Deployed 9913310 with MkDocs version: 1.6.1

.editorconfig

@@ -1,14 +0,0 @@
-# .editorconfig
-root = true
-
-# All files
-[*]
-charset = utf-8
-end_of_line = lf
-insert_final_newline = true
-trim_trailing_whitespace = true
-
-# Python files
-[*.py]
-indent_style = space
-indent_size = 2

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -1,115 +0,0 @@
-name: Bug report
-description: Create a report to help us improve CrewAI
-title: "[BUG]"
-labels: ["bug"]
-assignees: []
-body:
-  - type: textarea
-    id: description
-    attributes:
-      label: Description
-      description: Provide a clear and concise description of what the bug is.
-    validations:
-      required: true
-  - type: textarea
-    id: steps-to-reproduce
-    attributes:
-      label: Steps to Reproduce
-      description: Provide a step-by-step process to reproduce the behavior.
-      placeholder: |
-        1. Go to '...'
-        2. Click on '....'
-        3. Scroll down to '....'
-        4. See error
-    validations:
-      required: true
-  - type: textarea
-    id: expected-behavior
-    attributes:
-      label: Expected behavior
-      description: A clear and concise description of what you expected to happen.
-    validations:
-      required: true
-  - type: textarea
-    id: screenshots-code
-    attributes:
-      label: Screenshots/Code snippets
-      description: If applicable, add screenshots or code snippets to help explain your problem.
-    validations:
-      required: true
-  - type: dropdown
-    id: os
-    attributes:
-      label: Operating System
-      description: Select the operating system you're using
-      options:
-        - Ubuntu 20.04
-        - Ubuntu 22.04
-        - Ubuntu 24.04
-        - macOS Catalina
-        - macOS Big Sur
-        - macOS Monterey
-        - macOS Ventura
-        - macOS Sonoma
-        - Windows 10
-        - Windows 11
-        - Other (specify in additional context)
-    validations:
-      required: true
-  - type: dropdown
-    id: python-version
-    attributes:
-      label: Python Version
-      description: Version of Python your Crew is running on
-      options:
-        - '3.10'
-        - '3.11'
-        - '3.12'
-    validations:
-      required: true
-  - type: input
-    id: crewai-version
-    attributes:
-      label: crewAI Version
-      description: What version of CrewAI are you using
-    validations:
-      required: true
-  - type: input
-    id: crewai-tools-version
-    attributes:
-      label: crewAI Tools Version
-      description: What version of CrewAI Tools are you using 
-    validations:
-      required: true
-  - type: dropdown
-    id: virtual-environment
-    attributes:
-      label: Virtual Environment
-      description: What Virtual Environment are you running your crew in.
-      options:
-        - Venv
-        - Conda
-        - Poetry
-    validations:
-      required: true
-  - type: textarea
-    id: evidence
-    attributes:
-      label: Evidence
-      description: Include relevant information, logs or error messages. These can be screenshots.
-    validations:
-      required: true
-  - type: textarea
-    id: possible-solution
-    attributes:
-      label: Possible Solution
-      description: Have a solution in mind? Please suggest it here, or write "None".
-    validations:
-      required: true
-  - type: textarea
-    id: additional-context
-    attributes:
-      label: Additional context
-      description: Add any other context about the problem here.
-    validations:
-      required: true

.github/ISSUE_TEMPLATE/config.yml

@@ -1 +0,0 @@
-blank_issues_enabled: false

.github/ISSUE_TEMPLATE/feature_request.yml

@@ -1,65 +0,0 @@
-name: Feature request
-description: Suggest a new feature for CrewAI
-title: "[FEATURE]"
-labels: ["feature-request"]
-assignees: []
-body:
-  - type: markdown
-    attributes:
-      value: |
-        Thanks for taking the time to fill out this feature request!
-  - type: dropdown
-    id: feature-area
-    attributes:
-      label: Feature Area
-      description: Which area of CrewAI does this feature primarily relate to?
-      options:
-        - Core functionality
-        - Agent capabilities
-        - Task management
-        - Integration with external tools
-        - Performance optimization
-        - Documentation
-        - Other (please specify in additional context)
-    validations:
-      required: true
-  - type: textarea
-    id: problem
-    attributes:
-      label: Is your feature request related to a an existing bug? Please link it here.
-      description: A link to the bug or NA if not related to an existing bug.
-    validations:
-      required: true
-  - type: textarea
-    id: solution
-    attributes:
-      label: Describe the solution you'd like
-      description: A clear and concise description of what you want to happen.
-    validations:
-      required: true
-  - type: textarea
-    id: alternatives
-    attributes:
-      label: Describe alternatives you've considered
-      description: A clear and concise description of any alternative solutions or features you've considered.
-    validations:
-      required: false
-  - type: textarea
-    id: context
-    attributes:
-      label: Additional context
-      description: Add any other context, screenshots, or examples about the feature request here.
-    validations:
-      required: false
-  - type: dropdown
-    id: willingness-to-contribute
-    attributes:
-      label: Willingness to Contribute
-      description: Would you be willing to contribute to the implementation of this feature?
-      options:
-        - Yes, I'd be happy to submit a pull request
-        - I could provide more detailed specifications
-        - I can test the feature once it's implemented
-        - No, I'm just suggesting the idea
-    validations:
-      required: true

.github/codeql/codeql-config.yml

@@ -1,21 +0,0 @@
-name: "CodeQL Config"
-
-paths-ignore:
-  # Ignore template files - these are boilerplate code that shouldn't be analyzed
-  - "src/crewai/cli/templates/**"
-  # Ignore test cassettes - these are test fixtures/recordings
-  - "tests/cassettes/**"
-  # Ignore cache and build artifacts
-  - ".cache/**"
-  # Ignore documentation build artifacts
-  - "docs/.cache/**"
-  
-paths:
-  # Include all Python source code
-  - "src/**"
-  # Include tests (but exclude cassettes)
-  - "tests/**"
-
-# Configure specific queries or packs if needed
-# queries:
-#   - uses: security-and-quality

.github/security.md

@@ -1,50 +0,0 @@
-## CrewAI Security Policy
-
-We are committed to protecting the confidentiality, integrity, and availability of the CrewAI ecosystem. This policy explains how to report potential vulnerabilities and what you can expect from us when you do.
-
-### Scope
-
-We welcome reports for vulnerabilities that could impact:
-
-- CrewAI-maintained source code and repositories
-- CrewAI-operated infrastructure and services
-- Official CrewAI releases, packages, and distributions
-
-Issues affecting clearly unaffiliated third-party services or user-generated content are out of scope, unless you can demonstrate a direct impact on CrewAI systems or customers.
-
-### How to Report
-
-- **Please do not** disclose vulnerabilities via public GitHub issues, pull requests, or social media.
-- Email detailed reports to **security@crewai.com** with the subject line `Security Report`.
-- If you need to share large files or sensitive artifacts, mention it in your email and we will coordinate a secure transfer method.
-
-### What to Include
-
-Providing comprehensive information enables us to validate the issue quickly:
-
-- **Vulnerability overview** — a concise description and classification (e.g., RCE, privilege escalation)
-- **Affected components** — repository, branch, tag, or deployed service along with relevant file paths or endpoints
-- **Reproduction steps** — detailed, step-by-step instructions; include logs, screenshots, or screen recordings when helpful
-- **Proof-of-concept** — exploit details or code that demonstrates the impact (if available)
-- **Impact analysis** — severity assessment, potential exploitation scenarios, and any prerequisites or special configurations
-
-### Our Commitment
-
-- **Acknowledgement:** We aim to acknowledge your report within two business days.
-- **Communication:** We will keep you informed about triage results, remediation progress, and planned release timelines.
-- **Resolution:** Confirmed vulnerabilities will be prioritized based on severity and fixed as quickly as possible.
-- **Recognition:** We currently do not run a bug bounty program; any rewards or recognition are issued at CrewAI's discretion.
-
-### Coordinated Disclosure
-
-We ask that you allow us a reasonable window to investigate and remediate confirmed issues before any public disclosure. We will coordinate publication timelines with you whenever possible.
-
-### Safe Harbor
-
-We will not pursue or support legal action against individuals who, in good faith:
-
-- Follow this policy and refrain from violating any applicable laws
-- Avoid privacy violations, data destruction, or service disruption
-- Limit testing to systems in scope and respect rate limits and terms of service
-
-If you are unsure whether your testing is covered, please contact us at **security@crewai.com** before proceeding.

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

@@ -1,48 +0,0 @@
-name: Build uv cache
-
-on:
-  push:
-    branches:
-      - main
-    paths:
-      - "uv.lock"
-      - "pyproject.toml"
-  schedule:
-    - cron: "0 0 */5 * *"  # Run every 5 days at midnight UTC to prevent cache expiration
-  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

@@ -1,103 +0,0 @@
-# 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:
-      - "src/crewai/cli/templates/**"
-  pull_request:
-    branches: [ "main" ]
-    paths-ignore:
-      - "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: ${{ matrix.build-mode }}
-        config-file: ./.github/codeql/codeql-config.yml
-        # If you wish to specify custom queries, you can do so here or in a config file.
-        # By default, queries listed here will override any specified in a config file.
-        # Prefix the list here with "+" to use these queries and those in the config file.
-
-        # For more details on CodeQL's query packs, refer to: https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
-        # queries: security-extended,security-and-quality
-
-    # If the analyze step fails for one of the languages you are analyzing with
-    # "We were unable to automatically build your code", modify the matrix above
-    # to set the build mode to "manual" for that language. Then modify this step
-    # to build your code.
-    # ℹ️ Command-line programs to run using the OS shell.
-    # 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
-    - if: matrix.build-mode == 'manual'
-      shell: bash
-      run: |
-        echo 'If you are using a "manual" build mode for one or more of the' \
-          'languages you are analyzing, replace this with the commands to build' \
-          'your code, for example:'
-        echo '  make bootstrap'
-        echo '  make release'
-        exit 1
-
-    - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@v3
-      with:
-        category: "/language:${{matrix.language}}"

.github/workflows/linter.yml

@@ -1,68 +0,0 @@
-name: Lint
-
-on: [pull_request]
-
-permissions:
-  contents: read
-
-jobs:
-  lint:
-    runs-on: ubuntu-latest
-    env:
-      TARGET_BRANCH: ${{ github.event.pull_request.base.ref }}
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-
-      - name: Fetch Target Branch
-        run: git fetch origin $TARGET_BRANCH --depth=1
-
-      - name: Restore global uv cache
-        id: cache-restore
-        uses: actions/cache/restore@v4
-        with:
-          path: |
-            ~/.cache/uv
-            ~/.local/share/uv
-            .venv
-          key: uv-main-py3.11-${{ 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
-        run: |
-          merge_base=$(git merge-base origin/"$TARGET_BRANCH" HEAD)
-          changed_files=$(git diff --name-only --diff-filter=ACMRTUB "$merge_base" | grep '\.py$' || true)
-          echo "files<<EOF" >> $GITHUB_OUTPUT
-          echo "$changed_files" >> $GITHUB_OUTPUT
-          echo "EOF" >> $GITHUB_OUTPUT
-
-      - 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{} 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/notify-downstream.yml

@@ -1,33 +0,0 @@
-name: Notify Downstream
-
-on:
-  push:
-    branches:
-      - main
-
-permissions:
-  contents: read
-
-jobs:
-  notify-downstream:
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Generate GitHub App token
-        id: app-token
-        uses: tibdex/github-app-token@v2
-        with:
-          app_id: ${{ secrets.OSS_SYNC_APP_ID }}
-          private_key: ${{ secrets.OSS_SYNC_APP_PRIVATE_KEY }}
-
-      - name: Notify Repo B
-        uses: peter-evans/repository-dispatch@v3
-        with:
-          token: ${{ steps.app-token.outputs.token }}
-          repository: ${{ secrets.OSS_SYNC_DOWNSTREAM_REPO }}
-          event-type: upstream-commit
-          client-payload: |
-            {
-              "commit_sha": "${{ github.sha }}"
-            }
-

.github/workflows/stale.yml

@@ -1,29 +0,0 @@
-name: Mark stale issues and pull requests
-
-permissions:
-  contents: write
-  issues: write
-  pull-requests: write
-
-on:
-  schedule:
-    - cron: '10 12 * * *'
-  workflow_dispatch:
-
-jobs:
-  stale:
-    runs-on: ubuntu-latest
-    steps:
-    - uses: actions/stale@v9
-      with:
-        repo-token: ${{ secrets.GITHUB_TOKEN }}
-        stale-issue-label: 'no-issue-activity'
-        stale-issue-message: 'This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 5 days.'
-        close-issue-message: 'This issue was closed because it has been stalled for 5 days with no activity.'
-        days-before-issue-stale: 30
-        days-before-issue-close: 5
-        stale-pr-label: 'no-pr-activity'
-        stale-pr-message: 'This PR is stale because it has been open for 45 days with no activity.'
-        days-before-pr-stale: 45
-        days-before-pr-close: -1
-        operations-per-run: 1200

.github/workflows/tests.yml

@@ -1,97 +0,0 @@
-name: Run Tests
-
-on: [pull_request]
-
-permissions:
-  contents: read
-
-env:
-  OPENAI_API_KEY: fake-api-key
-  PYTHONUNBUFFERED: 1
-
-jobs:
-  tests:
-    name: tests (${{ matrix.python-version }})
-    runs-on: ubuntu-latest
-    timeout-minutes: 15
-    strategy:
-      fail-fast: true
-      matrix:
-        python-version: ['3.10', '3.11', '3.12', '3.13']
-        group: [1, 2, 3, 4, 5, 6, 7, 8]
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0  # Fetch all history for proper diff
-
-      - name: Restore global uv cache
-        id: cache-restore
-        uses: actions/cache/restore@v4
-        with:
-          path: |
-            ~/.cache/uv
-            ~/.local/share/uv
-            .venv
-          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
-          restore-keys: |
-            uv-main-py${{ matrix.python-version }}-
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v6
-        with:
-          version: "0.8.4"
-          python-version: ${{ matrix.python-version }}
-          enable-cache: false
-
-      - name: Install the project
-        run: uv sync --all-groups --all-extras
-
-      - name: Restore test durations
-        uses: actions/cache/restore@v4
-        with:
-          path: .test_durations_py*
-          key: test-durations-py${{ matrix.python-version }}
-
-      - name: Run tests (group ${{ matrix.group }} of 8)
-        run: |
-          PYTHON_VERSION_SAFE=$(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
-          
-          uv run pytest \
-            --block-network \
-            --timeout=30 \
-            -vv \
-            --splits 8 \
-            --group ${{ matrix.group }} \
-            $DURATIONS_ARG \
-            --durations=10 \
-            -n auto \
-            --maxfail=3
-
-      - name: Save uv caches
-        if: steps.cache-restore.outputs.cache-hit != 'true'
-        uses: actions/cache/save@v4
-        with:
-          path: |
-            ~/.cache/uv
-            ~/.local/share/uv
-            .venv
-          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}

.github/workflows/type-checker.yml

@@ -1,101 +0,0 @@
-name: Run Type Checks
-
-on: [pull_request]
-
-permissions:
-  contents: read
-
-jobs:
-  type-checker-matrix:
-    name: type-checker (${{ matrix.python-version }})
-    runs-on: ubuntu-latest
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ["3.10", "3.11", "3.12", "3.13"]
-
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0 # Fetch all history for proper diff
-
-      - name: Restore global uv cache
-        id: cache-restore
-        uses: actions/cache/restore@v4
-        with:
-          path: |
-            ~/.cache/uv
-            ~/.local/share/uv
-            .venv
-          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
-          restore-keys: |
-            uv-main-py${{ matrix.python-version }}-
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v6
-        with:
-          version: "0.8.4"
-          python-version: ${{ matrix.python-version }}
-          enable-cache: false
-
-      - name: Install dependencies
-        run: uv sync --all-groups --all-extras
-
-      - name: Get changed Python files
-        id: changed-files
-        run: |
-          # Get the list of changed Python files compared to the base branch
-          echo "Fetching changed files..."
-          git diff --name-only --diff-filter=ACMRT origin/${{ github.base_ref }}...HEAD -- '*.py' > changed_files.txt
-
-          # 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

@@ -1,71 +0,0 @@
-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

@@ -1,29 +0,0 @@
-.DS_Store
-.pytest_cache
-__pycache__
-dist/
-lib/
-.env
-assets/*
-.idea
-test/
-docs_crew/
-chroma.sqlite3
-old_en.json
-db/
-test.py
-rc-tests/*
-*.pkl
-temp/*
-.vscode/*
-crew_tasks_output.json
-.codesight
-.mypy_cache
-.ruff_cache
-.venv
-test_flow.html
-crewairules.mdc
-plan.md
-conceptual_plan.md
-build_image
-chromadb-*.lock

.pre-commit-config.yaml

@@ -1,19 +0,0 @@
-repos:
-  - repo: local
-    hooks:
-      - id: ruff
-        name: ruff
-        entry: uv run ruff check
-        language: system
-        types: [python]
-      - id: ruff-format
-        name: ruff-format
-        entry: uv run ruff format
-        language: system
-        types: [python]
-      - id: mypy
-        name: mypy
-        entry: uv run mypy
-        language: system
-        types: [python]
-        exclude: ^tests/

LICENSE

@@ -1,19 +0,0 @@
-Copyright (c) 2025 crewAI, Inc.
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.

README.md

@@ -1,777 +0,0 @@
-<p align="center">
-  <a href="https://github.com/crewAIInc/crewAI">
-    <img src="docs/images/crewai_logo.png" width="600px" alt="Open source Multi-AI Agent orchestration framework">
-  </a>
-</p>
-<p align="center" style="display: flex; justify-content: center; gap: 20px; align-items: center;">
-  <a href="https://trendshift.io/repositories/11239" target="_blank">
-    <img src="https://trendshift.io/api/badge/repositories/11239" alt="crewAIInc%2FcrewAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/>
-  </a>
-</p>
-
-<p align="center">
-  <a href="https://crewai.com">Homepage</a>
-  ·
-  <a href="https://docs.crewai.com">Docs</a>
-  ·
-  <a href="https://app.crewai.com">Start Cloud Trial</a>
-  ·
-  <a href="https://blog.crewai.com">Blog</a>
-  ·
-  <a href="https://community.crewai.com">Forum</a>
-</p>
-
-<p align="center">
-  <a href="https://github.com/crewAIInc/crewAI">
-    <img src="https://img.shields.io/github/stars/crewAIInc/crewAI" alt="GitHub Repo stars">
-  </a>
-  <a href="https://github.com/crewAIInc/crewAI/network/members">
-    <img src="https://img.shields.io/github/forks/crewAIInc/crewAI" alt="GitHub forks">
-  </a>
-  <a href="https://github.com/crewAIInc/crewAI/issues">
-    <img src="https://img.shields.io/github/issues/crewAIInc/crewAI" alt="GitHub issues">
-  </a>
-  <a href="https://github.com/crewAIInc/crewAI/pulls">
-    <img src="https://img.shields.io/github/issues-pr/crewAIInc/crewAI" alt="GitHub pull requests">
-  </a>
-  <a href="https://opensource.org/licenses/MIT">
-    <img src="https://img.shields.io/badge/License-MIT-green.svg" alt="License: MIT">
-  </a>
-</p>
-
-<p align="center">
-  <a href="https://pypi.org/project/crewai/">
-    <img src="https://img.shields.io/pypi/v/crewai" alt="PyPI version">
-  </a>
-  <a href="https://pypi.org/project/crewai/">
-    <img src="https://img.shields.io/pypi/dm/crewai" alt="PyPI downloads">
-  </a>
-  <a href="https://twitter.com/crewAIInc">
-    <img src="https://img.shields.io/twitter/follow/crewAIInc?style=social" alt="Twitter Follow">
-  </a>
-</p>
-
-### Fast and Flexible Multi-Agent Automation Framework
-
-> CrewAI is a lean, lightning-fast Python framework built entirely from scratch—completely **independent of LangChain or other agent frameworks**.
-> It empowers developers with both high-level simplicity and precise low-level control, ideal for creating autonomous AI agents tailored to any scenario.
-
-- **CrewAI Crews**: Optimize for autonomy and collaborative intelligence.
-- **CrewAI Flows**: Enable granular, event-driven control, single LLM calls for precise task orchestration and supports Crews natively
-
-With over 100,000 developers certified through our community courses at [learn.crewai.com](https://learn.crewai.com), CrewAI is rapidly becoming the
-standard for enterprise-ready AI automation.
-
-# CrewAI AMP Suite
-
-CrewAI AMP Suite is a comprehensive bundle tailored for organizations that require secure, scalable, and easy-to-manage agent-driven automation.
-
-You can try one part of the suite the [Crew Control Plane for free](https://app.crewai.com)
-
-## Crew Control Plane Key Features:
-
-- **Tracing & Observability**: Monitor and track your AI agents and workflows in real-time, including metrics, logs, and traces.
-- **Unified Control Plane**: A centralized platform for managing, monitoring, and scaling your AI agents and workflows.
-- **Seamless Integrations**: Easily connect with existing enterprise systems, data sources, and cloud infrastructure.
-- **Advanced Security**: Built-in robust security and compliance measures ensuring safe deployment and management.
-- **Actionable Insights**: Real-time analytics and reporting to optimize performance and decision-making.
-- **24/7 Support**: Dedicated enterprise support to ensure uninterrupted operation and quick resolution of issues.
-- **On-premise and Cloud Deployment Options**: Deploy CrewAI AMP on-premise or in the cloud, depending on your security and compliance requirements.
-
-CrewAI AMP is designed for enterprises seeking a powerful, reliable solution to transform complex business processes into efficient,
-intelligent automations.
-
-## Table of contents
-
-- [Why CrewAI?](#why-crewai)
-- [Getting Started](#getting-started)
-- [Key Features](#key-features)
-- [Understanding Flows and Crews](#understanding-flows-and-crews)
-- [CrewAI vs LangGraph](#how-crewai-compares)
-- [Examples](#examples)
-  - [Quick Tutorial](#quick-tutorial)
-  - [Write Job Descriptions](#write-job-descriptions)
-  - [Trip Planner](#trip-planner)
-  - [Stock Analysis](#stock-analysis)
-  - [Using Crews and Flows Together](#using-crews-and-flows-together)
-- [Connecting Your Crew to a Model](#connecting-your-crew-to-a-model)
-- [How CrewAI Compares](#how-crewai-compares)
-- [Frequently Asked Questions (FAQ)](#frequently-asked-questions-faq)
-- [Contribution](#contribution)
-- [Telemetry](#telemetry)
-- [License](#license)
-
-## Why CrewAI?
-
-<div align="center" style="margin-bottom: 30px;">
-  <img src="docs/images/asset.png" alt="CrewAI Logo" width="100%">
-</div>
-
-CrewAI unlocks the true potential of multi-agent automation, delivering the best-in-class combination of speed, flexibility, and control with either Crews of AI Agents or Flows of Events:
-
-- **Standalone Framework**: Built from scratch, independent of LangChain or any other agent framework.
-- **High Performance**: Optimized for speed and minimal resource usage, enabling faster execution.
-- **Flexible Low Level Customization**: Complete freedom to customize at both high and low levels - from overall workflows and system architecture to granular agent behaviors, internal prompts, and execution logic.
-- **Ideal for Every Use Case**: Proven effective for both simple tasks and highly complex, real-world, enterprise-grade scenarios.
-- **Robust Community**: Backed by a rapidly growing community of over **100,000 certified** developers offering comprehensive support and resources.
-
-CrewAI empowers developers and enterprises to confidently build intelligent automations, bridging the gap between simplicity, flexibility, and performance.
-
-## Getting Started
-
-Setup and run your first CrewAI agents by following this tutorial.
-
-[![CrewAI Getting Started Tutorial](https://img.youtube.com/vi/-kSOTtYzgEw/hqdefault.jpg)](https://www.youtube.com/watch?v=-kSOTtYzgEw "CrewAI Getting Started Tutorial")
-
-###
- Learning Resources
-
-Learn CrewAI through our comprehensive courses:
-
-- [Multi AI Agent Systems with CrewAI](https://www.deeplearning.ai/short-courses/multi-ai-agent-systems-with-crewai/) - Master the fundamentals of multi-agent systems
-- [Practical Multi AI Agents and Advanced Use Cases](https://www.deeplearning.ai/short-courses/practical-multi-ai-agents-and-advanced-use-cases-with-crewai/) - Deep dive into advanced implementations
-
-### Understanding Flows and Crews
-
-CrewAI offers two powerful, complementary approaches that work seamlessly together to build sophisticated AI applications:
-
-1. **Crews**: Teams of AI agents with true autonomy and agency, working together to accomplish complex tasks through role-based collaboration. Crews enable:
-
-   - Natural, autonomous decision-making between agents
-   - Dynamic task delegation and collaboration
-   - Specialized roles with defined goals and expertise
-   - Flexible problem-solving approaches
-2. **Flows**: Production-ready, event-driven workflows that deliver precise control over complex automations. Flows provide:
-
-   - Fine-grained control over execution paths for real-world scenarios
-   - Secure, consistent state management between tasks
-   - Clean integration of AI agents with production Python code
-   - Conditional branching for complex business logic
-
-The true power of CrewAI emerges when combining Crews and Flows. This synergy allows you to:
-
-- Build complex, production-grade applications
-- Balance autonomy with precise control
-- Handle sophisticated real-world scenarios
-- Maintain clean, maintainable code structure
-
-### Getting Started with Installation
-
-To get started with CrewAI, follow these simple steps:
-
-### 1. Installation
-
-Ensure you have Python >=3.10 <3.14 installed on your system. CrewAI uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
-
-First, install CrewAI:
-
-```shell
-pip install crewai
-```
-
-If you want to install the 'crewai' package along with its optional features that include additional tools for agents, you can do so by using the following command:
-
-```shell
-pip install 'crewai[tools]'
-```
-
-The command above installs the basic package and also adds extra components which require more dependencies to function.
-
-### Troubleshooting Dependencies
-
-If you encounter issues during installation or usage, here are some common solutions:
-
-#### Common Issues
-
-1. **ModuleNotFoundError: No module named 'tiktoken'**
-
-   - Install tiktoken explicitly: `pip install 'crewai[embeddings]'`
-   - If using embedchain or other tools: `pip install 'crewai[tools]'`
-2. **Failed building wheel for tiktoken**
-
-   - Ensure Rust compiler is installed (see installation steps above)
-   - For Windows: Verify Visual C++ Build Tools are installed
-   - Try upgrading pip: `pip install --upgrade pip`
-   - If issues persist, use a pre-built wheel: `pip install tiktoken --prefer-binary`
-
-### 2. Setting Up Your Crew with the YAML Configuration
-
-To create a new CrewAI project, run the following CLI (Command Line Interface) command:
-
-```shell
-crewai create crew <project_name>
-```
-
-This command creates a new project folder with the following structure:
-
-```
-my_project/
-├── .gitignore
-├── pyproject.toml
-├── README.md
-├── .env
-└── src/
-    └── my_project/
-        ├── __init__.py
-        ├── main.py
-        ├── crew.py
-        ├── tools/
-        │   ├── custom_tool.py
-        │   └── __init__.py
-        └── config/
-            ├── agents.yaml
-            └── tasks.yaml
-```
-
-You can now start developing your crew by editing the files in the `src/my_project` folder. The `main.py` file is the entry point of the project, the `crew.py` file is where you define your crew, the `agents.yaml` file is where you define your agents, and the `tasks.yaml` file is where you define your tasks.
-
-#### To customize your project, you can:
-
-- Modify `src/my_project/config/agents.yaml` to define your agents.
-- Modify `src/my_project/config/tasks.yaml` to define your tasks.
-- Modify `src/my_project/crew.py` to add your own logic, tools, and specific arguments.
-- Modify `src/my_project/main.py` to add custom inputs for your agents and tasks.
-- Add your environment variables into the `.env` file.
-
-#### Example of a simple crew with a sequential process:
-
-Instantiate your crew:
-
-```shell
-crewai create crew latest-ai-development
-```
-
-Modify the files as needed to fit your use case:
-
-**agents.yaml**
-
-```yaml
-# src/my_project/config/agents.yaml
-researcher:
-  role: >
-    {topic} Senior Data Researcher
-  goal: >
-    Uncover cutting-edge developments in {topic}
-  backstory: >
-    You're a seasoned researcher with a knack for uncovering the latest
-    developments in {topic}. Known for your ability to find the most relevant
-    information and present it in a clear and concise manner.
-
-reporting_analyst:
-  role: >
-    {topic} Reporting Analyst
-  goal: >
-    Create detailed reports based on {topic} data analysis and research findings
-  backstory: >
-    You're a meticulous analyst with a keen eye for detail. You're known for
-    your ability to turn complex data into clear and concise reports, making
-    it easy for others to understand and act on the information you provide.
-```
-
-**tasks.yaml**
-
-```yaml
-# src/my_project/config/tasks.yaml
-research_task:
-  description: >
-    Conduct a thorough research about {topic}
-    Make sure you find any interesting and relevant information given
-    the current year is 2025.
-  expected_output: >
-    A list with 10 bullet points of the most relevant information about {topic}
-  agent: researcher
-
-reporting_task:
-  description: >
-    Review the context you got and expand each topic into a full section for a report.
-    Make sure the report is detailed and contains any and all relevant information.
-  expected_output: >
-    A fully fledge reports with the mains topics, each with a full section of information.
-    Formatted as markdown without '```'
-  agent: reporting_analyst
-  output_file: report.md
-```
-
-**crew.py**
-
-```python
-# src/my_project/crew.py
-from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task
-from crewai_tools import SerperDevTool
-from crewai.agents.agent_builder.base_agent import BaseAgent
-from typing import List
-
-@CrewBase
-class LatestAiDevelopmentCrew():
-	"""LatestAiDevelopment crew"""
-	agents: List[BaseAgent]
-	tasks: List[Task]
-
-	@agent
-	def researcher(self) -> Agent:
-		return Agent(
-			config=self.agents_config['researcher'],
-			verbose=True,
-			tools=[SerperDevTool()]
-		)
-
-	@agent
-	def reporting_analyst(self) -> Agent:
-		return Agent(
-			config=self.agents_config['reporting_analyst'],
-			verbose=True
-		)
-
-	@task
-	def research_task(self) -> Task:
-		return Task(
-			config=self.tasks_config['research_task'],
-		)
-
-	@task
-	def reporting_task(self) -> Task:
-		return Task(
-			config=self.tasks_config['reporting_task'],
-			output_file='report.md'
-		)
-
-	@crew
-	def crew(self) -> Crew:
-		"""Creates the LatestAiDevelopment crew"""
-		return Crew(
-			agents=self.agents, # Automatically created by the @agent decorator
-			tasks=self.tasks, # Automatically created by the @task decorator
-			process=Process.sequential,
-			verbose=True,
-		)
-```
-
-**main.py**
-
-```python
-#!/usr/bin/env python
-# src/my_project/main.py
-import sys
-from latest_ai_development.crew import LatestAiDevelopmentCrew
-
-def run():
-    """
-    Run the crew.
-    """
-    inputs = {
-        'topic': 'AI Agents'
-    }
-    LatestAiDevelopmentCrew().crew().kickoff(inputs=inputs)
-```
-
-### 3. Running Your Crew
-
-Before running your crew, make sure you have the following keys set as environment variables in your `.env` file:
-
-- An [OpenAI API key](https://platform.openai.com/account/api-keys) (or other LLM API key): `OPENAI_API_KEY=sk-...`
-- A [Serper.dev](https://serper.dev/) API key: `SERPER_API_KEY=YOUR_KEY_HERE`
-
-Lock the dependencies and install them by using the CLI command but first, navigate to your project directory:
-
-```shell
-cd my_project
-crewai install (Optional)
-```
-
-To run your crew, execute the following command in the root of your project:
-
-```bash
-crewai run
-```
-
-or
-
-```bash
-python src/my_project/main.py
-```
-
-If an error happens due to the usage of poetry, please run the following command to update your crewai package:
-
-```bash
-crewai update
-```
-
-You should see the output in the console and the `report.md` file should be created in the root of your project with the full final report.
-
-In addition to the sequential process, you can use the hierarchical process, which automatically assigns a manager to the defined crew to properly coordinate the planning and execution of tasks through delegation and validation of results. [See more about the processes here](https://docs.crewai.com/core-concepts/Processes/).
-
-## Key Features
-
-CrewAI stands apart as a lean, standalone, high-performance multi-AI Agent framework delivering simplicity, flexibility, and precise control—free from the complexity and limitations found in other agent frameworks.
-
-- **Standalone & Lean**: Completely independent from other frameworks like LangChain, offering faster execution and lighter resource demands.
-- **Flexible & Precise**: Easily orchestrate autonomous agents through intuitive [Crews](https://docs.crewai.com/concepts/crews) or precise [Flows](https://docs.crewai.com/concepts/flows), achieving perfect balance for your needs.
-- **Seamless Integration**: Effortlessly combine Crews (autonomy) and Flows (precision) to create complex, real-world automations.
-- **Deep Customization**: Tailor every aspect—from high-level workflows down to low-level internal prompts and agent behaviors.
-- **Reliable Performance**: Consistent results across simple tasks and complex, enterprise-level automations.
-- **Thriving Community**: Backed by robust documentation and over 100,000 certified developers, providing exceptional support and guidance.
-
-Choose CrewAI to easily build powerful, adaptable, and production-ready AI automations.
-
-## Examples
-
-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/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/crews/trip_planner)
-- [Stock Analysis](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/stock_analysis)
-
-### Quick Tutorial
-
-[![CrewAI Tutorial](https://img.youtube.com/vi/tnejrr-0a94/maxresdefault.jpg)](https://www.youtube.com/watch?v=tnejrr-0a94 "CrewAI Tutorial")
-
-### Write Job Descriptions
-
-[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/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/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")
-
-### Using Crews and Flows Together
-
-CrewAI's power truly shines when combining Crews with Flows to create sophisticated automation pipelines.
-CrewAI flows support logical operators like `or_` and `and_` to combine multiple conditions. This can be used with `@start`, `@listen`, or `@router` decorators to create complex triggering conditions.
-
-- `or_`: Triggers when any of the specified conditions are met.
-- `and_`Triggers when all of the specified conditions are met.
-
-Here's how you can orchestrate multiple Crews within a Flow:
-
-```python
-from crewai.flow.flow import Flow, listen, start, router, or_
-from crewai import Crew, Agent, Task, Process
-from pydantic import BaseModel
-
-# Define structured state for precise control
-class MarketState(BaseModel):
-    sentiment: str = "neutral"
-    confidence: float = 0.0
-    recommendations: list = []
-
-class AdvancedAnalysisFlow(Flow[MarketState]):
-    @start()
-    def fetch_market_data(self):
-        # Demonstrate low-level control with structured state
-        self.state.sentiment = "analyzing"
-        return {"sector": "tech", "timeframe": "1W"}  # These parameters match the task description template
-
-    @listen(fetch_market_data)
-    def analyze_with_crew(self, market_data):
-        # Show crew agency through specialized roles
-        analyst = Agent(
-            role="Senior Market Analyst",
-            goal="Conduct deep market analysis with expert insight",
-            backstory="You're a veteran analyst known for identifying subtle market patterns"
-        )
-        researcher = Agent(
-            role="Data Researcher",
-            goal="Gather and validate supporting market data",
-            backstory="You excel at finding and correlating multiple data sources"
-        )
-
-        analysis_task = Task(
-            description="Analyze {sector} sector data for the past {timeframe}",
-            expected_output="Detailed market analysis with confidence score",
-            agent=analyst
-        )
-        research_task = Task(
-            description="Find supporting data to validate the analysis",
-            expected_output="Corroborating evidence and potential contradictions",
-            agent=researcher
-        )
-
-        # Demonstrate crew autonomy
-        analysis_crew = Crew(
-            agents=[analyst, researcher],
-            tasks=[analysis_task, research_task],
-            process=Process.sequential,
-            verbose=True
-        )
-        return analysis_crew.kickoff(inputs=market_data)  # Pass market_data as named inputs
-
-    @router(analyze_with_crew)
-    def determine_next_steps(self):
-        # Show flow control with conditional routing
-        if self.state.confidence > 0.8:
-            return "high_confidence"
-        elif self.state.confidence > 0.5:
-            return "medium_confidence"
-        return "low_confidence"
-
-    @listen("high_confidence")
-    def execute_strategy(self):
-        # Demonstrate complex decision making
-        strategy_crew = Crew(
-            agents=[
-                Agent(role="Strategy Expert",
-                      goal="Develop optimal market strategy")
-            ],
-            tasks=[
-                Task(description="Create detailed strategy based on analysis",
-                     expected_output="Step-by-step action plan")
-            ]
-        )
-        return strategy_crew.kickoff()
-
-    @listen(or_("medium_confidence", "low_confidence"))
-    def request_additional_analysis(self):
-        self.state.recommendations.append("Gather more data")
-        return "Additional analysis required"
-```
-
-This example demonstrates how to:
-
-1. Use Python code for basic data operations
-2. Create and execute Crews as steps in your workflow
-3. Use Flow decorators to manage the sequence of operations
-4. Implement conditional branching based on Crew results
-
-## Connecting Your Crew to a Model
-
-CrewAI supports using various LLMs through a variety of connection options. By default your agents will use the OpenAI API when querying the model. However, there are several other ways to allow your agents to connect to models. For example, you can configure your agents to use a local model via the Ollama tool.
-
-Please refer to the [Connect CrewAI to LLMs](https://docs.crewai.com/how-to/LLM-Connections/) page for details on configuring your agents' connections to models.
-
-## How CrewAI Compares
-
-**CrewAI's Advantage**: CrewAI combines autonomous agent intelligence with precise workflow control through its unique Crews and Flows architecture. The framework excels at both high-level orchestration and low-level customization, enabling complex, production-grade systems with granular control.
-
-- **LangGraph**: While LangGraph provides a foundation for building agent workflows, its approach requires significant boilerplate code and complex state management patterns. The framework's tight coupling with LangChain can limit flexibility when implementing custom agent behaviors or integrating with external systems.
-
-*P.S. CrewAI demonstrates significant performance advantages over LangGraph, executing 5.76x faster in certain cases like this QA task example ([see comparison](https://github.com/crewAIInc/crewAI-examples/tree/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/QA%20Agent)) while achieving higher evaluation scores with faster completion times in certain coding tasks, like in this example ([detailed analysis](https://github.com/crewAIInc/crewAI-examples/blob/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/Coding%20Assistant/coding_assistant_eval.ipynb)).*
-
-- **Autogen**: While Autogen excels at creating conversational agents capable of working together, it lacks an inherent concept of process. In Autogen, orchestrating agents' interactions requires additional programming, which can become complex and cumbersome as the scale of tasks grows.
-- **ChatDev**: ChatDev introduced the idea of processes into the realm of AI agents, but its implementation is quite rigid. Customizations in ChatDev are limited and not geared towards production environments, which can hinder scalability and flexibility in real-world applications.
-
-## Contribution
-
-CrewAI is open-source and we welcome contributions. If you're looking to contribute, please:
-
-- Fork the repository.
-- Create a new branch for your feature.
-- Add your feature or improvement.
-- Send a pull request.
-- We appreciate your input!
-
-### Installing Dependencies
-
-```bash
-uv lock
-uv sync
-```
-
-### Virtual Env
-
-```bash
-uv venv
-```
-
-### Pre-commit hooks
-
-```bash
-pre-commit install
-```
-
-### Running Tests
-
-```bash
-uv run pytest .
-```
-
-### Running static type checks
-
-```bash
-uvx mypy src
-```
-
-### Packaging
-
-```bash
-uv build
-```
-
-### Installing Locally
-
-```bash
-pip install dist/*.tar.gz
-```
-
-## Telemetry
-
-CrewAI uses anonymous telemetry to collect usage data with the main purpose of helping us improve the library by focusing our efforts on the most used features, integrations and tools.
-
-It's pivotal to understand that **NO data is collected** concerning prompts, task descriptions, agents' backstories or goals, usage of tools, API calls, responses, any data processed by the agents, or secrets and environment variables, with the exception of the conditions mentioned. When the `share_crew` feature is enabled, detailed data including task descriptions, agents' backstories or goals, and other specific attributes are collected to provide deeper insights while respecting user privacy. Users can disable telemetry by setting the environment variable OTEL_SDK_DISABLED to true.
-
-Data collected includes:
-
-- Version of CrewAI
-  - So we can understand how many users are using the latest version
-- Version of Python
-  - So we can decide on what versions to better support
-- General OS (e.g. number of CPUs, macOS/Windows/Linux)
-  - So we know what OS we should focus on and if we could build specific OS related features
-- Number of agents and tasks in a crew
-  - So we make sure we are testing internally with similar use cases and educate people on the best practices
-- Crew Process being used
-  - Understand where we should focus our efforts
-- If Agents are using memory or allowing delegation
-  - Understand if we improved the features or maybe even drop them
-- If Tasks are being executed in parallel or sequentially
-  - Understand if we should focus more on parallel execution
-- Language model being used
-  - Improved support on most used languages
-- Roles of agents in a crew
-  - Understand high level use cases so we can build better tools, integrations and examples about it
-- Tools names available
-  - Understand out of the publicly available tools, which ones are being used the most so we can improve them
-
-Users can opt-in to Further Telemetry, sharing the complete telemetry data by setting the `share_crew` attribute to `True` on their Crews. Enabling `share_crew` results in the collection of detailed crew and task execution data, including `goal`, `backstory`, `context`, and `output` of tasks. This enables a deeper insight into usage patterns while respecting the user's choice to share.
-
-## License
-
-CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/blob/main/LICENSE).
-
-## Frequently Asked Questions (FAQ)
-
-### General
-
-- [What exactly is CrewAI?](#q-what-exactly-is-crewai)
-- [How do I install CrewAI?](#q-how-do-i-install-crewai)
-- [Does CrewAI depend on LangChain?](#q-does-crewai-depend-on-langchain)
-- [Is CrewAI open-source?](#q-is-crewai-open-source)
-- [Does CrewAI collect data from users?](#q-does-crewai-collect-data-from-users)
-
-### Features and Capabilities
-
-- [Can CrewAI handle complex use cases?](#q-can-crewai-handle-complex-use-cases)
-- [Can I use CrewAI with local AI models?](#q-can-i-use-crewai-with-local-ai-models)
-- [What makes Crews different from Flows?](#q-what-makes-crews-different-from-flows)
-- [How is CrewAI better than LangChain?](#q-how-is-crewai-better-than-langchain)
-- [Does CrewAI support fine-tuning or training custom models?](#q-does-crewai-support-fine-tuning-or-training-custom-models)
-
-### Resources and Community
-
-- [Where can I find real-world CrewAI examples?](#q-where-can-i-find-real-world-crewai-examples)
-- [How can I contribute to CrewAI?](#q-how-can-i-contribute-to-crewai)
-
-### Enterprise Features
-
-- [What additional features does CrewAI AMP offer?](#q-what-additional-features-does-crewai-amp-offer)
-- [Is CrewAI AMP available for cloud and on-premise deployments?](#q-is-crewai-amp-available-for-cloud-and-on-premise-deployments)
-- [Can I try CrewAI AMP for free?](#q-can-i-try-crewai-amp-for-free)
-
-### Q: What exactly is CrewAI?
-
-A: CrewAI is a standalone, lean, and fast Python framework built specifically for orchestrating autonomous AI agents. Unlike frameworks like LangChain, CrewAI does not rely on external dependencies, making it leaner, faster, and simpler.
-
-### Q: How do I install CrewAI?
-
-A: Install CrewAI using pip:
-
-```shell
-pip install crewai
-```
-
-For additional tools, use:
-
-```shell
-pip install 'crewai[tools]'
-```
-
-### Q: Does CrewAI depend on LangChain?
-
-A: No. CrewAI is built entirely from the ground up, with no dependencies on LangChain or other agent frameworks. This ensures a lean, fast, and flexible experience.
-
-### Q: Can CrewAI handle complex use cases?
-
-A: Yes. CrewAI excels at both simple and highly complex real-world scenarios, offering deep customization options at both high and low levels, from internal prompts to sophisticated workflow orchestration.
-
-### Q: Can I use CrewAI with local AI models?
-
-A: Absolutely! CrewAI supports various language models, including local ones. Tools like Ollama and LM Studio allow seamless integration. Check the [LLM Connections documentation](https://docs.crewai.com/how-to/LLM-Connections/) for more details.
-
-### Q: What makes Crews different from Flows?
-
-A: Crews provide autonomous agent collaboration, ideal for tasks requiring flexible decision-making and dynamic interaction. Flows offer precise, event-driven control, ideal for managing detailed execution paths and secure state management. You can seamlessly combine both for maximum effectiveness.
-
-### Q: How is CrewAI better than LangChain?
-
-A: CrewAI provides simpler, more intuitive APIs, faster execution speeds, more reliable and consistent results, robust documentation, and an active community—addressing common criticisms and limitations associated with LangChain.
-
-### Q: Is CrewAI open-source?
-
-A: Yes, CrewAI is open-source and actively encourages community contributions and collaboration.
-
-### Q: Does CrewAI collect data from users?
-
-A: CrewAI collects anonymous telemetry data strictly for improvement purposes. Sensitive data such as prompts, tasks, or API responses are never collected unless explicitly enabled by the user.
-
-### Q: Where can I find real-world CrewAI examples?
-
-A: Check out practical examples in the [CrewAI-examples repository](https://github.com/crewAIInc/crewAI-examples), covering use cases like trip planners, stock analysis, and job postings.
-
-### Q: How can I contribute to CrewAI?
-
-A: Contributions are warmly welcomed! Fork the repository, create your branch, implement your changes, and submit a pull request. See the Contribution section of the README for detailed guidelines.
-
-### Q: What additional features does CrewAI AMP offer?
-
-A: CrewAI AMP provides advanced features such as a unified control plane, real-time observability, secure integrations, advanced security, actionable insights, and dedicated 24/7 enterprise support.
-
-### Q: Is CrewAI AMP available for cloud and on-premise deployments?
-
-A: Yes, CrewAI AMP supports both cloud-based and on-premise deployment options, allowing enterprises to meet their specific security and compliance requirements.
-
-### Q: Can I try CrewAI AMP for free?
-
-A: Yes, you can explore part of the CrewAI AMP Suite by accessing the [Crew Control Plane](https://app.crewai.com) for free.
-
-### Q: Does CrewAI support fine-tuning or training custom models?
-
-A: Yes, CrewAI can integrate with custom-trained or fine-tuned models, allowing you to enhance your agents with domain-specific knowledge and accuracy.
-
-### Q: Can CrewAI agents interact with external tools and APIs?
-
-A: Absolutely! CrewAI agents can easily integrate with external tools, APIs, and databases, empowering them to leverage real-world data and resources.
-
-### Q: Is CrewAI suitable for production environments?
-
-A: Yes, CrewAI is explicitly designed with production-grade standards, ensuring reliability, stability, and scalability for enterprise deployments.
-
-### Q: How scalable is CrewAI?
-
-A: CrewAI is highly scalable, supporting simple automations and large-scale enterprise workflows involving numerous agents and complex tasks simultaneously.
-
-### Q: Does CrewAI offer debugging and monitoring tools?
-
-A: Yes, CrewAI AMP includes advanced debugging, tracing, and real-time observability features, simplifying the management and troubleshooting of your automations.
-
-### Q: What programming languages does CrewAI support?
-
-A: CrewAI is primarily Python-based but easily integrates with services and APIs written in any programming language through its flexible API integration capabilities.
-
-### Q: Does CrewAI offer educational resources for beginners?
-
-A: Yes, CrewAI provides extensive beginner-friendly tutorials, courses, and documentation through learn.crewai.com, supporting developers at all skill levels.
-
-### Q: Can CrewAI automate human-in-the-loop workflows?
-
-A: Yes, CrewAI fully supports human-in-the-loop workflows, allowing seamless collaboration between human experts and AI agents for enhanced decision-making.

api-reference/introduction.mdx

@@ -1,29 +1,28 @@
 ---
 title: "Introduction"
-description: "Complete reference for the CrewAI AMP REST API"
+description: "Complete reference for the CrewAI Enterprise REST API"
 icon: "code"
-mode: "wide"
 ---
 
-# CrewAI AMP API
+# CrewAI Enterprise API
 
-Welcome to the CrewAI AMP API reference. This API allows you to programmatically interact with your deployed crews, enabling integration with your applications, workflows, and services.
+Welcome to the CrewAI Enterprise API reference. This API allows you to programmatically interact with your deployed crews, enabling integration with your applications, workflows, and services.
 
 ## Quick Start
 
 <Steps>
   <Step title="Get Your API Credentials">
-    Navigate to your crew's detail page in the CrewAI AMP dashboard and copy your Bearer Token from the Status tab.
+    Navigate to your crew's detail page in the CrewAI Enterprise dashboard and copy your Bearer Token from the Status tab.
   </Step>
-
+  
   <Step title="Discover Required Inputs">
     Use the `GET /inputs` endpoint to see what parameters your crew expects.
   </Step>
-
+  
   <Step title="Start a Crew Execution">
     Call `POST /kickoff` with your inputs to start the crew execution and receive a `kickoff_id`.
   </Step>
-
+  
   <Step title="Monitor Progress">
     Use `GET /status/{kickoff_id}` to check execution status and retrieve results.
   </Step>
@@ -46,7 +45,7 @@ curl -H "Authorization: Bearer YOUR_CREW_TOKEN" \
 | **User Bearer Token** | User-scoped access | Limited permissions, suitable for user-specific operations |
 
 <Tip>
-You can find both token types in the Status tab of your crew's detail page in the CrewAI AMP dashboard.
+You can find both token types in the Status tab of your crew's detail page in the CrewAI Enterprise dashboard.
 </Tip>
 
 ## Base URL
@@ -62,7 +61,7 @@ Replace `your-crew-name` with your actual crew's URL from the dashboard.
 ## Typical Workflow
 
 1. **Discovery**: Call `GET /inputs` to understand what your crew needs
-2. **Execution**: Submit inputs via `POST /kickoff` to start processing
+2. **Execution**: Submit inputs via `POST /kickoff` to start processing  
 3. **Monitoring**: Poll `GET /status/{kickoff_id}` until completion
 4. **Results**: Extract the final output from the completed response
 
@@ -82,12 +81,12 @@ The API uses standard HTTP status codes:
 ## Interactive Testing
 
 <Info>
-**Why no "Send" button?** Since each CrewAI AMP user has their own unique crew URL, we use **reference mode** instead of an interactive playground to avoid confusion. This shows you exactly what the requests should look like without non-functional send buttons.
+**Why no "Send" button?** Since each CrewAI Enterprise user has their own unique crew URL, we use **reference mode** instead of an interactive playground to avoid confusion. This shows you exactly what the requests should look like without non-functional send buttons.
 </Info>
 
 Each endpoint page shows you:
 - ✅ **Exact request format** with all parameters
-- ✅ **Response examples** for success and error cases
+- ✅ **Response examples** for success and error cases  
 - ✅ **Code samples** in multiple languages (cURL, Python, JavaScript, etc.)
 - ✅ **Authentication examples** with proper Bearer token format
 
@@ -104,7 +103,7 @@ Each endpoint page shows you:
 
 **Example workflow:**
 1. **Copy this cURL example** from any endpoint page
-2. **Replace `your-actual-crew-name.crewai.com`** with your real crew URL
+2. **Replace `your-actual-crew-name.crewai.com`** with your real crew URL  
 3. **Replace the Bearer token** with your real token from the dashboard
 4. **Run the request** in your terminal or API client
 

assets/javascripts/bundle.13a4f30d.min.js

@@ -0,0 +1,16 @@
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assets/javascripts/lunr/min/lunr.ar.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.ar=function(){this.pipeline.reset(),this.pipeline.add(e.ar.trimmer,e.ar.stopWordFilter,e.ar.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.ar.stemmer))},e.ar.wordCharacters="ء-ٛٱـ",e.ar.trimmer=e.trimmerSupport.generateTrimmer(e.ar.wordCharacters),e.Pipeline.registerFunction(e.ar.trimmer,"trimmer-ar"),e.ar.stemmer=function(){var e=this;return e.result=!1,e.preRemoved=!1,e.sufRemoved=!1,e.pre={pre1:"ف ك ب و س ل ن ا ي ت",pre2:"ال لل",pre3:"بال وال فال تال كال ولل",pre4:"فبال كبال وبال وكال"},e.suf={suf1:"ه ك ت ن ا ي",suf2:"نك نه ها وك يا اه ون ين تن تم نا وا ان كم كن ني نن ما هم هن تك ته ات يه",suf3:"تين كهم نيه نهم ونه وها يهم ونا ونك وني وهم تكم تنا تها تني تهم كما كها ناه نكم هنا تان يها",suf4:"كموه ناها ونني ونهم تكما تموه تكاه كماه ناكم ناهم نيها وننا"},e.patterns=JSON.parse('{"pt43":[{"pt":[{"c":"ا","l":1}]},{"pt":[{"c":"ا,ت,ن,ي","l":0}],"mPt":[{"c":"ف","l":0,"m":1},{"c":"ع","l":1,"m":2},{"c":"ل","l":2,"m":3}]},{"pt":[{"c":"و","l":2}],"mPt":[{"c":"ف","l":0,"m":0},{"c":"ع","l":1,"m":1},{"c":"ل","l":2,"m":3}]},{"pt":[{"c":"ا","l":2}]},{"pt":[{"c":"ي","l":2}],"mPt":[{"c":"ف","l":0,"m":0},{"c":"ع","l":1,"m":1},{"c":"ا","l":2},{"c":"ل","l":3,"m":3}]},{"pt":[{"c":"م","l":0}]}],"pt53":[{"pt":[{"c":"ت","l":0},{"c":"ا","l":2}]},{"pt":[{"c":"ا,ن,ت,ي","l":0},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ت","l":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":0},{"c":"ا","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ع","l":2,"m":3},{"c":"ل","l":3,"m":4},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":0},{"c":"ا","l":3}],"mPt":[{"c":"ف","l":0,"m":1},{"c":"ع","l":1,"m":2},{"c":"ل","l":2,"m":4}]},{"pt":[{"c":"ا","l":3},{"c":"ن","l":4}]},{"pt":[{"c":"ت","l":0},{"c":"ي","l":3}]},{"pt":[{"c":"م","l":0},{"c":"و","l":3}]},{"pt":[{"c":"ا","l":1},{"c":"و","l":3}]},{"pt":[{"c":"و","l":1},{"c":"ا","l":2}]},{"pt":[{"c":"م","l":0},{"c":"ا","l":3}]},{"pt":[{"c":"م","l":0},{"c":"ي","l":3}]},{"pt":[{"c":"ا","l":2},{"c":"ن","l":3}]},{"pt":[{"c":"م","l":0},{"c":"ن","l":1}],"mPt":[{"c":"ا","l":0},{"c":"ن","l":1},{"c":"ف","l":2,"m":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"م","l":0},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ت","l":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"م","l":0},{"c":"ا","l":2}]},{"pt":[{"c":"م","l":1},{"c":"ا","l":3}]},{"pt":[{"c":"ي,ت,ا,ن","l":0},{"c":"ت","l":1}],"mPt":[{"c":"ف","l":0,"m":2},{"c":"ع","l":1,"m":3},{"c":"ا","l":2},{"c":"ل","l":3,"m":4}]},{"pt":[{"c":"ت,ي,ا,ن","l":0},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ت","l":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":2},{"c":"ي","l":3}]},{"pt":[{"c":"ا,ي,ت,ن","l":0},{"c":"ن","l":1}],"mPt":[{"c":"ا","l":0},{"c":"ن","l":1},{"c":"ف","l":2,"m":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":3},{"c":"ء","l":4}]}],"pt63":[{"pt":[{"c":"ا","l":0},{"c":"ت","l":2},{"c":"ا","l":4}]},{"pt":[{"c":"ا,ت,ن,ي","l":0},{"c":"س","l":1},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"س","l":1},{"c":"ت","l":2},{"c":"ف","l":3,"m":3},{"c":"ع","l":4,"m":4},{"c":"ا","l":5},{"c":"ل","l":6,"m":5}]},{"pt":[{"c":"ا,ن,ت,ي","l":0},{"c":"و","l":3}]},{"pt":[{"c":"م","l":0},{"c":"س","l":1},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"س","l":1},{"c":"ت","l":2},{"c":"ف","l":3,"m":3},{"c":"ع","l":4,"m":4},{"c":"ا","l":5},{"c":"ل","l":6,"m":5}]},{"pt":[{"c":"ي","l":1},{"c":"ي","l":3},{"c":"ا","l":4},{"c":"ء","l":5}]},{"pt":[{"c":"ا","l":0},{"c":"ن","l":1},{"c":"ا","l":4}]}],"pt54":[{"pt":[{"c":"ت","l":0}]},{"pt":[{"c":"ا,ي,ت,ن","l":0}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ع","l":2,"m":2},{"c":"ل","l":3,"m":3},{"c":"ر","l":4,"m":4},{"c":"ا","l":5},{"c":"ر","l":6,"m":4}]},{"pt":[{"c":"م","l":0}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ع","l":2,"m":2},{"c":"ل","l":3,"m":3},{"c":"ر","l":4,"m":4},{"c":"ا","l":5},{"c":"ر","l":6,"m":4}]},{"pt":[{"c":"ا","l":2}]},{"pt":[{"c":"ا","l":0},{"c":"ن","l":2}]}],"pt64":[{"pt":[{"c":"ا","l":0},{"c":"ا","l":4}]},{"pt":[{"c":"Line truncated

assets/javascripts/lunr/min/lunr.da.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Danish` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.da=function(){this.pipeline.reset(),this.pipeline.add(e.da.trimmer,e.da.stopWordFilter,e.da.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.da.stemmer))},e.da.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.da.trimmer=e.trimmerSupport.generateTrimmer(e.da.wordCharacters),e.Pipeline.registerFunction(e.da.trimmer,"trimmer-da"),e.da.stemmer=function(){var r=e.stemmerSupport.Among,i=e.stemmerSupport.SnowballProgram,n=new function(){function e(){var e,r=f.cursor+3;if(d=f.limit,0<=r&&r<=f.limit){for(a=r;;){if(e=f.cursor,f.in_grouping(w,97,248)){f.cursor=e;break}if(f.cursor=e,e>=f.limit)return;f.cursor++}for(;!f.out_grouping(w,97,248);){if(f.cursor>=f.limit)return;f.cursor++}d=f.cursor,d<a&&(d=a)}}function n(){var e,r;if(f.cursor>=d&&(r=f.limit_backward,f.limit_backward=d,f.ket=f.cursor,e=f.find_among_b(c,32),f.limit_backward=r,e))switch(f.bra=f.cursor,e){case 1:f.slice_del();break;case 2:f.in_grouping_b(p,97,229)&&f.slice_del()}}function t(){var e,r=f.limit-f.cursor;f.cursor>=d&&(e=f.limit_backward,f.limit_backward=d,f.ket=f.cursor,f.find_among_b(l,4)?(f.bra=f.cursor,f.limit_backward=e,f.cursor=f.limit-r,f.cursor>f.limit_backward&&(f.cursor--,f.bra=f.cursor,f.slice_del())):f.limit_backward=e)}function s(){var e,r,i,n=f.limit-f.cursor;if(f.ket=f.cursor,f.eq_s_b(2,"st")&&(f.bra=f.cursor,f.eq_s_b(2,"ig")&&f.slice_del()),f.cursor=f.limit-n,f.cursor>=d&&(r=f.limit_backward,f.limit_backward=d,f.ket=f.cursor,e=f.find_among_b(m,5),f.limit_backward=r,e))switch(f.bra=f.cursor,e){case 1:f.slice_del(),i=f.limit-f.cursor,t(),f.cursor=f.limit-i;break;case 2:f.slice_from("løs")}}function o(){var e;f.cursor>=d&&(e=f.limit_backward,f.limit_backward=d,f.ket=f.cursor,f.out_grouping_b(w,97,248)?(f.bra=f.cursor,u=f.slice_to(u),f.limit_backward=e,f.eq_v_b(u)&&f.slice_del()):f.limit_backward=e)}var a,d,u,c=[new r("hed",-1,1),new r("ethed",0,1),new r("ered",-1,1),new r("e",-1,1),new r("erede",3,1),new r("ende",3,1),new r("erende",5,1),new r("ene",3,1),new r("erne",3,1),new r("ere",3,1),new r("en",-1,1),new r("heden",10,1),new r("eren",10,1),new r("er",-1,1),new r("heder",13,1),new r("erer",13,1),new r("s",-1,2),new r("heds",16,1),new r("es",16,1),new r("endes",18,1),new r("erendes",19,1),new r("enes",18,1),new r("ernes",18,1),new r("eres",18,1),new r("ens",16,1),new r("hedens",24,1),new r("erens",24,1),new r("ers",16,1),new r("ets",16,1),new r("erets",28,1),new r("et",-1,1),new r("eret",30,1)],l=[new r("gd",-1,-1),new r("dt",-1,-1),new r("gt",-1,-1),new r("kt",-1,-1)],m=[new r("ig",-1,1),new r("lig",0,1),new r("elig",1,1),new r("els",-1,1),new r("løst",-1,2)],w=[17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,48,0,128],p=[239,254,42,3,0,0,0,0,0,0,0,0,0,0,0,0,16],f=new i;this.setCurrent=function(e){f.setCurrent(e)},this.getCurrent=function(){return f.getCurrent()},this.stem=function(){var r=f.cursor;return e(),f.limit_backward=r,f.cursor=f.limit,n(),f.cursor=f.limit,t(),f.cursor=f.limit,s(),f.cursor=f.limit,o(),!0}};return function(e){return"function"==typeof e.update?e.update(function(e){return n.setCurrent(e),n.stem(),n.getCurrent()}):(n.setCurrent(e),n.stem(),n.getCurrent())}}(),e.Pipeline.registerFunction(e.da.stemmer,"stemmer-da"),e.da.stopWordFilter=e.generateStopWordFilter("ad af alle alt anden at blev blive bliver da de dem den denne der deres det dette dig din disse dog du efter eller en end er et for fra ham han hans har havde have hende hendes her hos hun hvad hvis hvor i ikke ind jeg jer jo kunne man mange med meget men mig min mine mit mod ned noget nogle nu når og også om op os over på selv sig sin sine sit skal skulle som sådan thi til ud under var vi vil ville vor være været".split(" ")),e.Pipeline.registerFunction(e.da.stopWordFilter,"stopWordFilter-da")}});

assets/javascripts/lunr/min/lunr.de.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `German` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.de=function(){this.pipeline.reset(),this.pipeline.add(e.de.trimmer,e.de.stopWordFilter,e.de.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.de.stemmer))},e.de.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.de.trimmer=e.trimmerSupport.generateTrimmer(e.de.wordCharacters),e.Pipeline.registerFunction(e.de.trimmer,"trimmer-de"),e.de.stemmer=function(){var r=e.stemmerSupport.Among,n=e.stemmerSupport.SnowballProgram,i=new function(){function e(e,r,n){return!(!v.eq_s(1,e)||(v.ket=v.cursor,!v.in_grouping(p,97,252)))&&(v.slice_from(r),v.cursor=n,!0)}function i(){for(var r,n,i,s,t=v.cursor;;)if(r=v.cursor,v.bra=r,v.eq_s(1,"ß"))v.ket=v.cursor,v.slice_from("ss");else{if(r>=v.limit)break;v.cursor=r+1}for(v.cursor=t;;)for(n=v.cursor;;){if(i=v.cursor,v.in_grouping(p,97,252)){if(s=v.cursor,v.bra=s,e("u","U",i))break;if(v.cursor=s,e("y","Y",i))break}if(i>=v.limit)return void(v.cursor=n);v.cursor=i+1}}function s(){for(;!v.in_grouping(p,97,252);){if(v.cursor>=v.limit)return!0;v.cursor++}for(;!v.out_grouping(p,97,252);){if(v.cursor>=v.limit)return!0;v.cursor++}return!1}function t(){m=v.limit,l=m;var e=v.cursor+3;0<=e&&e<=v.limit&&(d=e,s()||(m=v.cursor,m<d&&(m=d),s()||(l=v.cursor)))}function o(){for(var e,r;;){if(r=v.cursor,v.bra=r,!(e=v.find_among(h,6)))return;switch(v.ket=v.cursor,e){case 1:v.slice_from("y");break;case 2:case 5:v.slice_from("u");break;case 3:v.slice_from("a");break;case 4:v.slice_from("o");break;case 6:if(v.cursor>=v.limit)return;v.cursor++}}}function c(){return m<=v.cursor}function u(){return l<=v.cursor}function a(){var e,r,n,i,s=v.limit-v.cursor;if(v.ket=v.cursor,(e=v.find_among_b(w,7))&&(v.bra=v.cursor,c()))switch(e){case 1:v.slice_del();break;case 2:v.slice_del(),v.ket=v.cursor,v.eq_s_b(1,"s")&&(v.bra=v.cursor,v.eq_s_b(3,"nis")&&v.slice_del());break;case 3:v.in_grouping_b(g,98,116)&&v.slice_del()}if(v.cursor=v.limit-s,v.ket=v.cursor,(e=v.find_among_b(f,4))&&(v.bra=v.cursor,c()))switch(e){case 1:v.slice_del();break;case 2:if(v.in_grouping_b(k,98,116)){var t=v.cursor-3;v.limit_backward<=t&&t<=v.limit&&(v.cursor=t,v.slice_del())}}if(v.cursor=v.limit-s,v.ket=v.cursor,(e=v.find_among_b(_,8))&&(v.bra=v.cursor,u()))switch(e){case 1:v.slice_del(),v.ket=v.cursor,v.eq_s_b(2,"ig")&&(v.bra=v.cursor,r=v.limit-v.cursor,v.eq_s_b(1,"e")||(v.cursor=v.limit-r,u()&&v.slice_del()));break;case 2:n=v.limit-v.cursor,v.eq_s_b(1,"e")||(v.cursor=v.limit-n,v.slice_del());break;case 3:if(v.slice_del(),v.ket=v.cursor,i=v.limit-v.cursor,!v.eq_s_b(2,"er")&&(v.cursor=v.limit-i,!v.eq_s_b(2,"en")))break;v.bra=v.cursor,c()&&v.slice_del();break;case 4:v.slice_del(),v.ket=v.cursor,e=v.find_among_b(b,2),e&&(v.bra=v.cursor,u()&&1==e&&v.slice_del())}}var d,l,m,h=[new r("",-1,6),new r("U",0,2),new r("Y",0,1),new r("ä",0,3),new r("ö",0,4),new r("ü",0,5)],w=[new r("e",-1,2),new r("em",-1,1),new r("en",-1,2),new r("ern",-1,1),new r("er",-1,1),new r("s",-1,3),new r("es",5,2)],f=[new r("en",-1,1),new r("er",-1,1),new r("st",-1,2),new r("est",2,1)],b=[new r("ig",-1,1),new r("lich",-1,1)],_=[new r("end",-1,1),new r("ig",-1,2),new r("ung",-1,1),new r("lich",-1,3),new r("isch",-1,2),new r("ik",-1,2),new r("heit",-1,3),new r("keit",-1,4)],p=[17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,8,0,32,8],g=[117,30,5],k=[117,30,4],v=new n;this.setCurrent=function(e){v.setCurrent(e)},this.getCurrent=function(){return v.getCurrent()},this.stem=function(){var e=v.cursor;return i(),v.cursor=e,t(),v.limit_backward=e,v.cursor=v.limit,a(),v.cursor=v.limit_backward,o(),!0}};return function(e){return"function"==typeof e.update?e.update(function(e){return i.setCurrent(e),i.stem(),i.getCurrent()}):(i.setCurrent(e),i.stem(),i.getCurrent())}}(),e.Pipeline.registerFunction(e.de.stemmer,"stemmer-de"),e.de.stopWordFilter=e.generateStopWordFilter("aber alle allem allen aller alles als also am an ander andere anderem anderen anderer anderes anderm andern anderr anders auch auf aus bei bin bis bist da damit dann das dasselbe dazu daß dein deine deinem deinen deiner deines dem demselben den denn denselben der derer derselbe derselben des desselben dessen dich die dies diese dieselbe dieselben diesem diesen dieser dieses dir doch dort du durch ein eine einem einen einer eines einig einige einigem einigen einiger einiges einmal er es etwas euch euer eure eurem euren eurer eures für gegen gewesen hab habe haben hat hatte hatten hier hin hinter ich ihm ihn ihnen ihr ihre ihrem ihren ihrer ihres im in indemLine truncated

assets/javascripts/lunr/min/lunr.du.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Dutch` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");console.warn('[Lunr Languages] Please use the "nl" instead of the "du". The "nl" code is the standard code for Dutch language, and "du" will be removed in the next major versions.'),e.du=function(){this.pipeline.reset(),this.pipeline.add(e.du.trimmer,e.du.stopWordFilter,e.du.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.du.stemmer))},e.du.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.du.trimmer=e.trimmerSupport.generateTrimmer(e.du.wordCharacters),e.Pipeline.registerFunction(e.du.trimmer,"trimmer-du"),e.du.stemmer=function(){var r=e.stemmerSupport.Among,i=e.stemmerSupport.SnowballProgram,n=new function(){function e(){for(var e,r,i,o=C.cursor;;){if(C.bra=C.cursor,e=C.find_among(b,11))switch(C.ket=C.cursor,e){case 1:C.slice_from("a");continue;case 2:C.slice_from("e");continue;case 3:C.slice_from("i");continue;case 4:C.slice_from("o");continue;case 5:C.slice_from("u");continue;case 6:if(C.cursor>=C.limit)break;C.cursor++;continue}break}for(C.cursor=o,C.bra=o,C.eq_s(1,"y")?(C.ket=C.cursor,C.slice_from("Y")):C.cursor=o;;)if(r=C.cursor,C.in_grouping(q,97,232)){if(i=C.cursor,C.bra=i,C.eq_s(1,"i"))C.ket=C.cursor,C.in_grouping(q,97,232)&&(C.slice_from("I"),C.cursor=r);else if(C.cursor=i,C.eq_s(1,"y"))C.ket=C.cursor,C.slice_from("Y"),C.cursor=r;else if(n(r))break}else if(n(r))break}function n(e){return C.cursor=e,e>=C.limit||(C.cursor++,!1)}function o(){_=C.limit,f=_,t()||(_=C.cursor,_<3&&(_=3),t()||(f=C.cursor))}function t(){for(;!C.in_grouping(q,97,232);){if(C.cursor>=C.limit)return!0;C.cursor++}for(;!C.out_grouping(q,97,232);){if(C.cursor>=C.limit)return!0;C.cursor++}return!1}function s(){for(var e;;)if(C.bra=C.cursor,e=C.find_among(p,3))switch(C.ket=C.cursor,e){case 1:C.slice_from("y");break;case 2:C.slice_from("i");break;case 3:if(C.cursor>=C.limit)return;C.cursor++}}function u(){return _<=C.cursor}function c(){return f<=C.cursor}function a(){var e=C.limit-C.cursor;C.find_among_b(g,3)&&(C.cursor=C.limit-e,C.ket=C.cursor,C.cursor>C.limit_backward&&(C.cursor--,C.bra=C.cursor,C.slice_del()))}function l(){var e;w=!1,C.ket=C.cursor,C.eq_s_b(1,"e")&&(C.bra=C.cursor,u()&&(e=C.limit-C.cursor,C.out_grouping_b(q,97,232)&&(C.cursor=C.limit-e,C.slice_del(),w=!0,a())))}function m(){var e;u()&&(e=C.limit-C.cursor,C.out_grouping_b(q,97,232)&&(C.cursor=C.limit-e,C.eq_s_b(3,"gem")||(C.cursor=C.limit-e,C.slice_del(),a())))}function d(){var e,r,i,n,o,t,s=C.limit-C.cursor;if(C.ket=C.cursor,e=C.find_among_b(h,5))switch(C.bra=C.cursor,e){case 1:u()&&C.slice_from("heid");break;case 2:m();break;case 3:u()&&C.out_grouping_b(z,97,232)&&C.slice_del()}if(C.cursor=C.limit-s,l(),C.cursor=C.limit-s,C.ket=C.cursor,C.eq_s_b(4,"heid")&&(C.bra=C.cursor,c()&&(r=C.limit-C.cursor,C.eq_s_b(1,"c")||(C.cursor=C.limit-r,C.slice_del(),C.ket=C.cursor,C.eq_s_b(2,"en")&&(C.bra=C.cursor,m())))),C.cursor=C.limit-s,C.ket=C.cursor,e=C.find_among_b(k,6))switch(C.bra=C.cursor,e){case 1:if(c()){if(C.slice_del(),i=C.limit-C.cursor,C.ket=C.cursor,C.eq_s_b(2,"ig")&&(C.bra=C.cursor,c()&&(n=C.limit-C.cursor,!C.eq_s_b(1,"e")))){C.cursor=C.limit-n,C.slice_del();break}C.cursor=C.limit-i,a()}break;case 2:c()&&(o=C.limit-C.cursor,C.eq_s_b(1,"e")||(C.cursor=C.limit-o,C.slice_del()));break;case 3:c()&&(C.slice_del(),l());break;case 4:c()&&C.slice_del();break;case 5:c()&&w&&C.slice_del()}C.cursor=C.limit-s,C.out_grouping_b(j,73,232)&&(t=C.limit-C.cursor,C.find_among_b(v,4)&&C.out_grouping_b(q,97,232)&&(C.cursor=C.limit-t,C.ket=C.cursor,C.cursor>C.limit_backward&&(C.cursor--,C.bra=C.cursor,C.slice_del())))}var f,_,w,b=[new r("",-1,6),new r("á",0,1),new r("ä",0,1),new r("é",0,2),new r("ë",0,2),new r("í",0,3),new r("ï",0,3),new r("ó",0,4),new r("ö",0,4),new r("ú",0,5),new r("ü",0,5)],p=[new r("",-1,3),new r("I",0,2),new r("Y",0,1)],g=[new r("dd",-1,-1),new r("kk",-1,-1),new r("tt",-1,-1)],h=[new r("ene",-1,2),new r("se",-1,3),new r("en",-1,2),new r("heden",2,1),new r("s",-1,3)],k=[new r("end",-1,1),new r("ig",-1,2),new r("ing",-1,1),new r("lijk",-1,3),new r("baar",-1,4),new r("bar",-1,5)],v=[new r("aa",-1,-1),new r("ee",-1,-1),new r("oo",-1,-1),new r("uu",-1,-1)],q=[17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,128],j=[1,0,0,17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,128],z=[17,67,16,1,0,0,0,0,0,0,0,0,0,0,0,0,128],C=new i;this.setCurrent=function(e){C.setCurrent(e)},this.getCurrent=function(){return C.getCurrent()},this.stem=function(){var r=C.cursor;return e(),C.cursor=r,o(),C.limit_backward=r,C.cursoLine truncated

assets/javascripts/lunr/min/lunr.el.min.js

@@ -0,0 +1 @@
+!function(e,t){"function"==typeof define&&define.amd?define(t):"object"==typeof exports?module.exports=t():t()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.el=function(){this.pipeline.reset(),void 0===this.searchPipeline&&this.pipeline.add(e.el.trimmer,e.el.normilizer),this.pipeline.add(e.el.stopWordFilter,e.el.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.el.stemmer))},e.el.wordCharacters="A-Za-zΑαΒβΓγΔδΕεΖζΗηΘθΙιΚκΛλΜμΝνΞξΟοΠπΡρΣσςΤτΥυΦφΧχΨψΩωΆάΈέΉήΊίΌόΎύΏώΪΐΫΰΐΰ",e.el.trimmer=e.trimmerSupport.generateTrimmer(e.el.wordCharacters),e.Pipeline.registerFunction(e.el.trimmer,"trimmer-el"),e.el.stemmer=function(){function e(e){return s.test(e)}function t(e){return/[ΑΕΗΙΟΥΩ]$/.test(e)}function r(e){return/[ΑΕΗΙΟΩ]$/.test(e)}function n(n){var s=n;if(n.length<3)return s;if(!e(n))return s;if(i.indexOf(n)>=0)return s;var u=new RegExp("(.*)("+Object.keys(l).join("|")+")$"),o=u.exec(s);return null!==o&&(s=o[1]+l[o[2]]),null!==(o=/^(.+?)(ΑΔΕΣ|ΑΔΩΝ)$/.exec(s))&&(s=o[1],/(ΟΚ|ΜΑΜ|ΜΑΝ|ΜΠΑΜΠ|ΠΑΤΕΡ|ΓΙΑΓΙ|ΝΤΑΝΤ|ΚΥΡ|ΘΕΙ|ΠΕΘΕΡ|ΜΟΥΣΑΜ|ΚΑΠΛΑΜ|ΠΑΡ|ΨΑΡ|ΤΖΟΥΡ|ΤΑΜΠΟΥΡ|ΓΑΛΑΤ|ΦΑΦΛΑΤ)$/.test(o[1])||(s+="ΑΔ")),null!==(o=/^(.+?)(ΕΔΕΣ|ΕΔΩΝ)$/.exec(s))&&(s=o[1],/(ΟΠ|ΙΠ|ΕΜΠ|ΥΠ|ΓΗΠ|ΔΑΠ|ΚΡΑΣΠ|ΜΙΛ)$/.test(o[1])&&(s+="ΕΔ")),null!==(o=/^(.+?)(ΟΥΔΕΣ|ΟΥΔΩΝ)$/.exec(s))&&(s=o[1],/(ΑΡΚ|ΚΑΛΙΑΚ|ΠΕΤΑΛ|ΛΙΧ|ΠΛΕΞ|ΣΚ|Σ|ΦΛ|ΦΡ|ΒΕΛ|ΛΟΥΛ|ΧΝ|ΣΠ|ΤΡΑΓ|ΦΕ)$/.test(o[1])&&(s+="ΟΥΔ")),null!==(o=/^(.+?)(ΕΩΣ|ΕΩΝ|ΕΑΣ|ΕΑ)$/.exec(s))&&(s=o[1],/^(Θ|Δ|ΕΛ|ΓΑΛ|Ν|Π|ΙΔ|ΠΑΡ|ΣΤΕΡ|ΟΡΦ|ΑΝΔΡ|ΑΝΤΡ)$/.test(o[1])&&(s+="Ε")),null!==(o=/^(.+?)(ΕΙΟ|ΕΙΟΣ|ΕΙΟΙ|ΕΙΑ|ΕΙΑΣ|ΕΙΕΣ|ΕΙΟΥ|ΕΙΟΥΣ|ΕΙΩΝ)$/.exec(s))&&o[1].length>4&&(s=o[1]),null!==(o=/^(.+?)(ΙΟΥΣ|ΙΑΣ|ΙΕΣ|ΙΟΣ|ΙΟΥ|ΙΟΙ|ΙΩΝ|ΙΟΝ|ΙΑ|ΙΟ)$/.exec(s))&&(s=o[1],(t(s)||s.length<2||/^(ΑΓ|ΑΓΓΕΛ|ΑΓΡ|ΑΕΡ|ΑΘΛ|ΑΚΟΥΣ|ΑΞ|ΑΣ|Β|ΒΙΒΛ|ΒΥΤ|Γ|ΓΙΑΓ|ΓΩΝ|Δ|ΔΑΝ|ΔΗΛ|ΔΗΜ|ΔΟΚΙΜ|ΕΛ|ΖΑΧΑΡ|ΗΛ|ΗΠ|ΙΔ|ΙΣΚ|ΙΣΤ|ΙΟΝ|ΙΩΝ|ΚΙΜΩΛ|ΚΟΛΟΝ|ΚΟΡ|ΚΤΗΡ|ΚΥΡ|ΛΑΓ|ΛΟΓ|ΜΑΓ|ΜΠΑΝ|ΜΠΡ|ΝΑΥΤ|ΝΟΤ|ΟΠΑΛ|ΟΞ|ΟΡ|ΟΣ|ΠΑΝΑΓ|ΠΑΤΡ|ΠΗΛ|ΠΗΝ|ΠΛΑΙΣ|ΠΟΝΤ|ΡΑΔ|ΡΟΔ|ΣΚ|ΣΚΟΡΠ|ΣΟΥΝ|ΣΠΑΝ|ΣΤΑΔ|ΣΥΡ|ΤΗΛ|ΤΙΜ|ΤΟΚ|ΤΟΠ|ΤΡΟΧ|ΦΙΛ|ΦΩΤ|Χ|ΧΙΛ|ΧΡΩΜ|ΧΩΡ)$/.test(o[1]))&&(s+="Ι"),/^(ΠΑΛ)$/.test(o[1])&&(s+="ΑΙ")),null!==(o=/^(.+?)(ΙΚΟΣ|ΙΚΟΝ|ΙΚΕΙΣ|ΙΚΟΙ|ΙΚΕΣ|ΙΚΟΥΣ|ΙΚΗ|ΙΚΗΣ|ΙΚΟ|ΙΚΑ|ΙΚΟΥ|ΙΚΩΝ|ΙΚΩΣ)$/.exec(s))&&(s=o[1],(t(s)||/^(ΑΔ|ΑΛ|ΑΜΑΝ|ΑΜΕΡ|ΑΜΜΟΧΑΛ|ΑΝΗΘ|ΑΝΤΙΔ|ΑΠΛ|ΑΤΤ|ΑΦΡ|ΒΑΣ|ΒΡΩΜ|ΓΕΝ|ΓΕΡ|Δ|ΔΙΚΑΝ|ΔΥΤ|ΕΙΔ|ΕΝΔ|ΕΞΩΔ|ΗΘ|ΘΕΤ|ΚΑΛΛΙΝ|ΚΑΛΠ|ΚΑΤΑΔ|ΚΟΥΖΙΝ|ΚΡ|ΚΩΔ|ΛΟΓ|Μ|ΜΕΡ|ΜΟΝΑΔ|ΜΟΥΛ|ΜΟΥΣ|ΜΠΑΓΙΑΤ|ΜΠΑΝ|ΜΠΟΛ|ΜΠΟΣ|ΜΥΣΤ|Ν|ΝΙΤ|ΞΙΚ|ΟΠΤ|ΠΑΝ|ΠΕΤΣ|ΠΙΚΑΝΤ|ΠΙΤΣ|ΠΛΑΣΤ|ΠΛΙΑΤΣ|ΠΟΝΤ|ΠΟΣΤΕΛΝ|ΠΡΩΤΟΔ|ΣΕΡΤ|ΣΗΜΑΝΤ|ΣΤΑΤ|ΣΥΝΑΔ|ΣΥΝΟΜΗΛ|ΤΕΛ|ΤΕΧΝ|ΤΡΟΠ|ΤΣΑΜ|ΥΠΟΔ|Φ|ΦΙΛΟΝ|ΦΥΛΟΔ|ΦΥΣ|ΧΑΣ)$/.test(o[1])||/(ΦΟΙΝ)$/.test(o[1]))&&(s+="ΙΚ")),"ΑΓΑΜΕ"===s&&(s="ΑΓΑΜ"),null!==(o=/^(.+?)(ΑΓΑΜΕ|ΗΣΑΜΕ|ΟΥΣΑΜΕ|ΗΚΑΜΕ|ΗΘΗΚΑΜΕ)$/.exec(s))&&(s=o[1]),null!==(o=/^(.+?)(ΑΜΕ)$/.exec(s))&&(s=o[1],/^(ΑΝΑΠ|ΑΠΟΘ|ΑΠΟΚ|ΑΠΟΣΤ|ΒΟΥΒ|ΞΕΘ|ΟΥΛ|ΠΕΘ|ΠΙΚΡ|ΠΟΤ|ΣΙΧ|Χ)$/.test(o[1])&&(s+="ΑΜ")),null!==(o=/^(.+?)(ΑΓΑΝΕ|ΗΣΑΝΕ|ΟΥΣΑΝΕ|ΙΟΝΤΑΝΕ|ΙΟΤΑΝΕ|ΙΟΥΝΤΑΝΕ|ΟΝΤΑΝΕ|ΟΤΑΝΕ|ΟΥΝΤΑΝΕ|ΗΚΑΝΕ|ΗΘΗΚΑΝΕ)$/.exec(s))&&(s=o[1],/^(ΤΡ|ΤΣ)$/.test(o[1])&&(s+="ΑΓΑΝ")),null!==(o=/^(.+?)(ΑΝΕ)$/.exec(s))&&(s=o[1],(r(s)||/^(ΒΕΤΕΡ|ΒΟΥΛΚ|ΒΡΑΧΜ|Γ|ΔΡΑΔΟΥΜ|Θ|ΚΑΛΠΟΥΖ|ΚΑΣΤΕΛ|ΚΟΡΜΟΡ|ΛΑΟΠΛ|ΜΩΑΜΕΘ|Μ|ΜΟΥΣΟΥΛΜΑΝ|ΟΥΛ|Π|ΠΕΛΕΚ|ΠΛ|ΠΟΛΙΣ|ΠΟΡΤΟΛ|ΣΑΡΑΚΑΤΣ|ΣΟΥΛΤ|ΤΣΑΡΛΑΤ|ΟΡΦ|ΤΣΙΓΓ|ΤΣΟΠ|ΦΩΤΟΣΤΕΦ|Χ|ΨΥΧΟΠΛ|ΑΓ|ΟΡΦ|ΓΑΛ|ΓΕΡ|ΔΕΚ|ΔΙΠΛ|ΑΜΕΡΙΚΑΝ|ΟΥΡ|ΠΙΘ|ΠΟΥΡΙΤ|Σ|ΖΩΝΤ|ΙΚ|ΚΑΣΤ|ΚΟΠ|ΛΙΧ|ΛΟΥΘΗΡ|ΜΑΙΝΤ|ΜΕΛ|ΣΙΓ|ΣΠ|ΣΤΕΓ|ΤΡΑΓ|ΤΣΑΓ|Φ|ΕΡ|ΑΔΑΠ|ΑΘΙΓΓ|ΑΜΗΧ|ΑΝΙΚ|ΑΝΟΡΓ|ΑΠΗΓ|ΑΠΙΘ|ΑΤΣΙΓΓ|ΒΑΣ|ΒΑΣΚ|ΒΑΘΥΓΑΛ|ΒΙΟΜΗΧ|ΒΡΑΧΥΚ|ΔΙΑΤ|ΔΙΑΦ|ΕΝΟΡΓ|ΘΥΣ|ΚΑΠΝΟΒΙΟΜΗΧ|ΚΑΤLine truncated

assets/javascripts/lunr/min/lunr.es.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Spanish` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,s){"function"==typeof define&&define.amd?define(s):"object"==typeof exports?module.exports=s():s()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.es=function(){this.pipeline.reset(),this.pipeline.add(e.es.trimmer,e.es.stopWordFilter,e.es.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.es.stemmer))},e.es.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.es.trimmer=e.trimmerSupport.generateTrimmer(e.es.wordCharacters),e.Pipeline.registerFunction(e.es.trimmer,"trimmer-es"),e.es.stemmer=function(){var s=e.stemmerSupport.Among,r=e.stemmerSupport.SnowballProgram,n=new function(){function e(){if(A.out_grouping(x,97,252)){for(;!A.in_grouping(x,97,252);){if(A.cursor>=A.limit)return!0;A.cursor++}return!1}return!0}function n(){if(A.in_grouping(x,97,252)){var s=A.cursor;if(e()){if(A.cursor=s,!A.in_grouping(x,97,252))return!0;for(;!A.out_grouping(x,97,252);){if(A.cursor>=A.limit)return!0;A.cursor++}}return!1}return!0}function i(){var s,r=A.cursor;if(n()){if(A.cursor=r,!A.out_grouping(x,97,252))return;if(s=A.cursor,e()){if(A.cursor=s,!A.in_grouping(x,97,252)||A.cursor>=A.limit)return;A.cursor++}}g=A.cursor}function a(){for(;!A.in_grouping(x,97,252);){if(A.cursor>=A.limit)return!1;A.cursor++}for(;!A.out_grouping(x,97,252);){if(A.cursor>=A.limit)return!1;A.cursor++}return!0}function t(){var e=A.cursor;g=A.limit,p=g,v=g,i(),A.cursor=e,a()&&(p=A.cursor,a()&&(v=A.cursor))}function o(){for(var e;;){if(A.bra=A.cursor,e=A.find_among(k,6))switch(A.ket=A.cursor,e){case 1:A.slice_from("a");continue;case 2:A.slice_from("e");continue;case 3:A.slice_from("i");continue;case 4:A.slice_from("o");continue;case 5:A.slice_from("u");continue;case 6:if(A.cursor>=A.limit)break;A.cursor++;continue}break}}function u(){return g<=A.cursor}function w(){return p<=A.cursor}function c(){return v<=A.cursor}function m(){var e;if(A.ket=A.cursor,A.find_among_b(y,13)&&(A.bra=A.cursor,(e=A.find_among_b(q,11))&&u()))switch(e){case 1:A.bra=A.cursor,A.slice_from("iendo");break;case 2:A.bra=A.cursor,A.slice_from("ando");break;case 3:A.bra=A.cursor,A.slice_from("ar");break;case 4:A.bra=A.cursor,A.slice_from("er");break;case 5:A.bra=A.cursor,A.slice_from("ir");break;case 6:A.slice_del();break;case 7:A.eq_s_b(1,"u")&&A.slice_del()}}function l(e,s){if(!c())return!0;A.slice_del(),A.ket=A.cursor;var r=A.find_among_b(e,s);return r&&(A.bra=A.cursor,1==r&&c()&&A.slice_del()),!1}function d(e){return!c()||(A.slice_del(),A.ket=A.cursor,A.eq_s_b(2,e)&&(A.bra=A.cursor,c()&&A.slice_del()),!1)}function b(){var e;if(A.ket=A.cursor,e=A.find_among_b(S,46)){switch(A.bra=A.cursor,e){case 1:if(!c())return!1;A.slice_del();break;case 2:if(d("ic"))return!1;break;case 3:if(!c())return!1;A.slice_from("log");break;case 4:if(!c())return!1;A.slice_from("u");break;case 5:if(!c())return!1;A.slice_from("ente");break;case 6:if(!w())return!1;A.slice_del(),A.ket=A.cursor,e=A.find_among_b(C,4),e&&(A.bra=A.cursor,c()&&(A.slice_del(),1==e&&(A.ket=A.cursor,A.eq_s_b(2,"at")&&(A.bra=A.cursor,c()&&A.slice_del()))));break;case 7:if(l(P,3))return!1;break;case 8:if(l(F,3))return!1;break;case 9:if(d("at"))return!1}return!0}return!1}function f(){var e,s;if(A.cursor>=g&&(s=A.limit_backward,A.limit_backward=g,A.ket=A.cursor,e=A.find_among_b(W,12),A.limit_backward=s,e)){if(A.bra=A.cursor,1==e){if(!A.eq_s_b(1,"u"))return!1;A.slice_del()}return!0}return!1}function _(){var e,s,r,n;if(A.cursor>=g&&(s=A.limit_backward,A.limit_backward=g,A.ket=A.cursor,e=A.find_among_b(L,96),A.limit_backward=s,e))switch(A.bra=A.cursor,e){case 1:r=A.limit-A.cursor,A.eq_s_b(1,"u")?(n=A.limit-A.cursor,A.eq_s_b(1,"g")?A.cursor=A.limit-n:A.cursor=A.limit-r):A.cursor=A.limit-r,A.bra=A.cursor;case 2:A.slice_del()}}function h(){var e,s;if(A.ket=A.cursor,e=A.find_among_b(z,8))switch(A.bra=A.cursor,e){case 1:u()&&A.slice_del();break;case 2:u()&&(A.slice_del(),A.ket=A.cursor,A.eq_s_b(1,"u")&&(A.bra=A.cursor,s=A.limit-A.cursor,A.eq_s_b(1,"g")&&(A.cursor=A.limit-s,u()&&A.slice_del())))}}var v,p,g,k=[new s("",-1,6),new s("á",0,1),new s("é",0,2),new s("í",0,3),new s("ó",0,4),new s("ú",0,5)],y=[new s("la",-1,-1),new s("sela",0,-1),new s("le",-1,-1),new s("me",-1,-1),new s("se",-1,-1),new s("lo",-1,-1),new s("selo",5,-1),new s("las",-1,-1),new s("selas",7,-1),new s("les",-1,-1),new s("los",-1,-1),new s("selos",10,-1),new s("nos",-1,-1)],q=[new s("ando",-1,6),new s("iendo",-1,6),new s("yendo",-1,7),new s("ándo",-1,2),new s("iéndo",-1,1),new s("ar",-1,6),new s("er",-1,6),new s("ir",-1,6),new s("ár",-1,3),new s("ér",-1,4),new s("ír",-1,5)],C=[new s("ic",-1,-1),new s("ad",-1,-1),new s("os",-1,-1),new s("iLine truncated

assets/javascripts/lunr/min/lunr.fi.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Finnish` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(i,e){"function"==typeof define&&define.amd?define(e):"object"==typeof exports?module.exports=e():e()(i.lunr)}(this,function(){return function(i){if(void 0===i)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===i.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");i.fi=function(){this.pipeline.reset(),this.pipeline.add(i.fi.trimmer,i.fi.stopWordFilter,i.fi.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(i.fi.stemmer))},i.fi.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",i.fi.trimmer=i.trimmerSupport.generateTrimmer(i.fi.wordCharacters),i.Pipeline.registerFunction(i.fi.trimmer,"trimmer-fi"),i.fi.stemmer=function(){var e=i.stemmerSupport.Among,r=i.stemmerSupport.SnowballProgram,n=new function(){function i(){f=A.limit,d=f,n()||(f=A.cursor,n()||(d=A.cursor))}function n(){for(var i;;){if(i=A.cursor,A.in_grouping(W,97,246))break;if(A.cursor=i,i>=A.limit)return!0;A.cursor++}for(A.cursor=i;!A.out_grouping(W,97,246);){if(A.cursor>=A.limit)return!0;A.cursor++}return!1}function t(){return d<=A.cursor}function s(){var i,e;if(A.cursor>=f)if(e=A.limit_backward,A.limit_backward=f,A.ket=A.cursor,i=A.find_among_b(h,10)){switch(A.bra=A.cursor,A.limit_backward=e,i){case 1:if(!A.in_grouping_b(x,97,246))return;break;case 2:if(!t())return}A.slice_del()}else A.limit_backward=e}function o(){var i,e,r;if(A.cursor>=f)if(e=A.limit_backward,A.limit_backward=f,A.ket=A.cursor,i=A.find_among_b(v,9))switch(A.bra=A.cursor,A.limit_backward=e,i){case 1:r=A.limit-A.cursor,A.eq_s_b(1,"k")||(A.cursor=A.limit-r,A.slice_del());break;case 2:A.slice_del(),A.ket=A.cursor,A.eq_s_b(3,"kse")&&(A.bra=A.cursor,A.slice_from("ksi"));break;case 3:A.slice_del();break;case 4:A.find_among_b(p,6)&&A.slice_del();break;case 5:A.find_among_b(g,6)&&A.slice_del();break;case 6:A.find_among_b(j,2)&&A.slice_del()}else A.limit_backward=e}function l(){return A.find_among_b(q,7)}function a(){return A.eq_s_b(1,"i")&&A.in_grouping_b(L,97,246)}function u(){var i,e,r;if(A.cursor>=f)if(e=A.limit_backward,A.limit_backward=f,A.ket=A.cursor,i=A.find_among_b(C,30)){switch(A.bra=A.cursor,A.limit_backward=e,i){case 1:if(!A.eq_s_b(1,"a"))return;break;case 2:case 9:if(!A.eq_s_b(1,"e"))return;break;case 3:if(!A.eq_s_b(1,"i"))return;break;case 4:if(!A.eq_s_b(1,"o"))return;break;case 5:if(!A.eq_s_b(1,"ä"))return;break;case 6:if(!A.eq_s_b(1,"ö"))return;break;case 7:if(r=A.limit-A.cursor,!l()&&(A.cursor=A.limit-r,!A.eq_s_b(2,"ie"))){A.cursor=A.limit-r;break}if(A.cursor=A.limit-r,A.cursor<=A.limit_backward){A.cursor=A.limit-r;break}A.cursor--,A.bra=A.cursor;break;case 8:if(!A.in_grouping_b(W,97,246)||!A.out_grouping_b(W,97,246))return}A.slice_del(),k=!0}else A.limit_backward=e}function c(){var i,e,r;if(A.cursor>=d)if(e=A.limit_backward,A.limit_backward=d,A.ket=A.cursor,i=A.find_among_b(P,14)){if(A.bra=A.cursor,A.limit_backward=e,1==i){if(r=A.limit-A.cursor,A.eq_s_b(2,"po"))return;A.cursor=A.limit-r}A.slice_del()}else A.limit_backward=e}function m(){var i;A.cursor>=f&&(i=A.limit_backward,A.limit_backward=f,A.ket=A.cursor,A.find_among_b(F,2)?(A.bra=A.cursor,A.limit_backward=i,A.slice_del()):A.limit_backward=i)}function w(){var i,e,r,n,t,s;if(A.cursor>=f){if(e=A.limit_backward,A.limit_backward=f,A.ket=A.cursor,A.eq_s_b(1,"t")&&(A.bra=A.cursor,r=A.limit-A.cursor,A.in_grouping_b(W,97,246)&&(A.cursor=A.limit-r,A.slice_del(),A.limit_backward=e,n=A.limit-A.cursor,A.cursor>=d&&(A.cursor=d,t=A.limit_backward,A.limit_backward=A.cursor,A.cursor=A.limit-n,A.ket=A.cursor,i=A.find_among_b(S,2))))){if(A.bra=A.cursor,A.limit_backward=t,1==i){if(s=A.limit-A.cursor,A.eq_s_b(2,"po"))return;A.cursor=A.limit-s}return void A.slice_del()}A.limit_backward=e}}function _(){var i,e,r,n;if(A.cursor>=f){for(i=A.limit_backward,A.limit_backward=f,e=A.limit-A.cursor,l()&&(A.cursor=A.limit-e,A.ket=A.cursor,A.cursor>A.limit_backward&&(A.cursor--,A.bra=A.cursor,A.slice_del())),A.cursor=A.limit-e,A.ket=A.cursor,A.in_grouping_b(y,97,228)&&(A.bra=A.cursor,A.out_grouping_b(W,97,246)&&A.slice_del()),A.cursor=A.limit-e,A.ket=A.cursor,A.eq_s_b(1,"j")&&(A.bra=A.cursor,r=A.limit-A.cursor,A.eq_s_b(1,"o")?A.slice_del():(A.cursor=A.limit-r,A.eq_s_b(1,"u")&&A.slice_del())),A.cursor=A.limit-e,A.ket=A.cursor,A.eq_s_b(1,"o")&&(A.bra=A.cursor,A.eq_s_b(1,"j")&&A.slice_del()),A.cursor=A.limit-e,A.limit_backward=i;;){if(n=A.limit-A.cursor,A.out_grouping_b(W,97,246)){A.cursor=A.limit-n;break}if(A.cursor=A.limit-n,A.cursor<=A.limit_backward)return;A.cursor--}A.ket=A.cursor,A.cursor>A.limit_backward&&(A.cursor--,A.bra=A.cursor,b=A.slice_to(),A.eq_v_b(b)&&A.slice_del())}}var k,b,d,f,h=[new e("pa",-1,1),new e("sti",-1,2),new e("kaan",-1,1),new e("han",-1,1),new e("kin",-1,1),new e("hän",-1,1),new e("kään",-1,1),new e("ko",-1,Line truncated

assets/javascripts/lunr/min/lunr.fr.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `French` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.fr=function(){this.pipeline.reset(),this.pipeline.add(e.fr.trimmer,e.fr.stopWordFilter,e.fr.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.fr.stemmer))},e.fr.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.fr.trimmer=e.trimmerSupport.generateTrimmer(e.fr.wordCharacters),e.Pipeline.registerFunction(e.fr.trimmer,"trimmer-fr"),e.fr.stemmer=function(){var r=e.stemmerSupport.Among,s=e.stemmerSupport.SnowballProgram,i=new function(){function e(e,r,s){return!(!W.eq_s(1,e)||(W.ket=W.cursor,!W.in_grouping(F,97,251)))&&(W.slice_from(r),W.cursor=s,!0)}function i(e,r,s){return!!W.eq_s(1,e)&&(W.ket=W.cursor,W.slice_from(r),W.cursor=s,!0)}function n(){for(var r,s;;){if(r=W.cursor,W.in_grouping(F,97,251)){if(W.bra=W.cursor,s=W.cursor,e("u","U",r))continue;if(W.cursor=s,e("i","I",r))continue;if(W.cursor=s,i("y","Y",r))continue}if(W.cursor=r,W.bra=r,!e("y","Y",r)){if(W.cursor=r,W.eq_s(1,"q")&&(W.bra=W.cursor,i("u","U",r)))continue;if(W.cursor=r,r>=W.limit)return;W.cursor++}}}function t(){for(;!W.in_grouping(F,97,251);){if(W.cursor>=W.limit)return!0;W.cursor++}for(;!W.out_grouping(F,97,251);){if(W.cursor>=W.limit)return!0;W.cursor++}return!1}function u(){var e=W.cursor;if(q=W.limit,g=q,p=q,W.in_grouping(F,97,251)&&W.in_grouping(F,97,251)&&W.cursor<W.limit)W.cursor++;else if(W.cursor=e,!W.find_among(v,3)){W.cursor=e;do{if(W.cursor>=W.limit){W.cursor=q;break}W.cursor++}while(!W.in_grouping(F,97,251))}q=W.cursor,W.cursor=e,t()||(g=W.cursor,t()||(p=W.cursor))}function o(){for(var e,r;;){if(r=W.cursor,W.bra=r,!(e=W.find_among(h,4)))break;switch(W.ket=W.cursor,e){case 1:W.slice_from("i");break;case 2:W.slice_from("u");break;case 3:W.slice_from("y");break;case 4:if(W.cursor>=W.limit)return;W.cursor++}}}function c(){return q<=W.cursor}function a(){return g<=W.cursor}function l(){return p<=W.cursor}function w(){var e,r;if(W.ket=W.cursor,e=W.find_among_b(C,43)){switch(W.bra=W.cursor,e){case 1:if(!l())return!1;W.slice_del();break;case 2:if(!l())return!1;W.slice_del(),W.ket=W.cursor,W.eq_s_b(2,"ic")&&(W.bra=W.cursor,l()?W.slice_del():W.slice_from("iqU"));break;case 3:if(!l())return!1;W.slice_from("log");break;case 4:if(!l())return!1;W.slice_from("u");break;case 5:if(!l())return!1;W.slice_from("ent");break;case 6:if(!c())return!1;if(W.slice_del(),W.ket=W.cursor,e=W.find_among_b(z,6))switch(W.bra=W.cursor,e){case 1:l()&&(W.slice_del(),W.ket=W.cursor,W.eq_s_b(2,"at")&&(W.bra=W.cursor,l()&&W.slice_del()));break;case 2:l()?W.slice_del():a()&&W.slice_from("eux");break;case 3:l()&&W.slice_del();break;case 4:c()&&W.slice_from("i")}break;case 7:if(!l())return!1;if(W.slice_del(),W.ket=W.cursor,e=W.find_among_b(y,3))switch(W.bra=W.cursor,e){case 1:l()?W.slice_del():W.slice_from("abl");break;case 2:l()?W.slice_del():W.slice_from("iqU");break;case 3:l()&&W.slice_del()}break;case 8:if(!l())return!1;if(W.slice_del(),W.ket=W.cursor,W.eq_s_b(2,"at")&&(W.bra=W.cursor,l()&&(W.slice_del(),W.ket=W.cursor,W.eq_s_b(2,"ic")))){W.bra=W.cursor,l()?W.slice_del():W.slice_from("iqU");break}break;case 9:W.slice_from("eau");break;case 10:if(!a())return!1;W.slice_from("al");break;case 11:if(l())W.slice_del();else{if(!a())return!1;W.slice_from("eux")}break;case 12:if(!a()||!W.out_grouping_b(F,97,251))return!1;W.slice_del();break;case 13:return c()&&W.slice_from("ant"),!1;case 14:return c()&&W.slice_from("ent"),!1;case 15:return r=W.limit-W.cursor,W.in_grouping_b(F,97,251)&&c()&&(W.cursor=W.limit-r,W.slice_del()),!1}return!0}return!1}function f(){var e,r;if(W.cursor<q)return!1;if(r=W.limit_backward,W.limit_backward=q,W.ket=W.cursor,!(e=W.find_among_b(x,35)))return W.limit_backward=r,!1;if(W.bra=W.cursor,1==e){if(!W.out_grouping_b(F,97,251))return W.limit_backward=r,!1;W.slice_del()}return W.limit_backward=r,!0}function m(){var e,r,s;if(W.cursor<q)return!1;if(r=W.limit_backward,W.limit_backward=q,W.ket=W.cursor,!(e=W.find_among_b(I,38)))return W.limit_backward=r,!1;switch(W.bra=W.cursor,e){case 1:if(!l())return W.limit_backward=r,!1;W.slice_del();break;case 2:W.slice_del();break;case 3:W.slice_del(),s=W.limit-W.cursor,W.ket=W.cursor,W.eq_s_b(1,"e")?(W.bra=W.cursor,W.slice_del()):W.cursor=W.limit-s}return W.limit_backward=r,!0}function _(){var e,r,s,i,n=W.limit-W.cursor;if(W.ket=W.cursor,W.eq_s_b(1,"s")?(W.bra=W.cursor,r=W.limit-W.cursor,W.out_grouping_b(S,97,232)?(W.cursor=W.limit-r,W.slice_del()):W.cursor=W.limit-n):W.cursor=W.limit-n,W.cursor>=q){if(s=W.limit_backward,W.limit_backwarLine truncated

assets/javascripts/lunr/min/lunr.he.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.he=function(){this.pipeline.reset(),this.pipeline.add(e.he.trimmer,e.he.stopWordFilter,e.he.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.he.stemmer))},e.he.wordCharacters="֑-״א-תa-zA-Zａ-ｚＡ-Ｚ0-9０-９",e.he.trimmer=e.trimmerSupport.generateTrimmer(e.he.wordCharacters),e.Pipeline.registerFunction(e.he.trimmer,"trimmer-he"),e.he.stemmer=function(){var e=this;return e.result=!1,e.preRemoved=!1,e.sufRemoved=!1,e.pre={pre1:"ה ו י ת",pre2:"ב כ ל מ ש כש",pre3:"הב הכ הל המ הש בש לכ",pre4:"וב וכ ול ומ וש",pre5:"מה שה כל",pre6:"מב מכ מל ממ מש",pre7:"בה בו בי בת כה כו כי כת לה לו לי לת",pre8:"ובה ובו ובי ובת וכה וכו וכי וכת ולה ולו ולי ולת"},e.suf={suf1:"ך כ ם ן נ",suf2:"ים ות וך וכ ום ון ונ הם הן יכ יך ינ ים",suf3:"תי תך תכ תם תן תנ",suf4:"ותי ותך ותכ ותם ותן ותנ",suf5:"נו כם כן הם הן",suf6:"ונו וכם וכן והם והן",suf7:"תכם תכן תנו תהם תהן",suf8:"הוא היא הם הן אני אתה את אנו אתם אתן",suf9:"ני נו כי כו כם כן תי תך תכ תם תן",suf10:"י ך כ ם ן נ ת"},e.patterns=JSON.parse('{"hebrewPatterns": [{"pt1": [{"c": "ה", "l": 0}]}, {"pt2": [{"c": "ו", "l": 0}]}, {"pt3": [{"c": "י", "l": 0}]}, {"pt4": [{"c": "ת", "l": 0}]}, {"pt5": [{"c": "מ", "l": 0}]}, {"pt6": [{"c": "ל", "l": 0}]}, {"pt7": [{"c": "ב", "l": 0}]}, {"pt8": [{"c": "כ", "l": 0}]}, {"pt9": [{"c": "ש", "l": 0}]}, {"pt10": [{"c": "כש", "l": 0}]}, {"pt11": [{"c": "בה", "l": 0}]}, {"pt12": [{"c": "וב", "l": 0}]}, {"pt13": [{"c": "וכ", "l": 0}]}, {"pt14": [{"c": "ול", "l": 0}]}, {"pt15": [{"c": "ומ", "l": 0}]}, {"pt16": [{"c": "וש", "l": 0}]}, {"pt17": [{"c": "הב", "l": 0}]}, {"pt18": [{"c": "הכ", "l": 0}]}, {"pt19": [{"c": "הל", "l": 0}]}, {"pt20": [{"c": "המ", "l": 0}]}, {"pt21": [{"c": "הש", "l": 0}]}, {"pt22": [{"c": "מה", "l": 0}]}, {"pt23": [{"c": "שה", "l": 0}]}, {"pt24": [{"c": "כל", "l": 0}]}]}'),e.execArray=["cleanWord","removeDiacritics","removeStopWords","normalizeHebrewCharacters"],e.stem=function(){var r=0;for(e.result=!1,e.preRemoved=!1,e.sufRemoved=!1;r<e.execArray.length&&1!=e.result;)e.result=e[e.execArray[r]](),r++},e.setCurrent=function(r){e.word=r},e.getCurrent=function(){return e.word},e.cleanWord=function(){return!!new RegExp("[^֑-״א-ת]").test("")},e.removeDiacritics=function(){var r=new RegExp("[ְ-ֿ]","g");return e.word=e.word.replace(r,""),!1},e.removeStopWords=function(){if("אבל או אולי אותו אותי אותך אותם אותן אותנו אז אחר אחרות אחרי אחריכן אחרים אחרת אי איזה איך אין איפה אל אלה אלו אם אנחנו אני אף אפשר את אתה אתכם אתכן אתם אתן באיזה באיזו בגלל בין בלבד בעבור בעזרת בכל בכן בלי במידה במקום שבו ברוב בשביל בשעה ש בתוך גם דרך הוא היא היה היי היכן היתה היתי הם הן הנה הסיבה שבגללה הרי ואילו ואת זאת זה זות יהיה יוכל יוכלו יותר מדי יכול יכולה יכולות יכולים יכל יכלה יכלו יש כאן כאשר כולם כולן כזה כי כיצד כך כל כלל כמו כן כפי כש לא לאו לאיזותך לאן לבין לה להיות להם להן לו לזה לזות לי לך לכם לכן למה למעלה למעלה מ למטה למטה מ למעט למקום שבו למרות לנו לעבר לעיכן לפיכך לפני מאד מאחורי מאיזו סיבה מאין מאיפה מבלי מבעד מדוע מה מהיכן מול מחוץ מי מידע מכאן מכל מכן מלבד מן מנין מסוגל מעט מעטים מעל מצד מקום בו מתחת מתי נגד נגר נו עד עז על עלי עליו עליה עליהם עליך עלינו עם עצמה עצמהם עצמהן עצמו עצמי עצמם עצמן עצמנו פה רק שוב של שלה שלהם שלהן שלו שלי שלך שלכה שלכם שלכן שלנו שם תהיה תחת".split(" ").indexOf(e.word)>=0)return!0},e.normalizeHebrewCharacters=function(){return e.word=e.word.replace("ך","כ"),e.word=e.word.replace("ם","מ"),e.word=e.word.replace("ן","נ"),e.word=e.word.replace("ף","פ"),e.word=e.word.replace("ץ","צ"),!1},function(r){return"function"==typeof r.update?r.update(function(r){return e.setLine truncated

assets/javascripts/lunr/min/lunr.hi.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.hi=function(){this.pipeline.reset(),this.pipeline.add(e.hi.trimmer,e.hi.stopWordFilter,e.hi.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.hi.stemmer))},e.hi.wordCharacters="ऀ-ःऄ-एऐ-टठ-यर-िी-ॏॐ-य़ॠ-९॰-ॿa-zA-Zａ-ｚＡ-Ｚ0-9０-９",e.hi.trimmer=e.trimmerSupport.generateTrimmer(e.hi.wordCharacters),e.Pipeline.registerFunction(e.hi.trimmer,"trimmer-hi"),e.hi.stopWordFilter=e.generateStopWordFilter("अत अपना अपनी अपने अभी अंदर आदि आप इत्यादि इन इनका इन्हीं इन्हें इन्हों इस इसका इसकी इसके इसमें इसी इसे उन उनका उनकी उनके उनको उन्हीं उन्हें उन्हों उस उसके उसी उसे एक एवं एस ऐसे और कई कर करता करते करना करने करें कहते कहा का काफ़ी कि कितना किन्हें किन्हों किया किर किस किसी किसे की कुछ कुल के को कोई कौन कौनसा गया घर जब जहाँ जा जितना जिन जिन्हें जिन्हों जिस जिसे जीधर जैसा जैसे जो तक तब तरह तिन तिन्हें तिन्हों तिस तिसे तो था थी थे दबारा दिया दुसरा दूसरे दो द्वारा न नके नहीं ना निहायत नीचे ने पर पहले पूरा पे फिर बनी बही बहुत बाद बाला बिलकुल भी भीतर मगर मानो मे में यदि यह यहाँ यही या यिह ये रखें रहा रहे ऱ्वासा लिए लिये लेकिन व वग़ैरह वर्ग वह वहाँ वहीं वाले वुह वे वो सकता सकते सबसे सभी साथ साबुत साभ सारा से सो संग ही हुआ हुई हुए है हैं हो होता होती होते होना होने".split(" ")),e.hi.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}();var r=e.wordcut;r.init(),e.hi.tokenizer=function(i){if(!arguments.length||null==i||void 0==i)return[];if(Array.isArray(i))return i.map(function(r){return isLunr2?new e.Token(r.toLowerCase()):r.toLowerCase()});var t=i.toString().toLowerCase().replace(/^\s+/,"");return r.cut(t).split("|")},e.Pipeline.registerFunction(e.hi.stemmer,"stemmer-hi"),e.Pipeline.registerFunction(e.hi.stopWordFilter,"stopWordFilter-hi")}});

assets/javascripts/lunr/min/lunr.hu.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Hungarian` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,n){"function"==typeof define&&define.amd?define(n):"object"==typeof exports?module.exports=n():n()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.hu=function(){this.pipeline.reset(),this.pipeline.add(e.hu.trimmer,e.hu.stopWordFilter,e.hu.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.hu.stemmer))},e.hu.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.hu.trimmer=e.trimmerSupport.generateTrimmer(e.hu.wordCharacters),e.Pipeline.registerFunction(e.hu.trimmer,"trimmer-hu"),e.hu.stemmer=function(){var n=e.stemmerSupport.Among,r=e.stemmerSupport.SnowballProgram,i=new function(){function e(){var e,n=L.cursor;if(d=L.limit,L.in_grouping(W,97,252))for(;;){if(e=L.cursor,L.out_grouping(W,97,252))return L.cursor=e,L.find_among(g,8)||(L.cursor=e,e<L.limit&&L.cursor++),void(d=L.cursor);if(L.cursor=e,e>=L.limit)return void(d=e);L.cursor++}if(L.cursor=n,L.out_grouping(W,97,252)){for(;!L.in_grouping(W,97,252);){if(L.cursor>=L.limit)return;L.cursor++}d=L.cursor}}function i(){return d<=L.cursor}function a(){var e;if(L.ket=L.cursor,(e=L.find_among_b(h,2))&&(L.bra=L.cursor,i()))switch(e){case 1:L.slice_from("a");break;case 2:L.slice_from("e")}}function t(){var e=L.limit-L.cursor;return!!L.find_among_b(p,23)&&(L.cursor=L.limit-e,!0)}function s(){if(L.cursor>L.limit_backward){L.cursor--,L.ket=L.cursor;var e=L.cursor-1;L.limit_backward<=e&&e<=L.limit&&(L.cursor=e,L.bra=e,L.slice_del())}}function c(){var e;if(L.ket=L.cursor,(e=L.find_among_b(_,2))&&(L.bra=L.cursor,i())){if((1==e||2==e)&&!t())return;L.slice_del(),s()}}function o(){L.ket=L.cursor,L.find_among_b(v,44)&&(L.bra=L.cursor,i()&&(L.slice_del(),a()))}function w(){var e;if(L.ket=L.cursor,(e=L.find_among_b(z,3))&&(L.bra=L.cursor,i()))switch(e){case 1:L.slice_from("e");break;case 2:case 3:L.slice_from("a")}}function l(){var e;if(L.ket=L.cursor,(e=L.find_among_b(y,6))&&(L.bra=L.cursor,i()))switch(e){case 1:case 2:L.slice_del();break;case 3:L.slice_from("a");break;case 4:L.slice_from("e")}}function u(){var e;if(L.ket=L.cursor,(e=L.find_among_b(j,2))&&(L.bra=L.cursor,i())){if((1==e||2==e)&&!t())return;L.slice_del(),s()}}function m(){var e;if(L.ket=L.cursor,(e=L.find_among_b(C,7))&&(L.bra=L.cursor,i()))switch(e){case 1:L.slice_from("a");break;case 2:L.slice_from("e");break;case 3:case 4:case 5:case 6:case 7:L.slice_del()}}function k(){var e;if(L.ket=L.cursor,(e=L.find_among_b(P,12))&&(L.bra=L.cursor,i()))switch(e){case 1:case 4:case 7:case 9:L.slice_del();break;case 2:case 5:case 8:L.slice_from("e");break;case 3:case 6:L.slice_from("a")}}function f(){var e;if(L.ket=L.cursor,(e=L.find_among_b(F,31))&&(L.bra=L.cursor,i()))switch(e){case 1:case 4:case 7:case 8:case 9:case 12:case 13:case 16:case 17:case 18:L.slice_del();break;case 2:case 5:case 10:case 14:case 19:L.slice_from("a");break;case 3:case 6:case 11:case 15:case 20:L.slice_from("e")}}function b(){var e;if(L.ket=L.cursor,(e=L.find_among_b(S,42))&&(L.bra=L.cursor,i()))switch(e){case 1:case 4:case 5:case 6:case 9:case 10:case 11:case 14:case 15:case 16:case 17:case 20:case 21:case 24:case 25:case 26:case 29:L.slice_del();break;case 2:case 7:case 12:case 18:case 22:case 27:L.slice_from("a");break;case 3:case 8:case 13:case 19:case 23:case 28:L.slice_from("e")}}var d,g=[new n("cs",-1,-1),new n("dzs",-1,-1),new n("gy",-1,-1),new n("ly",-1,-1),new n("ny",-1,-1),new n("sz",-1,-1),new n("ty",-1,-1),new n("zs",-1,-1)],h=[new n("á",-1,1),new n("é",-1,2)],p=[new n("bb",-1,-1),new n("cc",-1,-1),new n("dd",-1,-1),new n("ff",-1,-1),new n("gg",-1,-1),new n("jj",-1,-1),new n("kk",-1,-1),new n("ll",-1,-1),new n("mm",-1,-1),new n("nn",-1,-1),new n("pp",-1,-1),new n("rr",-1,-1),new n("ccs",-1,-1),new n("ss",-1,-1),new n("zzs",-1,-1),new n("tt",-1,-1),new n("vv",-1,-1),new n("ggy",-1,-1),new n("lly",-1,-1),new n("nny",-1,-1),new n("tty",-1,-1),new n("ssz",-1,-1),new n("zz",-1,-1)],_=[new n("al",-1,1),new n("el",-1,2)],v=[new n("ba",-1,-1),new n("ra",-1,-1),new n("be",-1,-1),new n("re",-1,-1),new n("ig",-1,-1),new n("nak",-1,-1),new n("nek",-1,-1),new n("val",-1,-1),new n("vel",-1,-1),new n("ul",-1,-1),new n("nál",-1,-1),new n("nél",-1,-1),new n("ból",-1,-1),new n("ról",-1,-1),new n("tól",-1,-1),new n("bõl",-1,-1),new n("rõl",-1,-1),new n("tõl",-1,-1),new n("ül",-1,-1),new n("n",-1,-1),new n("an",19,-1),new n("ban",20,-1),new n("en",19,-1),new n("ben",22,-1),new n("képpen",22,-1),new n("on",19,-1),new n("ön",19,-1),new n("képp",-1,-1),new n("kor",-1,-1),new n("t",-1,-1),new n("at",29,-1),new n("et",29,-1),new n("ként",29,-1),new n("anként",32,-1),new n("enként",32,-1),new n("onként",32,-1),Line truncated

assets/javascripts/lunr/min/lunr.hy.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.hy=function(){this.pipeline.reset(),this.pipeline.add(e.hy.trimmer,e.hy.stopWordFilter)},e.hy.wordCharacters="[A-Za-z԰-֏ff-ﭏ]",e.hy.trimmer=e.trimmerSupport.generateTrimmer(e.hy.wordCharacters),e.Pipeline.registerFunction(e.hy.trimmer,"trimmer-hy"),e.hy.stopWordFilter=e.generateStopWordFilter("դու և եք էիր էիք հետո նաև նրանք որը վրա է որ պիտի են այս մեջ ն իր ու ի այդ որոնք այն կամ էր մի ես համար այլ իսկ էին ենք հետ ին թ էինք մենք նրա նա դուք եմ էի ըստ որպես ում".split(" ")),e.Pipeline.registerFunction(e.hy.stopWordFilter,"stopWordFilter-hy"),e.hy.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}(),e.Pipeline.registerFunction(e.hy.stemmer,"stemmer-hy")}});

assets/javascripts/lunr/min/lunr.it.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Italian` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.it=function(){this.pipeline.reset(),this.pipeline.add(e.it.trimmer,e.it.stopWordFilter,e.it.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.it.stemmer))},e.it.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.it.trimmer=e.trimmerSupport.generateTrimmer(e.it.wordCharacters),e.Pipeline.registerFunction(e.it.trimmer,"trimmer-it"),e.it.stemmer=function(){var r=e.stemmerSupport.Among,n=e.stemmerSupport.SnowballProgram,i=new function(){function e(e,r,n){return!(!x.eq_s(1,e)||(x.ket=x.cursor,!x.in_grouping(L,97,249)))&&(x.slice_from(r),x.cursor=n,!0)}function i(){for(var r,n,i,o,t=x.cursor;;){if(x.bra=x.cursor,r=x.find_among(h,7))switch(x.ket=x.cursor,r){case 1:x.slice_from("à");continue;case 2:x.slice_from("è");continue;case 3:x.slice_from("ì");continue;case 4:x.slice_from("ò");continue;case 5:x.slice_from("ù");continue;case 6:x.slice_from("qU");continue;case 7:if(x.cursor>=x.limit)break;x.cursor++;continue}break}for(x.cursor=t;;)for(n=x.cursor;;){if(i=x.cursor,x.in_grouping(L,97,249)){if(x.bra=x.cursor,o=x.cursor,e("u","U",i))break;if(x.cursor=o,e("i","I",i))break}if(x.cursor=i,x.cursor>=x.limit)return void(x.cursor=n);x.cursor++}}function o(e){if(x.cursor=e,!x.in_grouping(L,97,249))return!1;for(;!x.out_grouping(L,97,249);){if(x.cursor>=x.limit)return!1;x.cursor++}return!0}function t(){if(x.in_grouping(L,97,249)){var e=x.cursor;if(x.out_grouping(L,97,249)){for(;!x.in_grouping(L,97,249);){if(x.cursor>=x.limit)return o(e);x.cursor++}return!0}return o(e)}return!1}function s(){var e,r=x.cursor;if(!t()){if(x.cursor=r,!x.out_grouping(L,97,249))return;if(e=x.cursor,x.out_grouping(L,97,249)){for(;!x.in_grouping(L,97,249);){if(x.cursor>=x.limit)return x.cursor=e,void(x.in_grouping(L,97,249)&&x.cursor<x.limit&&x.cursor++);x.cursor++}return void(k=x.cursor)}if(x.cursor=e,!x.in_grouping(L,97,249)||x.cursor>=x.limit)return;x.cursor++}k=x.cursor}function a(){for(;!x.in_grouping(L,97,249);){if(x.cursor>=x.limit)return!1;x.cursor++}for(;!x.out_grouping(L,97,249);){if(x.cursor>=x.limit)return!1;x.cursor++}return!0}function u(){var e=x.cursor;k=x.limit,p=k,g=k,s(),x.cursor=e,a()&&(p=x.cursor,a()&&(g=x.cursor))}function c(){for(var e;;){if(x.bra=x.cursor,!(e=x.find_among(q,3)))break;switch(x.ket=x.cursor,e){case 1:x.slice_from("i");break;case 2:x.slice_from("u");break;case 3:if(x.cursor>=x.limit)return;x.cursor++}}}function w(){return k<=x.cursor}function l(){return p<=x.cursor}function m(){return g<=x.cursor}function f(){var e;if(x.ket=x.cursor,x.find_among_b(C,37)&&(x.bra=x.cursor,(e=x.find_among_b(z,5))&&w()))switch(e){case 1:x.slice_del();break;case 2:x.slice_from("e")}}function v(){var e;if(x.ket=x.cursor,!(e=x.find_among_b(S,51)))return!1;switch(x.bra=x.cursor,e){case 1:if(!m())return!1;x.slice_del();break;case 2:if(!m())return!1;x.slice_del(),x.ket=x.cursor,x.eq_s_b(2,"ic")&&(x.bra=x.cursor,m()&&x.slice_del());break;case 3:if(!m())return!1;x.slice_from("log");break;case 4:if(!m())return!1;x.slice_from("u");break;case 5:if(!m())return!1;x.slice_from("ente");break;case 6:if(!w())return!1;x.slice_del();break;case 7:if(!l())return!1;x.slice_del(),x.ket=x.cursor,e=x.find_among_b(P,4),e&&(x.bra=x.cursor,m()&&(x.slice_del(),1==e&&(x.ket=x.cursor,x.eq_s_b(2,"at")&&(x.bra=x.cursor,m()&&x.slice_del()))));break;case 8:if(!m())return!1;x.slice_del(),x.ket=x.cursor,e=x.find_among_b(F,3),e&&(x.bra=x.cursor,1==e&&m()&&x.slice_del());break;case 9:if(!m())return!1;x.slice_del(),x.ket=x.cursor,x.eq_s_b(2,"at")&&(x.bra=x.cursor,m()&&(x.slice_del(),x.ket=x.cursor,x.eq_s_b(2,"ic")&&(x.bra=x.cursor,m()&&x.slice_del())))}return!0}function b(){var e,r;x.cursor>=k&&(r=x.limit_backward,x.limit_backward=k,x.ket=x.cursor,e=x.find_among_b(W,87),e&&(x.bra=x.cursor,1==e&&x.slice_del()),x.limit_backward=r)}function d(){var e=x.limit-x.cursor;if(x.ket=x.cursor,x.in_grouping_b(y,97,242)&&(x.bra=x.cursor,w()&&(x.slice_del(),x.ket=x.cursor,x.eq_s_b(1,"i")&&(x.bra=x.cursor,w()))))return void x.slice_del();x.cursor=x.limit-e}function _(){d(),x.ket=x.cursor,x.eq_s_b(1,"h")&&(x.bra=x.cursor,x.in_grouping_b(U,99,103)&&w()&&x.slice_del())}var g,p,k,h=[new r("",-1,7),new r("qu",0,6),new r("á",0,1),new r("é",0,2),new r("í",0,3),new r("ó",0,4),new r("ú",0,5)],q=[new r("",-1,3),new r("I",0,1),new r("U",0,2)],C=[new r("la",-1,-1),new r("cela",0,-1),new r("gliela",0,-1),new r("mela",0,-1),new r("tela",0,-1),new r("vela",0,-1),new r("le",-1,-1),new r("cele",6,-1),new r("gliele",6Line truncated

assets/javascripts/lunr/min/lunr.ja.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");var r="2"==e.version[0];e.ja=function(){this.pipeline.reset(),this.pipeline.add(e.ja.trimmer,e.ja.stopWordFilter,e.ja.stemmer),r?this.tokenizer=e.ja.tokenizer:(e.tokenizer&&(e.tokenizer=e.ja.tokenizer),this.tokenizerFn&&(this.tokenizerFn=e.ja.tokenizer))};var t=new e.TinySegmenter;e.ja.tokenizer=function(i){var n,o,s,p,a,u,m,l,c,f;if(!arguments.length||null==i||void 0==i)return[];if(Array.isArray(i))return i.map(function(t){return r?new e.Token(t.toLowerCase()):t.toLowerCase()});for(o=i.toString().toLowerCase().replace(/^\s+/,""),n=o.length-1;n>=0;n--)if(/\S/.test(o.charAt(n))){o=o.substring(0,n+1);break}for(a=[],s=o.length,c=0,l=0;c<=s;c++)if(u=o.charAt(c),m=c-l,u.match(/\s/)||c==s){if(m>0)for(p=t.segment(o.slice(l,c)).filter(function(e){return!!e}),f=l,n=0;n<p.length;n++)r?a.push(new e.Token(p[n],{position:[f,p[n].length],index:a.length})):a.push(p[n]),f+=p[n].length;l=c+1}return a},e.ja.stemmer=function(){return function(e){return e}}(),e.Pipeline.registerFunction(e.ja.stemmer,"stemmer-ja"),e.ja.wordCharacters="一二三四五六七八九十百千万億兆一-龠々〆ヵヶぁ-んァ-ヴーｱ-ﾝﾞa-zA-Zａ-ｚＡ-Ｚ0-9０-９",e.ja.trimmer=e.trimmerSupport.generateTrimmer(e.ja.wordCharacters),e.Pipeline.registerFunction(e.ja.trimmer,"trimmer-ja"),e.ja.stopWordFilter=e.generateStopWordFilter("これ それ あれ この その あの ここ そこ あそこ こちら どこ だれ なに なん 何 私 貴方 貴方方 我々 私達 あの人 あのかた 彼女 彼 です あります おります います は が の に を で え から まで より も どの と し それで しかし".split(" ")),e.Pipeline.registerFunction(e.ja.stopWordFilter,"stopWordFilter-ja"),e.jp=e.ja,e.Pipeline.registerFunction(e.jp.stemmer,"stemmer-jp"),e.Pipeline.registerFunction(e.jp.trimmer,"trimmer-jp"),e.Pipeline.registerFunction(e.jp.stopWordFilter,"stopWordFilter-jp")}});

assets/javascripts/lunr/min/lunr.jp.min.js

@@ -0,0 +1 @@
+module.exports=require("./lunr.ja");

assets/javascripts/lunr/min/lunr.kn.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.kn=function(){this.pipeline.reset(),this.pipeline.add(e.kn.trimmer,e.kn.stopWordFilter,e.kn.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.kn.stemmer))},e.kn.wordCharacters="ಀ-಄ಅ-ಔಕ-ಹಾ-ೌ಼-ಽೕ-ೖೝ-ೞೠ-ೡೢ-ೣ೤೥೦-೯ೱ-ೳ",e.kn.trimmer=e.trimmerSupport.generateTrimmer(e.kn.wordCharacters),e.Pipeline.registerFunction(e.kn.trimmer,"trimmer-kn"),e.kn.stopWordFilter=e.generateStopWordFilter("ಮತ್ತು ಈ ಒಂದು ರಲ್ಲಿ ಹಾಗೂ ಎಂದು ಅಥವಾ ಇದು ರ ಅವರು ಎಂಬ ಮೇಲೆ ಅವರ ತನ್ನ ಆದರೆ ತಮ್ಮ ನಂತರ ಮೂಲಕ ಹೆಚ್ಚು ನ ಆ ಕೆಲವು ಅನೇಕ ಎರಡು ಹಾಗು ಪ್ರಮುಖ ಇದನ್ನು ಇದರ ಸುಮಾರು ಅದರ ಅದು ಮೊದಲ ಬಗ್ಗೆ ನಲ್ಲಿ ರಂದು ಇತರ ಅತ್ಯಂತ ಹೆಚ್ಚಿನ ಸಹ ಸಾಮಾನ್ಯವಾಗಿ ನೇ ಹಲವಾರು ಹೊಸ ದಿ ಕಡಿಮೆ ಯಾವುದೇ ಹೊಂದಿದೆ ದೊಡ್ಡ ಅನ್ನು ಇವರು ಪ್ರಕಾರ ಇದೆ ಮಾತ್ರ ಕೂಡ ಇಲ್ಲಿ ಎಲ್ಲಾ ವಿವಿಧ ಅದನ್ನು ಹಲವು ರಿಂದ ಕೇವಲ ದ ದಕ್ಷಿಣ ಗೆ ಅವನ ಅತಿ ನೆಯ ಬಹಳ ಕೆಲಸ ಎಲ್ಲ ಪ್ರತಿ ಇತ್ಯಾದಿ ಇವು ಬೇರೆ ಹೀಗೆ ನಡುವೆ ಇದಕ್ಕೆ ಎಸ್ ಇವರ ಮೊದಲು ಶ್ರೀ ಮಾಡುವ ಇದರಲ್ಲಿ ರೀತಿಯ ಮಾಡಿದ ಕಾಲ ಅಲ್ಲಿ ಮಾಡಲು ಅದೇ ಈಗ ಅವು ಗಳು ಎ ಎಂಬುದು ಅವನು ಅಂದರೆ ಅವರಿಗೆ ಇರುವ ವಿಶೇಷ ಮುಂದೆ ಅವುಗಳ ಮುಂತಾದ ಮೂಲ ಬಿ ಮೀ ಒಂದೇ ಇನ್ನೂ ಹೆಚ್ಚಾಗಿ ಮಾಡಿ ಅವರನ್ನು ಇದೇ ಯ ರೀತಿಯಲ್ಲಿ ಜೊತೆ ಅದರಲ್ಲಿ ಮಾಡಿದರು ನಡೆದ ಆಗ ಮತ್ತೆ ಪೂರ್ವ ಆತ ಬಂದ ಯಾವ ಒಟ್ಟು ಇತರೆ ಹಿಂದೆ ಪ್ರಮಾಣದ ಗಳನ್ನು ಕುರಿತು ಯು ಆದ್ದರಿಂದ ಅಲ್ಲದೆ ನಗರದ ಮೇಲಿನ ಏಕೆಂದರೆ ರಷ್ಟು ಎಂಬುದನ್ನು ಬಾರಿ ಎಂದರೆ ಹಿಂದಿನ ಆದರೂ ಆದ ಸಂಬಂಧಿಸಿದ ಮತ್ತೊಂದು ಸಿ ಆತನ ".split(" ")),e.kn.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}();var r=e.wordcut;r.init(),e.kn.tokenizer=function(t){if(!arguments.length||null==t||void 0==t)return[];if(Array.isArray(t))return t.map(function(r){return isLunr2?new e.Token(r.toLowerCase()):r.toLowerCase()});var n=t.toString().toLowerCase().replace(/^\s+/,"");return r.cut(n).split("|")},e.Pipeline.registerFunction(e.kn.stemmer,"stemmer-kn"),e.Pipeline.registerFunction(e.kn.stopWordFilter,"stopWordFilter-kn")}});

assets/javascripts/lunr/min/lunr.ko.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.ko=function(){this.pipeline.reset(),this.pipeline.add(e.ko.trimmer,e.ko.stopWordFilter)},e.ko.wordCharacters="[A-Za-z가-힣]",e.ko.trimmer=e.trimmerSupport.generateTrimmer(e.ko.wordCharacters),e.Pipeline.registerFunction(e.ko.trimmer,"trimmer-ko"),e.ko.stopWordFilter=e.generateStopWordFilter("아 휴 아이구 아이쿠 아이고 어 나 우리 저희 따라 의해 을 를 에 의 가 으로 로 에게 뿐이다 의거하여 근거하여 입각하여 기준으로 예하면 예를 들면 예를 들자면 저 소인 소생 저희 지말고 하지마 하지마라 다른 물론 또한 그리고 비길수 없다 해서는 안된다 뿐만 아니라 만이 아니다 만은 아니다 막론하고 관계없이 그치지 않다 그러나 그런데 하지만 든간에 논하지 않다 따지지 않다 설사 비록 더라도 아니면 만 못하다 하는 편이 낫다 불문하고 향하여 향해서 향하다 쪽으로 틈타 이용하여 타다 오르다 제외하고 이 외에 이 밖에 하여야 비로소 한다면 몰라도 외에도 이곳 여기 부터 기점으로 따라서 할 생각이다 하려고하다 이리하여 그리하여 그렇게 함으로써 하지만 일때 할때 앞에서 중에서 보는데서 으로써 로써 까지 해야한다 일것이다 반드시 할줄알다 할수있다 할수있어 임에 틀림없다 한다면 등 등등 제 겨우 단지 다만 할뿐 딩동 댕그 대해서 대하여 대하면 훨씬 얼마나 얼마만큼 얼마큼 남짓 여 얼마간 약간 다소 좀 조금 다수 몇 얼마 지만 하물며 또한 그러나 그렇지만 하지만 이외에도 대해 말하자면 뿐이다 다음에 반대로 반대로 말하자면 이와 반대로 바꾸어서 말하면 바꾸어서 한다면 만약 그렇지않으면 까악 툭 딱 삐걱거리다 보드득 비걱거리다 꽈당 응당 해야한다 에 가서 각 각각 여러분 각종 각자 제각기 하도록하다 와 과 그러므로 그래서 고로 한 까닭에 하기 때문에 거니와 이지만 대하여 관하여 관한 과연 실로 아니나다를가 생각한대로 진짜로 한적이있다 하곤하였다 하 하하 허허 아하 거바 와 오 왜 어째서 무엇때문에 어찌 하겠는가 무슨 어디 어느곳 더군다나 하물며 더욱이는 어느때 언제 야 이봐 어이 여보시오 흐흐 흥 휴 헉헉 헐떡헐떡 영차 여차 어기여차 끙끙 아야 앗 아야 콸콸 졸졸 좍좍 뚝뚝 주룩주룩 솨 우르르 그래도 또 그리고 바꾸어말하면 바꾸어말하자면 혹은 혹시 답다 및 그에 따르는 때가 되어 즉 지든지 설령 가령 하더라도 할지라도 일지라도 지든지 몇 거의 하마터면 인젠 이젠 된바에야 된이상 만큼\t어찌됏든 그위에 게다가 점에서 보아 비추어 보아 고려하면 하게될것이다 일것이다 비교적 좀 보다더 비하면 시키다 하게하다 할만하다 의해서 연이서 이어서 잇따라 뒤따라 뒤이어 결국 의지하여 기대여 통하여 자마자 더욱더 불구하고 얼마든지 마음대로 주저하지 않고 곧 즉시 바로 당장 하자마자 밖에 안된다 하면된다 그래 그렇지 요컨대 다시 말하자면 바꿔 말하면 즉 구체적으로 말하자면 시작하여 시초에 이상 허 헉 허걱 바와같이 해도좋다 해도된다 게다가 더구나 하물며 와르르 팍 퍽 펄렁 동안 이래 하고있었다 이었다 에서 로부터 까지 예하면 했어요 해요 함께 같이 더불어 마저 마저도 양자 모두 습니다 가까스로 하려고하다 즈음하여 다른 다른 방면으로 해봐요 습니까 했어요 말할것도 없고 무릎쓰고 개의치않고 하는것만 못하다 하는것이 낫다 매 매번 들 모 어느것 어느 로써 갖고말하자면 어디 어느쪽 어느것 어느해 어느 년도 라 해도 언젠가 어떤것 어느것 저기 저쪽 저것 그때 그럼 그러면 요만한걸 그래 그때 저것만큼 그저 이르기까지 할 줄 안다 할 힘이 있다 너 너희 당신 어찌 설마 차라리 할지언정 할지라도 할망정 할지언정 구토하다 게우다 토하다 메쓰겁다 옆사람 퉤 쳇 의거하여 근거하여 의해 따라 힘입어 그 다음 버금 두번째로 기타 첫번째로 나머지는 그중에서 견지에서 형식으로 쓰여 입장에서 위해서 단지 의해되다 하도록시키다 뿐만아니라 반대로 전후 전자 앞의것 잠시 잠깐 하면서 그렇지만 다음에 그러한즉 그런즉 남들 아무거나 어찌하Line truncated

assets/javascripts/lunr/min/lunr.multi.min.js

@@ -0,0 +1 @@
+!function(e,t){"function"==typeof define&&define.amd?define(t):"object"==typeof exports?module.exports=t():t()(e.lunr)}(this,function(){return function(e){e.multiLanguage=function(){for(var t=Array.prototype.slice.call(arguments),i=t.join("-"),r="",n=[],s=[],p=0;p<t.length;++p)"en"==t[p]?(r+="\\w",n.unshift(e.stopWordFilter),n.push(e.stemmer),s.push(e.stemmer)):(r+=e[t[p]].wordCharacters,e[t[p]].stopWordFilter&&n.unshift(e[t[p]].stopWordFilter),e[t[p]].stemmer&&(n.push(e[t[p]].stemmer),s.push(e[t[p]].stemmer)));var o=e.trimmerSupport.generateTrimmer(r);return e.Pipeline.registerFunction(o,"lunr-multi-trimmer-"+i),n.unshift(o),function(){this.pipeline.reset(),this.pipeline.add.apply(this.pipeline,n),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add.apply(this.searchPipeline,s))}}}});

assets/javascripts/lunr/min/lunr.nl.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Dutch` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(r,e){"function"==typeof define&&define.amd?define(e):"object"==typeof exports?module.exports=e():e()(r.lunr)}(this,function(){return function(r){if(void 0===r)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===r.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");r.nl=function(){this.pipeline.reset(),this.pipeline.add(r.nl.trimmer,r.nl.stopWordFilter,r.nl.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(r.nl.stemmer))},r.nl.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",r.nl.trimmer=r.trimmerSupport.generateTrimmer(r.nl.wordCharacters),r.Pipeline.registerFunction(r.nl.trimmer,"trimmer-nl"),r.nl.stemmer=function(){var e=r.stemmerSupport.Among,i=r.stemmerSupport.SnowballProgram,n=new function(){function r(){for(var r,e,i,o=C.cursor;;){if(C.bra=C.cursor,r=C.find_among(b,11))switch(C.ket=C.cursor,r){case 1:C.slice_from("a");continue;case 2:C.slice_from("e");continue;case 3:C.slice_from("i");continue;case 4:C.slice_from("o");continue;case 5:C.slice_from("u");continue;case 6:if(C.cursor>=C.limit)break;C.cursor++;continue}break}for(C.cursor=o,C.bra=o,C.eq_s(1,"y")?(C.ket=C.cursor,C.slice_from("Y")):C.cursor=o;;)if(e=C.cursor,C.in_grouping(q,97,232)){if(i=C.cursor,C.bra=i,C.eq_s(1,"i"))C.ket=C.cursor,C.in_grouping(q,97,232)&&(C.slice_from("I"),C.cursor=e);else if(C.cursor=i,C.eq_s(1,"y"))C.ket=C.cursor,C.slice_from("Y"),C.cursor=e;else if(n(e))break}else if(n(e))break}function n(r){return C.cursor=r,r>=C.limit||(C.cursor++,!1)}function o(){_=C.limit,d=_,t()||(_=C.cursor,_<3&&(_=3),t()||(d=C.cursor))}function t(){for(;!C.in_grouping(q,97,232);){if(C.cursor>=C.limit)return!0;C.cursor++}for(;!C.out_grouping(q,97,232);){if(C.cursor>=C.limit)return!0;C.cursor++}return!1}function s(){for(var r;;)if(C.bra=C.cursor,r=C.find_among(p,3))switch(C.ket=C.cursor,r){case 1:C.slice_from("y");break;case 2:C.slice_from("i");break;case 3:if(C.cursor>=C.limit)return;C.cursor++}}function u(){return _<=C.cursor}function c(){return d<=C.cursor}function a(){var r=C.limit-C.cursor;C.find_among_b(g,3)&&(C.cursor=C.limit-r,C.ket=C.cursor,C.cursor>C.limit_backward&&(C.cursor--,C.bra=C.cursor,C.slice_del()))}function l(){var r;w=!1,C.ket=C.cursor,C.eq_s_b(1,"e")&&(C.bra=C.cursor,u()&&(r=C.limit-C.cursor,C.out_grouping_b(q,97,232)&&(C.cursor=C.limit-r,C.slice_del(),w=!0,a())))}function m(){var r;u()&&(r=C.limit-C.cursor,C.out_grouping_b(q,97,232)&&(C.cursor=C.limit-r,C.eq_s_b(3,"gem")||(C.cursor=C.limit-r,C.slice_del(),a())))}function f(){var r,e,i,n,o,t,s=C.limit-C.cursor;if(C.ket=C.cursor,r=C.find_among_b(h,5))switch(C.bra=C.cursor,r){case 1:u()&&C.slice_from("heid");break;case 2:m();break;case 3:u()&&C.out_grouping_b(j,97,232)&&C.slice_del()}if(C.cursor=C.limit-s,l(),C.cursor=C.limit-s,C.ket=C.cursor,C.eq_s_b(4,"heid")&&(C.bra=C.cursor,c()&&(e=C.limit-C.cursor,C.eq_s_b(1,"c")||(C.cursor=C.limit-e,C.slice_del(),C.ket=C.cursor,C.eq_s_b(2,"en")&&(C.bra=C.cursor,m())))),C.cursor=C.limit-s,C.ket=C.cursor,r=C.find_among_b(k,6))switch(C.bra=C.cursor,r){case 1:if(c()){if(C.slice_del(),i=C.limit-C.cursor,C.ket=C.cursor,C.eq_s_b(2,"ig")&&(C.bra=C.cursor,c()&&(n=C.limit-C.cursor,!C.eq_s_b(1,"e")))){C.cursor=C.limit-n,C.slice_del();break}C.cursor=C.limit-i,a()}break;case 2:c()&&(o=C.limit-C.cursor,C.eq_s_b(1,"e")||(C.cursor=C.limit-o,C.slice_del()));break;case 3:c()&&(C.slice_del(),l());break;case 4:c()&&C.slice_del();break;case 5:c()&&w&&C.slice_del()}C.cursor=C.limit-s,C.out_grouping_b(z,73,232)&&(t=C.limit-C.cursor,C.find_among_b(v,4)&&C.out_grouping_b(q,97,232)&&(C.cursor=C.limit-t,C.ket=C.cursor,C.cursor>C.limit_backward&&(C.cursor--,C.bra=C.cursor,C.slice_del())))}var d,_,w,b=[new e("",-1,6),new e("á",0,1),new e("ä",0,1),new e("é",0,2),new e("ë",0,2),new e("í",0,3),new e("ï",0,3),new e("ó",0,4),new e("ö",0,4),new e("ú",0,5),new e("ü",0,5)],p=[new e("",-1,3),new e("I",0,2),new e("Y",0,1)],g=[new e("dd",-1,-1),new e("kk",-1,-1),new e("tt",-1,-1)],h=[new e("ene",-1,2),new e("se",-1,3),new e("en",-1,2),new e("heden",2,1),new e("s",-1,3)],k=[new e("end",-1,1),new e("ig",-1,2),new e("ing",-1,1),new e("lijk",-1,3),new e("baar",-1,4),new e("bar",-1,5)],v=[new e("aa",-1,-1),new e("ee",-1,-1),new e("oo",-1,-1),new e("uu",-1,-1)],q=[17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,128],z=[1,0,0,17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,128],j=[17,67,16,1,0,0,0,0,0,0,0,0,0,0,0,0,128],C=new i;this.setCurrent=function(r){C.setCurrent(r)},this.getCurrent=function(){return C.getCurrent()},this.stem=function(){var e=C.cursor;return r(),C.cursor=e,o(),C.limit_backward=e,C.cursor=C.limit,f(),C.cursor=C.limit_backward,s(),!0}};return function(r){return"function"==typeof r.update?r.update(function(r){return n.setCurrent(r),n.stem(),n.getCurrent()}):(n.setCurrLine truncated

assets/javascripts/lunr/min/lunr.no.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Norwegian` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.no=function(){this.pipeline.reset(),this.pipeline.add(e.no.trimmer,e.no.stopWordFilter,e.no.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.no.stemmer))},e.no.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.no.trimmer=e.trimmerSupport.generateTrimmer(e.no.wordCharacters),e.Pipeline.registerFunction(e.no.trimmer,"trimmer-no"),e.no.stemmer=function(){var r=e.stemmerSupport.Among,n=e.stemmerSupport.SnowballProgram,i=new function(){function e(){var e,r=w.cursor+3;if(a=w.limit,0<=r||r<=w.limit){for(s=r;;){if(e=w.cursor,w.in_grouping(d,97,248)){w.cursor=e;break}if(e>=w.limit)return;w.cursor=e+1}for(;!w.out_grouping(d,97,248);){if(w.cursor>=w.limit)return;w.cursor++}a=w.cursor,a<s&&(a=s)}}function i(){var e,r,n;if(w.cursor>=a&&(r=w.limit_backward,w.limit_backward=a,w.ket=w.cursor,e=w.find_among_b(m,29),w.limit_backward=r,e))switch(w.bra=w.cursor,e){case 1:w.slice_del();break;case 2:n=w.limit-w.cursor,w.in_grouping_b(c,98,122)?w.slice_del():(w.cursor=w.limit-n,w.eq_s_b(1,"k")&&w.out_grouping_b(d,97,248)&&w.slice_del());break;case 3:w.slice_from("er")}}function t(){var e,r=w.limit-w.cursor;w.cursor>=a&&(e=w.limit_backward,w.limit_backward=a,w.ket=w.cursor,w.find_among_b(u,2)?(w.bra=w.cursor,w.limit_backward=e,w.cursor=w.limit-r,w.cursor>w.limit_backward&&(w.cursor--,w.bra=w.cursor,w.slice_del())):w.limit_backward=e)}function o(){var e,r;w.cursor>=a&&(r=w.limit_backward,w.limit_backward=a,w.ket=w.cursor,e=w.find_among_b(l,11),e?(w.bra=w.cursor,w.limit_backward=r,1==e&&w.slice_del()):w.limit_backward=r)}var s,a,m=[new r("a",-1,1),new r("e",-1,1),new r("ede",1,1),new r("ande",1,1),new r("ende",1,1),new r("ane",1,1),new r("ene",1,1),new r("hetene",6,1),new r("erte",1,3),new r("en",-1,1),new r("heten",9,1),new r("ar",-1,1),new r("er",-1,1),new r("heter",12,1),new r("s",-1,2),new r("as",14,1),new r("es",14,1),new r("edes",16,1),new r("endes",16,1),new r("enes",16,1),new r("hetenes",19,1),new r("ens",14,1),new r("hetens",21,1),new r("ers",14,1),new r("ets",14,1),new r("et",-1,1),new r("het",25,1),new r("ert",-1,3),new r("ast",-1,1)],u=[new r("dt",-1,-1),new r("vt",-1,-1)],l=[new r("leg",-1,1),new r("eleg",0,1),new r("ig",-1,1),new r("eig",2,1),new r("lig",2,1),new r("elig",4,1),new r("els",-1,1),new r("lov",-1,1),new r("elov",7,1),new r("slov",7,1),new r("hetslov",9,1)],d=[17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,48,0,128],c=[119,125,149,1],w=new n;this.setCurrent=function(e){w.setCurrent(e)},this.getCurrent=function(){return w.getCurrent()},this.stem=function(){var r=w.cursor;return e(),w.limit_backward=r,w.cursor=w.limit,i(),w.cursor=w.limit,t(),w.cursor=w.limit,o(),!0}};return function(e){return"function"==typeof e.update?e.update(function(e){return i.setCurrent(e),i.stem(),i.getCurrent()}):(i.setCurrent(e),i.stem(),i.getCurrent())}}(),e.Pipeline.registerFunction(e.no.stemmer,"stemmer-no"),e.no.stopWordFilter=e.generateStopWordFilter("alle at av bare begge ble blei bli blir blitt både båe da de deg dei deim deira deires dem den denne der dere deres det dette di din disse ditt du dykk dykkar då eg ein eit eitt eller elles en enn er et ett etter for fordi fra før ha hadde han hans har hennar henne hennes her hjå ho hoe honom hoss hossen hun hva hvem hver hvilke hvilken hvis hvor hvordan hvorfor i ikke ikkje ikkje ingen ingi inkje inn inni ja jeg kan kom korleis korso kun kunne kva kvar kvarhelst kven kvi kvifor man mange me med medan meg meget mellom men mi min mine mitt mot mykje ned no noe noen noka noko nokon nokor nokre nå når og også om opp oss over på samme seg selv si si sia sidan siden sin sine sitt sjøl skal skulle slik so som som somme somt så sånn til um upp ut uten var vart varte ved vere verte vi vil ville vore vors vort vår være være vært å".split(" ")),e.Pipeline.registerFunction(e.no.stopWordFilter,"stopWordFilter-no")}});

assets/javascripts/lunr/min/lunr.pt.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Portuguese` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.pt=function(){this.pipeline.reset(),this.pipeline.add(e.pt.trimmer,e.pt.stopWordFilter,e.pt.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.pt.stemmer))},e.pt.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.pt.trimmer=e.trimmerSupport.generateTrimmer(e.pt.wordCharacters),e.Pipeline.registerFunction(e.pt.trimmer,"trimmer-pt"),e.pt.stemmer=function(){var r=e.stemmerSupport.Among,s=e.stemmerSupport.SnowballProgram,n=new function(){function e(){for(var e;;){if(z.bra=z.cursor,e=z.find_among(k,3))switch(z.ket=z.cursor,e){case 1:z.slice_from("a~");continue;case 2:z.slice_from("o~");continue;case 3:if(z.cursor>=z.limit)break;z.cursor++;continue}break}}function n(){if(z.out_grouping(y,97,250)){for(;!z.in_grouping(y,97,250);){if(z.cursor>=z.limit)return!0;z.cursor++}return!1}return!0}function i(){if(z.in_grouping(y,97,250))for(;!z.out_grouping(y,97,250);){if(z.cursor>=z.limit)return!1;z.cursor++}return g=z.cursor,!0}function o(){var e,r,s=z.cursor;if(z.in_grouping(y,97,250))if(e=z.cursor,n()){if(z.cursor=e,i())return}else g=z.cursor;if(z.cursor=s,z.out_grouping(y,97,250)){if(r=z.cursor,n()){if(z.cursor=r,!z.in_grouping(y,97,250)||z.cursor>=z.limit)return;z.cursor++}g=z.cursor}}function t(){for(;!z.in_grouping(y,97,250);){if(z.cursor>=z.limit)return!1;z.cursor++}for(;!z.out_grouping(y,97,250);){if(z.cursor>=z.limit)return!1;z.cursor++}return!0}function a(){var e=z.cursor;g=z.limit,b=g,h=g,o(),z.cursor=e,t()&&(b=z.cursor,t()&&(h=z.cursor))}function u(){for(var e;;){if(z.bra=z.cursor,e=z.find_among(q,3))switch(z.ket=z.cursor,e){case 1:z.slice_from("ã");continue;case 2:z.slice_from("õ");continue;case 3:if(z.cursor>=z.limit)break;z.cursor++;continue}break}}function w(){return g<=z.cursor}function m(){return b<=z.cursor}function c(){return h<=z.cursor}function l(){var e;if(z.ket=z.cursor,!(e=z.find_among_b(F,45)))return!1;switch(z.bra=z.cursor,e){case 1:if(!c())return!1;z.slice_del();break;case 2:if(!c())return!1;z.slice_from("log");break;case 3:if(!c())return!1;z.slice_from("u");break;case 4:if(!c())return!1;z.slice_from("ente");break;case 5:if(!m())return!1;z.slice_del(),z.ket=z.cursor,e=z.find_among_b(j,4),e&&(z.bra=z.cursor,c()&&(z.slice_del(),1==e&&(z.ket=z.cursor,z.eq_s_b(2,"at")&&(z.bra=z.cursor,c()&&z.slice_del()))));break;case 6:if(!c())return!1;z.slice_del(),z.ket=z.cursor,e=z.find_among_b(C,3),e&&(z.bra=z.cursor,1==e&&c()&&z.slice_del());break;case 7:if(!c())return!1;z.slice_del(),z.ket=z.cursor,e=z.find_among_b(P,3),e&&(z.bra=z.cursor,1==e&&c()&&z.slice_del());break;case 8:if(!c())return!1;z.slice_del(),z.ket=z.cursor,z.eq_s_b(2,"at")&&(z.bra=z.cursor,c()&&z.slice_del());break;case 9:if(!w()||!z.eq_s_b(1,"e"))return!1;z.slice_from("ir")}return!0}function f(){var e,r;if(z.cursor>=g){if(r=z.limit_backward,z.limit_backward=g,z.ket=z.cursor,e=z.find_among_b(S,120))return z.bra=z.cursor,1==e&&z.slice_del(),z.limit_backward=r,!0;z.limit_backward=r}return!1}function d(){var e;z.ket=z.cursor,(e=z.find_among_b(W,7))&&(z.bra=z.cursor,1==e&&w()&&z.slice_del())}function v(e,r){if(z.eq_s_b(1,e)){z.bra=z.cursor;var s=z.limit-z.cursor;if(z.eq_s_b(1,r))return z.cursor=z.limit-s,w()&&z.slice_del(),!1}return!0}function p(){var e;if(z.ket=z.cursor,e=z.find_among_b(L,4))switch(z.bra=z.cursor,e){case 1:w()&&(z.slice_del(),z.ket=z.cursor,z.limit-z.cursor,v("u","g")&&v("i","c"));break;case 2:z.slice_from("c")}}function _(){if(!l()&&(z.cursor=z.limit,!f()))return z.cursor=z.limit,void d();z.cursor=z.limit,z.ket=z.cursor,z.eq_s_b(1,"i")&&(z.bra=z.cursor,z.eq_s_b(1,"c")&&(z.cursor=z.limit,w()&&z.slice_del()))}var h,b,g,k=[new r("",-1,3),new r("ã",0,1),new r("õ",0,2)],q=[new r("",-1,3),new r("a~",0,1),new r("o~",0,2)],j=[new r("ic",-1,-1),new r("ad",-1,-1),new r("os",-1,-1),new r("iv",-1,1)],C=[new r("ante",-1,1),new r("avel",-1,1),new r("ível",-1,1)],P=[new r("ic",-1,1),new r("abil",-1,1),new r("iv",-1,1)],F=[new r("ica",-1,1),new r("ância",-1,1),new r("ência",-1,4),new r("ira",-1,9),new r("adora",-1,1),new r("osa",-1,1),new r("ista",-1,1),new r("iva",-1,8),new r("eza",-1,1),new r("logía",-1,2),new r("idade",-1,7),new r("ante",-1,1),new r("mente",-1,6),new r("amente",12,5),new r("ável",-1,1),new r("ível",-1,1),new r("ución",-1,3),new r("ico",-1,1),new r("ismo",-1,1),new r("oso",-1,1),new r("amento",-1,1),new r("imento",-1,1),new r("ivo",-1,8),new r("aça~o",-1,1),new r("ador",-1,1),new r("icas",-1,1),new r("ências",-1,4),new r("iras",-1,9),Line truncated

assets/javascripts/lunr/min/lunr.ro.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Romanian` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,i){"function"==typeof define&&define.amd?define(i):"object"==typeof exports?module.exports=i():i()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.ro=function(){this.pipeline.reset(),this.pipeline.add(e.ro.trimmer,e.ro.stopWordFilter,e.ro.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.ro.stemmer))},e.ro.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.ro.trimmer=e.trimmerSupport.generateTrimmer(e.ro.wordCharacters),e.Pipeline.registerFunction(e.ro.trimmer,"trimmer-ro"),e.ro.stemmer=function(){var i=e.stemmerSupport.Among,r=e.stemmerSupport.SnowballProgram,n=new function(){function e(e,i){L.eq_s(1,e)&&(L.ket=L.cursor,L.in_grouping(W,97,259)&&L.slice_from(i))}function n(){for(var i,r;;){if(i=L.cursor,L.in_grouping(W,97,259)&&(r=L.cursor,L.bra=r,e("u","U"),L.cursor=r,e("i","I")),L.cursor=i,L.cursor>=L.limit)break;L.cursor++}}function t(){if(L.out_grouping(W,97,259)){for(;!L.in_grouping(W,97,259);){if(L.cursor>=L.limit)return!0;L.cursor++}return!1}return!0}function a(){if(L.in_grouping(W,97,259))for(;!L.out_grouping(W,97,259);){if(L.cursor>=L.limit)return!0;L.cursor++}return!1}function o(){var e,i,r=L.cursor;if(L.in_grouping(W,97,259)){if(e=L.cursor,!t())return void(h=L.cursor);if(L.cursor=e,!a())return void(h=L.cursor)}L.cursor=r,L.out_grouping(W,97,259)&&(i=L.cursor,t()&&(L.cursor=i,L.in_grouping(W,97,259)&&L.cursor<L.limit&&L.cursor++),h=L.cursor)}function u(){for(;!L.in_grouping(W,97,259);){if(L.cursor>=L.limit)return!1;L.cursor++}for(;!L.out_grouping(W,97,259);){if(L.cursor>=L.limit)return!1;L.cursor++}return!0}function c(){var e=L.cursor;h=L.limit,k=h,g=h,o(),L.cursor=e,u()&&(k=L.cursor,u()&&(g=L.cursor))}function s(){for(var e;;){if(L.bra=L.cursor,e=L.find_among(z,3))switch(L.ket=L.cursor,e){case 1:L.slice_from("i");continue;case 2:L.slice_from("u");continue;case 3:if(L.cursor>=L.limit)break;L.cursor++;continue}break}}function w(){return h<=L.cursor}function m(){return k<=L.cursor}function l(){return g<=L.cursor}function f(){var e,i;if(L.ket=L.cursor,(e=L.find_among_b(C,16))&&(L.bra=L.cursor,m()))switch(e){case 1:L.slice_del();break;case 2:L.slice_from("a");break;case 3:L.slice_from("e");break;case 4:L.slice_from("i");break;case 5:i=L.limit-L.cursor,L.eq_s_b(2,"ab")||(L.cursor=L.limit-i,L.slice_from("i"));break;case 6:L.slice_from("at");break;case 7:L.slice_from("aţi")}}function p(){var e,i=L.limit-L.cursor;if(L.ket=L.cursor,(e=L.find_among_b(P,46))&&(L.bra=L.cursor,m())){switch(e){case 1:L.slice_from("abil");break;case 2:L.slice_from("ibil");break;case 3:L.slice_from("iv");break;case 4:L.slice_from("ic");break;case 5:L.slice_from("at");break;case 6:L.slice_from("it")}return _=!0,L.cursor=L.limit-i,!0}return!1}function d(){var e,i;for(_=!1;;)if(i=L.limit-L.cursor,!p()){L.cursor=L.limit-i;break}if(L.ket=L.cursor,(e=L.find_among_b(F,62))&&(L.bra=L.cursor,l())){switch(e){case 1:L.slice_del();break;case 2:L.eq_s_b(1,"ţ")&&(L.bra=L.cursor,L.slice_from("t"));break;case 3:L.slice_from("ist")}_=!0}}function b(){var e,i,r;if(L.cursor>=h){if(i=L.limit_backward,L.limit_backward=h,L.ket=L.cursor,e=L.find_among_b(q,94))switch(L.bra=L.cursor,e){case 1:if(r=L.limit-L.cursor,!L.out_grouping_b(W,97,259)&&(L.cursor=L.limit-r,!L.eq_s_b(1,"u")))break;case 2:L.slice_del()}L.limit_backward=i}}function v(){var e;L.ket=L.cursor,(e=L.find_among_b(S,5))&&(L.bra=L.cursor,w()&&1==e&&L.slice_del())}var _,g,k,h,z=[new i("",-1,3),new i("I",0,1),new i("U",0,2)],C=[new i("ea",-1,3),new i("aţia",-1,7),new i("aua",-1,2),new i("iua",-1,4),new i("aţie",-1,7),new i("ele",-1,3),new i("ile",-1,5),new i("iile",6,4),new i("iei",-1,4),new i("atei",-1,6),new i("ii",-1,4),new i("ului",-1,1),new i("ul",-1,1),new i("elor",-1,3),new i("ilor",-1,4),new i("iilor",14,4)],P=[new i("icala",-1,4),new i("iciva",-1,4),new i("ativa",-1,5),new i("itiva",-1,6),new i("icale",-1,4),new i("aţiune",-1,5),new i("iţiune",-1,6),new i("atoare",-1,5),new i("itoare",-1,6),new i("ătoare",-1,5),new i("icitate",-1,4),new i("abilitate",-1,1),new i("ibilitate",-1,2),new i("ivitate",-1,3),new i("icive",-1,4),new i("ative",-1,5),new i("itive",-1,6),new i("icali",-1,4),new i("atori",-1,5),new i("icatori",18,4),new i("itori",-1,6),new i("ători",-1,5),new i("icitati",-1,4),new i("abilitati",-1,1),new i("ivitati",-1,3),new i("icivi",-1,4),new i("ativi",-1,5),new i("itivi",-1,6),new i("icităi",-1,4),new i("abilităi",-1,1),new i("ivităi",-1,3),new i("icităţi",-1,4),new i("abilităţi",-1,1),new i("ivităţi",-1,3),new i("ical",-1,4),new i("ator",-1,5),new i("icator",35,4),new i("itor",-1,6),new i("ător",-1,5),new i("iciv",-1,4),neLine truncated

assets/javascripts/lunr/min/lunr.ru.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Russian` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,n){"function"==typeof define&&define.amd?define(n):"object"==typeof exports?module.exports=n():n()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.ru=function(){this.pipeline.reset(),this.pipeline.add(e.ru.trimmer,e.ru.stopWordFilter,e.ru.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.ru.stemmer))},e.ru.wordCharacters="Ѐ-҄҇-ԯᴫᵸⷠ-ⷿꙀ-ꚟ︮︯",e.ru.trimmer=e.trimmerSupport.generateTrimmer(e.ru.wordCharacters),e.Pipeline.registerFunction(e.ru.trimmer,"trimmer-ru"),e.ru.stemmer=function(){var n=e.stemmerSupport.Among,r=e.stemmerSupport.SnowballProgram,t=new function(){function e(){for(;!W.in_grouping(S,1072,1103);){if(W.cursor>=W.limit)return!1;W.cursor++}return!0}function t(){for(;!W.out_grouping(S,1072,1103);){if(W.cursor>=W.limit)return!1;W.cursor++}return!0}function w(){b=W.limit,_=b,e()&&(b=W.cursor,t()&&e()&&t()&&(_=W.cursor))}function i(){return _<=W.cursor}function u(e,n){var r,t;if(W.ket=W.cursor,r=W.find_among_b(e,n)){switch(W.bra=W.cursor,r){case 1:if(t=W.limit-W.cursor,!W.eq_s_b(1,"а")&&(W.cursor=W.limit-t,!W.eq_s_b(1,"я")))return!1;case 2:W.slice_del()}return!0}return!1}function o(){return u(h,9)}function s(e,n){var r;return W.ket=W.cursor,!!(r=W.find_among_b(e,n))&&(W.bra=W.cursor,1==r&&W.slice_del(),!0)}function c(){return s(g,26)}function m(){return!!c()&&(u(C,8),!0)}function f(){return s(k,2)}function l(){return u(P,46)}function a(){s(v,36)}function p(){var e;W.ket=W.cursor,(e=W.find_among_b(F,2))&&(W.bra=W.cursor,i()&&1==e&&W.slice_del())}function d(){var e;if(W.ket=W.cursor,e=W.find_among_b(q,4))switch(W.bra=W.cursor,e){case 1:if(W.slice_del(),W.ket=W.cursor,!W.eq_s_b(1,"н"))break;W.bra=W.cursor;case 2:if(!W.eq_s_b(1,"н"))break;case 3:W.slice_del()}}var _,b,h=[new n("в",-1,1),new n("ив",0,2),new n("ыв",0,2),new n("вши",-1,1),new n("ивши",3,2),new n("ывши",3,2),new n("вшись",-1,1),new n("ившись",6,2),new n("ывшись",6,2)],g=[new n("ее",-1,1),new n("ие",-1,1),new n("ое",-1,1),new n("ые",-1,1),new n("ими",-1,1),new n("ыми",-1,1),new n("ей",-1,1),new n("ий",-1,1),new n("ой",-1,1),new n("ый",-1,1),new n("ем",-1,1),new n("им",-1,1),new n("ом",-1,1),new n("ым",-1,1),new n("его",-1,1),new n("ого",-1,1),new n("ему",-1,1),new n("ому",-1,1),new n("их",-1,1),new n("ых",-1,1),new n("ею",-1,1),new n("ою",-1,1),new n("ую",-1,1),new n("юю",-1,1),new n("ая",-1,1),new n("яя",-1,1)],C=[new n("ем",-1,1),new n("нн",-1,1),new n("вш",-1,1),new n("ивш",2,2),new n("ывш",2,2),new n("щ",-1,1),new n("ющ",5,1),new n("ующ",6,2)],k=[new n("сь",-1,1),new n("ся",-1,1)],P=[new n("ла",-1,1),new n("ила",0,2),new n("ыла",0,2),new n("на",-1,1),new n("ена",3,2),new n("ете",-1,1),new n("ите",-1,2),new n("йте",-1,1),new n("ейте",7,2),new n("уйте",7,2),new n("ли",-1,1),new n("или",10,2),new n("ыли",10,2),new n("й",-1,1),new n("ей",13,2),new n("уй",13,2),new n("л",-1,1),new n("ил",16,2),new n("ыл",16,2),new n("ем",-1,1),new n("им",-1,2),new n("ым",-1,2),new n("н",-1,1),new n("ен",22,2),new n("ло",-1,1),new n("ило",24,2),new n("ыло",24,2),new n("но",-1,1),new n("ено",27,2),new n("нно",27,1),new n("ет",-1,1),new n("ует",30,2),new n("ит",-1,2),new n("ыт",-1,2),new n("ют",-1,1),new n("уют",34,2),new n("ят",-1,2),new n("ны",-1,1),new n("ены",37,2),new n("ть",-1,1),new n("ить",39,2),new n("ыть",39,2),new n("ешь",-1,1),new n("ишь",-1,2),new n("ю",-1,2),new n("ую",44,2)],v=[new n("а",-1,1),new n("ев",-1,1),new n("ов",-1,1),new n("е",-1,1),new n("ие",3,1),new n("ье",3,1),new n("и",-1,1),new n("еи",6,1),new n("ии",6,1),new n("ами",6,1),new n("ями",6,1),new n("иями",10,1),new n("й",-1,1),new n("ей",12,1),new n("ией",13,1),new n("ий",12,1),new n("ой",12,1),new n("ам",-1,1),new n("ем",-1,1),new n("ием",18,1),new n("ом",-1,1),new n("ям",-1,1),new n("иям",21,1),new n("о",-1,1),new n("у",-1,1),new n("ах",-1,1),new n("ях",-1,1),new n("иях",26,1),new n("ы",-1,1),new n("ь",-1,1),new n("ю",-1,1),new n("ию",30,1),new n("ью",30,1),new n("я",-1,1),new n("ия",33,1),new n("ья",33,1)],F=[new n("ост",-1,1),new n("ость",-1,1)],q=[new n("ейше",-1,1),new n("н",-1,2),new n("ейш",-1,1),new n("ь",-1,3)],S=[33,65,8,232],W=new r;this.setCurrent=function(e){W.setCurrent(e)},this.getCurrent=function(){return W.getCurrent()},this.stem=function(){return w(),W.cursor=W.limit,!(W.cursor<b)&&(W.limit_backward=b,o()||(W.cursor=W.limit,f()||(W.cursor=W.limit),m()||(W.cursor=W.limit,l()||(W.cursor=W.limit,a()))),W.cursor=W.limit,W.ket=W.cursor,W.eq_s_b(1,"и"Line truncated

assets/javascripts/lunr/min/lunr.sa.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.sa=function(){this.pipeline.reset(),this.pipeline.add(e.sa.trimmer,e.sa.stopWordFilter,e.sa.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.sa.stemmer))},e.sa.wordCharacters="ऀ-ःऄ-एऐ-टठ-यर-िी-ॏॐ-य़ॠ-९॰-ॿ꣠-꣱ꣲ-ꣷ꣸-ꣻ꣼-ꣽꣾ-ꣿᆰ0-ᆰ9",e.sa.trimmer=e.trimmerSupport.generateTrimmer(e.sa.wordCharacters),e.Pipeline.registerFunction(e.sa.trimmer,"trimmer-sa"),e.sa.stopWordFilter=e.generateStopWordFilter('तथा अयम्‌ एकम्‌ इत्यस्मिन्‌ तथा तत्‌ वा अयम्‌ इत्यस्य ते आहूत उपरि तेषाम्‌  किन्तु तेषाम्‌ तदा इत्यनेन अधिकः इत्यस्य तत्‌ केचन बहवः द्वि तथा महत्वपूर्णः अयम्‌ अस्य  विषये अयं अस्ति तत्‌ प्रथमः विषये इत्युपरि इत्युपरि इतर अधिकतमः अधिकः अपि सामान्यतया ठ इतरेतर नूतनम्‌ द  न्यूनम्‌ कश्चित्‌ वा विशालः द  सः अस्ति तदनुसारम् तत्र अस्ति केवलम्‌ अपि अत्र सर्वे विविधाः तत्‌ बहवः यतः इदानीम्‌ द  दक्षिण इत्यस्मै तस्य उपरि नथ अतीव कार्यम्‌ सर्वे एकैकम्‌ इत्यादि। एते सन्ति  उत इत्थम्‌ मध्ये एतदर्थं . स कस्य प्रथमः श्री. करोति अस्मिन् प्रकारः निर्मिता कालः तत्र कर्तुं  समान अधुना ते सन्ति स एकः अस्ति सः अर्थात् तेषां कृते . स्थितम्  विशेषः अग्रिम तेषाम्‌ समान स्रोतः ख म समान इदानीमपि अधिकतया करोतु ते समान इत्यस्य वीथी सह यस्मिन्  कृतवान्‌ धृतः तदा पुनः पूर्वं सः आगतः किम्‌ कुल इतर पुरा  मात्रा स विषये उ अतएव अपि नगरस्य  उपरि यतः प्रतिशतं  कतरः कालः साधनानि भूत तथापि जात सम्बन्धि अन्यत्‌ ग अतः अस्माकं स्वकीयाः अस्माकं इदानीं अन्तः इत्यादयः भवन्तः इत्यादयः एते एताः तस्य अस्य इदम् एते तेषां तेषां तेषां तान् तेषां तेषां तेषां समानः सः एकः च तादृशाः बहवः अन्ये च वदन्ति यत् कियत् कस्मै  कस्मै  यस्मै  यस्मै  यस्मै  यस्मै न अतिनीचः किन्तु प्रथमं सम्पूर्णतया  ततः चिरकालानन्तरं पुस्तकं सम्पूर्णतया अन्तः  किन्तु अत्र वा इह इव श्रद्धाय अवशिष्यते  परन्तु अन्ये वर्गाः सन्ति ते सन्ति शक्नुवन्ति सर्वे मिलित्वा सर्वे एकत्र"'.split(" ")),e.sa.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}();var r=e.wordcut;r.init(),e.sa.tokenizer=function(t){if(!arguments.length||null==t||void 0==t)return[];if(Array.isArray(t))return t.map(function(r){return isLunr2?new e.Token(r.toLowerCase()):r.toLowerCase()});var i=t.toString().toLowerCase().replace(/^\s+/,"");return r.cut(i).split("|")},e.Pipeline.registerFunction(e.sa.stemmer,"stemmer-sa"),e.Pipeline.registerFunction(e.sa.stopWordFilter,"stopWordFilter-sa")}});

assets/javascripts/lunr/min/lunr.stemmer.support.min.js

@@ -0,0 +1 @@
+!function(r,t){"function"==typeof define&&define.amd?define(t):"object"==typeof exports?module.exports=t():t()(r.lunr)}(this,function(){return function(r){r.stemmerSupport={Among:function(r,t,i,s){if(this.toCharArray=function(r){for(var t=r.length,i=new Array(t),s=0;s<t;s++)i[s]=r.charCodeAt(s);return i},!r&&""!=r||!t&&0!=t||!i)throw"Bad Among initialisation: s:"+r+", substring_i: "+t+", result: "+i;this.s_size=r.length,this.s=this.toCharArray(r),this.substring_i=t,this.result=i,this.method=s},SnowballProgram:function(){var r;return{bra:0,ket:0,limit:0,cursor:0,limit_backward:0,setCurrent:function(t){r=t,this.cursor=0,this.limit=t.length,this.limit_backward=0,this.bra=this.cursor,this.ket=this.limit},getCurrent:function(){var t=r;return r=null,t},in_grouping:function(t,i,s){if(this.cursor<this.limit){var e=r.charCodeAt(this.cursor);if(e<=s&&e>=i&&(e-=i,t[e>>3]&1<<(7&e)))return this.cursor++,!0}return!1},in_grouping_b:function(t,i,s){if(this.cursor>this.limit_backward){var e=r.charCodeAt(this.cursor-1);if(e<=s&&e>=i&&(e-=i,t[e>>3]&1<<(7&e)))return this.cursor--,!0}return!1},out_grouping:function(t,i,s){if(this.cursor<this.limit){var e=r.charCodeAt(this.cursor);if(e>s||e<i)return this.cursor++,!0;if(e-=i,!(t[e>>3]&1<<(7&e)))return this.cursor++,!0}return!1},out_grouping_b:function(t,i,s){if(this.cursor>this.limit_backward){var e=r.charCodeAt(this.cursor-1);if(e>s||e<i)return this.cursor--,!0;if(e-=i,!(t[e>>3]&1<<(7&e)))return this.cursor--,!0}return!1},eq_s:function(t,i){if(this.limit-this.cursor<t)return!1;for(var s=0;s<t;s++)if(r.charCodeAt(this.cursor+s)!=i.charCodeAt(s))return!1;return this.cursor+=t,!0},eq_s_b:function(t,i){if(this.cursor-this.limit_backward<t)return!1;for(var s=0;s<t;s++)if(r.charCodeAt(this.cursor-t+s)!=i.charCodeAt(s))return!1;return this.cursor-=t,!0},find_among:function(t,i){for(var s=0,e=i,n=this.cursor,u=this.limit,o=0,h=0,c=!1;;){for(var a=s+(e-s>>1),f=0,l=o<h?o:h,_=t[a],m=l;m<_.s_size;m++){if(n+l==u){f=-1;break}if(f=r.charCodeAt(n+l)-_.s[m])break;l++}if(f<0?(e=a,h=l):(s=a,o=l),e-s<=1){if(s>0||e==s||c)break;c=!0}}for(;;){var _=t[s];if(o>=_.s_size){if(this.cursor=n+_.s_size,!_.method)return _.result;var b=_.method();if(this.cursor=n+_.s_size,b)return _.result}if((s=_.substring_i)<0)return 0}},find_among_b:function(t,i){for(var s=0,e=i,n=this.cursor,u=this.limit_backward,o=0,h=0,c=!1;;){for(var a=s+(e-s>>1),f=0,l=o<h?o:h,_=t[a],m=_.s_size-1-l;m>=0;m--){if(n-l==u){f=-1;break}if(f=r.charCodeAt(n-1-l)-_.s[m])break;l++}if(f<0?(e=a,h=l):(s=a,o=l),e-s<=1){if(s>0||e==s||c)break;c=!0}}for(;;){var _=t[s];if(o>=_.s_size){if(this.cursor=n-_.s_size,!_.method)return _.result;var b=_.method();if(this.cursor=n-_.s_size,b)return _.result}if((s=_.substring_i)<0)return 0}},replace_s:function(t,i,s){var e=s.length-(i-t),n=r.substring(0,t),u=r.substring(i);return r=n+s+u,this.limit+=e,this.cursor>=i?this.cursor+=e:this.cursor>t&&(this.cursor=t),e},slice_check:function(){if(this.bra<0||this.bra>this.ket||this.ket>this.limit||this.limit>r.length)throw"faulty slice operation"},slice_from:function(r){this.slice_check(),this.replace_s(this.bra,this.ket,r)},slice_del:function(){this.slice_from("")},insert:function(r,t,i){var s=this.replace_s(r,t,i);r<=this.bra&&(this.bra+=s),r<=this.ket&&(this.ket+=s)},slice_to:function(){return this.slice_check(),r.substring(this.bra,this.ket)},eq_v_b:function(r){return this.eq_s_b(r.length,r)}}}},r.trimmerSupport={generateTrimmer:function(r){var t=new RegExp("^[^"+r+"]+"),i=new RegExp("[^"+r+"]+$");return function(r){return"function"==typeof r.update?r.update(function(r){return r.replace(t,"").replace(i,"")}):r.replace(t,"").replace(i,"")}}}}});

assets/javascripts/lunr/min/lunr.sv.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Swedish` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.sv=function(){this.pipeline.reset(),this.pipeline.add(e.sv.trimmer,e.sv.stopWordFilter,e.sv.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.sv.stemmer))},e.sv.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",e.sv.trimmer=e.trimmerSupport.generateTrimmer(e.sv.wordCharacters),e.Pipeline.registerFunction(e.sv.trimmer,"trimmer-sv"),e.sv.stemmer=function(){var r=e.stemmerSupport.Among,n=e.stemmerSupport.SnowballProgram,t=new function(){function e(){var e,r=w.cursor+3;if(o=w.limit,0<=r||r<=w.limit){for(a=r;;){if(e=w.cursor,w.in_grouping(l,97,246)){w.cursor=e;break}if(w.cursor=e,w.cursor>=w.limit)return;w.cursor++}for(;!w.out_grouping(l,97,246);){if(w.cursor>=w.limit)return;w.cursor++}o=w.cursor,o<a&&(o=a)}}function t(){var e,r=w.limit_backward;if(w.cursor>=o&&(w.limit_backward=o,w.cursor=w.limit,w.ket=w.cursor,e=w.find_among_b(u,37),w.limit_backward=r,e))switch(w.bra=w.cursor,e){case 1:w.slice_del();break;case 2:w.in_grouping_b(d,98,121)&&w.slice_del()}}function i(){var e=w.limit_backward;w.cursor>=o&&(w.limit_backward=o,w.cursor=w.limit,w.find_among_b(c,7)&&(w.cursor=w.limit,w.ket=w.cursor,w.cursor>w.limit_backward&&(w.bra=--w.cursor,w.slice_del())),w.limit_backward=e)}function s(){var e,r;if(w.cursor>=o){if(r=w.limit_backward,w.limit_backward=o,w.cursor=w.limit,w.ket=w.cursor,e=w.find_among_b(m,5))switch(w.bra=w.cursor,e){case 1:w.slice_del();break;case 2:w.slice_from("lös");break;case 3:w.slice_from("full")}w.limit_backward=r}}var a,o,u=[new r("a",-1,1),new r("arna",0,1),new r("erna",0,1),new r("heterna",2,1),new r("orna",0,1),new r("ad",-1,1),new r("e",-1,1),new r("ade",6,1),new r("ande",6,1),new r("arne",6,1),new r("are",6,1),new r("aste",6,1),new r("en",-1,1),new r("anden",12,1),new r("aren",12,1),new r("heten",12,1),new r("ern",-1,1),new r("ar",-1,1),new r("er",-1,1),new r("heter",18,1),new r("or",-1,1),new r("s",-1,2),new r("as",21,1),new r("arnas",22,1),new r("ernas",22,1),new r("ornas",22,1),new r("es",21,1),new r("ades",26,1),new r("andes",26,1),new r("ens",21,1),new r("arens",29,1),new r("hetens",29,1),new r("erns",21,1),new r("at",-1,1),new r("andet",-1,1),new r("het",-1,1),new r("ast",-1,1)],c=[new r("dd",-1,-1),new r("gd",-1,-1),new r("nn",-1,-1),new r("dt",-1,-1),new r("gt",-1,-1),new r("kt",-1,-1),new r("tt",-1,-1)],m=[new r("ig",-1,1),new r("lig",0,1),new r("els",-1,1),new r("fullt",-1,3),new r("löst",-1,2)],l=[17,65,16,1,0,0,0,0,0,0,0,0,0,0,0,0,24,0,32],d=[119,127,149],w=new n;this.setCurrent=function(e){w.setCurrent(e)},this.getCurrent=function(){return w.getCurrent()},this.stem=function(){var r=w.cursor;return e(),w.limit_backward=r,w.cursor=w.limit,t(),w.cursor=w.limit,i(),w.cursor=w.limit,s(),!0}};return function(e){return"function"==typeof e.update?e.update(function(e){return t.setCurrent(e),t.stem(),t.getCurrent()}):(t.setCurrent(e),t.stem(),t.getCurrent())}}(),e.Pipeline.registerFunction(e.sv.stemmer,"stemmer-sv"),e.sv.stopWordFilter=e.generateStopWordFilter("alla allt att av blev bli blir blivit de dem den denna deras dess dessa det detta dig din dina ditt du där då efter ej eller en er era ert ett från för ha hade han hans har henne hennes hon honom hur här i icke ingen inom inte jag ju kan kunde man med mellan men mig min mina mitt mot mycket ni nu när någon något några och om oss på samma sedan sig sin sina sitta själv skulle som så sådan sådana sådant till under upp ut utan vad var vara varför varit varje vars vart vem vi vid vilka vilkas vilken vilket vår våra vårt än är åt över".split(" ")),e.Pipeline.registerFunction(e.sv.stopWordFilter,"stopWordFilter-sv")}});

assets/javascripts/lunr/min/lunr.ta.min.js

@@ -0,0 +1 @@
+!function(e,t){"function"==typeof define&&define.amd?define(t):"object"==typeof exports?module.exports=t():t()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.ta=function(){this.pipeline.reset(),this.pipeline.add(e.ta.trimmer,e.ta.stopWordFilter,e.ta.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.ta.stemmer))},e.ta.wordCharacters="஀-உஊ-ஏஐ-ஙச-ட஠-னப-யர-ஹ஺-ிீ-௉ொ-௏ௐ-௙௚-௟௠-௩௪-௯௰-௹௺-௿a-zA-Zａ-ｚＡ-Ｚ0-9０-９",e.ta.trimmer=e.trimmerSupport.generateTrimmer(e.ta.wordCharacters),e.Pipeline.registerFunction(e.ta.trimmer,"trimmer-ta"),e.ta.stopWordFilter=e.generateStopWordFilter("அங்கு அங்கே அது அதை அந்த அவர் அவர்கள் அவள் அவன் அவை ஆக ஆகவே ஆகையால் ஆதலால் ஆதலினால் ஆனாலும் ஆனால் இங்கு இங்கே இது இதை இந்த இப்படி இவர் இவர்கள் இவள் இவன் இவை இவ்வளவு உனக்கு உனது உன் உன்னால் எங்கு எங்கே எது எதை எந்த எப்படி எவர் எவர்கள் எவள் எவன் எவை எவ்வளவு எனக்கு எனது எனவே என் என்ன என்னால் ஏது ஏன் தனது தன்னால் தானே தான் நாங்கள் நாம் நான் நீ நீங்கள்".split(" ")),e.ta.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}();var t=e.wordcut;t.init(),e.ta.tokenizer=function(r){if(!arguments.length||null==r||void 0==r)return[];if(Array.isArray(r))return r.map(function(t){return isLunr2?new e.Token(t.toLowerCase()):t.toLowerCase()});var i=r.toString().toLowerCase().replace(/^\s+/,"");return t.cut(i).split("|")},e.Pipeline.registerFunction(e.ta.stemmer,"stemmer-ta"),e.Pipeline.registerFunction(e.ta.stopWordFilter,"stopWordFilter-ta")}});

assets/javascripts/lunr/min/lunr.te.min.js

@@ -0,0 +1 @@
+!function(e,t){"function"==typeof define&&define.amd?define(t):"object"==typeof exports?module.exports=t():t()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.te=function(){this.pipeline.reset(),this.pipeline.add(e.te.trimmer,e.te.stopWordFilter,e.te.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.te.stemmer))},e.te.wordCharacters="ఀ-ఄఅ-ఔక-హా-ౌౕ-ౖౘ-ౚౠ-ౡౢ-ౣ౦-౯౸-౿఼ఽ్ౝ౷౤౥",e.te.trimmer=e.trimmerSupport.generateTrimmer(e.te.wordCharacters),e.Pipeline.registerFunction(e.te.trimmer,"trimmer-te"),e.te.stopWordFilter=e.generateStopWordFilter("అందరూ అందుబాటులో అడగండి అడగడం అడ్డంగా అనుగుణంగా అనుమతించు అనుమతిస్తుంది అయితే ఇప్పటికే ఉన్నారు ఎక్కడైనా ఎప్పుడు ఎవరైనా ఎవరో ఏ ఏదైనా ఏమైనప్పటికి ఒక ఒకరు కనిపిస్తాయి కాదు కూడా గా గురించి చుట్టూ చేయగలిగింది తగిన తర్వాత దాదాపు దూరంగా నిజంగా పై ప్రకారం ప్రక్కన మధ్య మరియు మరొక మళ్ళీ మాత్రమే మెచ్చుకో వద్ద వెంట వేరుగా వ్యతిరేకంగా సంబంధం".split(" ")),e.te.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}();var t=e.wordcut;t.init(),e.te.tokenizer=function(r){if(!arguments.length||null==r||void 0==r)return[];if(Array.isArray(r))return r.map(function(t){return isLunr2?new e.Token(t.toLowerCase()):t.toLowerCase()});var i=r.toString().toLowerCase().replace(/^\s+/,"");return t.cut(i).split("|")},e.Pipeline.registerFunction(e.te.stemmer,"stemmer-te"),e.Pipeline.registerFunction(e.te.stopWordFilter,"stopWordFilter-te")}});

assets/javascripts/lunr/min/lunr.th.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");var r="2"==e.version[0];e.th=function(){this.pipeline.reset(),this.pipeline.add(e.th.trimmer),r?this.tokenizer=e.th.tokenizer:(e.tokenizer&&(e.tokenizer=e.th.tokenizer),this.tokenizerFn&&(this.tokenizerFn=e.th.tokenizer))},e.th.wordCharacters="[฀-๿]",e.th.trimmer=e.trimmerSupport.generateTrimmer(e.th.wordCharacters),e.Pipeline.registerFunction(e.th.trimmer,"trimmer-th");var t=e.wordcut;t.init(),e.th.tokenizer=function(i){if(!arguments.length||null==i||void 0==i)return[];if(Array.isArray(i))return i.map(function(t){return r?new e.Token(t):t});var n=i.toString().replace(/^\s+/,"");return t.cut(n).split("|")}}});

assets/javascripts/lunr/min/lunr.tr.min.js

@@ -0,0 +1,18 @@
+/*!
+ * Lunr languages, `Turkish` language
+ * https://github.com/MihaiValentin/lunr-languages
+ *
+ * Copyright 2014, Mihai Valentin
+ * http://www.mozilla.org/MPL/
+ */
+/*!
+ * based on
+ * Snowball JavaScript Library v0.3
+ * http://code.google.com/p/urim/
+ * http://snowball.tartarus.org/
+ *
+ * Copyright 2010, Oleg Mazko
+ * http://www.mozilla.org/MPL/
+ */
+
+!function(r,i){"function"==typeof define&&define.amd?define(i):"object"==typeof exports?module.exports=i():i()(r.lunr)}(this,function(){return function(r){if(void 0===r)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===r.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");r.tr=function(){this.pipeline.reset(),this.pipeline.add(r.tr.trimmer,r.tr.stopWordFilter,r.tr.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(r.tr.stemmer))},r.tr.wordCharacters="A-Za-zªºÀ-ÖØ-öø-ʸˠ-ˤᴀ-ᴥᴬ-ᵜᵢ-ᵥᵫ-ᵷᵹ-ᶾḀ-ỿⁱⁿₐ-ₜKÅℲⅎⅠ-ↈⱠ-ⱿꜢ-ꞇꞋ-ꞭꞰ-ꞷꟷ-ꟿꬰ-ꭚꭜ-ꭤff-stＡ-Ｚａ-ｚ",r.tr.trimmer=r.trimmerSupport.generateTrimmer(r.tr.wordCharacters),r.Pipeline.registerFunction(r.tr.trimmer,"trimmer-tr"),r.tr.stemmer=function(){var i=r.stemmerSupport.Among,e=r.stemmerSupport.SnowballProgram,n=new function(){function r(r,i,e){for(;;){var n=Dr.limit-Dr.cursor;if(Dr.in_grouping_b(r,i,e)){Dr.cursor=Dr.limit-n;break}if(Dr.cursor=Dr.limit-n,Dr.cursor<=Dr.limit_backward)return!1;Dr.cursor--}return!0}function n(){var i,e;i=Dr.limit-Dr.cursor,r(Wr,97,305);for(var n=0;n<Br.length;n++){e=Dr.limit-Dr.cursor;var t=Br[n];if(Dr.eq_s_b(1,t[0])&&r(t[1],t[2],t[3]))return Dr.cursor=Dr.limit-i,!0;Dr.cursor=Dr.limit-e}return Dr.cursor=Dr.limit-e,!(!Dr.eq_s_b(1,"ü")||!r(Zr,246,252))&&(Dr.cursor=Dr.limit-i,!0)}function t(r,i){var e,n=Dr.limit-Dr.cursor;return r()&&(Dr.cursor=Dr.limit-n,Dr.cursor>Dr.limit_backward&&(Dr.cursor--,e=Dr.limit-Dr.cursor,i()))?(Dr.cursor=Dr.limit-e,!0):(Dr.cursor=Dr.limit-n,r()?(Dr.cursor=Dr.limit-n,!1):(Dr.cursor=Dr.limit-n,!(Dr.cursor<=Dr.limit_backward)&&(Dr.cursor--,!!i()&&(Dr.cursor=Dr.limit-n,!0))))}function u(r){return t(r,function(){return Dr.in_grouping_b(Wr,97,305)})}function o(){return u(function(){return Dr.eq_s_b(1,"n")})}function s(){return u(function(){return Dr.eq_s_b(1,"s")})}function c(){return u(function(){return Dr.eq_s_b(1,"y")})}function l(){return t(function(){return Dr.in_grouping_b(Lr,105,305)},function(){return Dr.out_grouping_b(Wr,97,305)})}function a(){return Dr.find_among_b(ur,10)&&l()}function m(){return n()&&Dr.in_grouping_b(Lr,105,305)&&s()}function d(){return Dr.find_among_b(or,2)}function f(){return n()&&Dr.in_grouping_b(Lr,105,305)&&c()}function b(){return n()&&Dr.find_among_b(sr,4)}function w(){return n()&&Dr.find_among_b(cr,4)&&o()}function _(){return n()&&Dr.find_among_b(lr,2)&&c()}function k(){return n()&&Dr.find_among_b(ar,2)}function p(){return n()&&Dr.find_among_b(mr,4)}function g(){return n()&&Dr.find_among_b(dr,2)}function y(){return n()&&Dr.find_among_b(fr,4)}function z(){return n()&&Dr.find_among_b(br,2)}function v(){return n()&&Dr.find_among_b(wr,2)&&c()}function h(){return Dr.eq_s_b(2,"ki")}function q(){return n()&&Dr.find_among_b(_r,2)&&o()}function C(){return n()&&Dr.find_among_b(kr,4)&&c()}function P(){return n()&&Dr.find_among_b(pr,4)}function F(){return n()&&Dr.find_among_b(gr,4)&&c()}function S(){return Dr.find_among_b(yr,4)}function W(){return n()&&Dr.find_among_b(zr,2)}function L(){return n()&&Dr.find_among_b(vr,4)}function x(){return n()&&Dr.find_among_b(hr,8)}function A(){return Dr.find_among_b(qr,2)}function E(){return n()&&Dr.find_among_b(Cr,32)&&c()}function j(){return Dr.find_among_b(Pr,8)&&c()}function T(){return n()&&Dr.find_among_b(Fr,4)&&c()}function Z(){return Dr.eq_s_b(3,"ken")&&c()}function B(){var r=Dr.limit-Dr.cursor;return!(T()||(Dr.cursor=Dr.limit-r,E()||(Dr.cursor=Dr.limit-r,j()||(Dr.cursor=Dr.limit-r,Z()))))}function D(){if(A()){var r=Dr.limit-Dr.cursor;if(S()||(Dr.cursor=Dr.limit-r,W()||(Dr.cursor=Dr.limit-r,C()||(Dr.cursor=Dr.limit-r,P()||(Dr.cursor=Dr.limit-r,F()||(Dr.cursor=Dr.limit-r))))),T())return!1}return!0}function G(){if(W()){Dr.bra=Dr.cursor,Dr.slice_del();var r=Dr.limit-Dr.cursor;return Dr.ket=Dr.cursor,x()||(Dr.cursor=Dr.limit-r,E()||(Dr.cursor=Dr.limit-r,j()||(Dr.cursor=Dr.limit-r,T()||(Dr.cursor=Dr.limit-r)))),nr=!1,!1}return!0}function H(){if(!L())return!0;var r=Dr.limit-Dr.cursor;return!E()&&(Dr.cursor=Dr.limit-r,!j())}function I(){var r,i=Dr.limit-Dr.cursor;return!(S()||(Dr.cursor=Dr.limit-i,F()||(Dr.cursor=Dr.limit-i,P()||(Dr.cursor=Dr.limit-i,C()))))||(Dr.bra=Dr.cursor,Dr.slice_del(),r=Dr.limit-Dr.cursor,Dr.ket=Dr.cursor,T()||(Dr.cursor=Dr.limit-r),!1)}function J(){var r,i=Dr.limit-Dr.cursor;if(Dr.ket=Dr.cursor,nr=!0,B()&&(Dr.cursor=Dr.limit-i,D()&&(Dr.cursor=Dr.limit-i,G()&&(Dr.cursor=Dr.limit-i,H()&&(Dr.cursor=Dr.limit-i,I()))))){if(Dr.cursor=Dr.limit-i,!x())return;Dr.bra=Dr.cursor,Dr.slice_del(),Dr.ket=Dr.cursor,r=Dr.limit-Dr.cursor,S()||(Dr.cursor=Dr.limit-r,W()||(Dr.cursor=Dr.limit-r,C()||(Dr.cursor=Dr.limit-r,P()||(Dr.cursor=Dr.limit-r,F()||(Dr.cursor=Dr.limit-r))))),T()||(Dr.cursor=Dr.limit-r)}Dr.bra=Dr.cursor,Dr.slice_del()}function K(){var r,i,e,n;if(Dr.ket=Dr.cursor,h()){if(r=Dr.limit-Dr.cursorLine truncated

assets/javascripts/lunr/min/lunr.vi.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.vi=function(){this.pipeline.reset(),this.pipeline.add(e.vi.stopWordFilter,e.vi.trimmer)},e.vi.wordCharacters="[A-Za-ẓ̀͐́͑̉̃̓ÂâÊêÔôĂ-ăĐ-đƠ-ơƯ-ư]",e.vi.trimmer=e.trimmerSupport.generateTrimmer(e.vi.wordCharacters),e.Pipeline.registerFunction(e.vi.trimmer,"trimmer-vi"),e.vi.stopWordFilter=e.generateStopWordFilter("là cái nhưng mà".split(" "))}});

assets/javascripts/lunr/min/lunr.zh.min.js

@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r(require("@node-rs/jieba")):r()(e.lunr)}(this,function(e){return function(r,t){if(void 0===r)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===r.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");var i="2"==r.version[0];r.zh=function(){this.pipeline.reset(),this.pipeline.add(r.zh.trimmer,r.zh.stopWordFilter,r.zh.stemmer),i?this.tokenizer=r.zh.tokenizer:(r.tokenizer&&(r.tokenizer=r.zh.tokenizer),this.tokenizerFn&&(this.tokenizerFn=r.zh.tokenizer))},r.zh.tokenizer=function(n){if(!arguments.length||null==n||void 0==n)return[];if(Array.isArray(n))return n.map(function(e){return i?new r.Token(e.toLowerCase()):e.toLowerCase()});t&&e.load(t);var o=n.toString().trim().toLowerCase(),s=[];e.cut(o,!0).forEach(function(e){s=s.concat(e.split(" "))}),s=s.filter(function(e){return!!e});var u=0;return s.map(function(e,t){if(i){var n=o.indexOf(e,u),s={};return s.position=[n,e.length],s.index=t,u=n,new r.Token(e,s)}return e})},r.zh.wordCharacters="\\w一-龥",r.zh.trimmer=r.trimmerSupport.generateTrimmer(r.zh.wordCharacters),r.Pipeline.registerFunction(r.zh.trimmer,"trimmer-zh"),r.zh.stemmer=function(){return function(e){return e}}(),r.Pipeline.registerFunction(r.zh.stemmer,"stemmer-zh"),r.zh.stopWordFilter=r.generateStopWordFilter("的 一 不 在 人 有 是 为 為 以 于 於 上 他 而 后 後 之 来 來 及 了 因 下 可 到 由 这 這 与 與 也 此 但 并 並 个 個 其 已 无 無 小 我 们 們 起 最 再 今 去 好 只 又 或 很 亦 某 把 那 你 乃 它 吧 被 比 别 趁 当 當 从 從 得 打 凡 儿 兒 尔 爾 该 該 各 给 給 跟 和 何 还 還 即 几 幾 既 看 据 據 距 靠 啦 另 么 麽 每 嘛 拿 哪 您 凭 憑 且 却 卻 让 讓 仍 啥 如 若 使 谁 誰 虽 雖 随 隨 同 所 她 哇 嗡 往 些 向 沿 哟 喲 用 咱 则 則 怎 曾 至 致 着 著 诸 諸 自".split(" ")),r.Pipeline.registerFunction(r.zh.stopWordFilter,"stopWordFilter-zh")}});

assets/javascripts/lunr/tinyseg.js

@@ -0,0 +1,206 @@
+/**
+ * export the module via AMD, CommonJS or as a browser global
+ * Export code from https://github.com/umdjs/umd/blob/master/returnExports.js
+ */
+;(function (root, factory) {
+    if (typeof define === 'function' && define.amd) {
+        // AMD. Register as an anonymous module.
+        define(factory)
+    } else if (typeof exports === 'object') {
+        /**
+         * Node. Does not work with strict CommonJS, but
+         * only CommonJS-like environments that support module.exports,
+         * like Node.
+         */
+        module.exports = factory()
+    } else {
+        // Browser globals (root is window)
+        factory()(root.lunr);
+    }
+}(this, function () {
+    /**
+     * Just return a value to define the module export.
+     * This example returns an object, but the module
+     * can return a function as the exported value.
+     */
+
+    return function(lunr) {
+        // TinySegmenter 0.1 -- Super compact Japanese tokenizer in Javascript
+        // (c) 2008 Taku Kudo <taku@chasen.org>
+        // TinySegmenter is freely distributable under the terms of a new BSD licence.
+        // For details, see http://chasen.org/~taku/software/TinySegmenter/LICENCE.txt
+
+        function TinySegmenter() {
+          var patterns = {
+            "[一二三四五六七八九十百千万億兆]":"M",
+            "[一-龠々〆ヵヶ]":"H",
+            "[ぁ-ん]":"I",
+            "[ァ-ヴーｱ-ﾝﾞｰ]":"K",
+            "[a-zA-Zａ-ｚＡ-Ｚ]":"A",
+            "[0-9０-９]":"N"
+          }
+          this.chartype_ = [];
+          for (var i in patterns) {
+            var regexp = new RegExp(i);
+            this.chartype_.push([regexp, patterns[i]]);
+          }
+
+          this.BIAS__ = -332
+          this.BC1__ = {"HH":6,"II":2461,"KH":406,"OH":-1378};
+          this.BC2__ = {"AA":-3267,"AI":2744,"AN":-878,"HH":-4070,"HM":-1711,"HN":4012,"HO":3761,"IA":1327,"IH":-1184,"II":-1332,"IK":1721,"IO":5492,"KI":3831,"KK":-8741,"MH":-3132,"MK":3334,"OO":-2920};
+          this.BC3__ = {"HH":996,"HI":626,"HK":-721,"HN":-1307,"HO":-836,"IH":-301,"KK":2762,"MK":1079,"MM":4034,"OA":-1652,"OH":266};
+          this.BP1__ = {"BB":295,"OB":304,"OO":-125,"UB":352};
+          this.BP2__ = {"BO":60,"OO":-1762};
+          this.BQ1__ = {"BHH":1150,"BHM":1521,"BII":-1158,"BIM":886,"BMH":1208,"BNH":449,"BOH":-91,"BOO":-2597,"OHI":451,"OIH":-296,"OKA":1851,"OKH":-1020,"OKK":904,"OOO":2965};
+          this.BQ2__ = {"BHH":118,"BHI":-1159,"BHM":466,"BIH":-919,"BKK":-1720,"BKO":864,"OHH":-1139,"OHM":-181,"OIH":153,"UHI":-1146};
+          this.BQ3__ = {"BHH":-792,"BHI":2664,"BII":-299,"BKI":419,"BMH":937,"BMM":8335,"BNN":998,"BOH":775,"OHH":2174,"OHM":439,"OII":280,"OKH":1798,"OKI":-793,"OKO":-2242,"OMH":-2402,"OOO":11699};
+          this.BQ4__ = {"BHH":-3895,"BIH":3761,"BII":-4654,"BIK":1348,"BKK":-1806,"BMI":-3385,"BOO":-12396,"OAH":926,"OHH":266,"OHK":-2036,"ONN":-973};
+          this.BW1__ = {",と":660,",同":727,"B1あ":1404,"B1同":542,"、と":660,"、同":727,"」と":1682,"あっ":1505,"いう":1743,"いっ":-2055,"いる":672,"うし":-4817,"うん":665,"から":3472,"がら":600,"こう":-790,"こと":2083,"こん":-1262,"さら":-4143,"さん":4573,"した":2641,"して":1104,"すで":-3399,"そこ":1977,"それ":-871,"たち":1122,"ため":601,"った":3463,"つい":-802,"てい":805,"てき":1249,"でき":1127,"です":3445,"では":844,"とい":-4915,"とみ":1922,"どこ":3887,"ない":5713,"なっ":3015,"など":7379,"なん":-1113,"にし":2468,"には":1498,"にも":1671,"に対":-912,"の一":-501,"の中":741,"ませ":2448,"まで":1711,"まま":2600,"まる":-2155,"やむ":-1947,"よっ":-2565,"れた":2369,"れで":-913,"をし":1860,"を見":731,"亡く":-1886,"京都":2558,"取り":-2784,"大き":-2604,"大阪":1497,"平方":-2314,"引き":-1336,"日本":-195,"本当":-2423,"毎日":-2113,"目指":-724,"Ｂ１あ":1404,"Ｂ１同":542,"｣と":1682};
+          this.BW2__ = {"..":-11822,"11":-669,"――":-5730,"−−":-13175,"いう":-1609,"うか":2490,"かし":-1350,"かも":-602,"から":-7194,"かれ":4612,"がい":853,"がら":-3198,"きた":1941,"くな":-1597,"こと":-8392,"この":-4193,"させ":4533,"され":13168,"さん":-3977,"しい":-1819,"しか":-545,"した":5078,"して":972,"しな":939,"その":-3744,"たい":-1253,"たた":-662,"ただ":-3857,"たち":-786,"たと":1224,"たは":-939,"った":4589,"って":1647,"っと":-2094,"てい":6144,"てき":3640,"てく":2551,"ては":-3110,"ても":-3065,"でい":2666,"でき":-1528,"でし":-3828,"です":-4761,"でも":-4203,"とい":1890,"とこ":-1746,"とと":-2279,"との":720,"とみ":5168,"とも":-3941,"ない":-2488,"なが":-1313,"など":-6509,"なの":2614,"なん":3099,"にお":-1615,"にし":2748,"にな":2454,"によ":-7236,"に対":-14943,"に従":-4688,"に関":-11388,"のか":2093,"ので":-7059,"のに":-6041,"のの":-6125,"はい":1073,"はが":-1033,"はず":-2532,"ばれ":1813,"まし":-1316,"まで":-6621,"まれ":5409,"めて":-3153,"もい":2230,"もの":-10713,"らか":-944,"らし":-1611,"らに":-1897,"りし":651,"りま":1620,"れた":4270,"れて":849,"れば":4114,"ろう":6067,"われ":7901,"を通":-11877,"んだ":728,"んな":-4115,"一人":602,"一方":-1375,"一日":970,"一部":-1051,"上が":-4479,"会社":-1116,"出て":2163,"分の":-7758,"同党":970,"同日":-913,"大阪":-2471,"委員":-1250,"少な":-1050,"年度":-8669,"年間":-1626,"府県":-2363,"手権":-1982,"新聞":-4066,"日新":-722,"日本":-7068,"日米":3372,"曜日":-601,"朝鮮":-2355,"本人":-2697,"東京":-1543,"然と":-1384,"社会":-1276,"立て":-990,"第に":-1612,"米国":-4268,"１１":-669};
+          this.BW3__ = {"あた":-2194,"あり":719,"ある":3846,"い.":-1185,"い。":-1185,"いい":5308,"いえ":2079,"いく":3029,"いた":2056,"いっ":1883,"いる":5600,"いわ":1527,"うち":1117,"うと":4798,"えと":1454,"か.":2857,"か。":2857,"かけ":-743,"かっ":-4098,"かに":-669,"から":6520,"かり":-2670,"が,":1816,"が、":1816,"がき":-4855,"がけ":-1127,"がっ":-913,"がら":-4977,"がり":-2064,"きた":1645,"けど":1374,"こと":7397,"この":1542,"ころ":-2757,"さい":-714,"さを":976,"し,":1557,"し、":1557,"しい":-3714,"した":3562,"して":1449,"しな":2608,"しま":1200,"す.":-1310,"す。":-1310,"する":6521,"ず,":3426,"ず、":3426,"ずに":841,"そう":428,"た.":8875,"た。":8875,"たい":-594,"たの":812,"たり":-1183,"たる":-853,"だ.":4098,"だ。":4098,"だっ":1004,"った":-4748,"って":300,"てい":6240,"てお":855,"ても":302,"です":1437,"でに":-1482,"では":2295,"とう":-1387,"とし":2266,"との":541,"とも":-3543,"どう":4664,"ない":1796,"なく":-903,"など":2135,"に,":-1021,"に、":-1021,"にし":1771,"にな":1906,"には":2644,"の,":-724,"の、":-724,"の子":-1000,"は,":1337,"は、":1337,"べき":2181,"まし":1113,"ます":6943,"まっ":-1549,"まで":6154,"まれ":-793,"らし":1479,"られ":6820,"るる":3818,"れ,":854,"れ、":854,"れた":1850,"れて":1375,"れば":-3246,"れる":1091,"われ":-605,"んだ":606,"んで":798,"カ月":990,"会議":860,"入り":1232,"大会":2217,"始め":1681,"市":965,"新聞":-5055,"日,":974,"日、":974,"社会":2024,"ｶ月":990};
+          this.TC1__ = {"AAA":1093,"HHH":1029,"HHM":580,"HII":998,"HOH":-390,"HOM":-331,"IHI":1169,"IOH":-142,"IOI":-1015,"IOM":467,"MMH":187,"OOI":-1832};
+          this.TC2__ = {"HHO":2088,"HII":-1023,"HMM":-1154,"IHI":-1965,"KKH":703,"OII":-2649};
+          this.TC3__ = {"AAA":-294,"HHH":346,"HHI":-341,"HII":-1088,"HIK":731,"HOH":-1486,"IHH":128,"IHI":-3041,"IHO":-1935,"IIH":-825,"IIM":-1035,"IOI":-542,"KHH":-1216,"KKA":491,"KKH":-1217,"KOK":-1009,"MHH":-2694,"MHM":-457,"MHO":123,"MMH":-471,"NNH":-1689,"NNO":662,"OHO":-3393};
+          this.TC4__ = {"HHH":-203,"HHI":1344,"HHK":365,"HHM":-122,"HHN":182,"HHO":669,"HIH":804,"HII":679,"HOH":446,"IHH":695,"IHO":-2324,"IIH":321,"III":1497,"IIO":656,"IOO":54,"KAK":4845,"KKA":3386,"KKK":3065,"MHH":-405,"MHI":201,"MMH":-241,"MMM":661,"MOM":841};
+          this.TQ1__ = {"BHHH":-227,"BHHI":316,"BHIH":-132,"BIHH":60,"BIII":1595,"BNHH":-744,"BOHH":225,"BOOO":-908,"OAKK":482,"OHHH":281,"OHIH":249,"OIHI":200,"OIIH":-68};
+          this.TQ2__ = {"BIHH":-1401,"BIII":-1033,"BKAK":-543,"BOOO":-5591};
+          this.TQ3__ = {"BHHH":478,"BHHM":-1073,"BHIH":222,"BHII":-504,"BIIH":-116,"BIII":-105,"BMHI":-863,"BMHM":-464,"BOMH":620,"OHHH":346,"OHHI":1729,"OHII":997,"OHMH":481,"OIHH":623,"OIIH":1344,"OKAK":2792,"OKHH":587,"OKKA":679,"OOHH":110,"OOII":-685};
+          this.TQ4__ = {"BHHH":-721,"BHHM":-3604,"BHII":-966,"BIIH":-607,"BIII":-2181,"OAAA":-2763,"OAKK":180,"OHHH":-294,"OHHI":2446,"OHHO":480,"OHIH":-1573,"OIHH":1935,"OIHI":-493,"OIIH":626,"OIII":-4007,"OKAK":-8156};
+          this.TW1__ = {"につい":-4681,"東京都":2026};
+          this.TW2__ = {"ある程":-2049,"いった":-1256,"ころが":-2434,"しょう":3873,"その後":-4430,"だって":-1049,"ていた":1833,"として":-4657,"ともに":-4517,"もので":1882,"一気に":-792,"初めて":-1512,"同時に":-8097,"大きな":-1255,"対して":-2721,"社会党":-3216};
+          this.TW3__ = {"いただ":-1734,"してい":1314,"として":-4314,"につい":-5483,"にとっ":-5989,"に当た":-6247,"ので,":-727,"ので、":-727,"のもの":-600,"れから":-3752,"十二月":-2287};
+          this.TW4__ = {"いう.":8576,"いう。":8576,"からな":-2348,"してい":2958,"たが,":1516,"たが、":1516,"ている":1538,"という":1349,"ました":5543,"ません":1097,"ようと":-4258,"よると":5865};
+          this.UC1__ = {"A":484,"K":93,"M":645,"O":-505};
+          this.UC2__ = {"A":819,"H":1059,"I":409,"M":3987,"N":5775,"O":646};
+          this.UC3__ = {"A":-1370,"I":2311};
+          this.UC4__ = {"A":-2643,"H":1809,"I":-1032,"K":-3450,"M":3565,"N":3876,"O":6646};
+          this.UC5__ = {"H":313,"I":-1238,"K":-799,"M":539,"O":-831};
+          this.UC6__ = {"H":-506,"I":-253,"K":87,"M":247,"O":-387};
+          this.UP1__ = {"O":-214};
+          this.UP2__ = {"B":69,"O":935};
+          this.UP3__ = {"B":189};
+          this.UQ1__ = {"BH":21,"BI":-12,"BK":-99,"BN":142,"BO":-56,"OH":-95,"OI":477,"OK":410,"OO":-2422};
+          this.UQ2__ = {"BH":216,"BI":113,"OK":1759};
+          this.UQ3__ = {"BA":-479,"BH":42,"BI":1913,"BK":-7198,"BM":3160,"BN":6427,"BO":14761,"OI":-827,"ON":-3212};
+          this.UW1__ = {",":156,"、":156,"「":-463,"あ":-941,"う":-127,"が":-553,"き":121,"こ":505,"で":-201,"と":-547,"ど":-123,"に":-789,"の":-185,"は":-847,"も":-466,"や":-470,"よ":182,"ら":-292,"り":208,"れ":169,"を":-446,"ん":-137,"・":-135,"主":-402,"京":-268,"区":-912,"午":871,"国":-460,"大":561,"委":729,"市":-411,"日":-141,"理":361,"生":-408,"県":-386,"都":-718,"｢":-463,"･":-135};
+          this.UW2__ = {",":-829,"、":-829,"〇":892,"「":-645,"」":3145,"あ":-538,"い":505,"う":134,"お":-502,"か":1454,"が":-856,"く":-412,"こ":1141,"さ":878,"ざ":540,"し":1529,"す":-675,"せ":300,"そ":-1011,"た":188,"だ":1837,"つ":-949,"て":-291,"で":-268,"と":-981,"ど":1273,"な":1063,"に":-1764,"の":130,"は":-409,"ひ":-1273,"べ":1261,"ま":600,"も":-1263,"や":-402,"よ":1639,"り":-579,"る":-694,"れ":571,"を":-2516,"ん":2095,"ア":-587,"カ":306,"キ":568,"ッ":831,"三":-758,"不":-2150,"世":-302,"中":-968,"主":-861,"事":492,"人":-123,"会":978,"保":362,"入":548,"初":-3025,"副":-1566,"北":-3414,"区":-422,"大":-1769,"天":-865,"太":-483,"子":-1519,"学":760,"実":1023,"小":-2009,"市":-813,"年":-1060,"強":1067,"手":-1519,"揺":-1033,"政":1522,"文":-1355,"新":-1682,"日":-1815,"明":-1462,"最":-630,"朝":-1843,"本":-1650,"東":-931,"果":-665,"次":-2378,"民":-180,"気":-1740,"理":752,"発":529,"目":-1584,"相":-242,"県":-1165,"立":-763,"第":810,"米":509,"自":-1353,"行":838,"西":-744,"見":-3874,"調":1010,"議":1198,"込":3041,"開":1758,"間":-1257,"｢":-645,"｣":3145,"ｯ":831,"ｱ":-587,"ｶ":306,"ｷ":568};
+          this.UW3__ = {",":4889,"1":-800,"−":-1723,"、":4889,"々":-2311,"〇":5827,"」":2670,"〓":-3573,"あ":-2696,"い":1006,"う":2342,"え":1983,"お":-4864,"か":-1163,"が":3271,"く":1004,"け":388,"げ":401,"こ":-3552,"ご":-3116,"さ":-1058,"し":-395,"す":584,"せ":3685,"そ":-5228,"た":842,"ち":-521,"っ":-1444,"つ":-1081,"て":6167,"で":2318,"と":1691,"ど":-899,"な":-2788,"に":2745,"の":4056,"は":4555,"ひ":-2171,"ふ":-1798,"へ":1199,"ほ":-5516,"ま":-4384,"み":-120,"め":1205,"も":2323,"や":-788,"よ":-202,"ら":727,"り":649,"る":5905,"れ":2773,"わ":-1207,"を":6620,"ん":-518,"ア":551,"グ":1319,"ス":874,"ッ":-1350,"ト":521,"ム":1109,"ル":1591,"ロ":2201,"ン":278,"・":-3794,"一":-1619,"下":-1759,"世":-2087,"両":3815,"中":653,"主":-758,"予":-1193,"二":974,"人":2742,"今":792,"他":1889,"以":-1368,"低":811,"何":4265,"作":-361,"保":-2439,"元":4858,"党":3593,"全":1574,"公":-3030,"六":755,"共":-1880,"円":5807,"再":3095,"分":457,"初":2475,"別":1129,"前":2286,"副":4437,"力":365,"動":-949,"務":-1872,"化":1327,"北":-1038,"区":4646,"千":-2309,"午":-783,"協":-1006,"口":483,"右":1233,"各":3588,"合":-241,"同":3906,"和":-837,"員":4513,"国":642,"型":1389,"場":1219,"外":-241,"妻":2016,"学":-1356,"安":-423,"実":-1008,"家":1078,"小":-513,"少":-3102,"州":1155,"市":3197,"平":-1804,"年":2416,"広":-1030,"府":1605,"度":1452,"建":-2352,"当":-3885,"得":1905,"思":-1291,"性":1822,"戸":-488,"指":-3973,"政":-2013,"教":-1479,"数":3222,"文":-1489,"新":1764,"日":2099,"旧":5792,"昨":-661,"時":-1248,"曜":-951,"最":-937,"月":4125,"期":360,"李":3094,"村":364,"東":-805,"核":5156,"森":2438,"業":484,"氏":2613,"民":-1694,"決":-1073,"法":1868,"海":-495,"無":979,"物":461,"特":-3850,"生":-273,"用":914,"町":1215,"的":7313,"直":-1835,"省":792,"県":6293,"知":-1528,"私":4231,"税":401,"立":-960,"第":1201,"米":7767,"系":3066,"約":3663,"級":1384,"統":-4229,"総":1163,"線":1255,"者":6457,"能":725,"自":-2869,"英":785,"見":1044,"調":-562,"財":-733,"費":1777,"車":1835,"軍":1375,"込":-1504,"通":-1136,"選":-681,"郎":1026,"郡":4404,"部":1200,"金":2163,"長":421,"開":-1432,"間":1302,"関":-1282,"雨":2009,"電":-1045,"非":2066,"駅":1620,"１":-800,"｣":2670,"･":-3794,"ｯ":-1350,"ｱ":551,"ｸﾞ":1319,"ｽ":874,"ﾄ":521,"ﾑ":1109,"ﾙ":1591,"ﾛ":2201,"ﾝ":278};
+          this.UW4__ = {",":3930,".":3508,"―":-4841,"、":3930,"。":3508,"〇":4999,"「":1895,"」":3798,"〓":-5156,"あ":4752,"い":-3435,"う":-640,"え":-2514,"お":2405,"か":530,"が":6006,"き":-4482,"ぎ":-3821,"く":-3788,"け":-4376,"げ":-4734,"こ":2255,"ご":1979,"さ":2864,"し":-843,"じ":-2506,"す":-731,"ず":1251,"せ":181,"そ":4091,"た":5034,"だ":5408,"ち":-3654,"っ":-5882,"つ":-1659,"て":3994,"で":7410,"と":4547,"な":5433,"に":6499,"ぬ":1853,"ね":1413,"の":7396,"は":8578,"ば":1940,"ひ":4249,"び":-4134,"ふ":1345,"へ":6665,"べ":-744,"ほ":1464,"ま":1051,"み":-2082,"む":-882,"め":-5046,"も":4169,"ゃ":-2666,"や":2795,"ょ":-1544,"よ":3351,"ら":-2922,"り":-9726,"る":-14896,"れ":-2613,"ろ":-4570,"わ":-1783,"を":13150,"ん":-2352,"カ":2145,"コ":1789,"セ":1287,"ッ":-724,"ト":-403,"メ":-1635,"ラ":-881,"リ":-541,"ル":-856,"ン":-3637,"・":-4371,"ー":-11870,"一":-2069,"中":2210,"予":782,"事":-190,"井":-1768,"人":1036,"以":544,"会":950,"体":-1286,"作":530,"側":4292,"先":601,"党":-2006,"共":-1212,"内":584,"円":788,"初":1347,"前":1623,"副":3879,"力":-302,"動":-740,"務":-2715,"化":776,"区":4517,"協":1013,"参":1555,"合":-1834,"和":-681,"員":-910,"器":-851,"回":1500,"国":-619,"園":-1200,"地":866,"場":-1410,"塁":-2094,"士":-1413,"多":1067,"大":571,"子":-4802,"学":-1397,"定":-1057,"寺":-809,"小":1910,"屋":-1328,"山":-1500,"島":-2056,"川":-2667,"市":2771,"年":374,"庁":-4556,"後":456,"性":553,"感":916,"所":-1566,"支":856,"改":787,"政":2182,"教":704,"文":522,"方":-856,"日":1798,"時":1829,"最":845,"月":-9066,"木":-485,"来":-442,"校":-360,"業":-1043,"氏":5388,"民":-2716,"気":-910,"沢":-939,"済":-543,"物":-735,"率":672,"球":-1267,"生":-1286,"産":-1101,"田":-2900,"町":1826,"的":2586,"目":922,"省":-3485,"県":2997,"空":-867,"立":-2112,"第":788,"米":2937,"系":786,"約":2171,"経":1146,"統":-1169,"総":940,"線":-994,"署":749,"者":2145,"能":-730,"般":-852,"行":-792,"規":792,"警":-1184,"議":-244,"谷":-1000,"賞":730,"車":-1481,"軍":1158,"輪":-1433,"込":-3370,"近":929,"道":-1291,"選":2596,"郎":-4866,"都":1192,"野":-1100,"銀":-2213,"長":357,"間":-2344,"院":-2297,"際":-2604,"電":-878,"領":-1659,"題":-792,"館":-1984,"首":1749,"高":2120,"｢":1895,"｣":3798,"･":-4371,"ｯ":-724,"ｰ":-11870,"ｶ":2145,"ｺ":1789,"ｾ":1287,"ﾄ":-403,"ﾒ":-1635,"ﾗ":-881,"ﾘ":-541,"ﾙ":-856,"ﾝ":-3637};
+          this.UW5__ = {",":465,".":-299,"1":-514,"E2":-32768,"]":-2762,"、":465,"。":-299,"「":363,"あ":1655,"い":331,"う":-503,"え":1199,"お":527,"か":647,"が":-421,"き":1624,"ぎ":1971,"く":312,"げ":-983,"さ":-1537,"し":-1371,"す":-852,"だ":-1186,"ち":1093,"っ":52,"つ":921,"て":-18,"で":-850,"と":-127,"ど":1682,"な":-787,"に":-1224,"の":-635,"は":-578,"べ":1001,"み":502,"め":865,"ゃ":3350,"ょ":854,"り":-208,"る":429,"れ":504,"わ":419,"を":-1264,"ん":327,"イ":241,"ル":451,"ン":-343,"中":-871,"京":722,"会":-1153,"党":-654,"務":3519,"区":-901,"告":848,"員":2104,"大":-1296,"学":-548,"定":1785,"嵐":-1304,"市":-2991,"席":921,"年":1763,"思":872,"所":-814,"挙":1618,"新":-1682,"日":218,"月":-4353,"査":932,"格":1356,"機":-1508,"氏":-1347,"田":240,"町":-3912,"的":-3149,"相":1319,"省":-1052,"県":-4003,"研":-997,"社":-278,"空":-813,"統":1955,"者":-2233,"表":663,"語":-1073,"議":1219,"選":-1018,"郎":-368,"長":786,"間":1191,"題":2368,"館":-689,"１":-514,"Ｅ２":-32768,"｢":363,"ｲ":241,"ﾙ":451,"ﾝ":-343};
+          this.UW6__ = {",":227,".":808,"1":-270,"E1":306,"、":227,"。":808,"あ":-307,"う":189,"か":241,"が":-73,"く":-121,"こ":-200,"じ":1782,"す":383,"た":-428,"っ":573,"て":-1014,"で":101,"と":-105,"な":-253,"に":-149,"の":-417,"は":-236,"も":-206,"り":187,"る":-135,"を":195,"ル":-673,"ン":-496,"一":-277,"中":201,"件":-800,"会":624,"前":302,"区":1792,"員":-1212,"委":798,"学":-960,"市":887,"広":-695,"後":535,"業":-697,"相":753,"社":-507,"福":974,"空":-822,"者":1811,"連":463,"郎":1082,"１":-270,"Ｅ１":306,"ﾙ":-673,"ﾝ":-496};
+          
+          return this;
+        }
+        TinySegmenter.prototype.ctype_ = function(str) {
+          for (var i in this.chartype_) {
+            if (str.match(this.chartype_[i][0])) {
+              return this.chartype_[i][1];
+            }
+          }
+          return "O";
+        }
+
+        TinySegmenter.prototype.ts_ = function(v) {
+          if (v) { return v; }
+          return 0;
+        }
+
+        TinySegmenter.prototype.segment = function(input) {
+          if (input == null || input == undefined || input == "") {
+            return [];
+          }
+          var result = [];
+          var seg = ["B3","B2","B1"];
+          var ctype = ["O","O","O"];
+          var o = input.split("");
+          for (i = 0; i < o.length; ++i) {
+            seg.push(o[i]);
+            ctype.push(this.ctype_(o[i]))
+          }
+          seg.push("E1");
+          seg.push("E2");
+          seg.push("E3");
+          ctype.push("O");
+          ctype.push("O");
+          ctype.push("O");
+          var word = seg[3];
+          var p1 = "U";
+          var p2 = "U";
+          var p3 = "U";
+          for (var i = 4; i < seg.length - 3; ++i) {
+            var score = this.BIAS__;
+            var w1 = seg[i-3];
+            var w2 = seg[i-2];
+            var w3 = seg[i-1];
+            var w4 = seg[i];
+            var w5 = seg[i+1];
+            var w6 = seg[i+2];
+            var c1 = ctype[i-3];
+            var c2 = ctype[i-2];
+            var c3 = ctype[i-1];
+            var c4 = ctype[i];
+            var c5 = ctype[i+1];
+            var c6 = ctype[i+2];
+            score += this.ts_(this.UP1__[p1]);
+            score += this.ts_(this.UP2__[p2]);
+            score += this.ts_(this.UP3__[p3]);
+            score += this.ts_(this.BP1__[p1 + p2]);
+            score += this.ts_(this.BP2__[p2 + p3]);
+            score += this.ts_(this.UW1__[w1]);
+            score += this.ts_(this.UW2__[w2]);
+            score += this.ts_(this.UW3__[w3]);
+            score += this.ts_(this.UW4__[w4]);
+            score += this.ts_(this.UW5__[w5]);
+            score += this.ts_(this.UW6__[w6]);
+            score += this.ts_(this.BW1__[w2 + w3]);
+            score += this.ts_(this.BW2__[w3 + w4]);
+            score += this.ts_(this.BW3__[w4 + w5]);
+            score += this.ts_(this.TW1__[w1 + w2 + w3]);
+            score += this.ts_(this.TW2__[w2 + w3 + w4]);
+            score += this.ts_(this.TW3__[w3 + w4 + w5]);
+            score += this.ts_(this.TW4__[w4 + w5 + w6]);
+            score += this.ts_(this.UC1__[c1]);
+            score += this.ts_(this.UC2__[c2]);
+            score += this.ts_(this.UC3__[c3]);
+            score += this.ts_(this.UC4__[c4]);
+            score += this.ts_(this.UC5__[c5]);
+            score += this.ts_(this.UC6__[c6]);
+            score += this.ts_(this.BC1__[c2 + c3]);
+            score += this.ts_(this.BC2__[c3 + c4]);
+            score += this.ts_(this.BC3__[c4 + c5]);
+            score += this.ts_(this.TC1__[c1 + c2 + c3]);
+            score += this.ts_(this.TC2__[c2 + c3 + c4]);
+            score += this.ts_(this.TC3__[c3 + c4 + c5]);
+            score += this.ts_(this.TC4__[c4 + c5 + c6]);
+        //  score += this.ts_(this.TC5__[c4 + c5 + c6]);    
+            score += this.ts_(this.UQ1__[p1 + c1]);
+            score += this.ts_(this.UQ2__[p2 + c2]);
+            score += this.ts_(this.UQ3__[p3 + c3]);
+            score += this.ts_(this.BQ1__[p2 + c2 + c3]);
+            score += this.ts_(this.BQ2__[p2 + c3 + c4]);
+            score += this.ts_(this.BQ3__[p3 + c2 + c3]);
+            score += this.ts_(this.BQ4__[p3 + c3 + c4]);
+            score += this.ts_(this.TQ1__[p2 + c1 + c2 + c3]);
+            score += this.ts_(this.TQ2__[p2 + c2 + c3 + c4]);
+            score += this.ts_(this.TQ3__[p3 + c1 + c2 + c3]);
+            score += this.ts_(this.TQ4__[p3 + c2 + c3 + c4]);
+            var p = "O";
+            if (score > 0) {
+              result.push(word);
+              word = "";
+              p = "B";
+            }
+            p1 = p2;
+            p2 = p3;
+            p3 = p;
+            word += seg[i];
+          }
+          result.push(word);
+
+          return result;
+        }
+
+        lunr.TinySegmenter = TinySegmenter;
+    };
+
+}));

assets/javascripts/workers/search.d50fe291.min.js

@@ -0,0 +1,42 @@
+"use strict";(()=>{var xe=Object.create;var U=Object.defineProperty,ve=Object.defineProperties,Se=Object.getOwnPropertyDescriptor,Te=Object.getOwnPropertyDescriptors,Qe=Object.getOwnPropertyNames,J=Object.getOwnPropertySymbols,Ee=Object.getPrototypeOf,Z=Object.prototype.hasOwnProperty,be=Object.prototype.propertyIsEnumerable;var K=Math.pow,X=(t,e,r)=>e in t?U(t,e,{enumerable:!0,configurable:!0,writable:!0,value:r}):t[e]=r,A=(t,e)=>{for(var r in e||(e={}))Z.call(e,r)&&X(t,r,e[r]);if(J)for(var r of J(e))be.call(e,r)&&X(t,r,e[r]);return t},G=(t,e)=>ve(t,Te(e));var Le=(t,e)=>()=>(e||t((e={exports:{}}).exports,e),e.exports);var we=(t,e,r,n)=>{if(e&&typeof e=="object"||typeof e=="function")for(let i of Qe(e))!Z.call(t,i)&&i!==r&&U(t,i,{get:()=>e[i],enumerable:!(n=Se(e,i))||n.enumerable});return t};var Pe=(t,e,r)=>(r=t!=null?xe(Ee(t)):{},we(e||!t||!t.__esModule?U(r,"default",{value:t,enumerable:!0}):r,t));var B=(t,e,r)=>new Promise((n,i)=>{var s=u=>{try{a(r.next(u))}catch(c){i(c)}},o=u=>{try{a(r.throw(u))}catch(c){i(c)}},a=u=>u.done?n(u.value):Promise.resolve(u.value).then(s,o);a((r=r.apply(t,e)).next())});var re=Le((ee,te)=>{/**
+ * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.9
+ * Copyright (C) 2020 Oliver Nightingale
+ * @license MIT
+ */(function(){var t=function(e){var r=new t.Builder;return r.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),r.searchPipeline.add(t.stemmer),e.call(r,r),r.build()};t.version="2.3.9";/*!
+ * lunr.utils
+ * Copyright (C) 2020 Oliver Nightingale
+ */t.utils={},t.utils.warn=function(e){return function(r){e.console&&console.warn&&console.warn(r)}}(this),t.utils.asString=function(e){return e==null?"":e.toString()},t.utils.clone=function(e){if(e==null)return e;for(var r=Object.create(null),n=Object.keys(e),i=0;i<n.length;i++){var s=n[i],o=e[s];if(Array.isArray(o)){r[s]=o.slice();continue}if(typeof o=="string"||typeof o=="number"||typeof o=="boolean"){r[s]=o;continue}throw new TypeError("clone is not deep and does not support nested objects")}return r},t.FieldRef=function(e,r,n){this.docRef=e,this.fieldName=r,this._stringValue=n},t.FieldRef.joiner="/",t.FieldRef.fromString=function(e){var r=e.indexOf(t.FieldRef.joiner);if(r===-1)throw"malformed field ref string";var n=e.slice(0,r),i=e.slice(r+1);return new t.FieldRef(i,n,e)},t.FieldRef.prototype.toString=function(){return this._stringValue==null&&(this._stringValue=this.fieldName+t.FieldRef.joiner+this.docRef),this._stringValue};/*!
+ * lunr.Set
+ * Copyright (C) 2020 Oliver Nightingale
+ */t.Set=function(e){if(this.elements=Object.create(null),e){this.length=e.length;for(var r=0;r<this.length;r++)this.elements[e[r]]=!0}else this.length=0},t.Set.complete={intersect:function(e){return e},union:function(){return this},contains:function(){return!0}},t.Set.empty={intersect:function(){return this},union:function(e){return e},contains:function(){return!1}},t.Set.prototype.contains=function(e){return!!this.elements[e]},t.Set.prototype.intersect=function(e){var r,n,i,s=[];if(e===t.Set.complete)return this;if(e===t.Set.empty)return e;this.length<e.length?(r=this,n=e):(r=e,n=this),i=Object.keys(r.elements);for(var o=0;o<i.length;o++){var a=i[o];a in n.elements&&s.push(a)}return new t.Set(s)},t.Set.prototype.union=function(e){return e===t.Set.complete?t.Set.complete:e===t.Set.empty?this:new t.Set(Object.keys(this.elements).concat(Object.keys(e.elements)))},t.idf=function(e,r){var n=0;for(var i in e)i!="_index"&&(n+=Object.keys(e[i]).length);var s=(r-n+.5)/(n+.5);return Math.log(1+Math.abs(s))},t.Token=function(e,r){this.str=e||"",this.metadata=r||{}},t.Token.prototype.toString=function(){return this.str},t.Token.prototype.update=function(e){return this.str=e(this.str,this.metadata),this},t.Token.prototype.clone=function(e){return e=e||function(r){return r},new t.Token(e(this.str,this.metadata),this.metadata)};/*!
+ * lunr.tokenizer
+ * Copyright (C) 2020 Oliver Nightingale
+ */t.tokenizer=function(e,r){if(e==null||e==null)return[];if(Array.isArray(e))return e.map(function(g){return new t.Token(t.utils.asString(g).toLowerCase(),t.utils.clone(r))});for(var n=e.toString().toLowerCase(),i=n.length,s=[],o=0,a=0;o<=i;o++){var u=n.charAt(o),c=o-a;if(u.match(t.tokenizer.separator)||o==i){if(c>0){var f=t.utils.clone(r)||{};f.position=[a,c],f.index=s.length,s.push(new t.Token(n.slice(a,o),f))}a=o+1}}return s},t.tokenizer.separator=/[\s\-]+/;/*!
+ * lunr.Pipeline
+ * Copyright (C) 2020 Oliver Nightingale
+ */t.Pipeline=function(){this._stack=[]},t.Pipeline.registeredFunctions=Object.create(null),t.Pipeline.registerFunction=function(e,r){r in this.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+r),e.label=r,t.Pipeline.registeredFunctions[e.label]=e},t.Pipeline.warnIfFunctionNotRegistered=function(e){var r=e.label&&e.label in this.registeredFunctions;r||t.utils.warn(`Function is not registered with pipeline. This may cause problems when serialising the index.
+`,e)},t.Pipeline.load=function(e){var r=new t.Pipeline;return e.forEach(function(n){var i=t.Pipeline.registeredFunctions[n];if(i)r.add(i);else throw new Error("Cannot load unregistered function: "+n)}),r},t.Pipeline.prototype.add=function(){var e=Array.prototype.slice.call(arguments);e.forEach(function(r){t.Pipeline.warnIfFunctionNotRegistered(r),this._stack.push(r)},this)},t.Pipeline.prototype.after=function(e,r){t.Pipeline.warnIfFunctionNotRegistered(r);var n=this._stack.indexOf(e);if(n==-1)throw new Error("Cannot find existingFn");n=n+1,this._stack.splice(n,0,r)},t.Pipeline.prototype.before=function(e,r){t.Pipeline.warnIfFunctionNotRegistered(r);var n=this._stack.indexOf(e);if(n==-1)throw new Error("Cannot find existingFn");this._stack.splice(n,0,r)},t.Pipeline.prototype.remove=function(e){var r=this._stack.indexOf(e);r!=-1&&this._stack.splice(r,1)},t.Pipeline.prototype.run=function(e){for(var r=this._stack.length,n=0;n<r;n++){for(var i=this._stack[n],s=[],o=0;o<e.length;o++){var a=i(e[o],o,e);if(!(a==null||a===""))if(Array.isArray(a))for(var u=0;u<a.length;u++)s.push(a[u]);else s.push(a)}e=s}return e},t.Pipeline.prototype.runString=function(e,r){var n=new t.Token(e,r);return this.run([n]).map(function(i){return i.toString()})},t.Pipeline.prototype.reset=function(){this._stack=[]},t.Pipeline.prototype.toJSON=function(){return this._stack.map(function(e){return t.Pipeline.warnIfFunctionNotRegistered(e),e.label})};/*!
+ * lunr.Vector
+ * Copyright (C) 2020 Oliver Nightingale
+ */t.Vector=function(e){this._magnitude=0,this.elements=e||[]},t.Vector.prototype.positionForIndex=function(e){if(this.elements.length==0)return 0;for(var r=0,n=this.elements.length/2,i=n-r,s=Math.floor(i/2),o=this.elements[s*2];i>1&&(o<e&&(r=s),o>e&&(n=s),o!=e);)i=n-r,s=r+Math.floor(i/2),o=this.elements[s*2];if(o==e||o>e)return s*2;if(o<e)return(s+1)*2},t.Vector.prototype.insert=function(e,r){this.upsert(e,r,function(){throw"duplicate index"})},t.Vector.prototype.upsert=function(e,r,n){this._magnitude=0;var i=this.positionForIndex(e);this.elements[i]==e?this.elements[i+1]=n(this.elements[i+1],r):this.elements.splice(i,0,e,r)},t.Vector.prototype.magnitude=function(){if(this._magnitude)return this._magnitude;for(var e=0,r=this.elements.length,n=1;n<r;n+=2){var i=this.elements[n];e+=i*i}return this._magnitude=Math.sqrt(e)},t.Vector.prototype.dot=function(e){for(var r=0,n=this.elements,i=e.elements,s=n.length,o=i.length,a=0,u=0,c=0,f=0;c<s&&f<o;)a=n[c],u=i[f],a<u?c+=2:a>u?f+=2:a==u&&(r+=n[c+1]*i[f+1],c+=2,f+=2);return r},t.Vector.prototype.similarity=function(e){return this.dot(e)/this.magnitude()||0},t.Vector.prototype.toArray=function(){for(var e=new Array(this.elements.length/2),r=1,n=0;r<this.elements.length;r+=2,n++)e[n]=this.elements[r];return e},t.Vector.prototype.toJSON=function(){return this.elements};/*!
+ * lunr.stemmer
+ * Copyright (C) 2020 Oliver Nightingale
+ * Includes code from - http://tartarus.org/~martin/PorterStemmer/js.txt
+ */t.stemmer=function(){var e={ational:"ate",tional:"tion",enci:"ence",anci:"ance",izer:"ize",bli:"ble",alli:"al",entli:"ent",eli:"e",ousli:"ous",ization:"ize",ation:"ate",ator:"ate",alism:"al",iveness:"ive",fulness:"ful",ousness:"ous",aliti:"al",iviti:"ive",biliti:"ble",logi:"log"},r={icate:"ic",ative:"",alize:"al",iciti:"ic",ical:"ic",ful:"",ness:""},n="[^aeiou]",i="[aeiouy]",s=n+"[^aeiouy]*",o=i+"[aeiou]*",a="^("+s+")?"+o+s,u="^("+s+")?"+o+s+"("+o+")?$",c="^("+s+")?"+o+s+o+s,f="^("+s+")?"+i,g=new RegExp(a),l=new RegExp(c),m=new RegExp(u),x=new RegExp(f),v=/^(.+?)(ss|i)es$/,d=/^(.+?)([^s])s$/,y=/^(.+?)eed$/,b=/^(.+?)(ed|ing)$/,E=/.$/,w=/(at|bl|iz)$/,R=new RegExp("([^aeiouylsz])\\1$"),j=new RegExp("^"+s+i+"[^aeiouwxy]$"),_=/^(.+?[^aeiou])y$/,D=/^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/,N=/^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/,C=/^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/,V=/^(.+?)(s|t)(ion)$/,P=/^(.+?)e$/,z=/ll$/,$=new RegExp("^"+s+i+"[^aeiouwxy]$"),M=function(h){var S,k,L,p,T,O,F;if(h.length<3)return h;if(L=h.substr(0,1),L=="y"&&(h=L.toUpperCase()+h.substr(1)),p=v,T=d,p.test(h)?h=h.replace(p,"$1$2"):T.test(h)&&(h=h.replace(T,"$1$2")),p=y,T=b,p.test(h)){var Q=p.exec(h);p=g,p.test(Q[1])&&(p=E,h=h.replace(p,""))}else if(T.test(h)){var Q=T.exec(h);S=Q[1],T=x,T.test(S)&&(h=S,T=w,O=R,F=j,T.test(h)?h=h+"e":O.test(h)?(p=E,h=h.replace(p,"")):F.test(h)&&(h=h+"e"))}if(p=_,p.test(h)){var Q=p.exec(h);S=Q[1],h=S+"i"}if(p=D,p.test(h)){var Q=p.exec(h);S=Q[1],k=Q[2],p=g,p.test(S)&&(h=S+e[k])}if(p=N,p.test(h)){var Q=p.exec(h);S=Q[1],k=Q[2],p=g,p.test(S)&&(h=S+r[k])}if(p=C,T=V,p.test(h)){var Q=p.exec(h);S=Q[1],p=l,p.test(S)&&(h=S)}else if(T.test(h)){var Q=T.exec(h);S=Q[1]+Q[2],T=l,T.test(S)&&(h=S)}if(p=P,p.test(h)){var Q=p.exec(h);S=Q[1],p=l,T=m,O=$,(p.test(S)||T.test(S)&&!O.test(S))&&(h=S)}return p=z,T=l,p.test(h)&&T.test(h)&&(p=E,h=h.replace(p,"")),L=="y"&&(h=L.toLowerCase()+h.substr(1)),h};return function(I){return I.update(M)}}(),t.Pipeline.registerFunction(t.stemmer,"stemmer");/*!
+ * lunr.stopWordFilter
+ * Copyright (C) 2020 Oliver Nightingale
+ */t.generateStopWordFilter=function(e){var r=e.reduce(function(n,i){return n[i]=i,n},{});return function(n){if(n&&r[n.toString()]!==n.toString())return n}},t.stopWordFilter=t.generateStopWordFilter(["a","able","about","across","after","all","almost","also","am","among","an","and","any","are","as","at","be","because","been","but","by","can","cannot","could","dear","did","do","does","either","else","ever","every","for","from","get","got","had","has","have","he","her","hers","him","his","how","however","i","if","in","into","is","it","its","just","least","let","like","likely","may","me","might","most","must","my","neither","no","nor","not","of","off","often","on","only","or","other","our","own","rather","said","say","says","she","should","since","so","some","than","that","the","their","them","then","there","these","they","this","tis","to","too","twas","us","wants","was","we","were","what","when","where","which","while","who","whom","why","will","with","would","yet","you","your"]),t.Pipeline.registerFunction(t.stopWordFilter,"stopWordFilter");/*!
+ * lunr.trimmer
+ * Copyright (C) 2020 Oliver Nightingale
+ */t.trimmer=function(e){return e.update(function(r){return r.replace(/^\W+/,"").replace(/\W+$/,"")})},t.Pipeline.registerFunction(t.trimmer,"trimmer");/*!
+ * lunr.TokenSet
+ * Copyright (C) 2020 Oliver Nightingale
+ */t.TokenSet=function(){this.final=!1,this.edges={},this.id=t.TokenSet._nextId,t.TokenSet._nextId+=1},t.TokenSet._nextId=1,t.TokenSet.fromArray=function(e){for(var r=new t.TokenSet.Builder,n=0,i=e.length;n<i;n++)r.insert(e[n]);return r.finish(),r.root},t.TokenSet.fromClause=function(e){return"editDistance"in e?t.TokenSet.fromFuzzyString(e.term,e.editDistance):t.TokenSet.fromString(e.term)},t.TokenSet.fromFuzzyString=function(e,r){for(var n=new t.TokenSet,i=[{node:n,editsRemaining:r,str:e}];i.length;){var s=i.pop();if(s.str.length>0){var o=s.str.charAt(0),a;o in s.node.edges?a=s.node.edges[o]:(a=new t.TokenSet,s.node.edges[o]=a),s.str.length==1&&(a.final=!0),i.push({node:a,editsRemaining:s.editsRemaining,str:s.str.slice(1)})}if(s.editsRemaining!=0){if("*"in s.node.edges)var u=s.node.edges["*"];else{var u=new t.TokenSet;s.node.edges["*"]=u}if(s.str.length==0&&(u.final=!0),i.push({node:u,editsRemaining:s.editsRemaining-1,str:s.str}),s.str.length>1&&i.push({node:s.node,editsRemaining:s.editsRemaining-1,str:s.str.slice(1)}),s.str.length==1&&(s.node.final=!0),s.str.length>=1){if("*"in s.node.edges)var c=s.node.edges["*"];else{var c=new t.TokenSet;s.node.edges["*"]=c}s.str.length==1&&(c.final=!0),i.push({node:c,editsRemaining:s.editsRemaining-1,str:s.str.slice(1)})}if(s.str.length>1){var f=s.str.charAt(0),g=s.str.charAt(1),l;g in s.node.edges?l=s.node.edges[g]:(l=new t.TokenSet,s.node.edges[g]=l),s.str.length==1&&(l.final=!0),i.push({node:l,editsRemaining:s.editsRemaining-1,str:f+s.str.slice(2)})}}}return n},t.TokenSet.fromString=function(e){for(var r=new t.TokenSet,n=r,i=0,s=e.length;i<s;i++){var o=e[i],a=i==s-1;if(o=="*")r.edges[o]=r,r.final=a;else{var u=new t.TokenSet;u.final=a,r.edges[o]=u,r=u}}return n},t.TokenSet.prototype.toArray=function(){for(var e=[],r=[{prefix:"",node:this}];r.length;){var n=r.pop(),i=Object.keys(n.node.edges),s=i.length;n.node.final&&(n.prefix.charAt(0),e.push(n.prefix));for(var o=0;o<s;o++){var a=i[o];r.push({prefix:n.prefix.concat(a),node:n.node.edges[a]})}}return e},t.TokenSet.prototype.toString=function(){if(this._str)return this._str;for(var e=this.final?"1":"0",r=Object.keys(this.edges).sort(),n=r.length,i=0;i<n;i++){var s=r[i],o=this.edges[s];e=e+s+o.id}return e},t.TokenSet.prototype.intersect=function(e){for(var r=new t.TokenSet,n=void 0,i=[{qNode:e,output:r,node:this}];i.length;){n=i.pop();for(var s=Object.keys(n.qNode.edges),o=s.length,a=Object.keys(n.node.edges),u=a.length,c=0;c<o;c++)for(var f=s[c],g=0;g<u;g++){var l=a[g];if(l==f||f=="*"){var m=n.node.edges[l],x=n.qNode.edges[f],v=m.final&&x.final,d=void 0;l in n.output.edges?(d=n.output.edges[l],d.final=d.final||v):(d=new t.TokenSet,d.final=v,n.output.edges[l]=d),i.push({qNode:x,output:d,node:m})}}}return r},t.TokenSet.Builder=function(){this.previousWord="",this.root=new t.TokenSet,this.uncheckedNodes=[],this.minimizedNodes={}},t.TokenSet.Builder.prototype.insert=function(e){var r,n=0;if(e<this.previousWord)throw new Error("Out of order word insertion");for(var i=0;i<e.length&&i<this.previousWord.length&&e[i]==this.previousWord[i];i++)n++;this.minimize(n),this.uncheckedNodes.length==0?r=this.root:r=this.uncheckedNodes[this.uncheckedNodes.length-1].child;for(var i=n;i<e.length;i++){var s=new t.TokenSet,o=e[i];r.edges[o]=s,this.uncheckedNodes.push({parent:r,char:o,child:s}),r=s}r.final=!0,this.previousWord=e},t.TokenSet.Builder.prototype.finish=function(){this.minimize(0)},t.TokenSet.Builder.prototype.minimize=function(e){for(var r=this.uncheckedNodes.length-1;r>=e;r--){var n=this.uncheckedNodes[r],i=n.child.toString();i in this.minimizedNodes?n.parent.edges[n.char]=this.minimizedNodes[i]:(n.child._str=i,this.minimizedNodes[i]=n.child),this.uncheckedNodes.pop()}};/*!
+ * lunr.Index
+ * Copyright (C) 2020 Oliver Nightingale
+ */t.Index=function(e){this.invertedIndex=e.invertedIndex,this.fieldVectors=e.fieldVectors,this.tokenSet=e.tokenSet,this.fields=e.fields,this.pipeline=e.pipeline},t.Index.prototype.search=function(e){return this.query(function(r){var n=new t.QueryParser(e,r);n.parse()})},t.Index.prototype.query=function(e){for(var r=new t.Query(this.fields),n=Object.create(null),i=Object.create(null),s=Object.create(null),o=Object.create(null),a=Object.create(null),u=0;u<this.fields.length;u++)i[this.fields[u]]=new t.Vector;e.call(r,r);for(var u=0;u<r.clauses.length;u++){var c=r.clauses[u],f=null,g=t.Set.empty;c.usePipeline?f=this.pipeline.runString(c.term,{fields:c.fields}):f=[c.term];for(var l=0;l<f.length;l++){var m=f[l];c.term=m;var x=t.TokenSet.fromClause(c),v=this.tokenSet.intersect(x).toArray();if(v.length===0&&c.presence===t.Query.presence.REQUIRED){for(var d=0;d<c.fields.length;d++){var y=c.fields[d];o[y]=t.Set.empty}break}for(var b=0;b<v.length;b++)for(var E=v[b],w=this.invertedIndex[E],R=w._index,d=0;d<c.fields.length;d++){var y=c.fields[d],j=w[y],_=Object.keys(j),D=E+"/"+y,N=new t.Set(_);if(c.presence==t.Query.presence.REQUIRED&&(g=g.union(N),o[y]===void 0&&(o[y]=t.Set.complete)),c.presence==t.Query.presence.PROHIBITED){a[y]===void 0&&(a[y]=t.Set.empty),a[y]=a[y].union(N);continue}if(i[y].upsert(R,c.boost,function(ye,me){return ye+me}),!s[D]){for(var C=0;C<_.length;C++){var V=_[C],P=new t.FieldRef(V,y),z=j[V],$;($=n[P])===void 0?n[P]=new t.MatchData(E,y,z):$.add(E,y,z)}s[D]=!0}}}if(c.presence===t.Query.presence.REQUIRED)for(var d=0;d<c.fields.length;d++){var y=c.fields[d];o[y]=o[y].intersect(g)}}for(var M=t.Set.complete,I=t.Set.empty,u=0;u<this.fields.length;u++){var y=this.fields[u];o[y]&&(M=M.intersect(o[y])),a[y]&&(I=I.union(a[y]))}var h=Object.keys(n),S=[],k=Object.create(null);if(r.isNegated()){h=Object.keys(this.fieldVectors);for(var u=0;u<h.length;u++){var P=h[u],L=t.FieldRef.fromString(P);n[P]=new t.MatchData}}for(var u=0;u<h.length;u++){var L=t.FieldRef.fromString(h[u]),p=L.docRef;if(M.contains(p)&&!I.contains(p)){var T=this.fieldVectors[L],O=i[L.fieldName].similarity(T),F;if((F=k[p])!==void 0)F.score+=O,F.matchData.combine(n[L]);else{var Q={ref:p,score:O,matchData:n[L]};k[p]=Q,S.push(Q)}}}return S.sort(function(pe,ge){return ge.score-pe.score})},t.Index.prototype.toJSON=function(){var e=Object.keys(this.invertedIndex).sort().map(function(n){return[n,this.invertedIndex[n]]},this),r=Object.keys(this.fieldVectors).map(function(n){return[n,this.fieldVectors[n].toJSON()]},this);return{version:t.version,fields:this.fields,fieldVectors:r,invertedIndex:e,pipeline:this.pipeline.toJSON()}},t.Index.load=function(e){var r={},n={},i=e.fieldVectors,s=Object.create(null),o=e.invertedIndex,a=new t.TokenSet.Builder,u=t.Pipeline.load(e.pipeline);e.version!=t.version&&t.utils.warn("Version mismatch when loading serialised index. Current version of lunr '"+t.version+"' does not match serialized index '"+e.version+"'");for(var c=0;c<i.length;c++){var f=i[c],g=f[0],l=f[1];n[g]=new t.Vector(l)}for(var c=0;c<o.length;c++){var f=o[c],m=f[0],x=f[1];a.insert(m),s[m]=x}return a.finish(),r.fields=e.fields,r.fieldVectors=n,r.invertedIndex=s,r.tokenSet=a.root,r.pipeline=u,new t.Index(r)};/*!
+ * lunr.Builder
+ * Copyright (C) 2020 Oliver Nightingale
+ */t.Builder=function(){this._ref="id",this._fields=Object.create(null),this._documents=Object.create(null),this.invertedIndex=Object.create(null),this.fieldTermFrequencies={},this.fieldLengths={},this.tokenizer=t.tokenizer,this.pipeline=new t.Pipeline,this.searchPipeline=new t.Pipeline,this.documentCount=0,this._b=.75,this._k1=1.2,this.termIndex=0,this.metadataWhitelist=[]},t.Builder.prototype.ref=function(e){this._ref=e},t.Builder.prototype.field=function(e,r){if(/\//.test(e))throw new RangeError("Field '"+e+"' contains illegal character '/'");this._fields[e]=r||{}},t.Builder.prototype.b=function(e){e<0?this._b=0:e>1?this._b=1:this._b=e},t.Builder.prototype.k1=function(e){this._k1=e},t.Builder.prototype.add=function(e,r){var n=e[this._ref],i=Object.keys(this._fields);this._documents[n]=r||{},this.documentCount+=1;for(var s=0;s<i.length;s++){var o=i[s],a=this._fields[o].extractor,u=a?a(e):e[o],c=this.tokenizer(u,{fields:[o]}),f=this.pipeline.run(c),g=new t.FieldRef(n,o),l=Object.create(null);this.fieldTermFrequencies[g]=l,this.fieldLengths[g]=0,this.fieldLengths[g]+=f.length;for(var m=0;m<f.length;m++){var x=f[m];if(l[x]==null&&(l[x]=0),l[x]+=1,this.invertedIndex[x]==null){var v=Object.create(null);v._index=this.termIndex,this.termIndex+=1;for(var d=0;d<i.length;d++)v[i[d]]=Object.create(null);this.invertedIndex[x]=v}this.invertedIndex[x][o][n]==null&&(this.invertedIndex[x][o][n]=Object.create(null));for(var y=0;y<this.metadataWhitelist.length;y++){var b=this.metadataWhitelist[y],E=x.metadata[b];this.invertedIndex[x][o][n][b]==null&&(this.invertedIndex[x][o][n][b]=[]),this.invertedIndex[x][o][n][b].push(E)}}}},t.Builder.prototype.calculateAverageFieldLengths=function(){for(var e=Object.keys(this.fieldLengths),r=e.length,n={},i={},s=0;s<r;s++){var o=t.FieldRef.fromString(e[s]),a=o.fieldName;i[a]||(i[a]=0),i[a]+=1,n[a]||(n[a]=0),n[a]+=this.fieldLengths[o]}for(var u=Object.keys(this._fields),s=0;s<u.length;s++){var c=u[s];n[c]=n[c]/i[c]}this.averageFieldLength=n},t.Builder.prototype.createFieldVectors=function(){for(var e={},r=Object.keys(this.fieldTermFrequencies),n=r.length,i=Object.create(null),s=0;s<n;s++){for(var o=t.FieldRef.fromString(r[s]),a=o.fieldName,u=this.fieldLengths[o],c=new t.Vector,f=this.fieldTermFrequencies[o],g=Object.keys(f),l=g.length,m=this._fields[a].boost||1,x=this._documents[o.docRef].boost||1,v=0;v<l;v++){var d=g[v],y=f[d],b=this.invertedIndex[d]._index,E,w,R;i[d]===void 0?(E=t.idf(this.invertedIndex[d],this.documentCount),i[d]=E):E=i[d],w=E*((this._k1+1)*y)/(this._k1*(1-this._b+this._b*(u/this.averageFieldLength[a]))+y),w*=m,w*=x,R=Math.round(w*1e3)/1e3,c.insert(b,R)}e[o]=c}this.fieldVectors=e},t.Builder.prototype.createTokenSet=function(){this.tokenSet=t.TokenSet.fromArray(Object.keys(this.invertedIndex).sort())},t.Builder.prototype.build=function(){return this.calculateAverageFieldLengths(),this.createFieldVectors(),this.createTokenSet(),new t.Index({invertedIndex:this.invertedIndex,fieldVectors:this.fieldVectors,tokenSet:this.tokenSet,fields:Object.keys(this._fields),pipeline:this.searchPipeline})},t.Builder.prototype.use=function(e){var r=Array.prototype.slice.call(arguments,1);r.unshift(this),e.apply(this,r)},t.MatchData=function(e,r,n){for(var i=Object.create(null),s=Object.keys(n||{}),o=0;o<s.length;o++){var a=s[o];i[a]=n[a].slice()}this.metadata=Object.create(null),e!==void 0&&(this.metadata[e]=Object.create(null),this.metadata[e][r]=i)},t.MatchData.prototype.combine=function(e){for(var r=Object.keys(e.metadata),n=0;n<r.length;n++){var i=r[n],s=Object.keys(e.metadata[i]);this.metadata[i]==null&&(this.metadata[i]=Object.create(null));for(var o=0;o<s.length;o++){var a=s[o],u=Object.keys(e.metadata[i][a]);this.metadata[i][a]==null&&(this.metadata[i][a]=Object.create(null));for(var c=0;c<u.length;c++){var f=u[c];this.metadata[i][a][f]==null?this.metadata[i][a][f]=e.metadata[i][a][f]:this.metadata[i][a][f]=this.metadata[i][a][f].concat(e.metadata[i][a][f])}}}},t.MatchData.prototype.add=function(e,r,n){if(!(e in this.metadata)){this.metadata[e]=Object.create(null),this.metadata[e][r]=n;return}if(!(r in this.metadata[e])){this.metadata[e][r]=n;return}for(var i=Object.keys(n),s=0;s<i.length;s++){var o=i[s];o in this.metadata[e][r]?this.metadata[e][r][o]=this.metadata[e][r][o].concat(n[o]):this.metadata[e][r][o]=n[o]}},t.Query=function(e){this.clauses=[],this.allFields=e},t.Query.wildcard=new String("*"),t.Query.wildcard.NONE=0,t.Query.wildcard.LEADING=1,t.Query.wildcard.TRAILING=2,t.Query.presence={OPTIONAL:1,REQUIRED:2,PROHIBITED:3},t.Query.prototype.clause=function(e){return"fields"in e||(e.fields=this.allFields),"boost"in e||(e.boost=1),"usePipeline"in e||(e.usePipeline=!0),"wildcard"in e||(e.wildcard=t.Query.wildcard.NONE),e.wildcard&t.Query.wildcard.LEADING&&e.term.charAt(0)!=t.Query.wildcard&&(e.term="*"+e.term),e.wildcard&t.Query.wildcard.TRAILING&&e.term.slice(-1)!=t.Query.wildcard&&(e.term=""+e.term+"*"),"presence"in e||(e.presence=t.Query.presence.OPTIONAL),this.clauses.
Line truncated
+//# sourceMappingURL=search.d50fe291.min.js.map
+

assets/javascripts/workers/search.d50fe291.min.js.map

@@ -0,0 +1,7 @@
+{
+  "version": 3,
+  "sources": ["node_modules/lunr/lunr.js", "src/templates/assets/javascripts/integrations/search/worker/main/index.ts", "src/templates/assets/javascripts/browser/element/_/index.ts", "src/templates/assets/javascripts/polyfills/index.ts", "src/templates/assets/javascripts/integrations/search/config/index.ts", "src/templates/assets/javascripts/integrations/search/internal/_/index.ts", "src/templates/assets/javascripts/integrations/search/internal/extract/index.ts", "src/templates/assets/javascripts/integrations/search/internal/highlight/index.ts", "src/templates/assets/javascripts/integrations/search/internal/tokenize/index.ts", "src/templates/assets/javascripts/integrations/search/query/transform/index.ts", "src/templates/assets/javascripts/integrations/search/query/_/index.ts", "src/templates/assets/javascripts/integrations/search/query/segment/index.ts", "src/templates/assets/javascripts/integrations/search/_/index.ts"],
+  "sourcesContent": ["/**\n * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.9\n * Copyright (C) 2020 Oliver Nightingale\n * @license MIT\n */\n\n;(function(){\n\n/**\n * A convenience function for configuring and constructing\n * a new lunr Index.\n *\n * A lunr.Builder instance is created and the pipeline setup\n * with a trimmer, stop word filter and stemmer.\n *\n * This builder object is yielded to the configuration function\n * that is passed as a parameter, allowing the list of fields\n * and other builder parameters to be customised.\n *\n * All documents _must_ be added within the passed config function.\n *\n * @example\n * var idx = lunr(function () {\n *   this.field('title')\n *   this.field('body')\n *   this.ref('id')\n *\n *   documents.forEach(function (doc) {\n *     this.add(doc)\n *   }, this)\n * })\n *\n * @see {@link lunr.Builder}\n * @see {@link lunr.Pipeline}\n * @see {@link lunr.trimmer}\n * @see {@link lunr.stopWordFilter}\n * @see {@link lunr.stemmer}\n * @namespace {function} lunr\n */\nvar lunr = function (config) {\n  var builder = new lunr.Builder\n\n  builder.pipeline.add(\n    lunr.trimmer,\n    lunr.stopWordFilter,\n    lunr.stemmer\n  )\n\n  builder.searchPipeline.add(\n    lunr.stemmer\n  )\n\n  config.call(builder, builder)\n  return builder.build()\n}\n\nlunr.version = \"2.3.9\"\n/*!\n * lunr.utils\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A namespace containing utils for the rest of the lunr library\n * @namespace lunr.utils\n */\nlunr.utils = {}\n\n/**\n * Print a warning message to the console.\n *\n * @param {String} message The message to be printed.\n * @memberOf lunr.utils\n * @function\n */\nlunr.utils.warn = (function (global) {\n  /* eslint-disable no-console */\n  return function (message) {\n    if (global.console && console.warn) {\n      console.warn(message)\n    }\n  }\n  /* eslint-enable no-console */\n})(this)\n\n/**\n * Convert an object to a string.\n *\n * In the case of `null` and `undefined` the function returns\n * the empty string, in all other cases the result of calling\n * `toString` on the passed object is returned.\n *\n * @param {Any} obj The object to convert to a string.\n * @return {String} string representation of the passed object.\n * @memberOf lunr.utils\n */\nlunr.utils.asString = function (obj) {\n  if (obj === void 0 || obj === null) {\n    return \"\"\n  } else {\n    return obj.toString()\n  }\n}\n\n/**\n * Clones an object.\n *\n * Will create a copy of an existing object such that any mutations\n * on the copy cannot affect the original.\n *\n * Only shallow objects are supported, passing a nested object to this\n * function will cause a TypeError.\n *\n * Objects with primitives, and arrays of primitives are supported.\n *\n * @param {Object} obj The object to clone.\n * @return {Object} a clone of the passed object.\n * @throws {TypeError} when a nested object is passed.\n * @memberOf Utils\n */\nlunr.utils.clone = function (obj) {\n  if (obj === null || obj === undefined) {\n    return obj\n  }\n\n  var clone = Object.create(null),\n      keys = Object.keys(obj)\n\n  for (var i = 0; i < keys.length; i++) {\n    var key = keys[i],\n        val = obj[key]\n\n    if (Array.isArray(val)) {\n      clone[key] = val.slice()\n      continue\n    }\n\n    if (typeof val === 'string' ||\n        typeof val === 'number' ||\n        typeof val === 'boolean') {\n      clone[key] = val\n      continue\n    }\n\n    throw new TypeError(\"clone is not deep and does not support nested objects\")\n  }\n\n  return clone\n}\nlunr.FieldRef = function (docRef, fieldName, stringValue) {\n  this.docRef = docRef\n  this.fieldName = fieldName\n  this._stringValue = stringValue\n}\n\nlunr.FieldRef.joiner = \"/\"\n\nlunr.FieldRef.fromString = function (s) {\n  var n = s.indexOf(lunr.FieldRef.joiner)\n\n  if (n === -1) {\n    throw \"malformed field ref string\"\n  }\n\n  var fieldRef = s.slice(0, n),\n      docRef = s.slice(n + 1)\n\n  return new lunr.FieldRef (docRef, fieldRef, s)\n}\n\nlunr.FieldRef.prototype.toString = function () {\n  if (this._stringValue == undefined) {\n    this._stringValue = this.fieldName + lunr.FieldRef.joiner + this.docRef\n  }\n\n  return this._stringValue\n}\n/*!\n * lunr.Set\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A lunr set.\n *\n * @constructor\n */\nlunr.Set = function (elements) {\n  this.elements = Object.create(null)\n\n  if (elements) {\n    this.length = elements.length\n\n    for (var i = 0; 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changelog.mdx

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+---
+title: Changelog
+description: View the latest updates and changes to CrewAI
+icon: timeline
+---
+
+<Update label="2024-05-22" description="v0.121.0" tags={["Latest"]}>
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01210.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.121.0">View on GitHub</a>
+  </div>
+
+  **Core Improvements & Fixes**
+  - Fixed encoding error when creating tools
+  - Fixed failing llama test
+  - Updated logging configuration for consistency
+  - Enhanced telemetry initialization and event handling
+
+  **New Features & Enhancements**
+  - Added **markdown attribute** to the Task class
+  - Added **reasoning attribute** to the Agent class
+  - Added **inject_date flag** to Agent for automatic date injection
+  - Implemented **HallucinationGuardrail** (no-op with test coverage)
+
+  **Documentation & Guides**
+  - Added documentation for **StagehandTool** and improved MDX structure
+  - Added documentation for **MCP integration** and updated enterprise docs
+  - Documented knowledge events and updated reasoning docs
+  - Added stop parameter documentation
+  - Fixed import references in doc examples (before_kickoff, after_kickoff)
+  - General docs updates and restructuring for clarity
+</Update>
+
+<Update label="2024-05-15" description="v0.120.1">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01201.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.120.1">View on GitHub</a>
+  </div>
+
+  **Core Improvements & Fixes**
+  - Fixed **interpolation with hyphens**
+</Update>
+
+<Update label="2024-05-14" description="v0.120.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01200.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.120.0">View on GitHub</a>
+  </div>
+
+  **Core Improvements & Fixes**
+  - Enabled **full Ruff rule set** by default for stricter linting
+  - Addressed race condition in FilteredStream using context managers
+  - Fixed agent knowledge reset issue
+  - Refactored agent fetching logic into utility module
+
+  **New Features & Enhancements**
+  - Added support for **loading an Agent directly from a repository**
+  - Enabled setting an empty context for Task
+  - Enhanced Agent repository feedback and fixed Tool auto-import behavior
+  - Introduced direct initialization of knowledge (bypassing knowledge_sources)
+
+  **Documentation & Guides**
+  - Updated security.md for current security practices
+  - Cleaned up Google setup section for clarity
+  - Added link to AI Studio when entering Gemini key
+  - Updated Arize Phoenix observability guide
+  - Refreshed flow documentation
+</Update>
+
+<Update label="2024-05-08" description="v0.119.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01190.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.119.0">View on GitHub</a>
+  </div>
+
+  **Core Improvements & Fixes**
+  - Improved test reliability by enhancing pytest handling for flaky tests
+  - Fixed memory reset crash when embedding dimensions mismatch
+  - Enabled parent flow identification for Crew and LiteAgent
+  - Prevented telemetry-related crashes when unavailable
+  - Upgraded **LiteLLM version** for better compatibility
+  - Fixed llama converter tests by removing skip_external_api
+
+  **New Features & Enhancements**
+  - Introduced **knowledge retrieval prompt re-writing** in Agent for improved tracking and debugging
+  - Made LLM setup and quickstart guides model-agnostic
+
+  **Documentation & Guides**
+  - Added advanced configuration docs for the RAG tool
+  - Updated Windows troubleshooting guide
+  - Refined documentation examples for better clarity
+  - Fixed typos across docs and config files
+</Update>
+
+<Update label="2024-04-28" description="v0.118.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01180.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.118.0">View on GitHub</a>
+  </div>
+
+  **Core Improvements & Fixes**
+  - Fixed issues with missing prompt or system templates
+  - Removed global logging configuration to avoid unintended overrides
+  - Renamed **TaskGuardrail to LLMGuardrail** for improved clarity
+  - Downgraded litellm to version 1.167.1 for compatibility
+  - Added missing init.py files to ensure proper module initialization
+
+  **New Features & Enhancements**
+  - Added support for **no-code Guardrail creation** to simplify AI behavior controls
+
+  **Documentation & Guides**
+  - Removed CrewStructuredTool from public documentation to reflect internal usage
+  - Updated enterprise documentation and YouTube embed for improved onboarding experience
+</Update>
+
+<Update label="2024-04-20" description="v0.117.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01170.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.117.0">View on GitHub</a>
+  </div>
+
+  **New Features & Enhancements**
+  - Added `result_as_answer` parameter support in `@tool` decorator.
+  - Introduced support for new language models: GPT-4.1, Gemini-2.0, and Gemini-2.5 Pro.
+  - Enhanced knowledge management capabilities.
+  - Added Huggingface provider option in CLI.
+  - Improved compatibility and CI support for Python 3.10+.
+
+  **Core Improvements & Fixes**
+  - Fixed issues with incorrect template parameters and missing inputs.
+  - Improved asynchronous flow handling with coroutine condition checks.
+  - Enhanced memory management with isolated configuration and correct memory object copying.
+  - Fixed initialization of lite agents with correct references.
+  - Addressed Python type hint issues and removed redundant imports.
+  - Updated event placement for improved tool usage tracking.
+  - Raised explicit exceptions when flows fail.
+  - Removed unused code and redundant comments from various modules.
+  - Updated GitHub App token action to v2.
+
+  **Documentation & Guides**
+  - Enhanced documentation structure, including enterprise deployment instructions.
+  - Automatically create output folders for documentation generation.
+  - Fixed broken link in WeaviateVectorSearchTool documentation.
+  - Fixed guardrail documentation usage and import paths for JSON search tools.
+  - Updated documentation for CodeInterpreterTool.
+  - Improved SEO, contextual navigation, and error handling for documentation pages.
+</Update>
+
+<Update label="2024-04-25" description="v0.117.1">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01171.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.117.1">View on GitHub</a>
+  </div>
+
+  **Core Improvements & Fixes**
+  - Upgraded **crewai-tools** to latest version
+  - Upgraded **liteLLM** to latest version
+  - Fixed **Mem0 OSS**
+</Update>
+
+<Update label="2024-04-07" description="v0.114.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01140.png" />
+  </Frame>
+
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.114.0">View on GitHub</a>
+  </div>
+
+  **New Features & Enhancements**
+  - Agents as an atomic unit. (`Agent(...).kickoff()`)
+  - Support for [Custom LLM implementations](https://docs.crewai.com/guides/advanced/custom-llm).
+  - Integrated External Memory and [Opik observability](https://docs.crewai.com/how-to/opik-observability).
+  - Enhanced YAML extraction.
+  - Multimodal agent validation.
+  - Added Secure fingerprints for agents and crews.
+
+  **Core Improvements & Fixes**
+  - Improved serialization, agent copying, and Python compatibility.
+  - Added wildcard support to `emit()`
+  - Added support for additional router calls and context window adjustments.
+  - Fixed typing issues, validation, and import statements.
+  - Improved method performance.
+  - Enhanced agent task handling, event emissions, and memory management.
+  - Fixed CLI issues, conditional tasks, cloning behavior, and tool outputs.
+
+  **Documentation & Guides**
+  - Improved documentation structure, theme, and organization.
+  - Added guides for Local NVIDIA NIM with WSL2, W&B Weave, and Arize Phoenix.
+  - Updated tool configuration examples, prompts, and observability docs.
+  - Guide on using singular agents within Flows.
+</Update>
+
+<Update label="2024-03-17" description="v0.108.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01080.png" />
+  </Frame>
+
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.108.0">View on GitHub</a>
+  </div>
+
+  **New Features & Enhancements**
+  - Converted tabs to spaces in `crew.py` template
+  - Enhanced LLM Streaming Response Handling and Event System
+  - Included `model_name`
+  - Enhanced Event Listener with rich visualization and improved logging
+  - Added fingerprints
+
+  **Bug Fixes**
+  - Fixed Mistral issues
+  - Fixed a bug in documentation
+  - Fixed type check error in fingerprint property
+
+  **Documentation Updates**
+  - Improved tool documentation
+  - Updated installation guide for the `uv` tool package
+  - Added instructions for upgrading crewAI with the `uv` tool
+  - Added documentation for `ApifyActorsTool`
+</Update>
+
+<Update label="2024-03-10" description="v0.105.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01050.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.105.0">View on GitHub</a>
+  </div>
+
+  **Core Improvements & Fixes**
+  - Fixed issues with missing template variables and user memory configuration
+  - Improved async flow support and addressed agent response formatting
+  - Enhanced memory reset functionality and fixed CLI memory commands
+  - Fixed type issues, tool calling properties, and telemetry decoupling
+
+  **New Features & Enhancements**
+  - Added Flow state export and improved state utilities
+  - Enhanced agent knowledge setup with optional crew embedder
+  - Introduced event emitter for better observability and LLM call tracking
+  - Added support for Python 3.10 and ChatOllama from langchain_ollama
+  - Integrated context window size support for the o3-mini model
+  - Added support for multiple router calls
+
+  **Documentation & Guides**
+  - Improved documentation layout and hierarchical structure
+  - Added QdrantVectorSearchTool guide and clarified event listener usage
+  - Fixed typos in prompts and updated Amazon Bedrock model listings
+</Update>
+
+<Update label="2024-02-12" description="v0.102.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01020.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.102.0">View on GitHub</a>
+  </div>
+
+  **Core Improvements & Fixes**
+  - Enhanced LLM Support: Improved structured LLM output, parameter handling, and formatting for Anthropic models
+  - Crew & Agent Stability: Fixed issues with cloning agents/crews using knowledge sources, multiple task outputs in conditional tasks, and ignored Crew task callbacks
+  - Memory & Storage Fixes: Fixed short-term memory handling with Bedrock, ensured correct embedder initialization, and added a reset memories function in the crew class
+  - Training & Execution Reliability: Fixed broken training and interpolation issues with dict and list input types
+
+  **New Features & Enhancements**
+  - Advanced Knowledge Management: Improved naming conventions and enhanced embedding configuration with custom embedder support
+  - Expanded Logging & Observability: Added JSON format support for logging and integrated MLflow tracing documentation
+  - Data Handling Improvements: Updated excel_knowledge_source.py to process multi-tab files
+  - General Performance & Codebase Clean-Up: Streamlined enterprise code alignment and resolved linting issues
+  - Adding new tool: `QdrantVectorSearchTool`
+
+  **Documentation & Guides**
+  - Updated AI & Memory Docs: Improved Bedrock, Google AI, and long-term memory documentation
+  - Task & Workflow Clarity: Added "Human Input" row to Task Attributes, Langfuse guide, and FileWriterTool documentation
+  - Fixed Various Typos & Formatting Issues
+</Update>
+
+<Update label="2024-01-28" description="v0.100.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v01000.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.100.0">View on GitHub</a>
+  </div>
+
+  **Features**
+  - Add Composio docs
+  - Add SageMaker as a LLM provider
+  
+  **Fixes**
+  - Overall LLM connection issues
+  - Using safe accessors on training
+  - Add version check to crew_chat.py
+  
+  **Documentation**
+  - New docs for crewai chat
+  - Improve formatting and clarity in CLI and Composio Tool docs
+</Update>
+
+<Update label="2024-01-20" description="v0.98.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v0980.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.98.0">View on GitHub</a>
+  </div>
+
+  **Features**
+  - Conversation crew v1
+  - Add unique ID to flow states
+  - Add @persist decorator with FlowPersistence interface
+  
+  **Integrations**
+  - Add SambaNova integration
+  - Add NVIDIA NIM provider in cli
+  - Introducing VoyageAI
+  
+  **Fixes**
+  - Fix API Key Behavior and Entity Handling in Mem0 Integration
+  - Fixed core invoke loop logic and relevant tests
+  - Make tool inputs actual objects and not strings
+  - Add important missing parts to creating tools
+  - Drop litellm version to prevent windows issue
+  - Before kickoff if inputs are none
+  - Fixed typos, nested pydantic model issue, and docling issues
+</Update>
+
+<Update label="2024-01-04" description="v0.95.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v0950.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.95.0">View on GitHub</a>
+  </div>
+
+  **New Features**
+  - Adding Multimodal Abilities to Crew
+  - Programatic Guardrails
+  - HITL multiple rounds
+  - Gemini 2.0 Support
+  - CrewAI Flows Improvements
+  - Add Workflow Permissions
+  - Add support for langfuse with litellm
+  - Portkey Integration with CrewAI
+  - Add interpolate_only method and improve error handling
+  - Docling Support
+  - Weviate Support
+  
+  **Fixes**
+  - output_file not respecting system path
+  - disk I/O error when resetting short-term memory
+  - CrewJSONEncoder now accepts enums
+  - Python max version
+  - Interpolation for output_file in Task
+  - Handle coworker role name case/whitespace properly
+  - Add tiktoken as explicit dependency and document Rust requirement
+  - Include agent knowledge in planning process
+  - Change storage initialization to None for KnowledgeStorage
+  - Fix optional storage checks
+  - include event emitter in flows
+  - Docstring, Error Handling, and Type Hints Improvements
+  - Suppressed userWarnings from litellm pydantic issues
+</Update>
+
+<Update label="2024-12-05" description="v0.86.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v0860.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.86.0">View on GitHub</a>
+  </div>
+  **Changes**
+  - Remove all references to pipeline and pipeline router
+  - Add Nvidia NIM as provider in Custom LLM
+  - Add knowledge demo + improve knowledge docs
+  - Add HITL multiple rounds of followup
+  - New docs about yaml crew with decorators
+  - Simplify template crew
+</Update>
+
+<Update label="2024-12-04" description="v0.85.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/releases/v0850.png" />
+  </Frame>
+  
+  <div style={{ textAlign: 'center', marginBottom: '1rem' }}>
+    <a href="https://github.com/crewAIInc/crewAI/releases/tag/0.85.0">View on GitHub</a>
+  </div>
+  **Features**
+  - Added knowledge to agent level
+  - Feat/remove langchain
+  - Improve typed task outputs
+  - Log in to Tool Repository on crewai login
+  
+  **Fixes**
+  - Fixes issues with result as answer not properly exiting LLM loop
+  - Fix missing key name when running with ollama provider
+  - Fix spelling issue found
+  
+  **Documentation**
+  - Update readme for running mypy
+  - Add knowledge to mint.json
+  - Update Github actions
+  - Update Agents docs to include two approaches for creating an agent
+  - Improvements to LLM Configuration and Usage
+</Update>
+
+<Update label="2024-11-25" description="v0.83.0">
+  **New Features**
+  - New before_kickoff and after_kickoff crew callbacks
+  - Support to pre-seed agents with Knowledge
+  - Add support for retrieving user preferences and memories using Mem0
+  
+  **Fixes**
+  - Fix Async Execution
+  - Upgrade chroma and adjust embedder function generator
+  - Update CLI Watson supported models + docs
+  - Reduce level for Bandit
+  - Fixing all tests
+  
+  **Documentation**
+  - Update Docs
+</Update>
+
+<Update label="2024-11-13" description="v0.80.0">
+  **Fixes**
+  - Fixing Tokens callback replacement bug
+  - Fixing Step callback issue
+  - Add cached prompt tokens info on usage metrics
+  - Fix crew_train_success test
+</Update>

concepts/agents.mdx

@@ -2,7 +2,6 @@
 title: Agents
 description: Detailed guide on creating and managing agents within the CrewAI framework.
 icon: robot
-mode: "wide"
 ---
 
 ## Overview of an Agent
@@ -20,7 +19,7 @@ Think of an agent as a specialized team member with specific skills, expertise,
 </Tip>
 
 <Note type="info" title="Enterprise Enhancement: Visual Agent Builder">
-CrewAI AMP includes a Visual Agent Builder that simplifies agent creation and configuration without writing code. Design your agents visually and test them in real-time.
+CrewAI Enterprise includes a Visual Agent Builder that simplifies agent creation and configuration without writing code. Design your agents visually and test them in real-time.
 
 ![Visual Agent Builder Screenshot](/images/enterprise/crew-studio-interface.png)
 
@@ -72,7 +71,7 @@ There are two ways to create agents in CrewAI: using **YAML configuration (recom
 
 Using YAML configuration provides a cleaner, more maintainable way to define agents. We strongly recommend using this approach in your CrewAI projects.
 
-After creating your CrewAI project as outlined in the [Installation](/en/installation) section, navigate to the `src/latest_ai_development/config/agents.yaml` file and modify the template to match your requirements.
+After creating your CrewAI project as outlined in the [Installation](/installation) section, navigate to the `src/latest_ai_development/config/agents.yaml` file and modify the template to match your requirements.
 
 <Note>
 Variables in your YAML files (like `{topic}`) will be replaced with values from your inputs when running the crew:
@@ -296,11 +295,6 @@ multimodal_agent = Agent(
   - `"safe"`: Uses Docker (recommended for production)
   - `"unsafe"`: Direct execution (use only in trusted environments)
 
-<Note>
-  This runs a default Docker image. If you want to configure the docker image, the checkout the Code Interpreter Tool in the tools section.
-  Add the code interpreter tool as a tool in the agent as a tool parameter.
-  </Note>
-
 #### Advanced Features
 - `multimodal`: Enable multimodal capabilities for processing text and visual content
 - `reasoning`: Enable agent to reflect and create plans before executing tasks
@@ -313,7 +307,7 @@ multimodal_agent = Agent(
 
 <Note>
 When using custom templates, ensure that both `system_template` and `prompt_template` are defined. The `response_template` is optional but recommended for consistent output formatting.
-</Note>
+</Note>  
 
 <Note>
 When using custom templates, you can use variables like `{role}`, `{goal}`, and `{backstory}` in your templates. These will be automatically populated during execution.
@@ -426,7 +420,7 @@ strict_agent = Agent(
 ```python Code
 # Perfect for document processing
 document_processor = Agent(
-    role="Document Analyst",
+    role="Document Analyst", 
     goal="Extract insights from large research papers",
     backstory="Expert at analyzing extensive documentation",
     respect_context_window=True,  # Handle large documents gracefully
@@ -527,103 +521,6 @@ agent = Agent(
 The context window management feature works automatically in the background. You don't need to call any special functions - just set `respect_context_window` to your preferred behavior and CrewAI handles the rest!
 </Note>
 
-## Direct Agent Interaction with `kickoff()`
-
-Agents can be used directly without going through a task or crew workflow using the `kickoff()` method. This provides a simpler way to interact with an agent when you don't need the full crew orchestration capabilities.
-
-### How `kickoff()` Works
-
-The `kickoff()` method allows you to send messages directly to an agent and get a response, similar to how you would interact with an LLM but with all the agent's capabilities (tools, reasoning, etc.).
-
-```python Code
-from crewai import Agent
-from crewai_tools import SerperDevTool
-
-# Create an agent
-researcher = Agent(
-    role="AI Technology Researcher",
-    goal="Research the latest AI developments",
-    tools=[SerperDevTool()],
-    verbose=True
-)
-
-# Use kickoff() to interact directly with the agent
-result = researcher.kickoff("What are the latest developments in language models?")
-
-# Access the raw response
-print(result.raw)
-```
-
-### Parameters and Return Values
-
-| Parameter         | Type                                | Description                                                               |
-| :---------------- | :---------------------------------- | :------------------------------------------------------------------------ |
-| `messages`        | `Union[str, List[Dict[str, str]]]`  | Either a string query or a list of message dictionaries with role/content |
-| `response_format` | `Optional[Type[Any]]`               | Optional Pydantic model for structured output                             |
-
-The method returns a `LiteAgentOutput` object with the following properties:
-
-- `raw`: String containing the raw output text
-- `pydantic`: Parsed Pydantic model (if a `response_format` was provided)
-- `agent_role`: Role of the agent that produced the output
-- `usage_metrics`: Token usage metrics for the execution
-
-### Structured Output
-
-You can get structured output by providing a Pydantic model as the `response_format`:
-
-```python Code
-from pydantic import BaseModel
-from typing import List
-
-class ResearchFindings(BaseModel):
-    main_points: List[str]
-    key_technologies: List[str]
-    future_predictions: str
-
-# Get structured output
-result = researcher.kickoff(
-    "Summarize the latest developments in AI for 2025",
-    response_format=ResearchFindings
-)
-
-# Access structured data
-print(result.pydantic.main_points)
-print(result.pydantic.future_predictions)
-```
-
-### Multiple Messages
-
-You can also provide a conversation history as a list of message dictionaries:
-
-```python Code
-messages = [
-    {"role": "user", "content": "I need information about large language models"},
-    {"role": "assistant", "content": "I'd be happy to help with that! What specifically would you like to know?"},
-    {"role": "user", "content": "What are the latest developments in 2025?"}
-]
-
-result = researcher.kickoff(messages)
-```
-
-### Async Support
-
-An asynchronous version is available via `kickoff_async()` with the same parameters:
-
-```python Code
-import asyncio
-
-async def main():
-    result = await researcher.kickoff_async("What are the latest developments in AI?")
-    print(result.raw)
-
-asyncio.run(main())
-```
-
-<Note>
-The `kickoff()` method uses a `LiteAgent` internally, which provides a simpler execution flow while preserving all of the agent's configuration (role, goal, backstory, tools, etc.).
-</Note>
-
 ## Important Considerations and Best Practices
 
 ### Security and Code Execution

concepts/cli.mdx

@@ -2,11 +2,8 @@
 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 AMP 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>
-
 ## Overview
 
 The CrewAI CLI provides a set of commands to interact with CrewAI, allowing you to create, train, run, and manage crews & flows.
@@ -89,7 +86,7 @@ crewai replay [OPTIONS]
 - `-t, --task_id TEXT`: Replay the crew from this task ID, including all subsequent tasks
 
 Example:
-```shell Terminal
+```shell Terminal    
 crewai replay -t task_123456
 ```
 
@@ -135,7 +132,7 @@ crewai test [OPTIONS]
 - `-m, --model TEXT`: LLM Model to run the tests on the Crew (default: "gpt-4o-mini")
 
 Example:
-```shell Terminal
+```shell Terminal    
 crewai test -n 5 -m gpt-3.5-turbo
 ```
 
@@ -152,7 +149,7 @@ Starting from version 0.103.0, the `crewai run` command can be used to run both
 </Note>
 
 <Note>
-Make sure to run these commands from the directory where your CrewAI project is set up.
+Make sure to run these commands from the directory where your CrewAI project is set up. 
 Some commands may require additional configuration or setup within your project structure.
 </Note>
 
@@ -186,10 +183,13 @@ def crew(self) -> Crew:
 
 ### 10. Deploy
 
-Deploy the crew or flow to [CrewAI AMP](https://app.crewai.com).
+Deploy the crew or flow to [CrewAI Enterprise](https://app.crewai.com).
 
-- **Authentication**: You need to be authenticated to deploy to CrewAI AMP.
-    You can login or create an account with:
+- **Authentication**: You need to be authenticated to deploy to CrewAI Enterprise.
+    ```shell Terminal
+    crewai signup
+    ```
+    If you already have an account, you can login with:
     ```shell Terminal
     crewai login
     ```
@@ -203,7 +203,7 @@ Deploy the crew or flow to [CrewAI AMP](https://app.crewai.com).
 
 ### 11. Organization Management
 
-Manage your CrewAI AMP organizations.
+Manage your CrewAI Enterprise organizations.
 
 ```shell Terminal
 crewai org [COMMAND] [OPTIONS]
@@ -227,17 +227,17 @@ crewai org switch <organization_id>
 ```
 
 <Note>
-You must be authenticated to CrewAI AMP to use these organization management commands.
+You must be authenticated to CrewAI Enterprise to use these organization management commands.
 </Note>
 
 - **Create a deployment** (continued):
     - Links the deployment to the corresponding remote GitHub repository (it usually detects this automatically).
 
-- **Deploy the Crew**: Once you are authenticated, you can deploy your crew or flow to CrewAI AMP.
+- **Deploy the Crew**: Once you are authenticated, you can deploy your crew or flow to CrewAI Enterprise.
     ```shell Terminal
     crewai deploy push
-    ```
-    - Initiates the deployment process on the CrewAI AMP platform.
+    ``` 
+    - Initiates the deployment process on the CrewAI Enterprise platform.
     - Upon successful initiation, it will output the Deployment created successfully! message along with the Deployment Name and a unique Deployment ID (UUID).
 
 - **Deployment Status**: You can check the status of your deployment with:
@@ -262,7 +262,7 @@ You must be authenticated to CrewAI AMP to use these organization management com
     ```shell Terminal
     crewai deploy remove
     ```
-    This deletes the deployment from the CrewAI AMP platform.
+    This deletes the deployment from the CrewAI Enterprise platform.
 
 - **Help Command**: You can get help with the CLI with:
     ```shell Terminal
@@ -270,44 +270,28 @@ You must be authenticated to CrewAI AMP to use these organization management com
     ```
     This shows the help message for the CrewAI Deploy CLI.
 
-Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI AMP](http://app.crewai.com) using the CLI.
+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
-  className="w-full aspect-video rounded-xl"
+  width="100%"
+  height="400"
   src="https://www.youtube.com/embed/3EqSV-CYDZA"
   title="CrewAI Deployment Guide"
-  frameBorder="0"
+  frameborder="0"
+  style={{ borderRadius: '10px' }}
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-  allowFullScreen
+  allowfullscreen
 ></iframe>
 
-### 11. Login
+### 11. API Keys
 
-Authenticate with CrewAI AMP using a secure device code flow (no email entry required).
+When running ```crewai create crew``` command, the CLI will first show you the top 5 most common LLM providers and ask you to select one.
 
-```shell Terminal
-crewai login
-```
+Once you've selected an LLM provider, you will be prompted for API keys.
 
-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
+#### Initial API key providers
 
-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.
-
-Once you've selected an LLM provider and model, you will be prompted for API keys.
-
-#### Available LLM Providers
-
-Here's a list of the most popular LLM providers suggested by the CLI:
+The CLI will initially prompt for API keys for the following services:
 
 * OpenAI
 * Groq
@@ -315,11 +299,11 @@ Here's a list of the most popular LLM providers suggested by the CLI:
 * Google Gemini
 * SambaNova
 
-When you select a provider, the CLI will then show you available models for that provider and prompt you to enter your API key.
+When you select a provider, the CLI will prompt you to enter your API key.
 
 #### Other Options
 
-If you select "other", you will be able to select from a list of LiteLLM supported providers.
+If you select option 6, you will be able to select from a list of LiteLLM supported providers.
 
 When you select a provider, the CLI will prompt you to enter the Key name and the API key.
 
@@ -327,85 +311,5 @@ See the following link for each provider's key name:
 
 * [LiteLLM Providers](https://docs.litellm.ai/docs/providers)
 
-### 13. Configuration Management
 
-Manage CLI configuration settings for CrewAI.
 
-```shell Terminal
-crewai config [COMMAND] [OPTIONS]
-```
-
-#### Commands:
-
-- `list`: Display all CLI configuration parameters
-```shell Terminal
-crewai config list
-```
-
-- `set`: Set a CLI configuration parameter
-```shell Terminal
-crewai config set <key> <value>
-```
-
-- `reset`: Reset all CLI configuration parameters to default values
-```shell Terminal
-crewai config reset
-```
-
-#### Available Configuration Parameters
-
-- `enterprise_base_url`: Base URL of the CrewAI AMP instance
-- `oauth2_provider`: OAuth2 provider used for authentication (e.g., workos, okta, auth0)
-- `oauth2_audience`: OAuth2 audience value, typically used to identify the target API or resource
-- `oauth2_client_id`: OAuth2 client ID issued by the provider, used during authentication requests
-- `oauth2_domain`: OAuth2 provider's domain (e.g., your-org.auth0.com) used for issuing tokens
-
-#### Examples
-
-Display current configuration:
-```shell Terminal
-crewai config list
-```
-
-Example output:
-| Setting             | Value                    | Description                                                 |
-| :------------------ | :----------------------- | :---------------------------------------------------------- |
-| enterprise_base_url | https://app.crewai.com   | Base URL of the CrewAI AMP 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
-crewai config set enterprise_base_url https://my-enterprise.crewai.com
-```
-
-Set OAuth2 provider:
-```shell Terminal
-crewai config set oauth2_provider auth0
-```
-
-Set OAuth2 domain:
-```shell Terminal
-crewai config set oauth2_domain my-company.auth0.com
-```
-
-Reset all configuration to defaults:
-```shell Terminal
-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>

concepts/collaboration.mdx

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

concepts/crews.mdx

@@ -2,7 +2,6 @@
 title: Crews
 description: Understanding and utilizing crews in the crewAI framework with comprehensive attributes and functionalities.
 icon: people-group
-mode: "wide"
 ---
 
 ## Overview
@@ -21,7 +20,8 @@ A crew in crewAI represents a collaborative group of agents working together to
 | **Function Calling LLM** _(optional)_ | `function_calling_llm` | If passed, the crew will use this LLM to do function calling for tools for all agents in the crew. Each agent can have its own LLM, which overrides the crew's LLM for function calling.                                                                  |
 | **Config** _(optional)_               | `config`               | Optional configuration settings for the crew, in `Json` or `Dict[str, Any]` format.                                                                                                                                                                       |
 | **Max RPM** _(optional)_              | `max_rpm`              | Maximum requests per minute the crew adheres to during execution. Defaults to `None`.                                                                                                                                                                     |
-| **Memory** _(optional)_               | `memory`               | Utilized for storing execution memories (short-term, long-term, entity memory).                                                                                                                                                                           |                                                                                                                                                                                       |
+| **Memory** _(optional)_               | `memory`               | Utilized for storing execution memories (short-term, long-term, entity memory).                                                                                                                                                                           |
+| **Memory Config** _(optional)_        | `memory_config`        | Configuration for the memory provider to be used by the crew.                                                                                                                                                                                             |
 | **Cache** _(optional)_                | `cache`                | Specifies whether to use a cache for storing the results of tools' execution. Defaults to `True`.                                                                                                                                                         |
 | **Embedder** _(optional)_             | `embedder`             | Configuration for the embedder to be used by the crew. Mostly used by memory for now. Default is `{"provider": "openai"}`.                                                                                                                                |
 | **Step Callback** _(optional)_        | `step_callback`        | A function that is called after each step of every agent. This can be used to log the agent's actions or to perform other operations; it won't override the agent-specific `step_callback`.                                                               |
@@ -32,7 +32,6 @@ A crew in crewAI represents a collaborative group of agents working together to
 | **Prompt File** _(optional)_          | `prompt_file`          | Path to the prompt JSON file to be used for the crew.                                                                                                                                                                                                     |
 | **Planning** *(optional)*             | `planning`             | Adds planning ability to the Crew. When activated before each Crew iteration, all Crew data is sent to an AgentPlanner that will plan the tasks and this plan will be added to each task description.                                                     |
 | **Planning LLM** *(optional)*         | `planning_llm`         | The language model used by the AgentPlanner in a planning process.                                                                                                                                                                                        |
-| **Knowledge Sources** _(optional)_    | `knowledge_sources`    | Knowledge sources available at the crew level, accessible to all the agents.                                                                                                                                                                                    |
 
 <Tip>
 **Crew Max RPM**: The `max_rpm` attribute sets the maximum number of requests per minute the crew can perform to avoid rate limits and will override individual agents' `max_rpm` settings if you set it.
@@ -46,7 +45,7 @@ There are two ways to create crews in CrewAI: using **YAML configuration (recomm
 
 Using YAML configuration provides a cleaner, more maintainable way to define crews and is consistent with how agents and tasks are defined in CrewAI projects.
 
-After creating your CrewAI project as outlined in the [Installation](/en/installation) section, you can define your crew in a class that inherits from `CrewBase` and uses decorators to define agents, tasks, and the crew itself.
+After creating your CrewAI project as outlined in the [Installation](/installation) section, you can define your crew in a class that inherits from `CrewBase` and uses decorators to define agents, tasks, and the crew itself.
 
 #### Example Crew Class with Decorators
 
@@ -67,8 +66,8 @@ class YourCrewName:
     # To see an example agent and task defined in YAML, checkout the following:
     # - Task: https://docs.crewai.com/concepts/tasks#yaml-configuration-recommended
     # - Agents: https://docs.crewai.com/concepts/agents#yaml-configuration-recommended
-    agents_config = 'config/agents.yaml'
-    tasks_config = 'config/tasks.yaml'
+    agents_config = 'config/agents.yaml' 
+    tasks_config = 'config/tasks.yaml' 
 
     @before_kickoff
     def prepare_inputs(self, inputs):
@@ -112,7 +111,7 @@ class YourCrewName:
     def crew(self) -> Crew:
         return Crew(
             agents=self.agents,  # Automatically collected by the @agent decorator
-            tasks=self.tasks,    # Automatically collected by the @task decorator.
+            tasks=self.tasks,    # Automatically collected by the @task decorator. 
             process=Process.sequential,
             verbose=True,
         )

concepts/event-listener.mdx

@@ -2,7 +2,6 @@
 title: 'Event Listeners'
 description: 'Tap into CrewAI events to build custom integrations and monitoring'
 icon: spinner
-mode: "wide"
 ---
 
 ## Overview
@@ -20,7 +19,7 @@ CrewAI uses an event bus architecture to emit events throughout the execution li
 When specific actions occur in CrewAI (like a Crew starting execution, an Agent completing a task, or a tool being used), the system emits corresponding events. You can register handlers for these events to execute custom code when they occur.
 
 <Note type="info" title="Enterprise Enhancement: Prompt Tracing">
-CrewAI AMP provides a built-in Prompt Tracing feature that leverages the event system to track, store, and visualize all prompts, completions, and associated metadata. This provides powerful debugging capabilities and transparency into your agent operations.
+CrewAI Enterprise provides a built-in Prompt Tracing feature that leverages the event system to track, store, and visualize all prompts, completions, and associated metadata. This provides powerful debugging capabilities and transparency into your agent operations.
 
 ![Prompt Tracing Dashboard](/images/enterprise/traces-overview.png)
 
@@ -45,12 +44,12 @@ To create a custom event listener, you need to:
 Here's a simple example of a custom event listener class:
 
 ```python
-from crewai.events import (
+from crewai.utilities.events import (
     CrewKickoffStartedEvent,
     CrewKickoffCompletedEvent,
     AgentExecutionCompletedEvent,
 )
-from crewai.events import BaseEventListener
+from crewai.utilities.events.base_event_listener import BaseEventListener
 
 class MyCustomListener(BaseEventListener):
     def __init__(self):
@@ -147,7 +146,7 @@ my_project/
 
 ```python
 # my_custom_listener.py
-from crewai.events import BaseEventListener
+from crewai.utilities.events.base_event_listener import BaseEventListener
 # ... import events ...
 
 class MyCustomListener(BaseEventListener):
@@ -178,7 +177,14 @@ class MyCustomCrew:
     # Your crew implementation...
 ```
 
-This is how third-party event listeners are registered in the CrewAI codebase.
+This is exactly how CrewAI's built-in `agentops_listener` is registered. In the CrewAI codebase, you'll find:
+
+```python
+# src/crewai/utilities/events/third_party/__init__.py
+from .agentops_listener import agentops_listener
+```
+
+This ensures the `agentops_listener` is loaded when the `crewai.utilities.events` package is imported.
 
 ## Available Event Types
 
@@ -227,11 +233,6 @@ CrewAI provides a wide range of events that you can listen for:
 - **KnowledgeQueryFailedEvent**: Emitted when a knowledge query fails
 - **KnowledgeSearchQueryFailedEvent**: Emitted when a knowledge search query fails
 
-### LLM Guardrail Events
-
-- **LLMGuardrailStartedEvent**: Emitted when a guardrail validation starts. Contains details about the guardrail being applied and retry count.
-- **LLMGuardrailCompletedEvent**: Emitted when a guardrail validation completes. Contains details about validation success/failure, results, and error messages if any.
-
 ### Flow Events
 
 - **FlowCreatedEvent**: Emitted when a Flow is created
@@ -249,17 +250,6 @@ CrewAI provides a wide range of events that you can listen for:
 - **LLMCallFailedEvent**: Emitted when an LLM call fails
 - **LLMStreamChunkEvent**: Emitted for each chunk received during streaming LLM responses
 
-### Memory Events
-
-- **MemoryQueryStartedEvent**: Emitted when a memory query is started. Contains the query, limit, and optional score threshold.
-- **MemoryQueryCompletedEvent**: Emitted when a memory query is completed successfully. Contains the query, results, limit, score threshold, and query execution time.
-- **MemoryQueryFailedEvent**: Emitted when a memory query fails. Contains the query, limit, score threshold, and error message.
-- **MemorySaveStartedEvent**: Emitted when a memory save operation is started. Contains the value to be saved, metadata, and optional agent role.
-- **MemorySaveCompletedEvent**: Emitted when a memory save operation is completed successfully. Contains the saved value, metadata, agent role, and save execution time.
-- **MemorySaveFailedEvent**: Emitted when a memory save operation fails. Contains the value, metadata, agent role, and error message.
-- **MemoryRetrievalStartedEvent**: Emitted when memory retrieval for a task prompt starts. Contains the optional task ID.
-- **MemoryRetrievalCompletedEvent**: Emitted when memory retrieval for a task prompt completes successfully. Contains the task ID, memory content, and retrieval execution time.
-
 ## Event Handler Structure
 
 Each event handler receives two parameters:
@@ -274,13 +264,84 @@ The structure of the event object depends on the event type, but all events inhe
 
 Additional fields vary by event type. For example, `CrewKickoffCompletedEvent` includes `crew_name` and `output` fields.
 
+## Real-World Example: Integration with AgentOps
+
+CrewAI includes an example of a third-party integration with [AgentOps](https://github.com/AgentOps-AI/agentops), a monitoring and observability platform for AI agents. Here's how it's implemented:
+
+```python
+from typing import Optional
+
+from crewai.utilities.events import (
+    CrewKickoffCompletedEvent,
+    ToolUsageErrorEvent,
+    ToolUsageStartedEvent,
+)
+from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.utilities.events.crew_events import CrewKickoffStartedEvent
+from crewai.utilities.events.task_events import TaskEvaluationEvent
+
+try:
+    import agentops
+    AGENTOPS_INSTALLED = True
+except ImportError:
+    AGENTOPS_INSTALLED = False
+
+class AgentOpsListener(BaseEventListener):
+    tool_event: Optional["agentops.ToolEvent"] = None
+    session: Optional["agentops.Session"] = None
+
+    def __init__(self):
+        super().__init__()
+
+    def setup_listeners(self, crewai_event_bus):
+        if not AGENTOPS_INSTALLED:
+            return
+
+        @crewai_event_bus.on(CrewKickoffStartedEvent)
+        def on_crew_kickoff_started(source, event: CrewKickoffStartedEvent):
+            self.session = agentops.init()
+            for agent in source.agents:
+                if self.session:
+                    self.session.create_agent(
+                        name=agent.role,
+                        agent_id=str(agent.id),
+                    )
+
+        @crewai_event_bus.on(CrewKickoffCompletedEvent)
+        def on_crew_kickoff_completed(source, event: CrewKickoffCompletedEvent):
+            if self.session:
+                self.session.end_session(
+                    end_state="Success",
+                    end_state_reason="Finished Execution",
+                )
+
+        @crewai_event_bus.on(ToolUsageStartedEvent)
+        def on_tool_usage_started(source, event: ToolUsageStartedEvent):
+            self.tool_event = agentops.ToolEvent(name=event.tool_name)
+            if self.session:
+                self.session.record(self.tool_event)
+
+        @crewai_event_bus.on(ToolUsageErrorEvent)
+        def on_tool_usage_error(source, event: ToolUsageErrorEvent):
+            agentops.ErrorEvent(exception=event.error, trigger_event=self.tool_event)
+```
+
+This listener initializes an AgentOps session when a Crew starts, registers agents with AgentOps, tracks tool usage, and ends the session when the Crew completes.
+
+The AgentOps listener is registered in CrewAI's event system through the import in `src/crewai/utilities/events/third_party/__init__.py`:
+
+```python
+from .agentops_listener import agentops_listener
+```
+
+This ensures the `agentops_listener` is loaded when the `crewai.utilities.events` package is imported.
 
 ## Advanced Usage: Scoped Handlers
 
 For temporary event handling (useful for testing or specific operations), you can use the `scoped_handlers` context manager:
 
 ```python
-from crewai.events import crewai_event_bus, CrewKickoffStartedEvent
+from crewai.utilities.events import crewai_event_bus, CrewKickoffStartedEvent
 
 with crewai_event_bus.scoped_handlers():
     @crewai_event_bus.on(CrewKickoffStartedEvent)

concepts/flows.mdx

@@ -2,7 +2,6 @@
 title: Flows
 description: Learn how to create and manage AI workflows using CrewAI Flows.
 icon: arrow-progress
-mode: "wide"
 ---
 
 ## Overview
@@ -98,13 +97,7 @@ The state's unique ID and stored data can be useful for tracking flow executions
 
 ### @start()
 
-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.
+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.
 
 ### @listen()
 
@@ -875,13 +868,14 @@ 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
-  className="w-full aspect-video rounded-xl"
+  width="560"
+  height="315"
   src="https://www.youtube.com/embed/MTb5my6VOT8"
-  title="CrewAI Flows overview"
-  frameBorder="0"
+  title="YouTube video player"
+  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

concepts/knowledge.mdx

@@ -2,7 +2,6 @@
 title: Knowledge
 description: What is knowledge in CrewAI and how to use it.
 icon: book
-mode: "wide"
 ---
 
 ## Overview
@@ -25,41 +24,6 @@ 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
@@ -717,11 +681,11 @@ CrewAI emits events during the knowledge retrieval process that you can listen f
 #### Example: Monitoring Knowledge Retrieval
 
 ```python
-from crewai.events import (
+from crewai.utilities.events import (
     KnowledgeRetrievalStartedEvent,
     KnowledgeRetrievalCompletedEvent,
-    BaseEventListener,
 )
+from crewai.utilities.events.base_event_listener import BaseEventListener
 
 class KnowledgeMonitorListener(BaseEventListener):
     def setup_listeners(self, crewai_event_bus):

concepts/llms.mdx

@@ -2,7 +2,6 @@
 title: 'LLMs'
 description: 'A comprehensive guide to configuring and using Large Language Models (LLMs) in your CrewAI projects'
 icon: 'microchip-ai'
-mode: "wide"
 ---
 
 ## Overview
@@ -271,7 +270,7 @@ In this section, you'll find detailed examples that help you select, configure,
     from crewai import LLM
 
     llm = LLM(
-        model="gemini-1.5-pro-latest", # or vertex_ai/gemini-1.5-pro-latest
+        model="gemini/gemini-1.5-pro-latest",
         temperature=0.7,
         vertex_credentials=vertex_credentials_json
     )
@@ -685,28 +684,6 @@ In this section, you'll find detailed examples that help you select, configure,
       - openrouter/deepseek/deepseek-chat
     </Info>
   </Accordion>
-
-  <Accordion title="Nebius AI Studio">
-    Set the following environment variables in your `.env` file:
-    ```toml Code
-    NEBIUS_API_KEY=<your-api-key>
-    ```
-
-    Example usage in your CrewAI project:
-    ```python Code
-    llm = LLM(
-        model="nebius/Qwen/Qwen3-30B-A3B"
-    )
-    ```
-
-    <Info>
-      Nebius AI Studio features:
-      - Large collection of open source models
-      - Higher rate limits
-      - Competitive pricing
-      - Good balance of speed and quality
-    </Info>
-  </Accordion>
 </AccordionGroup>
 
 ## Streaming Responses
@@ -734,10 +711,10 @@ CrewAI supports streaming responses from LLMs, allowing your application to rece
     CrewAI emits events for each chunk received during streaming:
 
     ```python
-    from crewai.events import (
+    from crewai.utilities.events import (
       LLMStreamChunkEvent
     )
-    from crewai.events import BaseEventListener
+    from crewai.utilities.events.base_event_listener import BaseEventListener
 
     class MyCustomListener(BaseEventListener):
         def setup_listeners(self, crewai_event_bus):
@@ -750,58 +727,9 @@ CrewAI supports streaming responses from LLMs, allowing your application to rece
     ```
 
     <Tip>
-      [Click here](https://docs.crewai.com/concepts/event-listener#event-listeners) for more details
+      [Click here](https://docs.crewai.com/concepts/event-listener#event-listeners) for more details 
     </Tip>
   </Tab>
-
-  <Tab title="Agent & Task Tracking">
-    All LLM events in CrewAI include agent and task information, allowing you to track and filter LLM interactions by specific agents or tasks:
-
-    ```python
-    from crewai import LLM, Agent, Task, Crew
-    from crewai.events import LLMStreamChunkEvent
-    from crewai.events import BaseEventListener
-
-    class MyCustomListener(BaseEventListener):
-        def setup_listeners(self, crewai_event_bus):
-            @crewai_event_bus.on(LLMStreamChunkEvent)
-            def on_llm_stream_chunk(source, event):
-                if researcher.id == event.agent_id:
-                    print("\n==============\n Got event:", event, "\n==============\n")
-
-
-    my_listener = MyCustomListener()
-
-    llm = LLM(model="gpt-4o-mini", temperature=0, stream=True)
-
-    researcher = Agent(
-        role="About User",
-        goal="You know everything about the user.",
-        backstory="""You are a master at understanding people and their preferences.""",
-        llm=llm,
-    )
-
-    search = Task(
-        description="Answer the following questions about the user: {question}",
-        expected_output="An answer to the question.",
-        agent=researcher,
-    )
-
-    crew = Crew(agents=[researcher], tasks=[search])
-
-    result = crew.kickoff(
-        inputs={"question": "..."}
-    )
-    ```
-
-    <Info>
-      This feature is particularly useful for:
-      - Debugging specific agent behaviors
-      - Logging LLM usage by task type
-      - Auditing which agents are making what types of LLM calls
-      - Performance monitoring of specific tasks
-    </Info>
-  </Tab>
 </Tabs>
 
 ## Structured LLM Calls
@@ -897,7 +825,7 @@ Learn how to get the most out of your LLM configuration:
       Remember to regularly monitor your token usage and adjust your configuration as needed to optimize costs and performance.
     </Info>
   </Accordion>
-
+  
   <Accordion title="Drop Additional Parameters">
     CrewAI internally uses Litellm for LLM calls, which allows you to drop additional parameters that are not needed for your specific use case. This can help simplify your code and reduce the complexity of your LLM configuration.
     For example, if you don't need to send the <code>stop</code> parameter, you can simply omit it from your LLM call:

concepts/memory.mdx

@@ -2,15 +2,15 @@
 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 **two 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 **three 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
+2. **User Memory** - User-specific memory with Mem0 integration (legacy approach)  
+3. **External Memory** - Standalone external memory providers (new approach)
 
 ## Memory System Components
 
@@ -19,7 +19,7 @@ The CrewAI framework provides a sophisticated memory system designed to signific
 | **Short-Term Memory**| Temporarily stores recent interactions and outcomes using `RAG`, enabling agents to recall and utilize information relevant to their current context during the current executions.|
 | **Long-Term Memory** | Preserves valuable insights and learnings from past executions, allowing agents to build and refine their knowledge over time. |
 | **Entity Memory**    | Captures and organizes information about entities (people, places, concepts) encountered during tasks, facilitating deeper understanding and relationship mapping. Uses `RAG` for storing entity information. |
-| **Contextual Memory**| Maintains the context of interactions by combining `ShortTermMemory`, `LongTermMemory`, `ExternalMemory` and `EntityMemory`, aiding in the coherence and relevance of agent responses over a sequence of tasks or a conversation. |
+| **Contextual Memory**| Maintains the context of interactions by combining `ShortTermMemory`, `LongTermMemory`, and `EntityMemory`, aiding in the coherence and relevance of agent responses over a sequence of tasks or a conversation. |
 
 ## 1. Basic Memory System (Recommended)
 
@@ -62,7 +62,7 @@ By default, CrewAI uses the `appdirs` library to determine storage locations fol
 ```
 ~/Library/Application Support/CrewAI/{project_name}/
 ├── knowledge/           # Knowledge base ChromaDB files
-├── short_term_memory/   # Short-term memory ChromaDB files
+├── short_term_memory/   # Short-term memory ChromaDB files  
 ├── long_term_memory/    # Long-term memory ChromaDB files
 ├── entities/            # Entity memory ChromaDB files
 └── long_term_memory_storage.db  # SQLite database
@@ -202,7 +202,7 @@ crew = Crew(
     tasks=[task],
     memory=True,
     embedder={
-        "provider": "anthropic", # Match your LLM provider
+        "provider": "anthropic",  # Match your LLM provider
         "config": {
             "api_key": "your-anthropic-key",
             "model": "text-embedding-3-small"
@@ -252,7 +252,7 @@ chroma_path = os.path.join(storage_path, "knowledge")
 if os.path.exists(chroma_path):
     client = chromadb.PersistentClient(path=chroma_path)
     collections = client.list_collections()
-
+    
     print("ChromaDB Collections:")
     for collection in collections:
         print(f"  - {collection.name}: {collection.count()} documents")
@@ -269,7 +269,7 @@ crew = Crew(agents=[...], tasks=[...], memory=True)
 
 # Reset specific memory types
 crew.reset_memories(command_type='short')     # Short-term memory
-crew.reset_memories(command_type='long')      # Long-term memory
+crew.reset_memories(command_type='long')      # Long-term memory  
 crew.reset_memories(command_type='entity')    # Entity memory
 crew.reset_memories(command_type='knowledge') # Knowledge storage
 ```
@@ -540,71 +540,16 @@ crew = Crew(
 )
 ```
 
-### Mem0 Provider
-
-Short-Term Memory and Entity Memory both supports a tight integration with both Mem0 OSS and Mem0 Client as a provider. Here is how you can use Mem0 as a provider.
-
-```python
-from crewai.memory.short_term.short_term_memory import ShortTermMemory
-from crewai.memory.entity_entity_memory import EntityMemory
-
-mem0_oss_embedder_config = {
-        "provider": "mem0",
-        "config": {
-            "user_id": "john",
-            "local_mem0_config": {
-                "vector_store": {"provider": "qdrant","config": {"host": "localhost", "port": 6333}},
-                "llm": {"provider": "openai","config": {"api_key": "your-api-key", "model": "gpt-4"}},
-                "embedder": {"provider": "openai","config": {"api_key": "your-api-key", "model": "text-embedding-3-small"}}
-            },
-            "infer": True # Optional defaults to True
-        },
-    }
-
-
-mem0_client_embedder_config = {
-        "provider": "mem0",
-        "config": {
-            "user_id": "john",
-            "org_id": "my_org_id",        # Optional
-            "project_id": "my_project_id", # Optional
-            "api_key": "custom-api-key"    # Optional - overrides env var
-            "run_id": "my_run_id",        # Optional - for short-term memory
-            "includes": "include1",       # Optional 
-            "excludes": "exclude1",       # Optional
-            "infer": True                 # Optional defaults to True
-            "custom_categories": new_categories  # Optional - custom categories for user memory
-        },
-    }
-
-
-short_term_memory_mem0_oss = ShortTermMemory(embedder_config=mem0_oss_embedder_config) # Short Term Memory with Mem0 OSS
-short_term_memory_mem0_client = ShortTermMemory(embedder_config=mem0_client_embedder_config) # Short Term Memory with Mem0 Client
-entity_memory_mem0_oss = EntityMemory(embedder_config=mem0_oss_embedder_config) # Entity Memory with Mem0 OSS
-entity_memory_mem0_client = EntityMemory(embedder_config=mem0_client_embedder_config) # Short Term Memory with Mem0 Client
-
-crew = Crew(
-    memory=True,
-    short_term_memory=short_term_memory_mem0_oss, # or short_term_memory_mem0_client
-    entity_memory=entity_memory_mem0_oss # or entity_memory_mem0_client
-)
-```
-
 ### Choosing the Right Embedding Provider
 
-When selecting an embedding provider, consider factors like performance, privacy, cost, and integration needs.  
-Below is a comparison to help you decide:
-
-| Provider       | Best For                       | Pros                              | Cons                      |
-| -------------- | ------------------------------ | --------------------------------- | ------------------------- |
-| **OpenAI**     | General use, high reliability  | High quality, widely tested       | Paid service, API key required |
-| **Ollama**     | Privacy-focused, cost savings  | Free, runs locally, fully private | Requires local installation/setup |
-| **Google AI**  | Integration in Google ecosystem| Strong performance, good support  | Google account required   |
-| **Azure OpenAI** | Enterprise & compliance needs| Enterprise-grade features, security | More complex setup process |
-| **Cohere**     | Multilingual content handling  | Excellent language support        | More niche use cases      |
-| **VoyageAI**   | Information retrieval & search | Optimized for retrieval tasks     | Relatively new provider   |
-| **Mem0**       | Per-user personalization       | Search-optimized embeddings       | Paid service, API key required |
-
+| Provider | Best For | Pros | Cons |
+|:---------|:----------|:------|:------|
+| **OpenAI** | General use, reliability | High quality, well-tested | Cost, requires API key |
+| **Ollama** | Privacy, cost savings | Free, local, private | Requires local setup |
+| **Google AI** | Google ecosystem | Good performance | Requires Google account |
+| **Azure OpenAI** | Enterprise, compliance | Enterprise features | Complex setup |
+| **Cohere** | Multilingual content | Great language support | Specialized use case |
+| **VoyageAI** | Retrieval tasks | Optimized for search | Newer provider |
 
 ### Environment Variable Configuration
 
@@ -651,7 +596,7 @@ providers_to_test = [
     {
         "name": "Ollama",
         "config": {
-            "provider": "ollama",
+            "provider": "ollama", 
             "config": {"model": "mxbai-embed-large"}
         }
     }
@@ -659,7 +604,7 @@ providers_to_test = [
 
 for provider in providers_to_test:
     print(f"\nTesting {provider['name']} embeddings...")
-
+    
     # Create crew with specific embedder
     crew = Crew(
         agents=[...],
@@ -667,7 +612,7 @@ for provider in providers_to_test:
         memory=True,
         embedder=provider['config']
     )
-
+    
     # Run your test and measure performance
     result = crew.kickoff()
     print(f"{provider['name']} completed successfully")
@@ -678,7 +623,7 @@ for provider in providers_to_test:
 **Model not found errors:**
 ```python
 # Verify model availability
-from crewai.rag.embeddings.configurator import EmbeddingConfigurator
+from crewai.utilities.embedding_configurator import EmbeddingConfigurator
 
 configurator = EmbeddingConfigurator()
 try:
@@ -710,17 +655,17 @@ import time
 
 def test_embedding_performance(embedder_config, test_text="This is a test document"):
     start_time = time.time()
-
+    
     crew = Crew(
         agents=[...],
         tasks=[...],
         memory=True,
         embedder=embedder_config
     )
-
+    
     # Simulate memory operation
     crew.kickoff()
-
+    
     end_time = time.time()
     return end_time - start_time
 
@@ -731,7 +676,7 @@ openai_time = test_embedding_performance({
 })
 
 ollama_time = test_embedding_performance({
-    "provider": "ollama",
+    "provider": "ollama", 
     "config": {"model": "mxbai-embed-large"}
 })
 
@@ -739,29 +684,67 @@ print(f"OpenAI: {openai_time:.2f}s")
 print(f"Ollama: {ollama_time:.2f}s")
 ```
 
-### Entity Memory batching behavior
+## 2. User Memory with Mem0 (Legacy)
 
-Entity Memory supports batching when saving multiple entities at once. When you pass a list of `EntityMemoryItem`, the system:
+<Warning>
+**Legacy Approach**: While fully functional, this approach is considered legacy. For new projects requiring user-specific memory, consider using External Memory instead.
+</Warning>
 
-- 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)
+User Memory integrates with [Mem0](https://mem0.ai/) to provide user-specific memory that persists across sessions and integrates with the crew's contextual memory system.
 
-This improves performance and observability when writing many entities in one operation.
+### Prerequisites
+```bash
+pip install mem0ai
+```
 
-## 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.
-
-### Basic External Memory with Mem0
+### Mem0 Cloud Configuration
 ```python
 import os
-from crewai import Agent, Crew, Process, Task
-from crewai.memory.external.external_memory import ExternalMemory
+from crewai import Crew, Process
 
-# Create external memory instance with local Mem0 Configuration
-external_memory = ExternalMemory(
-    embedder_config={
+# Set your Mem0 API key
+os.environ["MEM0_API_KEY"] = "m0-your-api-key"
+
+crew = Crew(
+    agents=[...],
+    tasks=[...],
+    memory=True,  # Required for contextual memory integration
+    memory_config={
+        "provider": "mem0",
+        "config": {"user_id": "john"},
+        "user_memory": {}  # Required - triggers user memory initialization
+    },
+    process=Process.sequential,
+    verbose=True
+)
+```
+
+### Advanced Mem0 Configuration
+```python
+crew = Crew(
+    agents=[...],
+    tasks=[...],
+    memory=True,
+    memory_config={
+        "provider": "mem0",
+        "config": {
+            "user_id": "john",
+            "org_id": "my_org_id",        # Optional
+            "project_id": "my_project_id", # Optional
+            "api_key": "custom-api-key"    # Optional - overrides env var
+        },
+        "user_memory": {}
+    }
+)
+```
+
+### Local Mem0 Configuration
+```python
+crew = Crew(
+    agents=[...],
+    tasks=[...],
+    memory=True,
+    memory_config={
         "provider": "mem0",
         "config": {
             "user_id": "john",
@@ -778,60 +761,37 @@ external_memory = ExternalMemory(
                     "provider": "openai",
                     "config": {"api_key": "your-api-key", "model": "text-embedding-3-small"}
                 }
-            },
-            "infer": True # Optional defaults to True
+            }
         },
+        "user_memory": {}
     }
 )
-
-crew = Crew(
-    agents=[...],
-    tasks=[...],
-    external_memory=external_memory, # Separate from basic memory
-    process=Process.sequential,
-    verbose=True
-)
 ```
 
-### Advanced External Memory with Mem0 Client
-When using Mem0 Client, you can customize the memory configuration further, by using parameters like 'includes', 'excludes', 'custom_categories', 'infer' and 'run_id' (this is only for short-term memory).
-You can find more details in the [Mem0 documentation](https://docs.mem0.ai/).
+## 3. External Memory (New Approach)
 
+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.
+
+### Basic External Memory with Mem0
 ```python
 import os
 from crewai import Agent, Crew, Process, Task
 from crewai.memory.external.external_memory import ExternalMemory
 
-new_categories = [
-    {"lifestyle_management_concerns": "Tracks daily routines, habits, hobbies and interests including cooking, time management and work-life balance"},
-    {"seeking_structure": "Documents goals around creating routines, schedules, and organized systems in various life areas"},
-    {"personal_information": "Basic information about the user including name, preferences, and personality traits"}
-]
-
 os.environ["MEM0_API_KEY"] = "your-api-key"
 
-# Create external memory instance with Mem0 Client
+# Create external memory instance
 external_memory = ExternalMemory(
     embedder_config={
-        "provider": "mem0",
-        "config": {
-            "user_id": "john",
-            "org_id": "my_org_id",        # Optional
-            "project_id": "my_project_id", # Optional
-            "api_key": "custom-api-key"    # Optional - overrides env var
-            "run_id": "my_run_id",        # Optional - for short-term memory
-            "includes": "include1",       # Optional 
-            "excludes": "exclude1",       # Optional
-            "infer": True                 # Optional defaults to True
-            "custom_categories": new_categories  # Optional - custom categories for user memory
-        },
+        "provider": "mem0", 
+        "config": {"user_id": "U-123"}
     }
 )
 
 crew = Crew(
     agents=[...],
     tasks=[...],
-    external_memory=external_memory, # Separate from basic memory
+    external_memory=external_memory,  # Separate from basic memory
     process=Process.sequential,
     verbose=True
 )
@@ -848,8 +808,8 @@ class CustomStorage(Storage):
 
     def save(self, value, metadata=None, agent=None):
         self.memories.append({
-            "value": value,
-            "metadata": metadata,
+            "value": value, 
+            "metadata": metadata, 
             "agent": agent
         })
 
@@ -870,18 +830,17 @@ crew = Crew(
 )
 ```
 
-## 🧠 Memory System Comparison
-
-| **Category**        | **Feature**            | **Basic Memory**            | **External Memory**         |
-|---------------------|------------------------|-----------------------------|------------------------------|
-| **Ease of Use**     | Setup Complexity       | Simple                      | Moderate                     |
-|                     | Integration            | Built-in (contextual)       | Standalone                   |
-| **Persistence**     | Storage                | Local files                 | Custom / Mem0                |
-|                     | Cross-session Support  | ✅                           | ✅                           |
-| **Personalization** | User-specific Memory   | ❌                          |  ✅                           |
-|                     | Custom Providers       | Limited                     | Any provider                 |
-| **Use Case Fit**    | Recommended For        | Most general use cases      | Specialized / custom needs   |
+## Memory System Comparison
 
+| Feature | Basic Memory | User Memory (Legacy) | External Memory |
+|---------|-------------|---------------------|----------------|
+| **Setup Complexity** | Simple | Medium | Medium |
+| **Integration** | Built-in contextual | Contextual + User-specific | Standalone |
+| **Storage** | Local files | Mem0 Cloud/Local | Custom/Mem0 |
+| **Cross-session** | ✅ | ✅ | ✅ |
+| **User-specific** | ❌ | ✅ | ✅ |
+| **Custom providers** | Limited | Mem0 only | Any provider |
+| **Recommended for** | Most use cases | Legacy projects | Specialized needs |
 
 ## Supported Embedding Providers
 
@@ -1027,201 +986,7 @@ crew = Crew(
 - 🫡 **Enhanced Personalization:** Memory enables agents to remember user preferences and historical interactions, leading to personalized experiences.
 - 🧠 **Improved Problem Solving:** Access to a rich memory store aids agents in making more informed decisions, drawing on past learnings and contextual insights.
 
-## Memory Events
-
-CrewAI's event system provides powerful insights into memory operations. By leveraging memory events, you can monitor, debug, and optimize your memory system's performance and behavior.
-
-### Available Memory Events
-
-CrewAI emits the following memory-related events:
-
-| Event | Description | Key Properties |
-| :---- | :---------- | :------------- |
-| **MemoryQueryStartedEvent** | Emitted when a memory query begins | `query`, `limit`, `score_threshold` |
-| **MemoryQueryCompletedEvent** | Emitted when a memory query completes successfully | `query`, `results`, `limit`, `score_threshold`, `query_time_ms` |
-| **MemoryQueryFailedEvent** | Emitted when a memory query fails | `query`, `limit`, `score_threshold`, `error` |
-| **MemorySaveStartedEvent** | Emitted when a memory save operation begins | `value`, `metadata`, `agent_role` |
-| **MemorySaveCompletedEvent** | Emitted when a memory save operation completes successfully | `value`, `metadata`, `agent_role`, `save_time_ms` |
-| **MemorySaveFailedEvent** | Emitted when a memory save operation fails | `value`, `metadata`, `agent_role`, `error` |
-| **MemoryRetrievalStartedEvent** | Emitted when memory retrieval for a task prompt starts | `task_id` |
-| **MemoryRetrievalCompletedEvent** | Emitted when memory retrieval completes successfully | `task_id`, `memory_content`, `retrieval_time_ms` |
-
-### Practical Applications
-
-#### 1. Memory Performance Monitoring
-
-Track memory operation timing to optimize your application:
-
-```python
-from crewai.events import (
-    BaseEventListener,
-    MemoryQueryCompletedEvent,
-    MemorySaveCompletedEvent
-)
-import time
-
-class MemoryPerformanceMonitor(BaseEventListener):
-    def __init__(self):
-        super().__init__()
-        self.query_times = []
-        self.save_times = []
-
-    def setup_listeners(self, crewai_event_bus):
-        @crewai_event_bus.on(MemoryQueryCompletedEvent)
-        def on_memory_query_completed(source, event: MemoryQueryCompletedEvent):
-            self.query_times.append(event.query_time_ms)
-            print(f"Memory query completed in {event.query_time_ms:.2f}ms. Query: '{event.query}'")
-            print(f"Average query time: {sum(self.query_times)/len(self.query_times):.2f}ms")
-
-        @crewai_event_bus.on(MemorySaveCompletedEvent)
-        def on_memory_save_completed(source, event: MemorySaveCompletedEvent):
-            self.save_times.append(event.save_time_ms)
-            print(f"Memory save completed in {event.save_time_ms:.2f}ms")
-            print(f"Average save time: {sum(self.save_times)/len(self.save_times):.2f}ms")
-
-# Create an instance of your listener
-memory_monitor = MemoryPerformanceMonitor()
-```
-
-#### 2. Memory Content Logging
-
-Log memory operations for debugging and insights:
-
-```python
-from crewai.events import (
-    BaseEventListener,
-    MemorySaveStartedEvent,
-    MemoryQueryStartedEvent,
-    MemoryRetrievalCompletedEvent
-)
-import logging
-
-# Configure logging
-logger = logging.getLogger('memory_events')
-
-class MemoryLogger(BaseEventListener):
-    def setup_listeners(self, crewai_event_bus):
-        @crewai_event_bus.on(MemorySaveStartedEvent)
-        def on_memory_save_started(source, event: MemorySaveStartedEvent):
-            if event.agent_role:
-                logger.info(f"Agent '{event.agent_role}' saving memory: {event.value[:50]}...")
-            else:
-                logger.info(f"Saving memory: {event.value[:50]}...")
-
-        @crewai_event_bus.on(MemoryQueryStartedEvent)
-        def on_memory_query_started(source, event: MemoryQueryStartedEvent):
-            logger.info(f"Memory query started: '{event.query}' (limit: {event.limit})")
-
-        @crewai_event_bus.on(MemoryRetrievalCompletedEvent)
-        def on_memory_retrieval_completed(source, event: MemoryRetrievalCompletedEvent):
-            if event.task_id:
-                logger.info(f"Memory retrieved for task {event.task_id} in {event.retrieval_time_ms:.2f}ms")
-            else:
-                logger.info(f"Memory retrieved in {event.retrieval_time_ms:.2f}ms")
-            logger.debug(f"Memory content: {event.memory_content}")
-
-# Create an instance of your listener
-memory_logger = MemoryLogger()
-```
-
-#### 3. Error Tracking and Notifications
-
-Capture and respond to memory errors:
-
-```python
-from crewai.events import (
-    BaseEventListener,
-    MemorySaveFailedEvent,
-    MemoryQueryFailedEvent
-)
-import logging
-from typing import Optional
-
-# Configure logging
-logger = logging.getLogger('memory_errors')
-
-class MemoryErrorTracker(BaseEventListener):
-    def __init__(self, notify_email: Optional[str] = None):
-        super().__init__()
-        self.notify_email = notify_email
-        self.error_count = 0
-
-    def setup_listeners(self, crewai_event_bus):
-        @crewai_event_bus.on(MemorySaveFailedEvent)
-        def on_memory_save_failed(source, event: MemorySaveFailedEvent):
-            self.error_count += 1
-            agent_info = f"Agent '{event.agent_role}'" if event.agent_role else "Unknown agent"
-            error_message = f"Memory save failed: {event.error}. {agent_info}"
-            logger.error(error_message)
-
-            if self.notify_email and self.error_count % 5 == 0:
-                self._send_notification(error_message)
-
-        @crewai_event_bus.on(MemoryQueryFailedEvent)
-        def on_memory_query_failed(source, event: MemoryQueryFailedEvent):
-            self.error_count += 1
-            error_message = f"Memory query failed: {event.error}. Query: '{event.query}'"
-            logger.error(error_message)
-
-            if self.notify_email and self.error_count % 5 == 0:
-                self._send_notification(error_message)
-
-    def _send_notification(self, message):
-        # Implement your notification system (email, Slack, etc.)
-        print(f"[NOTIFICATION] Would send to {self.notify_email}: {message}")
-
-# Create an instance of your listener
-error_tracker = MemoryErrorTracker(notify_email="admin@example.com")
-```
-
-### Integrating with Analytics Platforms
-
-Memory events can be forwarded to analytics and monitoring platforms to track performance metrics, detect anomalies, and visualize memory usage patterns:
-
-```python
-from crewai.events import (
-    BaseEventListener,
-    MemoryQueryCompletedEvent,
-    MemorySaveCompletedEvent
-)
-
-class MemoryAnalyticsForwarder(BaseEventListener):
-    def __init__(self, analytics_client):
-        super().__init__()
-        self.client = analytics_client
-
-    def setup_listeners(self, crewai_event_bus):
-        @crewai_event_bus.on(MemoryQueryCompletedEvent)
-        def on_memory_query_completed(source, event: MemoryQueryCompletedEvent):
-            # Forward query metrics to analytics platform
-            self.client.track_metric({
-                "event_type": "memory_query",
-                "query": event.query,
-                "duration_ms": event.query_time_ms,
-                "result_count": len(event.results) if hasattr(event.results, "__len__") else 0,
-                "timestamp": event.timestamp
-            })
-
-        @crewai_event_bus.on(MemorySaveCompletedEvent)
-        def on_memory_save_completed(source, event: MemorySaveCompletedEvent):
-            # Forward save metrics to analytics platform
-            self.client.track_metric({
-                "event_type": "memory_save",
-                "agent_role": event.agent_role,
-                "duration_ms": event.save_time_ms,
-                "timestamp": event.timestamp
-            })
-```
-
-### Best Practices for Memory Event Listeners
-
-1. **Keep handlers lightweight**: Avoid complex processing in event handlers to prevent performance impacts
-2. **Use appropriate logging levels**: Use INFO for normal operations, DEBUG for details, ERROR for issues
-3. **Batch metrics when possible**: Accumulate metrics before sending to external systems
-4. **Handle exceptions gracefully**: Ensure your event handlers don't crash due to unexpected data
-5. **Consider memory consumption**: Be mindful of storing large amounts of event data
-
 ## Conclusion
 
-Integrating CrewAI's memory system into your projects is straightforward. By leveraging the provided memory components and configurations,
+Integrating CrewAI's memory system into your projects is straightforward. By leveraging the provided memory components and configurations, 
 you can quickly empower your agents with the ability to remember, reason, and learn from their interactions, unlocking new levels of intelligence and capability.

concepts/planning.mdx

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

concepts/processes.mdx

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

concepts/reasoning.mdx

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

concepts/tasks.mdx

@@ -2,7 +2,6 @@
 title: Tasks
 description: Detailed guide on managing and creating tasks within the CrewAI framework.
 icon: list-check
-mode: "wide"
 ---
 
 ## Overview
@@ -14,7 +13,7 @@ Tasks provide all necessary details for execution, such as a description, the ag
 Tasks within CrewAI can be collaborative, requiring multiple agents to work together. This is managed through the task properties and orchestrated by the Crew's process, enhancing teamwork and efficiency.
 
 <Note type="info" title="Enterprise Enhancement: Visual Task Builder">
-CrewAI AMP includes a Visual Task Builder in Crew Studio that simplifies complex task creation and chaining. Design your task flows visually and test them in real-time without writing code.
+CrewAI Enterprise includes a Visual Task Builder in Crew Studio that simplifies complex task creation and chaining. Design your task flows visually and test them in real-time without writing code.
 
 ![Task Builder Screenshot](/images/enterprise/crew-studio-interface.png)
 
@@ -55,17 +54,9 @@ crew = Crew(
 | **Markdown** _(optional)_        | `markdown`        | `Optional[bool]`              | Whether the task should instruct the agent to return the final answer formatted in Markdown. Defaults to False.      |
 | **Config** _(optional)_          | `config`          | `Optional[Dict[str, Any]]`    | Task-specific configuration parameters.                                                                              |
 | **Output File** _(optional)_     | `output_file`     | `Optional[str]`               | File path for storing the task output.                                                                               |
-| **Create Directory** _(optional)_ | `create_directory` | `Optional[bool]`             | Whether to create the directory for output_file if it doesn't exist. Defaults to True.                               |
 | **Output JSON** _(optional)_     | `output_json`     | `Optional[Type[BaseModel]]`   | A Pydantic model to structure the JSON output.                                                                       |
 | **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
 
@@ -75,7 +66,7 @@ There are two ways to create tasks in CrewAI: using **YAML configuration (recomm
 
 Using YAML configuration provides a cleaner, more maintainable way to define tasks. We strongly recommend using this approach to define tasks in your CrewAI projects.
 
-After creating your CrewAI project as outlined in the [Installation](/en/installation) section, navigate to the `src/latest_ai_development/config/tasks.yaml` file and modify the template to match your specific task requirements.
+After creating your CrewAI project as outlined in the [Installation](/installation) section, navigate to the `src/latest_ai_development/config/tasks.yaml` file and modify the template to match your specific task requirements.
 
 <Note>
 Variables in your YAML files (like `{topic}`) will be replaced with values from your inputs when running the crew:
@@ -286,7 +277,7 @@ formatted_task = Task(
 
 When `markdown=True`, the agent will receive additional instructions to format the output using:
 - `#` for headers
-- `**text**` for bold text
+- `**text**` for bold text  
 - `*text*` for italic text
 - `-` or `*` for bullet points
 - `` `code` `` for inline code
@@ -341,11 +332,9 @@ Task guardrails provide a way to validate and transform task outputs before they
 are passed to the next task. This feature helps ensure data quality and provides
 feedback to agents when their output doesn't meet specific criteria.
 
-Guardrails are implemented as Python functions that contain custom validation logic, giving you complete control over the validation process and ensuring reliable, deterministic results.
+### Using Task Guardrails
 
-### Function-Based Guardrails
-
-To add a function-based guardrail to a task, provide a validation function through the `guardrail` parameter:
+To add a guardrail to a task, provide a validation function through the `guardrail` parameter:
 
 ```python Code
 from typing import Tuple, Union, Dict, Any
@@ -383,7 +372,9 @@ blog_task = Task(
    - On success: it returns a tuple of `(bool, Any)`. For example: `(True, validated_result)`
    - On Failure: it returns a tuple of `(bool, str)`. For example: `(False, "Error message explain the failure")`
 
+### LLMGuardrail
 
+The `LLMGuardrail` class offers a robust mechanism for validating task outputs.
 
 ### Error Handling Best Practices
 
@@ -438,7 +429,7 @@ 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 (`guardrail_max_retries`)
+   - Maximum retries are reached
 
 Example with retry handling:
 ```python Code
@@ -459,7 +450,7 @@ task = Task(
     expected_output="A valid JSON object",
     agent=analyst,
     guardrail=validate_json_output,
-    guardrail_max_retries=3  # Limit retry attempts
+    max_retries=3  # Limit retry attempts
 )
 ```
 
@@ -807,103 +798,197 @@ While creating and executing tasks, certain validation mechanisms are in place t
 
 These validations help in maintaining the consistency and reliability of task executions within the crewAI framework.
 
+## Task Guardrails
 
+Task guardrails provide a powerful way to validate, transform, or filter task outputs before they are passed to the next task. Guardrails are optional functions that execute before the next task starts, allowing you to ensure that task outputs meet specific requirements or formats.
+
+### Basic Usage
+
+#### Define your own logic to validate
+
+```python Code
+from typing import Tuple, Union
+from crewai import Task
+
+def validate_json_output(result: str) -> Tuple[bool, Union[dict, str]]:
+    """Validate that the output is valid JSON."""
+    try:
+        json_data = json.loads(result)
+        return (True, json_data)
+    except json.JSONDecodeError:
+        return (False, "Output must be valid JSON")
+
+task = Task(
+    description="Generate JSON data",
+    expected_output="Valid JSON object",
+    guardrail=validate_json_output
+)
+```
+
+#### Leverage a no-code approach for validation
+
+```python Code
+from crewai import Task
+
+task = Task(
+    description="Generate JSON data",
+    expected_output="Valid JSON object",
+    guardrail="Ensure the response is a valid JSON object"
+)
+```
+
+#### Using YAML
+
+```yaml
+research_task:
+  ...
+  guardrail: make sure each bullet contains a minimum of 100 words
+  ...
+```
+
+```python Code
+@CrewBase
+class InternalCrew:
+    agents_config = "config/agents.yaml"
+    tasks_config = "config/tasks.yaml"
+
+    ...
+    @task
+    def research_task(self):
+        return Task(config=self.tasks_config["research_task"])  # type: ignore[index]
+    ...
+```
+
+
+#### Use custom models for code generation
+
+```python Code
+from crewai import Task
+from crewai.llm import LLM
+
+task = Task(
+    description="Generate JSON data",
+    expected_output="Valid JSON object",
+    guardrail=LLMGuardrail(
+        description="Ensure the response is a valid JSON object",
+        llm=LLM(model="gpt-4o-mini"),
+    )
+)
+```
+
+### How Guardrails Work
+
+1. **Optional Attribute**: Guardrails are an optional attribute at the task level, allowing you to add validation only where needed.
+2. **Execution Timing**: The guardrail function is executed before the next task starts, ensuring valid data flow between tasks.
+3. **Return Format**: Guardrails must return a tuple of `(success, data)`:
+   - If `success` is `True`, `data` is the validated/transformed result
+   - If `success` is `False`, `data` is the error message
+4. **Result Routing**:
+   - On success (`True`), the result is automatically passed to the next task
+   - On failure (`False`), the error is sent back to the agent to generate a new answer
+
+### Common Use Cases
+
+#### Data Format Validation
+```python Code
+def validate_email_format(result: str) -> Tuple[bool, Union[str, str]]:
+    """Ensure the output contains a valid email address."""
+    import re
+    email_pattern = r'^[\w\.-]+@[\w\.-]+\.\w+$'
+    if re.match(email_pattern, result.strip()):
+        return (True, result.strip())
+    return (False, "Output must be a valid email address")
+```
+
+#### Content Filtering
+```python Code
+def filter_sensitive_info(result: str) -> Tuple[bool, Union[str, str]]:
+    """Remove or validate sensitive information."""
+    sensitive_patterns = ['SSN:', 'password:', 'secret:']
+    for pattern in sensitive_patterns:
+        if pattern.lower() in result.lower():
+            return (False, f"Output contains sensitive information ({pattern})")
+    return (True, result)
+```
+
+#### Data Transformation
+```python Code
+def normalize_phone_number(result: str) -> Tuple[bool, Union[str, str]]:
+    """Ensure phone numbers are in a consistent format."""
+    import re
+    digits = re.sub(r'\D', '', result)
+    if len(digits) == 10:
+        formatted = f"({digits[:3]}) {digits[3:6]}-{digits[6:]}"
+        return (True, formatted)
+    return (False, "Output must be a 10-digit phone number")
+```
+
+### Advanced Features
+
+#### Chaining Multiple Validations
+```python Code
+def chain_validations(*validators):
+    """Chain multiple validators together."""
+    def combined_validator(result):
+        for validator in validators:
+            success, data = validator(result)
+            if not success:
+                return (False, data)
+            result = data
+        return (True, result)
+    return combined_validator
+
+# Usage
+task = Task(
+    description="Get user contact info",
+    expected_output="Email and phone",
+    guardrail=chain_validations(
+        validate_email_format,
+        filter_sensitive_info
+    )
+)
+```
+
+#### Custom Retry Logic
+```python Code
+task = Task(
+    description="Generate data",
+    expected_output="Valid data",
+    guardrail=validate_data,
+    max_retries=5  # Override default retry limit
+)
+```
 
 ## Creating Directories when Saving Files
 
-The `create_directory` parameter controls whether CrewAI should automatically create directories when saving task outputs to files. This feature is particularly useful for organizing outputs and ensuring that file paths are correctly structured, especially when working with complex project hierarchies.
-
-### Default Behavior
-
-By default, `create_directory=True`, which means CrewAI will automatically create any missing directories in the output file path:
+You can now specify if a task should create directories when saving its output to a file. This is particularly useful for organizing outputs and ensuring that file paths are correctly structured.
 
 ```python Code
-# Default behavior - directories are created automatically
-report_task = Task(
-    description='Generate a comprehensive market analysis report',
-    expected_output='A detailed market analysis with charts and insights',
-    agent=analyst_agent,
-    output_file='reports/2025/market_analysis.md',  # Creates 'reports/2025/' if it doesn't exist
-    markdown=True
+# ...
+
+save_output_task = Task(
+    description='Save the summarized AI news to a file',
+    expected_output='File saved successfully',
+    agent=research_agent,
+    tools=[file_save_tool],
+    output_file='outputs/ai_news_summary.txt',
+    create_directory=True
 )
-```
 
-### Disabling Directory Creation
-
-If you want to prevent automatic directory creation and ensure that the directory already exists, set `create_directory=False`:
-
-```python Code
-# Strict mode - directory must already exist
-strict_output_task = Task(
-    description='Save critical data that requires existing infrastructure',
-    expected_output='Data saved to pre-configured location',
-    agent=data_agent,
-    output_file='secure/vault/critical_data.json',
-    create_directory=False  # Will raise RuntimeError if 'secure/vault/' doesn't exist
-)
-```
-
-### YAML Configuration
-
-You can also configure this behavior in your YAML task definitions:
-
-```yaml tasks.yaml
-analysis_task:
-  description: >
-    Generate quarterly financial analysis
-  expected_output: >
-    A comprehensive financial report with quarterly insights
-  agent: financial_analyst
-  output_file: reports/quarterly/q4_2024_analysis.pdf
-  create_directory: true  # Automatically create 'reports/quarterly/' directory
-
-audit_task:
-  description: >
-    Perform compliance audit and save to existing audit directory
-  expected_output: >
-    A compliance audit report
-  agent: auditor
-  output_file: audit/compliance_report.md
-  create_directory: false  # Directory must already exist
-```
-
-### Use Cases
-
-**Automatic Directory Creation (`create_directory=True`):**
-- Development and prototyping environments
-- Dynamic report generation with date-based folders
-- Automated workflows where directory structure may vary
-- Multi-tenant applications with user-specific folders
-
-**Manual Directory Management (`create_directory=False`):**
-- Production environments with strict file system controls
-- Security-sensitive applications where directories must be pre-configured
-- Systems with specific permission requirements
-- Compliance environments where directory creation is audited
-
-### Error Handling
-
-When `create_directory=False` and the directory doesn't exist, CrewAI will raise a `RuntimeError`:
-
-```python Code
-try:
-    result = crew.kickoff()
-except RuntimeError as e:
-    # Handle missing directory error
-    print(f"Directory creation failed: {e}")
-    # Create directory manually or use fallback location
+#...
 ```
 
 Check out the video below to see how to use structured outputs in CrewAI:
 
 <iframe
-  className="w-full aspect-video rounded-xl"
+  width="560"
+  height="315"
   src="https://www.youtube.com/embed/dNpKQk5uxHw"
-  title="Structured outputs in CrewAI"
-  frameBorder="0"
+  title="YouTube video player"
+  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

concepts/testing.mdx

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

concepts/tools.mdx

@@ -2,7 +2,6 @@
 title: Tools
 description: Understanding and leveraging tools within the CrewAI framework for agent collaboration and task execution.
 icon: screwdriver-wrench
-mode: "wide"
 ---
 
 ## Overview
@@ -17,7 +16,7 @@ This includes tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/cre
 enabling everything from simple searches to complex interactions and effective teamwork among agents.
 
 <Note type="info" title="Enterprise Enhancement: Tools Repository">
-CrewAI AMP provides a comprehensive Tools Repository with pre-built integrations for common business systems and APIs. Deploy agents with enterprise tools in minutes instead of days.
+CrewAI Enterprise provides a comprehensive Tools Repository with pre-built integrations for common business systems and APIs. Deploy agents with enterprise tools in minutes instead of days.
 
 The Enterprise Tools Repository includes:
 - Pre-built connectors for popular enterprise systems
@@ -208,7 +207,7 @@ from crewai.tools import BaseTool
 class AsyncCustomTool(BaseTool):
     name: str = "async_custom_tool"
     description: str = "An asynchronous custom tool"
-
+    
     async def _run(self, query: str = "") -> str:
         """Asynchronously run the tool"""
         # Your async implementation here

concepts/training.mdx

@@ -0,0 +1,67 @@
+---
+title: Training
+description: Learn how to train your CrewAI agents by giving them feedback early on and get consistent results.
+icon: dumbbell
+---
+
+## Overview
+
+The training feature in CrewAI allows you to train your AI agents using the command-line interface (CLI). 
+By running the command `crewai train -n <n_iterations>`, you can specify the number of iterations for the training process.
+
+During training, CrewAI utilizes techniques to optimize the performance of your agents along with human feedback. 
+This helps the agents improve their understanding, decision-making, and problem-solving abilities.
+
+### Training Your Crew Using the CLI
+
+To use the training feature, follow these steps:
+
+1. Open your terminal or command prompt.
+2. Navigate to the directory where your CrewAI project is located.
+3. Run the following command:
+
+```shell
+crewai train -n <n_iterations> <filename> (optional)
+```
+<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
+
+To train your crew programmatically, use the following steps:
+
+1. Define the number of iterations for training.
+2. Specify the input parameters for the training process.
+3. Execute the training command within a try-except block to handle potential errors.
+
+```python Code
+n_iterations = 2
+inputs = {"topic": "CrewAI Training"}
+filename = "your_model.pkl"
+
+try:
+    YourCrewName_Crew().crew().train(
+      n_iterations=n_iterations, 
+      inputs=inputs, 
+      filename=filename
+    )
+
+except Exception as e:
+    raise Exception(f"An error occurred while training the crew: {e}")
+```
+
+### 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.
+
+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.
+
+Happy training with CrewAI! 🚀
+  

docs.json

@@ -0,0 +1,410 @@
+{
+  "$schema": "https://mintlify.com/docs.json",
+  "theme": "mint",
+  "name": "CrewAI",
+  "colors": {
+    "primary": "#EB6658",
+    "light": "#F3A78B",
+    "dark": "#C94C3C"
+  },
+  "favicon": "images/favicon.svg",
+  "contextual": {
+    "options": [
+      "copy",
+      "view",
+      "chatgpt",
+      "claude"
+    ]
+  },
+  "navigation": {
+    "tabs": [
+      {
+        "tab": "Documentation",
+        "groups": [
+          {
+            "group": "Get Started",
+            "pages": [
+              "introduction",
+              "installation",
+              "quickstart"
+            ]
+          },
+          {
+            "group": "Guides",
+            "pages": [
+              {
+                "group": "Strategy",
+                "pages": [
+                  "guides/concepts/evaluating-use-cases"
+                ]
+              },
+              {
+                "group": "Agents",
+                "pages": [
+                  "guides/agents/crafting-effective-agents"
+                ]
+              },
+              {
+                "group": "Crews",
+                "pages": [
+                  "guides/crews/first-crew"
+                ]
+              },
+              {
+                "group": "Flows",
+                "pages": [
+                  "guides/flows/first-flow",
+                  "guides/flows/mastering-flow-state"
+                ]
+              },
+              {
+                "group": "Advanced",
+                "pages": [
+                  "guides/advanced/customizing-prompts",
+                  "guides/advanced/fingerprinting"
+                ]
+              }
+            ]
+          },
+          {
+            "group": "Core Concepts",
+            "pages": [
+              "concepts/agents",
+              "concepts/tasks",
+              "concepts/crews",
+              "concepts/flows",
+              "concepts/knowledge",
+              "concepts/llms",
+              "concepts/processes",
+              "concepts/collaboration",
+              "concepts/training",
+              "concepts/memory",
+              "concepts/reasoning",
+              "concepts/planning",
+              "concepts/testing",
+              "concepts/cli",
+              "concepts/tools",
+              "concepts/event-listener"
+            ]
+          },
+          {
+            "group": "MCP Integration",
+            "pages": [
+              "mcp/overview",
+              "mcp/stdio",
+              "mcp/sse",
+              "mcp/streamable-http",
+              "mcp/multiple-servers",
+              "mcp/security"
+            ]
+          },
+          {
+            "group": "Tools",
+            "pages": [
+              "tools/overview",
+              {
+                "group": "File & Document",
+                "pages": [
+                  "tools/file-document/overview",
+                  "tools/file-document/filereadtool",
+                  "tools/file-document/filewritetool",
+                  "tools/file-document/pdfsearchtool",
+                  "tools/file-document/docxsearchtool",
+                  "tools/file-document/mdxsearchtool",
+                  "tools/file-document/xmlsearchtool",
+                  "tools/file-document/txtsearchtool",
+                  "tools/file-document/jsonsearchtool",
+                  "tools/file-document/csvsearchtool",
+                  "tools/file-document/directorysearchtool",
+                  "tools/file-document/directoryreadtool"
+                ]
+              },
+              {
+                "group": "Web Scraping & Browsing",
+                "pages": [
+                  "tools/web-scraping/overview",
+                  "tools/web-scraping/scrapewebsitetool",
+                  "tools/web-scraping/scrapeelementfromwebsitetool",
+                  "tools/web-scraping/scrapflyscrapetool",
+                  "tools/web-scraping/seleniumscrapingtool",
+                  "tools/web-scraping/scrapegraphscrapetool",
+                  "tools/web-scraping/spidertool",
+                  "tools/web-scraping/browserbaseloadtool",
+                  "tools/web-scraping/hyperbrowserloadtool",
+                  "tools/web-scraping/stagehandtool",
+                  "tools/web-scraping/firecrawlcrawlwebsitetool",
+                  "tools/web-scraping/firecrawlscrapewebsitetool",
+                  "tools/web-scraping/firecrawlsearchtool"
+                ]
+              },
+              {
+                "group": "Search & Research",
+                "pages": [
+                  "tools/search-research/overview",
+                  "tools/search-research/serperdevtool",
+                  "tools/search-research/bravesearchtool",
+                  "tools/search-research/exasearchtool",
+                  "tools/search-research/linkupsearchtool",
+                  "tools/search-research/githubsearchtool",
+                  "tools/search-research/websitesearchtool",
+                  "tools/search-research/codedocssearchtool",
+                  "tools/search-research/youtubechannelsearchtool",
+                  "tools/search-research/youtubevideosearchtool"
+                ]
+              },
+              {
+                "group": "Database & Data",
+                "pages": [
+                  "tools/database-data/overview",
+                  "tools/database-data/mysqltool",
+                  "tools/database-data/pgsearchtool",
+                  "tools/database-data/snowflakesearchtool",
+                  "tools/database-data/nl2sqltool",
+                  "tools/database-data/qdrantvectorsearchtool",
+                  "tools/database-data/weaviatevectorsearchtool"
+                ]
+              },
+              {
+                "group": "AI & Machine Learning",
+                "pages": [
+                  "tools/ai-ml/overview",
+                  "tools/ai-ml/dalletool",
+                  "tools/ai-ml/visiontool",
+                  "tools/ai-ml/aimindtool",
+                  "tools/ai-ml/llamaindextool",
+                  "tools/ai-ml/langchaintool",
+                  "tools/ai-ml/ragtool",
+                  "tools/ai-ml/codeinterpretertool"
+                ]
+              },
+              {
+                "group": "Cloud & Storage",
+                "pages": [
+                  "tools/cloud-storage/overview",
+                  "tools/cloud-storage/s3readertool",
+                  "tools/cloud-storage/s3writertool",
+                  "tools/cloud-storage/bedrockinvokeagenttool",
+                  "tools/cloud-storage/bedrockkbretriever"
+                ]
+              },
+              {
+                "group": "Automation & Integration",
+                "pages": [
+                  "tools/automation/overview",
+                  "tools/automation/apifyactorstool",
+                  "tools/automation/composiotool",
+                  "tools/automation/multiontool"
+                ]
+              }
+            ]
+          },
+          {
+            "group": "Observability",
+            "pages": [
+              "observability/overview",
+              "observability/agentops",
+              "observability/arize-phoenix",
+              "observability/langfuse",
+              "observability/langtrace",
+              "observability/maxim",
+              "observability/mlflow",
+              "observability/openlit",
+              "observability/opik",
+              "observability/patronus-evaluation",
+              "observability/portkey",
+              "observability/weave"
+            ]
+          },
+          {
+            "group": "Learn",
+            "pages": [
+              "learn/overview",
+              "learn/llm-selection-guide",
+              "learn/conditional-tasks",
+              "learn/coding-agents",
+              "learn/create-custom-tools",
+              "learn/custom-llm",
+              "learn/custom-manager-agent",
+              "learn/customizing-agents",
+              "learn/dalle-image-generation",
+              "learn/force-tool-output-as-result",
+              "learn/hierarchical-process",
+              "learn/human-input-on-execution",
+              "learn/kickoff-async",
+              "learn/kickoff-for-each",
+              "learn/llm-connections",
+              "learn/multimodal-agents",
+              "learn/replay-tasks-from-latest-crew-kickoff",
+              "learn/sequential-process",
+              "learn/using-annotations"
+            ]
+          },
+          {
+            "group": "Telemetry",
+            "pages": [
+              "telemetry"
+            ]
+          }
+        ]
+      },
+      {
+        "tab": "Enterprise",
+        "groups": [
+          {
+            "group": "Getting Started",
+            "pages": [
+              "enterprise/introduction"
+            ]
+          },
+          {
+            "group": "Features",
+            "pages": [
+              "enterprise/features/tool-repository",
+              "enterprise/features/webhook-streaming",
+              "enterprise/features/traces",
+              "enterprise/features/hallucination-guardrail",
+              "enterprise/features/integrations"
+            ]
+          },
+          {
+            "group": "How-To Guides",
+            "pages": [
+              "enterprise/guides/build-crew",
+              "enterprise/guides/deploy-crew",
+              "enterprise/guides/kickoff-crew",
+              "enterprise/guides/update-crew",
+              "enterprise/guides/enable-crew-studio",
+              "enterprise/guides/azure-openai-setup",
+              "enterprise/guides/hubspot-trigger",
+              "enterprise/guides/react-component-export",
+              "enterprise/guides/salesforce-trigger",
+              "enterprise/guides/slack-trigger",
+              "enterprise/guides/team-management",
+              "enterprise/guides/webhook-automation",
+              "enterprise/guides/human-in-the-loop",
+              "enterprise/guides/zapier-trigger"
+            ]
+          },
+          {
+            "group": "Resources",
+            "pages": [
+              "enterprise/resources/frequently-asked-questions"
+            ]
+          }
+        ]
+      },
+      {
+        "tab": "API Reference",
+        "groups": [
+          {
+            "group": "Getting Started",
+            "pages": [
+              "api-reference/introduction"
+            ]
+          },
+          {
+            "group": "Endpoints",
+            "openapi": "enterprise-api.yaml"
+          }
+        ]
+      },
+      {
+        "tab": "Examples",
+        "groups": [
+          {
+            "group": "Examples",
+            "pages": [
+              "examples/example"
+            ]
+          }
+        ]
+      },
+      {
+        "tab": "Releases",
+        "groups": [
+          {
+            "group": "Releases",
+            "pages": [
+              "changelog"
+            ]
+          }
+        ]
+      }
+    ],
+    "global": {
+      "anchors": [
+        {
+          "anchor": "Website",
+          "href": "https://crewai.com",
+          "icon": "globe"
+        },
+        {
+          "anchor": "Forum",
+          "href": "https://community.crewai.com",
+          "icon": "discourse"
+        },
+        {
+          "anchor": "Crew GPT",
+          "href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
+          "icon": "robot"
+        },
+        {
+          "anchor": "Get Help",
+          "href": "mailto:support@crewai.com",
+          "icon": "headset"
+        }
+      ]
+    }
+  },
+  "logo": {
+    "light": "images/crew_only_logo.png",
+    "dark": "images/crew_only_logo.png"
+  },
+  "appearance": {
+    "default": "dark",
+    "strict": false
+  },
+  "navbar": {
+    "links": [
+      {
+        "label": "Start Cloud Trial",
+        "href": "https://app.crewai.com"
+      }
+    ],
+    "primary": {
+      "type": "github",
+      "href": "https://github.com/crewAIInc/crewAI"
+    }
+  },
+  "search": {
+    "prompt": "Search CrewAI docs"
+  },
+  "api": {
+    "baseUrl": "https://your-actual-crew-name.crewai.com",
+    "auth": {
+      "method": "bearer",
+      "name": "Authorization"
+    },
+    "playground": {
+      "mode": "simple"
+    }
+  },
+  "seo": {
+    "indexing": "all"
+  },
+  "errors": {
+    "404": {
+      "redirect": true
+    }
+  },
+  "footer": {
+    "socials": {
+      "website": "https://crewai.com",
+      "x": "https://x.com/crewAIInc",
+      "github": "https://github.com/crewAIInc/crewAI",
+      "linkedin": "https://www.linkedin.com/company/crewai-inc",
+      "youtube": "https://youtube.com/@crewAIInc",
+      "reddit": "https://www.reddit.com/r/crewAIInc/"
+    }
+  }
+}

docs/en/api-reference/inputs.mdx

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

docs/en/api-reference/kickoff.mdx

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

docs/en/api-reference/resume.mdx

@@ -1,6 +0,0 @@
----
-title: "POST /resume"
-description: "Resume crew execution with human feedback"
-openapi: "/enterprise-api.en.yaml POST /resume"
-mode: "wide"
----

docs/en/api-reference/status.mdx

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

docs/en/concepts/training.mdx

@@ -1,197 +0,0 @@
----
-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
-
-The training feature in CrewAI allows you to train your AI agents using the command-line interface (CLI).
-By running the command `crewai train -n <n_iterations>`, you can specify the number of iterations for the training process.
-
-During training, CrewAI utilizes techniques to optimize the performance of your agents along with human feedback.
-This helps the agents improve their understanding, decision-making, and problem-solving abilities.
-
-### Training Your Crew Using the CLI
-
-To use the training feature, follow these steps:
-
-1. Open your terminal or command prompt.
-2. Navigate to the directory where your CrewAI project is located.
-3. Run the following command:
-
-```shell
-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>
-
-<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:
-
-1. Define the number of iterations for training.
-2. Specify the input parameters for the training process.
-3. Execute the training command within a try-except block to handle potential errors.
-
-```python Code
-n_iterations = 2
-inputs = {"topic": "CrewAI Training"}
-filename = "your_model.pkl"
-
-try:
-    YourCrewName_Crew().crew().train(
-      n_iterations=n_iterations,
-      inputs=inputs,
-      filename=filename
-    )
-
-except Exception as e:
-    raise Exception(f"An error occurred while training the crew: {e}")
-```
-
-## How trained data is used by agents
-
-CrewAI uses the training artifacts in two ways: during training to incorporate your human feedback, and after training to guide agents with consolidated suggestions.
-
-### Training data flow
-
-```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"]
-
-  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
-
-  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
-
-<Warning>
-  When using smaller language models (≤7B parameters) for training data evaluation, be aware that they may face challenges with generating structured outputs and following complex instructions.
-</Warning>
-
-### Limitations of Small Models in Training Evaluation
-
-<CardGroup cols={2}>
-  <Card title="JSON Output Accuracy" icon="triangle-exclamation">
-    Smaller models often struggle with producing valid JSON responses needed for structured training evaluations, leading to parsing errors and incomplete data.
-  </Card>
-  <Card title="Evaluation Quality" icon="chart-line">
-    Models under 7B parameters may provide less nuanced evaluations with limited reasoning depth compared to larger models.
-  </Card>
-  <Card title="Instruction Following" icon="list-check">
-    Complex training evaluation criteria may not be fully followed or considered by smaller models.
-  </Card>
-  <Card title="Consistency" icon="rotate">
-    Evaluations across multiple training iterations may lack consistency with smaller models.
-  </Card>
-</CardGroup>
-
-### Recommendations for Training
-
-<Tabs>
-  <Tab title="Best Practice">
-    For optimal training quality and reliable evaluations, we strongly recommend using models with at least 7B parameters or larger:
-
-    ```python
-    from crewai import Agent, Crew, Task, LLM
-
-    # Recommended minimum for training evaluation
-    llm = LLM(model="mistral/open-mistral-7b")
-
-    # Better options for reliable training evaluation
-    llm = LLM(model="anthropic/claude-3-sonnet-20240229-v1:0")
-    llm = LLM(model="gpt-4o")
-
-    # Use this LLM with your agents
-    agent = Agent(
-        role="Training Evaluator",
-        goal="Provide accurate training feedback",
-        llm=llm
-    )
-    ```
-
-    <Tip>
-      More powerful models provide higher quality feedback with better reasoning, leading to more effective training iterations.
-    </Tip>
-  </Tab>
-  <Tab title="Small Model Usage">
-    If you must use smaller models for training evaluation, be aware of these constraints:
-
-    ```python
-    # Using a smaller model (expect some limitations)
-    llm = LLM(model="huggingface/microsoft/Phi-3-mini-4k-instruct")
-    ```
-
-    <Warning>
-      While CrewAI includes optimizations for small models, expect less reliable and less nuanced evaluation results that may require more human intervention during training.
-    </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

@@ -1,155 +0,0 @@
----
-title: 'Agent Repositories'
-description: 'Learn how to use Agent Repositories to share and reuse your agents across teams and projects'
-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
-- **Reusability**: Create an agent once and use it in multiple crews and projects
-- **Governance**: Implement organization-wide policies for agent configurations
-- **Collaboration**: Enable teams to share and build upon each other's work
-
-## Creating and Use Agent Repositories
-
-1. You must have an account at CrewAI, try the [free plan](https://app.crewai.com).
-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.
-
-<Frame>
-  ![Agent Repositories](/images/enterprise/create-agent-repository.png)
-</Frame>
-
-
-### Loading Agents from Repositories
-
-You can load agents from repositories in your code using the `from_repository` parameter to run locally:
-
-```python
-from crewai import Agent
-
-# Create an agent by loading it from a repository
-# The agent is loaded with all its predefined configurations
-researcher = Agent(
-    from_repository="market-research-agent"
-)
-```
-
-### Overriding Repository Settings
-
-You can override specific settings from the repository by providing them in the configuration:
-
-```python
-researcher = Agent(
-    from_repository="market-research-agent",
-    goal="Research the latest trends in AI development",  # Override the repository goal
-    verbose=True  # Add a setting not in the repository
-)
-```
-
-### Example: Creating a Crew with Repository Agents
-
-```python
-from crewai import Crew, Agent, Task
-
-# Load agents from repositories
-researcher = Agent(
-    from_repository="market-research-agent"
-)
-
-writer = Agent(
-    from_repository="content-writer-agent"
-)
-
-# Create tasks
-research_task = Task(
-    description="Research the latest trends in AI",
-    agent=researcher
-)
-
-writing_task = Task(
-    description="Write a comprehensive report based on the research",
-    agent=writer
-)
-
-# Create the crew
-crew = Crew(
-    agents=[researcher, writer],
-    tasks=[research_task, writing_task],
-    verbose=True
-)
-
-# Run the crew
-result = crew.kickoff()
-```
-
-### Example: Using `kickoff()` with Repository Agents
-
-You can also use repository agents directly with the `kickoff()` method for simpler interactions:
-
-```python
-from crewai import Agent
-from pydantic import BaseModel
-from typing import List
-
-# Define a structured output format
-class MarketAnalysis(BaseModel):
-    key_trends: List[str]
-    opportunities: List[str]
-    recommendation: str
-
-# Load an agent from repository
-analyst = Agent(
-    from_repository="market-analyst-agent",
-    verbose=True
-)
-
-# Get a free-form response
-result = analyst.kickoff("Analyze the AI market in 2025")
-print(result.raw)  # Access the raw response
-
-# Get structured output
-structured_result = analyst.kickoff(
-    "Provide a structured analysis of the AI market in 2025",
-    response_format=MarketAnalysis
-)
-
-# Access structured data
-print(f"Key Trends: {structured_result.pydantic.key_trends}")
-print(f"Recommendation: {structured_result.pydantic.recommendation}")
-```
-
-## Best Practices
-
-1. **Naming Convention**: Use clear, descriptive names for your repository agents
-2. **Documentation**: Include comprehensive descriptions for each agent
-3. **Tool Management**: Ensure that tools referenced by repository agents are available in your environment
-4. **Access Control**: Manage permissions to ensure only authorized team members can modify repository agents
-
-## Organization Management
-
-To switch between organizations or see your current organization, use the CrewAI CLI:
-
-```bash
-# View current organization
-crewai org current
-
-# Switch to a different organization
-crewai org switch <org_id>
-
-# List all available organizations
-crewai org list
-```
-
-<Note>
-When loading agents from repositories, you must be authenticated and switched to the correct organization. If you receive errors, check your authentication status and organization settings using the CLI commands above.
-</Note>

docs/en/enterprise/features/automations.mdx

@@ -1,104 +0,0 @@
----
-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

@@ -1,88 +0,0 @@
----
-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/marketplace.mdx

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

@@ -1,102 +0,0 @@
----
-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
-
-RBAC in CrewAI AMP enables secure, scalable access management through a combination of organization‑level roles and automation‑level visibility controls.
-
-<Frame>
-  <img src="/images/enterprise/users_and_roles.png" alt="RBAC overview in CrewAI AMP" />
-
-</Frame>
-
-## Users and Roles
-
-Each member in your CrewAI workspace is assigned a role, which determines their access across various features.
-
-You can:
-
-- Use predefined roles (Owner, Member)
-- Create custom roles tailored to specific permissions
-- Assign roles at any time through the settings panel
-
-You can configure users and roles in Settings → Roles.
-
-<Steps>
-  <Step title="Open Roles settings">
-    Go to <b>Settings → Roles</b> in CrewAI AMP.
-  </Step>
-  <Step title="Choose a role type">
-    Use a predefined role (<b>Owner</b>, <b>Member</b>) or click <b>Create role</b> to define a custom one.
-  </Step>
-  <Step title="Assign to members">
-    Select users and assign the role. You can change this anytime.
-  </Step>
-</Steps>
-
-### Configuration summary
-
-| Area | Where to configure | Options |
-|:---|:---|:---|
-| Users & Roles | Settings → Roles | Predefined: Owner, Member; Custom roles |
-| Automation visibility | Automation → Settings → Visibility | Private; Whitelist users/roles |
-
-## Automation‑level Access Control
-
-In addition to organization‑wide roles, CrewAI Automations support fine‑grained visibility settings that let you restrict access to specific automations by user or role.
-
-This is useful for:
-
-- Keeping sensitive or experimental automations private
-- Managing visibility across large teams or external collaborators
-- Testing automations in isolated contexts
-
-Deployments can be configured as private, meaning only whitelisted users and roles will be able to:
-
-- View the deployment
-- Run it or interact with its API
-- Access its logs, metrics, and settings
-
-The organization owner always has access, regardless of visibility settings.
-
-You can configure automation‑level access control in Automation → Settings → Visibility tab.
-
-<Steps>
-  <Step title="Open Visibility tab">
-    Navigate to <b>Automation → Settings → Visibility</b>.
-  </Step>
-  <Step title="Set visibility">
-    Choose <b>Private</b> to restrict access. The organization owner always retains access.
-  </Step>
-  <Step title="Whitelist access">
-    Add specific users and roles allowed to view, run, and access logs/metrics/settings.
-  </Step>
-  <Step title="Save and verify">
-    Save changes, then confirm that non‑whitelisted users cannot view or run the automation.
-  </Step>
-</Steps>
-
-### Private visibility: access outcomes
-
-| Action | Owner | Whitelisted user/role | Not whitelisted |
-|:---|:---|:---|:---|
-| View automation | ✓ | ✓ | ✗ |
-| Run automation/API | ✓ | ✓ | ✗ |
-| Access logs/metrics/settings | ✓ | ✓ | ✗ |
-
-<Tip>
-The organization owner always has access. In private mode, only whitelisted users and roles can view, run, and access logs/metrics/settings.
-</Tip>
-
-<Frame>
-  <img src="/images/enterprise/visibility.png" alt="Automation Visibility settings in CrewAI AMP" />
-
-</Frame>
-
-<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with RBAC questions.
-</Card>

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

@@ -1,249 +0,0 @@
----
-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 AMP Tool Repository and use them in your agents.
-
-  <Tip>
-  Before running the commands below, make sure you log in to your CrewAI AMP 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 AMP Tool Repository.
-      ```bash
-      crewai tool publish
-      ```
-    </Step>
-    <Step title="Install">
-      Install the tool from the CrewAI AMP 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/webhook-streaming.mdx

@@ -1,168 +0,0 @@
----
-title: Webhook Streaming
-description: "Using Webhook Streaming to stream events to your webhook"
-icon: "webhook"
-mode: "wide"
----
-
-## Overview
-
-Enterprise Event Streaming lets you receive real-time webhook updates about your crews and flows deployed to
-CrewAI AMP, such as model calls, tool usage, and flow steps.
-
-## Usage
-
-When using the Kickoff API, include a `webhooks` object to your request, for example:
-
-```json
-{
-  "inputs": {"foo": "bar"},
-  "webhooks": {
-    "events": ["crew_kickoff_started", "llm_call_started"],
-    "url": "https://your.endpoint/webhook",
-    "realtime": false,
-    "authentication": {
-      "strategy": "bearer",
-      "token": "my-secret-token"
-    }
-  }
-}
-```
-
-If `realtime` is set to `true`, each event is delivered individually and immediately, at the cost of crew/flow performance.
-
-## Webhook Format
-
-Each webhook sends a list of events:
-
-```json
-{
-  "events": [
-    {
-      "id": "event-id",
-      "execution_id": "crew-run-id",
-      "timestamp": "2025-02-16T10:58:44.965Z",
-      "type": "llm_call_started",
-      "data": {
-        "model": "gpt-4",
-        "messages": [
-          {"role": "system", "content": "You are an assistant."},
-          {"role": "user", "content": "Summarize this article."}
-        ]
-      }
-    }
-  ]
-}
-```
-
-The `data` object structure varies by event type. Refer to the [event list](https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events) on GitHub.
-
-As requests are sent over HTTP, the order of events can't be guaranteed. If you need ordering, use the `timestamp` field.
-
-## Supported Events
-
-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.
-
-### Flow Events:
-
-  - `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>
-</CardGroup>

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

@@ -1,255 +0,0 @@
----
-title: "Triggers Overview"
-description: "Understand how CrewAI AMP triggers work, how to manage them, and where to find integration-specific playbooks"
-icon: "face-smile"
-mode: "wide"
----
-
-CrewAI AMP 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 AMP Trigger Examples" href="https://github.com/crewAIInc/crewai-enterprise-trigger-examples" icon="github">
-    Check them out on GitHub!
-</Card>

docs/en/enterprise/guides/capture_telemetry_logs.mdx

@@ -1,35 +0,0 @@
----
-title: "Open Telemetry Logs"
-description: "Understand how to capture telemetry logs from your CrewAI AMP deployments"
-icon: "magnifying-glass-chart"
-mode: "wide"
----
-
-CrewAI AMP provides a powerful way to capture telemetry logs from your deployments. This allows you to monitor the performance of your agents and workflows, and to debug issues that may arise.
-
-## Prerequisites
-
-<CardGroup cols={2}>
-  <Card title="ENTERPRISE OTEL SETUP enabled" icon="users">
-    Your organization should have ENTERPRISE OTEL SETUP enabled
-  </Card>
-  <Card title="OTEL collector setup" icon="server">
-    Your organization should have an OTEL collector setup or a provider like Datadog log intake setup
-  </Card>
-</CardGroup>
-
-
-## How to capture telemetry logs
-
-1. Go to settings/organization tab
-2. Configure your OTEL collector setup
-3. Save
-
-
-
-Example to setup OTEL log collection capture to Datadog.
-
-
-<Frame>
-  ![Capture Telemetry Logs](/images/crewai-otel-export.png)
-</Frame>