload
+        },
+    )
+
+    return result
+```
+
+## Troubleshooting
+
+**Trigger not firing:**
+- Verify the trigger is enabled
+- Check integration connection status
+
+**Execution failures:**
+- Check the execution logs for error details
+- If you are developing, make sure the inputs include the `crewai_trigger_payload` parameter with the correct payload
+
+Automation triggers transform your CrewAI deployments into responsive, event-driven systems that can seamlessly integrate with your existing business processes and tools.
+
+<Card title="CrewAI Enterprise Trigger Examples" href="https://github.com/crewAIInc/crewai-enterprise-trigger-examples" icon="github">
+    Check them out on GitHub!
+</Card>

docs/en/enterprise/guides/azure-openai-setup.mdx

@@ -2,6 +2,7 @@
 title: "Azure OpenAI Setup"
 description: "Configure Azure OpenAI with Crew Studio for enterprise LLM connections"
 icon: "microsoft"
+mode: "wide"
 ---
 
 This guide walks you through connecting Azure OpenAI with Crew Studio for seamless enterprise AI operations.
@@ -9,12 +10,12 @@ This guide walks you through connecting Azure OpenAI with Crew Studio for seamle
 ## Setup Process
 
 <Steps>
-    <Step title="Access Azure OpenAI Studio">
-        1. In Azure, go to `Azure AI Services > select your deployment > open Azure OpenAI Studio`.
+    <Step title="Access Azure AI Foundry">
+        1. In Azure, go to [Azure AI Foundry](https://ai.azure.com/) > select your Azure OpenAI deployment.
         2. On the left menu, click `Deployments`. If you don't have one, create a deployment with your desired model.
         3. Once created, select your deployment and locate the `Target URI` and `Key` on the right side of the page. Keep this page open, as you'll need this information.
             <Frame>
-                <img src="/images/enterprise/azure-openai-studio.png" alt="Azure OpenAI Studio" />
+                <img src="/images/enterprise/azure-openai-studio.png" alt="Azure AI Foundry" />
             </Frame>
     </Step>
 
@@ -48,4 +49,4 @@ If you encounter issues:
 - Verify the Target URI format matches the expected pattern
 - Check that the API key is correct and has proper permissions
 - Ensure network access is configured to allow CrewAI connections
-- Confirm the deployment model matches what you've configured in CrewAI 
+- Confirm the deployment model matches what you've configured in CrewAI 

docs/en/enterprise/guides/build-crew.mdx

@@ -2,6 +2,7 @@
 title: "Build Crew"
 description: "A Crew is a group of agents that work together to complete a task."
 icon: "people-arrows"
+mode: "wide"
 ---
 
 ## Overview
@@ -11,14 +12,12 @@ icon: "people-arrows"
 ## Getting Started
 
 <iframe
-    width="100%"
-    height="400"
-    src="https://www.youtube.com/embed/-kSOTtYzgEw"
-    title="Building Crews with CrewAI CLI"
-    frameborder="0"
-    style={{ borderRadius: '10px' }}
-    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-    allowfullscreen
+  className="w-full aspect-video rounded-xl"
+  src="https://www.youtube.com/embed/-kSOTtYzgEw"
+  title="Building crews with the CrewAI CLI"
+  frameBorder="0"
+  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+  allowFullScreen
 ></iframe>
 
 ### Installation and Setup

docs/en/enterprise/guides/deploy-crew.mdx

@@ -2,6 +2,7 @@
 title: "Deploy Crew"
 description: "Deploying a Crew on CrewAI Enterprise"
 icon: "rocket"
+mode: "wide"
 ---
 
 <Note>

docs/en/enterprise/guides/enable-crew-studio.mdx

@@ -2,6 +2,7 @@
 title: "Enable Crew Studio"
 description: "Enabling Crew Studio on CrewAI Enterprise"
 icon: "comments"
+mode: "wide"
 ---
 
 <Tip>

docs/en/enterprise/guides/gmail-trigger.mdx

@@ -0,0 +1,85 @@
+---
+title: "Gmail Trigger"
+description: "Trigger automations when Gmail events occur (e.g., new emails, labels)."
+icon: "envelope"
+mode: "wide"
+---
+
+## Overview
+
+Use the Gmail Trigger to kick off your deployed crews when Gmail events happen in connected accounts, such as receiving a new email or messages matching a label/filter.
+
+<Tip>
+  Make sure Gmail is connected in Tools & Integrations and the trigger is enabled for your deployment.
+</Tip>
+
+## Enabling the Gmail Trigger
+
+1. Open your deployment in CrewAI Enterprise
+2. Go to the **Triggers** tab
+3. Locate **Gmail** and switch the toggle to enable
+
+<Frame>
+  <img src="/images/enterprise/trigger-selected.png" alt="Enable or disable triggers with toggle" />
+</Frame>
+
+## Example: Process new emails
+
+When a new email arrives, the Gmail Trigger will send the payload to your Crew or Flow. Below is a Crew example that parses and processes the trigger payload.
+
+```python
+@CrewBase
+class GmailProcessingCrew:
+    @agent
+    def parser(self) -> Agent:
+        return Agent(
+            config=self.agents_config['parser'],
+        )
+
+    @task
+    def parse_gmail_payload(self) -> Task:
+        return Task(
+            config=self.tasks_config['parse_gmail_payload'],
+            agent=self.parser(),
+        )
+
+    @task
+    def act_on_email(self) -> Task:
+        return Task(
+            config=self.tasks_config['act_on_email'],
+            agent=self.parser(),
+        )
+```
+
+The Gmail payload will be available via the standard context mechanisms. See the payload samples repository for structure and fields.
+
+### Sample payloads & crews
+
+The [CrewAI Enterprise Trigger Examples repository](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/gmail) includes:
+
+- `new-email-payload-1.json` / `new-email-payload-2.json` — production-style new message alerts with matching crews in `new-email-crew.py`
+- `thread-updated-sample-1.json` — follow-up messages on an existing thread, processed by `gmail-alert-crew.py`
+
+Use these samples to validate your parsing logic locally before wiring the trigger to your live Gmail accounts.
+
+## Monitoring Executions
+
+Track history and performance of triggered runs:
+
+<Frame>
+  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+</Frame>
+
+## Payload Reference
+
+See the sample payloads and field descriptions:
+
+<Card title="Gmail samples in Trigger Examples Repo" href="https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/gmail" icon="envelopes-bulk">
+    Gmail samples in Trigger Examples Repo
+</Card>
+
+## Troubleshooting
+
+- Ensure Gmail is connected in Tools & Integrations
+- Verify the Gmail Trigger is enabled on the Triggers tab
+- Check the execution logs and confirm the payload is passed as `crewai_trigger_payload`

docs/en/enterprise/guides/google-calendar-trigger.mdx

@@ -0,0 +1,65 @@
+---
+title: "Google Calendar Trigger"
+description: "Kick off crews when Google Calendar events are created, updated, or cancelled"
+icon: "calendar"
+mode: "wide"
+---
+
+## Overview
+
+Use the Google Calendar trigger to launch automations whenever calendar events change. Common use cases include briefing a team before a meeting, notifying stakeholders when a critical event is cancelled, or summarizing daily schedules.
+
+<Tip>
+  Make sure Google Calendar is connected in **Tools & Integrations** and enabled for the deployment you want to automate.
+</Tip>
+
+## Enabling the Google Calendar Trigger
+
+1. Open your deployment in CrewAI Enterprise
+2. Go to the **Triggers** tab
+3. Locate **Google Calendar** and switch the toggle to enable
+
+<Frame>
+  <img src="/images/enterprise/calendar-trigger.png" alt="Enable or disable triggers with toggle" />
+</Frame>
+
+## Example: Summarize meeting details
+
+The snippet below mirrors the `calendar-event-crew.py` example in the trigger repository. It parses the payload, analyses the attendees and timing, and produces a meeting brief for downstream tools.
+
+```python
+from calendar_event_crew import GoogleCalendarEventTrigger
+
+crew = GoogleCalendarEventTrigger().crew()
+result = crew.kickoff({
+    "crewai_trigger_payload": calendar_payload,
+})
+print(result.raw)
+```
+
+Use `crewai_trigger_payload` exactly as it is delivered by the trigger so the crew can extract the proper fields.
+
+## Sample payloads & crews
+
+The [Google Calendar examples](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_calendar) show how to handle multiple event types:
+
+- `new-event.json` → standard event creation handled by `calendar-event-crew.py`
+- `event-updated.json` / `event-started.json` / `event-ended.json` → in-flight updates processed by `calendar-meeting-crew.py`
+- `event-canceled.json` → cancellation workflow that alerts attendees via `calendar-meeting-crew.py`
+- Working location events use `calendar-working-location-crew.py` to extract on-site schedules
+
+Each crew transforms raw event metadata (attendees, rooms, working locations) into the summaries your teams need.
+
+## Monitoring Executions
+
+The **Executions** list in the deployment dashboard tracks every triggered run and surfaces payload metadata, output summaries, and errors.
+
+<Frame>
+  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+</Frame>
+
+## Troubleshooting
+
+- Ensure the correct Google account is connected and the trigger is enabled
+- Confirm your workflow handles all-day events (payloads use `start.date` and `end.date` instead of timestamps)
+- Check execution logs if reminders or attendee arrays are missing—calendar permissions can limit fields in the payload

docs/en/enterprise/guides/google-drive-trigger.mdx

@@ -0,0 +1,61 @@
+---
+title: "Google Drive Trigger"
+description: "Respond to Google Drive file events with automated crews"
+icon: "folder"
+mode: "wide"
+---
+
+## Overview
+
+Trigger your automations when files are created, updated, or removed in Google Drive. Typical workflows include summarizing newly uploaded content, enforcing sharing policies, or notifying owners when critical files change.
+
+<Tip>
+  Connect Google Drive in **Tools & Integrations** and confirm the trigger is enabled for the automation you want to monitor.
+</Tip>
+
+## Enabling the Google Drive Trigger
+
+1. Open your deployment in CrewAI Enterprise
+2. Go to the **Triggers** tab
+3. Locate **Google Drive** and switch the toggle to enable
+
+<Frame>
+  <img src="/images/enterprise/gdrive-trigger.png" alt="Enable or disable triggers with toggle" />
+</Frame>
+
+## Example: Summarize file activity
+
+The drive example crews parse the payload to extract file metadata, evaluate permissions, and publish a summary.
+
+```python
+from drive_file_crew import GoogleDriveFileTrigger
+
+crew = GoogleDriveFileTrigger().crew()
+crew.kickoff({
+    "crewai_trigger_payload": drive_payload,
+})
+```
+
+## Sample payloads & crews
+
+Explore the [Google Drive examples](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_drive) to cover different operations:
+
+- `new-file.json` → new uploads processed by `drive-file-crew.py`
+- `updated-file.json` → file edits and metadata changes handled by `drive-file-crew.py`
+- `deleted-file.json` → deletion events routed through `drive-file-deletion-crew.py`
+
+Each crew highlights the file name, operation type, owner, permissions, and security considerations so downstream systems can respond appropriately.
+
+## Monitoring Executions
+
+Track history and performance of triggered runs with the **Executions** list in the deployment dashboard.
+
+<Frame>
+  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+</Frame>
+
+## Troubleshooting
+
+- Verify Google Drive is connected and the trigger toggle is enabled
+- If a payload is missing permission data, ensure the connected account has access to the file or folder
+- The trigger sends file IDs only; use the Drive API if you need to fetch binary content during the crew run

docs/en/enterprise/guides/hubspot-trigger.mdx

@@ -2,6 +2,7 @@
 title: "HubSpot Trigger"
 description: "Trigger CrewAI crews directly from HubSpot Workflows"
 icon: "hubspot"
+mode: "wide"
 ---
 
 This guide provides a step-by-step process to set up HubSpot triggers for CrewAI Enterprise, enabling you to initiate crews directly from HubSpot Workflows.
@@ -50,4 +51,14 @@ This guide provides a step-by-step process to set up HubSpot triggers for CrewAI
 
 ## Additional Resources
 
-For more detailed information on available actions and customization options, refer to the [HubSpot Workflows Documentation](https://knowledge.hubspot.com/workflows/create-workflows). 
+### Sample payloads & crews
+
+You can jump-start development with the [HubSpot examples in the trigger repository](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/hubspot):
+
+- `record-created-contact.json`, `record-updated-contact.json` → contact lifecycle events handled by `hubspot-contact-crew.py`
+- `record-created-company.json`, `record-updated-company.json` → company enrichment flows in `hubspot-company-crew.py`
+- `record-created-deals.json`, `record-updated-deals.json` → deal pipeline automation in `hubspot-record-crew.py`
+
+Each crew demonstrates how to parse HubSpot record fields, enrich context, and return structured insights.
+
+For more detailed information on available actions and customization options, refer to the [HubSpot Workflows Documentation](https://knowledge.hubspot.com/workflows/create-workflows). 

docs/en/enterprise/guides/human-in-the-loop.mdx

@@ -2,6 +2,7 @@
 title: "HITL Workflows"
 description: "Learn how to implement Human-In-The-Loop workflows in CrewAI for enhanced decision-making"
 icon: "user-check"
+mode: "wide"
 ---
 
 Human-In-The-Loop (HITL) is a powerful approach that combines artificial intelligence with human expertise to enhance decision-making and improve task outcomes. This guide shows you how to implement HITL within CrewAI.

docs/en/enterprise/guides/kickoff-crew.mdx

@@ -2,6 +2,7 @@
 title: "Kickoff Crew"
 description: "Kickoff a Crew on CrewAI Enterprise"
 icon: "flag-checkered"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/guides/microsoft-teams-trigger.mdx

@@ -0,0 +1,52 @@
+---
+title: "Microsoft Teams Trigger"
+description: "Kick off crews from Microsoft Teams chat activity"
+icon: "microsoft"
+mode: "wide"
+---
+
+## Overview
+
+Use the Microsoft Teams trigger to start automations whenever a new chat is created. Common patterns include summarizing inbound requests, routing urgent messages to support teams, or creating follow-up tasks in other systems.
+
+<Tip>
+  Confirm Microsoft Teams is connected under **Tools & Integrations** and enabled in the **Triggers** tab for your deployment.
+</Tip>
+
+## Enabling the Microsoft Teams Trigger
+
+1. Open your deployment in CrewAI Enterprise
+2. Go to the **Triggers** tab
+3. Locate **Microsoft Teams** and switch the toggle to enable
+
+<Frame caption="Microsoft Teams trigger connection">
+  <img src="/images/enterprise/msteams-trigger.png" alt="Enable or disable triggers with toggle" />
+</Frame>
+
+## Example: Summarize a new chat thread
+
+```python
+from teams_chat_created_crew import MicrosoftTeamsChatTrigger
+
+crew = MicrosoftTeamsChatTrigger().crew()
+result = crew.kickoff({
+    "crewai_trigger_payload": teams_payload,
+})
+print(result.raw)
+```
+
+The crew parses thread metadata (subject, created time, roster) and generates an action plan for the receiving team.
+
+## Sample payloads & crews
+
+The [Microsoft Teams examples](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/microsoft-teams) include:
+
+- `chat-created.json` → chat creation payload processed by `teams-chat-created-crew.py`
+
+The crew demonstrates how to extract participants, initial messages, tenant information, and compliance metadata from the Microsoft Graph webhook payload.
+
+## Troubleshooting
+
+- Ensure the Teams connection is active; it must be refreshed if the tenant revokes permissions
+- Confirm the webhook subscription in Microsoft 365 is still valid if payloads stop arriving
+- Review execution logs for payload shape mismatches—Graph notifications may omit fields when a chat is private or restricted

docs/en/enterprise/guides/onedrive-trigger.mdx

@@ -0,0 +1,53 @@
+---
+title: "OneDrive Trigger"
+description: "Automate responses to OneDrive file activity"
+icon: "cloud"
+mode: "wide"
+---
+
+## Overview
+
+Start automations when files change inside OneDrive. You can generate audit summaries, notify security teams about external sharing, or update downstream line-of-business systems with new document metadata.
+
+<Tip>
+  Connect OneDrive in **Tools & Integrations** and toggle the trigger on for your deployment.
+</Tip>
+
+## Enabling the OneDrive Trigger
+
+1. Open your deployment in CrewAI Enterprise
+2. Go to the **Triggers** tab
+3. Locate **OneDrive** and switch the toggle to enable
+
+<Frame caption="Microsoft OneDrive trigger connection">
+  <img src="/images/enterprise/onedrive-trigger.png" alt="Enable or disable triggers with toggle" />
+</Frame>
+
+## Example: Audit file permissions
+
+```python
+from onedrive_file_crew import OneDriveFileTrigger
+
+crew = OneDriveFileTrigger().crew()
+crew.kickoff({
+    "crewai_trigger_payload": onedrive_payload,
+})
+```
+
+The crew inspects file metadata, user activity, and permission changes to produce a compliance-friendly summary.
+
+## Sample payloads & crews
+
+The [OneDrive examples](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/onedrive) showcase how to:
+
+- Parse file metadata, size, and folder paths
+- Track who created and last modified the file
+- Highlight permission and external sharing changes
+
+`onedrive-file-crew.py` bundles the analysis and summarization tasks so you can add remediation steps as needed.
+
+## Troubleshooting
+
+- Ensure the connected account has permission to read the file metadata included in the webhook
+- If the trigger fires but the payload is missing `permissions`, confirm the site-level sharing settings allow Graph to return this field
+- For large tenants, filter notifications upstream so the crew only runs on relevant directories

docs/en/enterprise/guides/outlook-trigger.mdx

@@ -0,0 +1,52 @@
+---
+title: "Outlook Trigger"
+description: "Launch automations from Outlook emails and calendar updates"
+icon: "microsoft"
+mode: "wide"
+---
+
+## Overview
+
+Automate responses when Outlook delivers a new message or when an event is removed from the calendar. Teams commonly route escalations, file tickets, or alert attendees of cancellations.
+
+<Tip>
+  Connect Outlook in **Tools & Integrations** and ensure the trigger is enabled for your deployment.
+</Tip>
+
+## Enabling the Outlook Trigger
+
+1. Open your deployment in CrewAI Enterprise
+2. Go to the **Triggers** tab
+3. Locate **Outlook** and switch the toggle to enable
+
+<Frame caption="Microsoft Outlook trigger connection">
+  <img src="/images/enterprise/outlook-trigger.png" alt="Enable or disable triggers with toggle" />
+</Frame>
+
+## Example: Summarize a new email
+
+```python
+from outlook_message_crew import OutlookMessageTrigger
+
+crew = OutlookMessageTrigger().crew()
+crew.kickoff({
+    "crewai_trigger_payload": outlook_payload,
+})
+```
+
+The crew extracts sender details, subject, body preview, and attachments before generating a structured response.
+
+## Sample payloads & crews
+
+Review the [Outlook examples](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/outlook) for two common scenarios:
+
+- `new-message.json` → new mail notifications parsed by `outlook-message-crew.py`
+- `event-removed.json` → calendar cleanup handled by `outlook-event-removal-crew.py`
+
+Each crew demonstrates how to handle Microsoft Graph payloads, normalize headers, and keep humans in-the-loop with concise summaries.
+
+## Troubleshooting
+
+- Verify the Outlook connector is still authorized; the subscription must be renewed periodically
+- If attachments are missing, confirm the webhook subscription includes the `includeResourceData` flag
+- Review execution logs when events fail to match—cancellation payloads lack attendee lists by design and the crew should account for that

docs/en/enterprise/guides/react-component-export.mdx

@@ -2,6 +2,7 @@
 title: "React Component Export"
 description: "Learn how to export and integrate CrewAI Enterprise React components into your applications"
 icon: "react"
+mode: "wide"
 ---
 
 This guide explains how to export CrewAI Enterprise crews as React components and integrate them into your own applications.

docs/en/enterprise/guides/salesforce-trigger.mdx

@@ -2,6 +2,7 @@
 title: "Salesforce Trigger"
 description: "Trigger CrewAI crews from Salesforce workflows for CRM automation"
 icon: "salesforce"
+mode: "wide"
 ---
 
 CrewAI Enterprise can be triggered from Salesforce to automate customer relationship management workflows and enhance your sales operations.
@@ -17,9 +18,14 @@ Salesforce is a leading customer relationship management (CRM) platform that hel
 
 ## Demo
 
-<Frame>
-    <iframe width="100%" height="400" src="https://www.youtube.com/embed/oJunVqjjfu4" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
-</Frame>
+<iframe
+  className="w-full aspect-video rounded-xl"
+  src="https://www.youtube.com/embed/oJunVqjjfu4"
+  title="CrewAI + Salesforce trigger demo"
+  frameBorder="0"
+  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+  allowFullScreen
+></iframe>
 
 ## Getting Started
 
@@ -41,4 +47,4 @@ Common Salesforce + CrewAI trigger scenarios include:
 
 ## Next Steps
 
-For detailed setup instructions and advanced configuration options, please contact CrewAI Enterprise support who can provide tailored guidance for your specific Salesforce environment and business needs. 
+For detailed setup instructions and advanced configuration options, please contact CrewAI Enterprise support who can provide tailored guidance for your specific Salesforce environment and business needs. 

docs/en/enterprise/guides/slack-trigger.mdx

@@ -2,6 +2,7 @@
 title: "Slack Trigger"
 description: "Trigger CrewAI crews directly from Slack using slash commands"
 icon: "slack"
+mode: "wide"
 ---
 
 This guide explains how to start a crew directly from Slack using CrewAI triggers.

docs/en/enterprise/guides/team-management.mdx

@@ -2,6 +2,7 @@
 title: "Team Management"
 description: "Learn how to invite and manage team members in your CrewAI Enterprise organization"
 icon: "users"
+mode: "wide"
 ---
 
 As an administrator of a CrewAI Enterprise account, you can easily invite new team members to join your organization. This guide will walk you through the process step-by-step.
@@ -13,14 +14,14 @@ As an administrator of a CrewAI Enterprise account, you can easily invite new te
         - Log in to your CrewAI Enterprise account
         - Look for the gear icon (⚙️) in the top right corner of the dashboard
         - Click on the gear icon to access the **Settings** page:
-            <Frame>
+            <Frame caption="Settings page">
                 <img src="/images/enterprise/settings-page.png" alt="Settings Page" />
             </Frame>
     </Step>
     <Step title="Navigate to the Members Section">
         - On the Settings page, you'll see a `Members` tab
         - Click on the `Members` tab to access the **Members** page:
-            <Frame>
+            <Frame caption="Members tab">
                 <img src="/images/enterprise/members-tab.png" alt="Members Tab" />
             </Frame>
     </Step>

docs/en/enterprise/guides/tool-repository.mdx

@@ -2,6 +2,7 @@
 title: Tool Repository
 description: "Using the Tool Repository to manage your tools"
 icon: "toolbox"
+mode: "wide"
 ---
 
 ## Overview
@@ -35,6 +36,52 @@ crewai tool install <tool-name>
 
 This installs the tool and adds it to `pyproject.toml`.
 
+You can use the tool by importing it and adding it to your agents:
+
+```python
+from your_tool.tool import YourTool
+
+custom_tool = YourTool()
+
+researcher = Agent(
+    role='Market Research Analyst',
+    goal='Provide up-to-date market analysis of the AI industry',
+    backstory='An expert analyst with a keen eye for market trends.',
+    tools=[custom_tool],
+    verbose=True
+)
+```
+
+## Adding other packages after installing a tool
+
+After installing a tool from the CrewAI Enterprise Tool Repository, you need to use the `crewai uv` command to add other packages to your project.
+Using pure `uv` commands will fail due to authentication to tool repository being handled by the CLI. By using the `crewai uv` command, you can add other packages to your project without having to worry about authentication.
+Any `uv` command can be used with the `crewai uv` command, making it a powerful tool for managing your project's dependencies without the hassle of managing authentication through environment variables or other methods.
+
+Say that you have installed a custom tool from the CrewAI Enterprise Tool Repository called "my-tool":
+
+```bash
+crewai tool install my-tool
+```
+
+And now you want to add another package to your project, you can use the following command:
+
+```bash
+crewai uv add requests
+```
+
+Other commands like `uv sync` or `uv remove` can also be used with the `crewai uv` command:
+
+```bash
+crewai uv sync
+```
+
+```bash
+crewai uv remove requests
+```
+
+This will add the package to your project and update `pyproject.toml` accordingly.
+
 ## Creating and Publishing Tools
 
 To create a new tool project:
@@ -101,7 +148,8 @@ You can check the security check status of a tool at:
 
 `CrewAI Enterprise > Tools > Your Tool > Versions`
 
-
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
   Contact our support team for assistance with API integration or troubleshooting.
 </Card>
+
+

docs/en/enterprise/guides/update-crew.mdx

@@ -2,6 +2,7 @@
 title: "Update Crew"
 description: "Updating a Crew on CrewAI Enterprise"
 icon: "pencil"
+mode: "wide"
 ---
 
 <Note>

docs/en/enterprise/guides/webhook-automation.mdx

@@ -2,6 +2,7 @@
 title: "Webhook Automation"
 description: "Automate CrewAI Enterprise workflows using webhooks with platforms like ActivePieces, Zapier, and Make.com"
 icon: "webhook"
+mode: "wide"
 ---
 
 CrewAI Enterprise allows you to automate your workflow using webhooks. This article will guide you through the process of setting up and using webhooks to kickoff your crew execution, with a focus on integration with ActivePieces, a workflow automation platform similar to Zapier and Make.com.
@@ -79,14 +80,24 @@ CrewAI Enterprise allows you to automate your workflow using webhooks. This arti
 
 ## Webhook Output Examples
 
+**Note:** Any `meta` object provided in your kickoff request will be included in all webhook payloads, allowing you to track requests and maintain context across the entire crew execution lifecycle.
+
 <Tabs>
     <Tab title="Step Webhook">
         `stepWebhookUrl` - Callback that will be executed upon each agent inner thought
 
         ```json
         {
-            "action": "**Preliminary Research Report on the Financial Industry for crewai Enterprise Solution**\n1. Industry Overview and Trends\nThe financial industry in ....\nConclusion:\nThe financial industry presents a fertile ground for implementing AI solutions like crewai, particularly in areas such as digital customer engagement, risk management, and regulatory compliance. Further engagement with the lead is recommended to better tailor the crewai solution to their specific needs and scale.",
-            "task_id": "97eba64f-958c-40a0-b61c-625fe635a3c0"
+            "prompt": "Research the financial industry for potential AI solutions",
+            "thought": "I need to conduct preliminary research on the financial industry",
+            "tool": "research_tool",
+            "tool_input": "financial industry AI solutions",
+            "result": "**Preliminary Research Report on the Financial Industry for crewai Enterprise Solution**\n1. Industry Overview and Trends\nThe financial industry in ....\nConclusion:\nThe financial industry presents a fertile ground for implementing AI solutions like crewai, particularly in areas such as digital customer engagement, risk management, and regulatory compliance. Further engagement with the lead is recommended to better tailor the crewai solution to their specific needs and scale.",
+            "kickoff_id": "97eba64f-958c-40a0-b61c-625fe635a3c0",
+            "meta": {
+                "requestId": "travel-req-123",
+                "source": "web-app"
+            }
         }
         ```
     </Tab>
@@ -95,8 +106,21 @@ CrewAI Enterprise allows you to automate your workflow using webhooks. This arti
 
         ```json
         {
-            "description": "Using the information gathered from the lead's data, conduct preliminary research on the lead's industry, company background, and potential use cases for crewai. Focus on finding relevant data that can aid in scoring the lead and planning a strategy to pitch them crewai.The financial industry presents a fertile ground for implementing AI solutions like crewai, particularly in areas such as digital customer engagement, risk management, and regulatory compliance. Further engagement with the lead is recommended to better tailor the crewai solution to their specific needs and scale.",
-            "task_id": "97eba64f-958c-40a0-b61c-625fe635a3c0"
+            "description": "Using the information gathered from the lead's data, conduct preliminary research on the lead's industry, company background, and potential use cases for crewai. Focus on finding relevant data that can aid in scoring the lead and planning a strategy to pitch them crewai.",
+            "name": "Industry Research Task",
+            "expected_output": "Detailed research report on the financial industry",
+            "summary": "The financial industry presents a fertile ground for implementing AI solutions like crewai, particularly in areas such as digital customer engagement, risk management, and regulatory compliance. Further engagement with the lead is recommended to better tailor the crewai solution to their specific needs and scale.",
+            "agent": "Research Agent",
+            "output": "**Preliminary Research Report on the Financial Industry for crewai Enterprise Solution**\n1. Industry Overview and Trends\nThe financial industry in ....\nConclusion:\nThe financial industry presents a fertile ground for implementing AI solutions like crewai, particularly in areas such as digital customer engagement, risk management, and regulatory compliance.",
+            "output_json": {
+                "industry": "financial",
+                "key_opportunities": ["digital customer engagement", "risk management", "regulatory compliance"]
+            },
+            "kickoff_id": "97eba64f-958c-40a0-b61c-625fe635a3c0",
+            "meta": {
+                "requestId": "travel-req-123",
+                "source": "web-app"
+            }
         }
         ```
     </Tab>
@@ -105,8 +129,9 @@ CrewAI Enterprise allows you to automate your workflow using webhooks. This arti
 
         ```json
         {
-            "task_id": "97eba64f-958c-40a0-b61c-625fe635a3c0",
-            "result": {
+            "kickoff_id": "97eba64f-958c-40a0-b61c-625fe635a3c0",
+            "result": "**Final Analysis Report**\n\nLead Score: Customer service enhancement and compliance are particularly relevant.\n\nTalking Points:\n- Highlight how crewai's AI solutions can transform customer service\n- Discuss crewai's potential for sustainability goals\n- Emphasize compliance capabilities\n- Stress adaptability for various operation scales",
+            "result_json": {
                 "lead_score": "Customer service enhancement, and compliance are particularly relevant.",
                 "talking_points": [
                     "Highlight how crewai's AI solutions can transform customer service with automated, personalized experiences and 24/7 support, improving both customer satisfaction and operational efficiency.",
@@ -114,6 +139,15 @@ CrewAI Enterprise allows you to automate your workflow using webhooks. This arti
                     "Emphasize crewai's ability to enhance compliance with evolving regulations through efficient data processing and reporting, reducing the risk of non-compliance penalties.",
                     "Stress the adaptability of crewai to support both extensive multinational operations and smaller, targeted projects, ensuring the solution grows with the institution's needs."
                 ]
+            },
+            "token_usage": {
+                "total_tokens": 1250,
+                "prompt_tokens": 800,
+                "completion_tokens": 450
+            },
+            "meta": {
+                "requestId": "travel-req-123",
+                "source": "web-app"
             }
         }
         ```

docs/en/enterprise/guides/zapier-trigger.mdx

@@ -2,6 +2,7 @@
 title: "Zapier Trigger"
 description: "Trigger CrewAI crews from Zapier workflows to automate cross-app workflows"
 icon: "bolt"
+mode: "wide"
 ---
 
 This guide will walk you through the process of setting up Zapier triggers for CrewAI Enterprise, allowing you to automate workflows between CrewAI Enterprise and other applications.

docs/en/enterprise/integrations/asana.mdx

@@ -2,6 +2,7 @@
 title: Asana Integration
 description: "Team task and project coordination with Asana integration for CrewAI."
 icon: "circle"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/box.mdx

@@ -2,6 +2,7 @@
 title: Box Integration
 description: "File storage and document management with Box integration for CrewAI."
 icon: "box"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/clickup.mdx

@@ -2,6 +2,7 @@
 title: ClickUp Integration
 description: "Task and productivity management with ClickUp integration for CrewAI."
 icon: "list-check"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/github.mdx

@@ -2,6 +2,7 @@
 title: GitHub Integration
 description: "Repository and issue management with GitHub integration for CrewAI."
 icon: "github"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/gmail.mdx

@@ -2,6 +2,7 @@
 title: Gmail Integration
 description: "Email and contact management with Gmail integration for CrewAI."
 icon: "envelope"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/google_calendar.mdx

@@ -2,6 +2,7 @@
 title: Google Calendar Integration
 description: "Event and schedule management with Google Calendar integration for CrewAI."
 icon: "calendar"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/google_sheets.mdx

@@ -2,6 +2,7 @@
 title: Google Sheets Integration
 description: "Spreadsheet data synchronization with Google Sheets integration for CrewAI."
 icon: "google"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/hubspot.mdx

@@ -2,6 +2,7 @@
 title: "HubSpot Integration"
 description: "Manage companies and contacts in HubSpot with CrewAI."
 icon: "briefcase"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/jira.mdx

@@ -2,6 +2,7 @@
 title: Jira Integration
 description: "Issue tracking and project management with Jira integration for CrewAI."
 icon: "bug"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/linear.mdx

@@ -2,6 +2,7 @@
 title: Linear Integration
 description: "Software project and bug tracking with Linear integration for CrewAI."
 icon: "list-check"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/notion.mdx

@@ -2,6 +2,7 @@
 title: Notion Integration
 description: "Page and database management with Notion integration for CrewAI."
 icon: "book"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/salesforce.mdx

@@ -2,6 +2,7 @@
 title: Salesforce Integration
 description: "CRM and sales automation with Salesforce integration for CrewAI."
 icon: "salesforce"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/shopify.mdx

@@ -2,6 +2,7 @@
 title: Shopify Integration
 description: "E-commerce and online store management with Shopify integration for CrewAI."
 icon: "shopify"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/slack.mdx

@@ -2,6 +2,7 @@
 title: Slack Integration
 description: "Team communication and collaboration with Slack integration for CrewAI."
 icon: "slack"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/stripe.mdx

@@ -2,6 +2,7 @@
 title: Stripe Integration
 description: "Payment processing and subscription management with Stripe integration for CrewAI."
 icon: "stripe"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/integrations/zendesk.mdx

@@ -2,6 +2,7 @@
 title: Zendesk Integration
 description: "Customer support and helpdesk management with Zendesk integration for CrewAI."
 icon: "headset"
+mode: "wide"
 ---
 
 ## Overview

docs/en/enterprise/introduction.mdx

@@ -2,6 +2,7 @@
 title: "CrewAI Enterprise"
 description: "Deploy, monitor, and scale your AI agent workflows"
 icon: "globe"
+mode: "wide"
 ---
 
 ## Introduction

docs/en/enterprise/resources/frequently-asked-questions.mdx

@@ -2,6 +2,7 @@
 title: FAQs
 description: "Frequently asked questions about CrewAI Enterprise"
 icon: "circle-question"
+mode: "wide"
 ---
 
 <AccordionGroup>
@@ -128,15 +129,14 @@ icon: "circle-question"
         </Steps>
 
         Here's a tutorial on how to consistently get structured outputs from your agents:
-        <Frame>
-            <iframe
-            height="400"
-            width="100%"
-            src="https://www.youtube.com/embed/dNpKQk5uxHw"
-            title="YouTube video player" frameborder="0"
-            allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-            allowfullscreen></iframe>
-        </Frame>
+        <iframe
+          className="w-full aspect-video rounded-xl"
+          src="https://www.youtube.com/embed/dNpKQk5uxHw"
+          title="Structured outputs in CrewAI"
+          frameBorder="0"
+          allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+          allowFullScreen
+        ></iframe>
     </Accordion>
 
     <Accordion title="How can I create custom tools for my CrewAI agents?">

docs/en/examples/cookbooks.mdx

@@ -2,16 +2,45 @@
 title: CrewAI Cookbooks
 description: Feature-focused quickstarts and notebooks for learning patterns fast.
 icon: book
+mode: "wide"
 ---
 
 ## Quickstarts & Demos
 
-<CardGroup cols={2}>
-  <Card title="Task Guardrails" icon="shield-check" href="https://github.com/crewAIInc/crewAI-quickstarts/tree/main/Task%20Guardrails"> 
-    Interactive notebooks for hands-on exploration.
+<CardGroup cols={3}>
+  <Card title="Collaboration" icon="people-arrows" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Collaboration/crewai_collaboration.ipynb">
+    Coordinate multiple agents on shared tasks. Includes notebook with end-to-end collaboration pattern.
   </Card>
+
+  <Card title="Planning" icon="timeline" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Planning/crewai_planning.ipynb">
+    Teach agents to reason about multi-step plans before execution using the planning toolkit.
+  </Card>
+
+  <Card title="Reasoning" icon="lightbulb" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Reasoning/crewai_reasoning.ipynb">
+    Explore self-reflection loops, critique prompts, and structured thinking patterns.
+  </Card>
+</CardGroup>
+
+<CardGroup cols={3}>
+  <Card title="Structured Guardrails" icon="shield-check" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Guardrails/task_guardrails.ipynb">
+    Apply task-level guardrails with retries, validation functions, and safe fallbacks.
+  </Card>
+
+  <Card title="Gemini Search & Grounding" icon="magnifying-glass" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Custom%20LLM/gemini_search_grounding_crewai.ipynb">
+    Connect CrewAI to Gemini with search grounding for factual, citation-rich outputs.
+  </Card>
+
+  <Card title="Gemini Video Summaries" icon="video" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Custom%20LLM/summarize_video_gemini_crewai.ipynb">
+    Generate video recaps using Gemini multimodal LLM and CrewAI orchestration.
+  </Card>
+</CardGroup>
+
+<CardGroup cols={2}>
   <Card title="Browse Quickstarts" icon="bolt" href="https://github.com/crewAIInc/crewAI-quickstarts">
-    Feature demos and small projects showcasing specific CrewAI capabilities.
+    View all notebooks and feature demos showcasing specific CrewAI capabilities.
+  </Card>
+  <Card title="Request a cookbook" icon="message-plus" href="https://community.crewai.com">
+    Missing a pattern? Drop a request in the community forum and we’ll expand the library.
   </Card>
 </CardGroup>
 
@@ -19,4 +48,3 @@ icon: book
 Use Cookbooks to learn a pattern quickly, then jump to Full Examples for production‑grade implementations.
 </Tip>
 
-

docs/en/examples/example.mdx

@@ -2,6 +2,7 @@
 title: CrewAI Examples
 description: Explore curated examples organized by Crews, Flows, Integrations, and Notebooks.
 icon: rocket-launch
+mode: "wide"
 ---
 
 ## Crews

docs/en/guides/advanced/customizing-prompts.mdx

@@ -2,6 +2,7 @@
 title: Customizing Prompts
 description: Dive deeper into low-level prompt customization for CrewAI, enabling super custom and complex use cases for different models and languages.
 icon: message-pen
+mode: "wide"
 ---
 
 ## Why Customize Prompts?

docs/en/guides/advanced/fingerprinting.mdx

@@ -2,6 +2,7 @@
 title: Fingerprinting
 description: Learn how to use CrewAI's fingerprinting system to uniquely identify and track components throughout their lifecycle.
 icon: fingerprint
+mode: "wide"
 ---
 
 ## Overview

docs/en/guides/agents/crafting-effective-agents.mdx

@@ -2,6 +2,7 @@
 title: Crafting Effective Agents
 description: Learn best practices for designing powerful, specialized AI agents that collaborate effectively to solve complex problems.
 icon: robot
+mode: "wide"
 ---
 
 ## The Art and Science of Agent Design

docs/en/guides/concepts/evaluating-use-cases.mdx

@@ -2,6 +2,7 @@
 title: Evaluating Use Cases for CrewAI
 description: Learn how to assess your AI application needs and choose the right approach between Crews and Flows based on complexity and precision requirements.
 icon: scale-balanced
+mode: "wide"
 ---
 
 ## Understanding the Decision Framework

docs/en/guides/crews/first-crew.mdx

@@ -2,6 +2,7 @@
 title: Build Your First Crew
 description: Step-by-step tutorial to create a collaborative AI team that works together to solve complex problems.
 icon: users-gear
+mode: "wide"
 ---
 
 ## Unleashing the Power of Collaborative AI

docs/en/guides/flows/first-flow.mdx

@@ -2,6 +2,7 @@
 title: Build Your First Flow
 description: Learn how to create structured, event-driven workflows with precise control over execution.
 icon: diagram-project
+mode: "wide"
 ---
 
 ## Taking Control of AI Workflows with Flows

docs/en/guides/flows/mastering-flow-state.mdx

@@ -2,6 +2,7 @@
 title: Mastering Flow State Management
 description: A comprehensive guide to managing, persisting, and leveraging state in CrewAI Flows for building robust AI applications.
 icon: diagram-project
+mode: "wide"
 ---
 
 ## Understanding the Power of State in Flows
@@ -348,6 +349,31 @@ class SelectivePersistFlow(Flow):
 
 ## Advanced State Patterns
 
+### Conditional starts and resumable execution
+
+Flows support conditional `@start()` and resumable execution for HITL/cyclic scenarios:
+
+```python
+from crewai.flow.flow import Flow, start, listen, and_, or_
+
+class ResumableFlow(Flow):
+    @start()  # unconditional start
+    def init(self):
+        ...
+
+    # Conditional start: run after "init" or external trigger name
+    @start("init")
+    def maybe_begin(self):
+        ...
+
+    @listen(and_(init, maybe_begin))
+    def proceed(self):
+        ...
+```
+
+- Conditional `@start()` accepts a method name, a router label, or a callable condition.
+- During resume, listeners continue from prior checkpoints; cycle/router branches honor resumption flags.
+
 ### State-Based Conditional Logic
 
 You can use state to implement complex conditional logic in your flows:

docs/en/installation.mdx

@@ -2,20 +2,19 @@
 title: Installation
 description: Get started with CrewAI - Install, configure, and build your first AI crew
 icon: wrench
+mode: "wide"
 ---
 
 ## Video Tutorial
 Watch this video tutorial for a step-by-step demonstration of the installation process:
 
 <iframe
-  width="100%"
-  height="400"
+  className="w-full aspect-video rounded-xl"
   src="https://www.youtube.com/embed/-kSOTtYzgEw"
   title="CrewAI Installation Guide"
-  frameborder="0"
-  style={{ borderRadius: '10px' }}
+  frameBorder="0"
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-  allowfullscreen
+  allowFullScreen
 ></iframe>
 
 ## Text Tutorial
@@ -30,6 +29,12 @@ Watch this video tutorial for a step-by-step demonstration of the installation p
   If you need to update Python, visit [python.org/downloads](https://python.org/downloads)
 </Note>
 
+<Note>
+  **OpenAI SDK Requirement**
+
+  CrewAI 0.175.0 requires `openai >= 1.13.3`. If you manage dependencies yourself, ensure your environment satisfies this constraint to avoid import/runtime issues.
+</Note>
+
 CrewAI uses the `uv` as its dependency management and package handling tool. It simplifies project setup and execution, offering a seamless experience.
 
 If you haven't installed `uv` yet, follow **step 1** to quickly get it set up on your system, else you can skip to **step 2**.

docs/en/introduction.mdx

@@ -2,6 +2,7 @@
 title: Introduction
 description: Build AI agent teams that work together to tackle complex tasks
 icon: handshake
+mode: "wide"
 ---
 
 # What is CrewAI?

docs/en/learn/before-and-after-kickoff-hooks.mdx

@@ -1,6 +1,7 @@
 ---
 title: Before and After Kickoff Hooks
 description: Learn how to use before and after kickoff hooks in CrewAI
+mode: "wide"
 ---
 
 CrewAI provides hooks that allow you to execute code before and after a crew's kickoff. These hooks are useful for preprocessing inputs or post-processing results.

docs/en/learn/bring-your-own-agent.mdx

@@ -2,6 +2,7 @@
 title: Bring your own agent
 description: Learn how to bring your own agents that work within a Crew.
 icon: robots
+mode: "wide"
 ---
 
 Interoperability is a core concept in CrewAI. This guide will show you how to bring your own agents that work within a Crew.

docs/en/learn/coding-agents.mdx

@@ -2,6 +2,7 @@
 title: Coding Agents
 description: Learn how to enable your CrewAI Agents to write and execute code, and explore advanced features for enhanced functionality.
 icon: rectangle-code
+mode: "wide"
 ---
 
 ## Introduction

docs/en/learn/conditional-tasks.mdx

@@ -2,6 +2,7 @@
 title: Conditional Tasks
 description: Learn how to use conditional tasks in a crewAI kickoff
 icon: diagram-subtask
+mode: "wide"
 ---
 
 ## Introduction

docs/en/learn/create-custom-tools.mdx

@@ -2,6 +2,7 @@
 title: Create Custom Tools
 description: Comprehensive guide on crafting, using, and managing custom tools within the CrewAI framework, including new functionalities and error handling.
 icon: hammer
+mode: "wide"
 ---
 
 ## Creating and Utilizing Tools in CrewAI