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53 Commits

Author SHA1 Message Date
Devin AI
30631a65a1 Fix lint issues in test script
- Use crew variable to avoid F841 unused variable error
- Remove API key logging to address CodeQL security alert
- Make path portable using os.path.join

Co-Authored-By: João <joao@crewai.com>
2025-09-20 21:33:20 +00:00
Devin AI
d46550d296 Fix TraceBatchManager authentication handling for issue #3559
- Move get_auth_token() call inside try-catch block in TraceBatchManager.__init__
- This allows graceful handling of AuthError when no authentication token is present
- Crews can now work without authentication by using ephemeral batches
- Add test to verify TraceBatchManager handles missing auth gracefully
- Add standalone test script that confirms the fix works correctly

Fixes issue where recent changes broke previously running crews due to
mandatory authentication in the tracing system.

Co-Authored-By: João <joao@crewai.com>
2025-09-20 21:29:35 +00:00
João Moura
0ee438c39d fix version (#3557) 2025-09-20 17:14:28 -03:00
Joao Moura
cbb9965bf7 preparing new version 2025-09-20 12:27:25 -07:00
João Moura
4951d30dd9 Dix issues with getting id (#3556)
* fix issues with getting id

* ignore linter

* fix: resolve ruff linting issues in tracing utils

---------

Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
2025-09-20 15:29:25 -03:00
Greyson LaLonde
7426969736 chore: apply ruff linting fixes and type annotations to memory module
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Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
2025-09-19 22:20:13 -04:00
Greyson LaLonde
d879be8b66 chore: fix ruff linting issues in agents module
fix(agents): linting, import paths, cache key alignment, and static method
2025-09-19 22:11:21 -04:00
Greyson LaLonde
24b84a4b68 chore: apply ruff linting fixes to crews module 2025-09-19 22:02:22 -04:00
Greyson LaLonde
8e571ea8a7 chore: fix ruff linting and mypy issues in knowledge module
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2025-09-19 21:39:15 -04:00
Greyson LaLonde
2cfc4d37b8 chore: apply ruff linting fixes to events module
fix: apply ruff linting to events
2025-09-19 20:10:55 -04:00
Greyson LaLonde
f4abc41235 chore: apply ruff linting fixes to CLI module
fix: apply ruff fixes to CLI and update Okta provider test
2025-09-19 19:55:55 -04:00
Greyson LaLonde
de5d3c3ad1 chore: add pydantic.mypy plugin for better type checking 2025-09-19 19:23:33 -04:00
Lorenze Jay
c062826779 chore: update dependencies and versioning for CrewAI 0.193.0 (#3542)
* chore: update dependencies and versioning for CrewAI

- Bump `crewai-tools` dependency version from `0.71.0` to `0.73.0` in `pyproject.toml`.
- Update CrewAI version from `0.186.1` to `0.193.0` in `__init__.py`.
- Adjust dependency versions in CLI templates for crew, flow, and tool to reflect the new CrewAI version.

This update ensures compatibility with the latest features and improvements in CrewAI.

* remove embedchain mock

* fix: remove last embedchain mocks

* fix: remove langchain_openai from tests

---------

Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
2025-09-19 16:01:55 -03:00
João Moura
9491fe8334 Adding Ability for user to get deeper observability (#3541)
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* feat(tracing): enhance first-time trace display and auto-open browser

* avoinding line breaking

* set tracing if user enables it

* linted

---------

Co-authored-by: lorenzejay <lorenzejaytech@gmail.com>
2025-09-18 21:47:09 -03:00
Greyson LaLonde
6f2ea013a7 docs: update RagTool references from EmbedChain to CrewAI native RAG (#3537)
* docs: update RagTool references from EmbedChain to CrewAI native RAG

* change ref to qdrant

* docs: update RAGTool to use Qdrant and add embedding_model example
2025-09-18 16:06:44 -07:00
Greyson LaLonde
39e8792ae5 fix: add l2 distance metric support for backward compatibility (#3540) 2025-09-18 18:36:33 -04:00
Lorenze Jay
2f682e1564 feat: update ChromaDB embedding function to use OpenAI API (#3538)
- Refactor the default embedding function to utilize OpenAI's embedding function with API key support.
- Import necessary OpenAI embedding function and configure it with the environment variable for the API key.
- Ensure compatibility with existing ChromaDB configuration model.
2025-09-18 14:50:35 -07:00
Greyson LaLonde
d4aa676195 feat: add configurable search parameters for RAG, knowledge, and memory (#3531)
- Add limit and score_threshold to BaseRagConfig, propagate to clients  
- Update default search params in RAG storage, knowledge, and memory (limit=5, threshold=0.6)  
- Fix linting (ruff, mypy, PERF203) and refactor save logic  
- Update tests for new defaults and ChromaDB behavior
2025-09-18 16:58:03 -04:00
Lorenze Jay
578fa8c2e4 Lorenze/ephemeral trace ask (#3530)
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* feat(tracing): implement first-time trace handling and improve event management

- Added FirstTimeTraceHandler for managing first-time user trace collection and display.
- Enhanced TraceBatchManager to support ephemeral trace URLs and improved event buffering.
- Updated TraceCollectionListener to utilize the new FirstTimeTraceHandler.
- Refactored type annotations across multiple files for consistency and clarity.
- Improved error handling and logging for trace-related operations.
- Introduced utility functions for trace viewing prompts and first execution checks.

* brought back crew finalize batch events

* refactor(trace): move instance variables to __init__ in TraceBatchManager

- Refactored TraceBatchManager to initialize instance variables in the constructor instead of as class variables.
- Improved clarity and encapsulation of the class state.

* fix(tracing): improve error handling in user data loading and saving

- Enhanced error handling in _load_user_data and _save_user_data functions to log warnings for JSON decoding and file access issues.
- Updated documentation for trace usage to clarify the addition of tracing parameters in Crew and Flow initialization.
- Refined state management in Flow class to ensure proper handling of state IDs when persistence is enabled.

* add some tests

* fix test

* fix tests

* refactor(tracing): enhance user input handling for trace viewing

- Replaced signal-based timeout handling with threading for user input in prompt_user_for_trace_viewing function.
- Improved user experience by allowing a configurable timeout for viewing execution traces.
- Updated tests to mock threading behavior and verify timeout handling correctly.

* fix(tracing): improve machine ID retrieval with error handling

- Added error handling to the _get_machine_id function to log warnings when retrieving the machine ID fails.
- Ensured that the function continues to provide a stable, privacy-preserving machine fingerprint even in case of errors.

* refactor(flow): streamline state ID assignment in Flow class

- Replaced direct attribute assignment with setattr for improved flexibility in handling state IDs.
- Enhanced code readability by simplifying the logic for setting the state ID when persistence is enabled.
2025-09-18 10:17:34 -07:00
Rip&Tear
6f5af2b27c Update CodeQL workflow to ignore specific paths (#3534)
Code QL, when configured through the GUI, does not allow for advanced configuration. This PR upgrades from an advanced file-based config which allows us to exclude certain paths.
2025-09-18 23:26:15 +08:00
Greyson LaLonde
8ee3cf4874 test: fix flaky agent repeated tool usage test (#3533)
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- Make assertion resilient to race condition with max iterations in CI  
- Add investigation notes and TODOs for deterministic executor flow
2025-09-17 22:00:32 -04:00
Greyson LaLonde
f2d3fd0c0f fix(events): add missing event exports to __init__.py (#3532) 2025-09-17 21:50:27 -04:00
Greyson LaLonde
f28e78c5ba refactor: unify rag storage with instance-specific client support (#3455)
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- ignore line length errors globally
- migrate knowledge/memory and crew query_knowledge to `SearchResult`
- remove legacy chromadb utils; fix empty metadata handling
- restore openai as default embedding provider; support instance-specific clients
- update and fix tests for `SearchResult` migration and rag changes
2025-09-17 14:46:54 -04:00
Greyson LaLonde
81bd81e5f5 fix: handle model parameter in OpenAI adapter initialization (#3510)
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2025-09-12 17:31:53 -04:00
Vidit Ostwal
1b00cc71ef Dropping messages from metadata in Mem0 Storage (#3390)
* Dropped messages from metadata and added user-assistant interaction directly

* Fixed test cases for this

* Fixed static type checking issue

* Changed logic to take latest user and assistant messages

* Added default value to be string

* Linting checks

* Removed duplication of tool calling

* Fixed Linting Changes

* Ruff check

* Removed console formatter file from commit

* Linting fixed

* Linting checks

* Ignoring missing imports error

* Added suggested changes

* Fixed import untyped error
2025-09-12 15:25:29 -04:00
Greyson LaLonde
45d0c9912c chore: add type annotations and docstrings to openai agent adapters (#3505) 2025-09-12 10:41:39 -04:00
Greyson LaLonde
1f1ab14b07 fix: resolve test duration cache issues in CI workflows (#3506)
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2025-09-12 08:38:47 -04:00
Lucas Gomide
1a70f1698e feat: add thread-safe platform context management (#3502)
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Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
2025-09-11 17:32:51 -04:00
Greyson LaLonde
8883fb656b feat(tests): add duration caching for pytest-split
- Cache test durations for optimized splitting
2025-09-11 15:16:05 -04:00
Greyson LaLonde
79d65e55a1 chore: add type annotations and docstrings to langgraph adapters (#3503) 2025-09-11 13:06:44 -04:00
Lorenze Jay
dde76bfec5 chore: bump CrewAI version to 0.186.1 and update dependencies in CLI templates (#3499)
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- Updated CrewAI version from 0.186.0 to 0.186.1 in `__init__.py`.
- Updated `crewai[tools]` dependency version in `pyproject.toml` for crew, flow, and tool templates to reflect the new CrewAI version.
2025-09-10 17:01:19 -07:00
Lorenze Jay
f554123af6 fix (#3498) 2025-09-10 16:55:25 -07:00
Lorenze Jay
4336e945b8 chore: update dependencies and version for CrewAI (#3497)
- Updated `crewai-tools` dependency from version 0.69.0 to 0.71.0 in `pyproject.toml`.
- Bumped CrewAI version from 0.177.0 to 0.186.0 in `__init__.py`.
- Updated dependency versions in CLI templates for crew, flow, and tool to reflect the new CrewAI version.
2025-09-10 16:03:58 -07:00
Lorenze Jay
75b916c85a Lorenze/fix tool call twice (#3495)
* test: add test to ensure tool is called only once during crew execution

- Introduced a new test case to validate that the counting_tool is executed exactly once during crew execution.
- Created a CountingTool class to track execution counts and log call history.
- Enhanced the test suite with a YAML cassette for consistent tool behavior verification.

* ensure tool function called only once

* refactor: simplify error handling in CrewStructuredTool

- Removed unnecessary try-except block around the tool function call to streamline execution flow.
- Ensured that the tool function is called directly, improving readability and maintainability.

* linted

* need to ignore for now as we cant infer the complex generic type within pydantic create_model_func

* fix tests
2025-09-10 15:20:21 -07:00
Greyson LaLonde
01be26ce2a chore: add build-cache, update jobs, remove redundant security check
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- Build and cache uv dependencies; update type-checker, tests, and linter to use cache  
- Remove separate security-checker
- Add explicit workflow permissions for compliance  
- Remove pull_request trigger from build-cache workflow
2025-09-10 13:02:24 -04:00
Greyson LaLonde
c3ad5887ef chore: add type annotations to utilities module (#3484)
- Update to Python 3.10+ typing across LLM, callbacks, storage, and errors
- Complete typing updates for crew_chat and hitl
- Add stop attr to mock LLM, suppress test warnings
- Add type-ignore for aisuite import
2025-09-10 10:56:17 -04:00
Lucas Gomide
260b49c10a fix: support to define MPC connection timeout on CrewBase instance (#3465)
* fix: support to define MPC connection timeout on CrewBase instance

* fix: resolve linter issues

* chore: ignore specific rule N802 on CrewBase class

* fix: ignore untyped import
2025-09-10 09:58:46 -04:00
Greyson LaLonde
1dc4f2e897 chore: add typing and docstrings to base_token_process module (#3486)
Co-authored-by: Lucas Gomide <lucaslg200@gmail.com>
2025-09-10 09:23:39 -04:00
Greyson LaLonde
b126ab22dd chore: refactor telemetry module with utility functions and modern typing (#3485)
Co-authored-by: Lucas Gomide <lucaslg200@gmail.com>
2025-09-10 09:18:21 -04:00
Greyson LaLonde
079cb72f6e chore: update typing in types module to Python 3.10+ syntax (#3482)
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2025-09-10 09:07:36 -04:00
Greyson LaLonde
83682d511f chore: modernize LLM interface typing and add constants (#3483)
* chore: update LLM interfaces to Python 3.10+ typing

* fix: add missing stop attribute to mock LLM and improve test infrastructure

* fix: correct type ignore comment for aisuite import
2025-09-10 08:30:49 -04:00
Samarth Rawat
6676d94ba1 Doc Fix: fixed number of memory types (#3288)
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* Update memory.mdx

* Update memory.mdx

---------

Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
2025-09-09 14:11:56 -04:00
Greyson LaLonde
d5126d159b chore: improve typing and docs in agents leaf files (#3461)
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- Add typing and Google-style docstrings to agents leaf files
- Add TODO notes
2025-09-08 11:57:34 -04:00
Greyson LaLonde
fa06aea8d5 chore: modernize security module typing (#3469)
- Disable E501, apply Ruff formatting
- Update typing (Self, BeforeValidator), remove dead code
- Convert Fingerprint to Pydantic dataclass and fix serialization/copy behavior
- Add TODO for dynamic namespace config
2025-09-08 11:52:59 -04:00
Greyson LaLonde
f936e0f69b chore: enhance typing and documentation in tasks module (#3467)
- Disable E501 line length linting rule
- Add Google-style docstrings to tasks leaf file
- Modernize typing and docs in task_output.py
- Improve typing and documentation in conditional_task.py
2025-09-08 11:42:23 -04:00
Greyson LaLonde
37c5e88d02 ci: configure pre-commit hooks and github actions to use uv run (#3479) 2025-09-08 11:30:28 -04:00
Kim
1a96ed7b00 fix: rebranding of Azure AI Studio (Azure OpenAI Studio) to Azure AI Foundry (#3424)
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Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
2025-09-05 20:42:05 -04:00
Tony Kipkemboi
1a1bb0ca3d docs: Docs updates (#3459)
* docs(cli): document device-code login and config reset guidance; renumber sections

* docs(cli): fix duplicate numbering (renumber Login/API Keys/Configuration sections)

* docs: Fix webhook documentation to include meta dict in all webhook payloads

- Add note explaining that meta objects from kickoff requests are included in all webhook payloads
- Update webhook examples to show proper payload structure including meta field
- Fix webhook examples to match actual API implementation
- Apply changes to English, Korean, and Portuguese documentation

Resolves the documentation gap where meta dict passing to webhooks was not documented despite being implemented in the API.

* WIP: CrewAI docs theme, changelog, GEO, localization

* docs(cli): fix merge markers; ensure mode: "wide"; convert ASCII tables to Markdown (en/pt-BR/ko)

* docs: add group icons across locales; split Automation/Integrations; update tools overviews and links
2025-09-05 17:40:11 -04:00
Mike Plachta
99b79ab20d docs: move Bedrock tool docs to integration folder and add CrewAI automation tool docs (#3403)
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
2025-09-05 15:12:35 -04:00
Mike Plachta
80974fec6c docs: expand webhook event types with detailed categorization and descriptions (#3369)
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2025-09-05 14:57:01 -04:00
Greyson LaLonde
30b9cdd944 chore: expand ruff rules with comprehensive linting (#3453) 2025-09-05 14:38:56 -04:00
Greyson LaLonde
610c1f70c0 chore: relax mypy configuration and exclude tests from CI (#3452) 2025-09-05 10:00:05 -04:00
Greyson LaLonde
ab82da02f9 refactor: cleanup crew agent executor (#3440)
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refactor: cleanup crew agent executor & add docs

- Remove dead code, unused imports, and obsolete methods
- Modernize with updated type hints and static _format_prompt
- Add docstrings for clarity
2025-09-04 15:32:47 -04:00
732 changed files with 15162 additions and 4300 deletions

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

102
.github/workflows/codeql.yml vendored Normal file
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@@ -0,0 +1,102 @@
# For most projects, this workflow file will not need changing; you simply need
# to commit it to your repository.
#
# You may wish to alter this file to override the set of languages analyzed,
# or to provide custom queries or build logic.
#
# ******** NOTE ********
# We have attempted to detect the languages in your repository. Please check
# the `language` matrix defined below to confirm you have the correct set of
# supported CodeQL languages.
#
name: "CodeQL Advanced"
on:
push:
branches: [ "main" ]
paths-ignore:
- "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: ${{ matrix.build-mode }}
# If you wish to specify custom queries, you can do so here or in a config file.
# By default, queries listed here will override any specified in a config file.
# Prefix the list here with "+" to use these queries and those in the config file.
# For more details on CodeQL's query packs, refer to: https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
# queries: security-extended,security-and-quality
# If the analyze step fails for one of the languages you are analyzing with
# "We were unable to automatically build your code", modify the matrix above
# to set the build mode to "manual" for that language. Then modify this step
# to build your code.
# Command-line programs to run using the OS shell.
# 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
- if: matrix.build-mode == 'manual'
shell: bash
run: |
echo 'If you are using a "manual" build mode for one or more of the' \
'languages you are analyzing, replace this with the commands to build' \
'your code, for example:'
echo ' make bootstrap'
echo ' make release'
exit 1
- name: Perform CodeQL Analysis
uses: github/codeql-action/analyze@v3
with:
category: "/language:${{matrix.language}}"

View File

@@ -2,6 +2,9 @@ name: Lint
on: [pull_request]
permissions:
contents: read
jobs:
lint:
runs-on: ubuntu-latest
@@ -15,19 +18,27 @@ jobs:
- 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:
enable-cache: true
cache-dependency-glob: |
**/pyproject.toml
**/uv.lock
- name: Set up Python
run: uv python install 3.11
version: "0.8.4"
python-version: "3.11"
enable-cache: false
- name: Install dependencies
run: uv sync --dev --no-install-project
run: uv sync --all-groups --all-extras --no-install-project
- name: Get Changed Python Files
id: changed-files
@@ -45,3 +56,13 @@ jobs:
| 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') }}

View File

@@ -1,29 +0,0 @@
name: Security Checker
on: [pull_request]
jobs:
security-check:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Install uv
uses: astral-sh/setup-uv@v6
with:
enable-cache: true
cache-dependency-glob: |
**/pyproject.toml
**/uv.lock
- name: Set up Python
run: uv python install 3.11
- name: Install dependencies
run: uv sync --dev --no-install-project
- name: Run Bandit
run: uv run bandit -c pyproject.toml -r src/ -ll

View File

@@ -3,7 +3,7 @@ name: Run Tests
on: [pull_request]
permissions:
contents: write
contents: read
env:
OPENAI_API_KEY: fake-api-key
@@ -22,29 +22,76 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0 # Fetch all history for proper diff
- name: Restore global uv cache
id: cache-restore
uses: actions/cache/restore@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
restore-keys: |
uv-main-py${{ matrix.python-version }}-
- name: Install uv
uses: astral-sh/setup-uv@v6
with:
enable-cache: true
cache-dependency-glob: |
**/pyproject.toml
**/uv.lock
- name: Set up Python ${{ matrix.python-version }}
run: uv python install ${{ matrix.python-version }}
version: "0.8.4"
python-version: ${{ matrix.python-version }}
enable-cache: false
- name: Install the project
run: uv sync --dev --all-extras
run: uv sync --all-groups --all-extras
- name: Restore test durations
uses: actions/cache/restore@v4
with:
path: .test_durations_py*
key: test-durations-py${{ matrix.python-version }}
- name: Run tests (group ${{ matrix.group }} of 8)
run: |
PYTHON_VERSION_SAFE=$(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') }}

View File

@@ -3,7 +3,7 @@ name: Run Type Checks
on: [pull_request]
permissions:
contents: write
contents: read
jobs:
type-checker-matrix:
@@ -20,19 +20,27 @@ jobs:
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:
enable-cache: true
cache-dependency-glob: |
**/pyproject.toml
**/uv.lock
- name: Set up Python ${{ matrix.python-version }}
run: uv python install ${{ matrix.python-version }}
version: "0.8.4"
python-version: ${{ matrix.python-version }}
enable-cache: false
- name: Install dependencies
run: uv sync --dev --no-install-project
run: uv sync --all-groups --all-extras
- name: Get changed Python files
id: changed-files
@@ -41,18 +49,18 @@ jobs:
echo "Fetching changed files..."
git diff --name-only --diff-filter=ACMRT origin/${{ github.base_ref }}...HEAD -- '*.py' > changed_files.txt
# Filter for files in src/ and tests/ directories
grep -E "^(src/|tests/)" changed_files.txt > filtered_changed_files.txt || true
# 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/ and tests/:"
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/ or tests/"
echo "No Python files changed in src/"
echo "has_changes=false" >> $GITHUB_OUTPUT
fi
@@ -64,7 +72,17 @@ jobs:
- name: No files to check
if: steps.changed-files.outputs.has_changes == 'false'
run: echo "No Python files in src/ or tests/ were modified - skipping type checks"
run: echo "No Python files in src/ were modified - skipping type checks"
- name: Save uv caches
if: steps.cache-restore.outputs.cache-hit != 'true'
uses: actions/cache/save@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
# Summary job to provide single status for branch protection
type-checker:

View File

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

View File

@@ -1,14 +1,19 @@
repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.12.11
- repo: local
hooks:
- id: ruff
args: ["--config", "pyproject.toml"]
name: ruff
entry: uv run ruff check
language: system
types: [python]
- id: ruff-format
args: ["--config", "pyproject.toml"]
- repo: https://github.com/pre-commit/mirrors-mypy
rev: v1.17.1
hooks:
name: ruff-format
entry: uv run ruff format
language: system
types: [python]
- id: mypy
args: ["--config-file", "pyproject.toml"]
name: mypy
entry: uv run mypy
language: system
types: [python]
exclude: ^tests/

View File

@@ -1,6 +1,6 @@
{
"$schema": "https://mintlify.com/docs.json",
"theme": "mint",
"theme": "aspen",
"name": "CrewAI",
"colors": {
"primary": "#EB6658",
@@ -28,20 +28,21 @@
"icon": "discourse"
},
{
"anchor": "Crew GPT",
"href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
"icon": "robot"
"anchor": "Blog",
"href": "https://blog.crewai.com",
"icon": "newspaper"
},
{
"anchor": "Releases",
"href": "https://github.com/crewAIInc/crewAI/releases",
"icon": "tag"
"anchor": "CrewGPT",
"href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
"icon": "robot"
}
]
},
"tabs": [
{
"tab": "Documentation",
"icon": "book-open",
"groups": [
{
"group": "Get Started",
@@ -52,18 +53,22 @@
"pages": [
{
"group": "Strategy",
"icon": "compass",
"pages": ["en/guides/concepts/evaluating-use-cases"]
},
{
"group": "Agents",
"icon": "user",
"pages": ["en/guides/agents/crafting-effective-agents"]
},
{
"group": "Crews",
"icon": "users",
"pages": ["en/guides/crews/first-crew"]
},
{
"group": "Flows",
"icon": "code-branch",
"pages": [
"en/guides/flows/first-flow",
"en/guides/flows/mastering-flow-state"
@@ -71,6 +76,7 @@
},
{
"group": "Advanced",
"icon": "gear",
"pages": [
"en/guides/advanced/customizing-prompts",
"en/guides/advanced/fingerprinting"
@@ -116,6 +122,7 @@
"en/tools/overview",
{
"group": "File & Document",
"icon": "folder-open",
"pages": [
"en/tools/file-document/overview",
"en/tools/file-document/filereadtool",
@@ -135,6 +142,7 @@
},
{
"group": "Web Scraping & Browsing",
"icon": "globe",
"pages": [
"en/tools/web-scraping/overview",
"en/tools/web-scraping/scrapewebsitetool",
@@ -154,6 +162,7 @@
},
{
"group": "Search & Research",
"icon": "magnifying-glass",
"pages": [
"en/tools/search-research/overview",
"en/tools/search-research/serperdevtool",
@@ -175,6 +184,7 @@
},
{
"group": "Database & Data",
"icon": "database",
"pages": [
"en/tools/database-data/overview",
"en/tools/database-data/mysqltool",
@@ -189,6 +199,7 @@
},
{
"group": "AI & Machine Learning",
"icon": "brain",
"pages": [
"en/tools/ai-ml/overview",
"en/tools/ai-ml/dalletool",
@@ -202,16 +213,26 @@
},
{
"group": "Cloud & Storage",
"icon": "cloud",
"pages": [
"en/tools/cloud-storage/overview",
"en/tools/cloud-storage/s3readertool",
"en/tools/cloud-storage/s3writertool",
"en/tools/cloud-storage/bedrockinvokeagenttool",
"en/tools/cloud-storage/bedrockkbretriever"
]
},
{
"group": "Automation & Integration",
"group": "Integrations",
"icon": "plug",
"pages": [
"en/tools/tool-integrations/overview",
"en/tools/tool-integrations/bedrockinvokeagenttool",
"en/tools/tool-integrations/crewaiautomationtool"
]
},
{
"group": "Automation",
"icon": "bolt",
"pages": [
"en/tools/automation/overview",
"en/tools/automation/apifyactorstool",
@@ -273,6 +294,7 @@
},
{
"tab": "Enterprise",
"icon": "briefcase",
"groups": [
{
"group": "Getting Started",
@@ -339,6 +361,7 @@
},
{
"tab": "API Reference",
"icon": "magnifying-glass",
"groups": [
{
"group": "Getting Started",
@@ -353,12 +376,23 @@
},
{
"tab": "Examples",
"icon": "code",
"groups": [
{
"group": "Examples",
"pages": ["en/examples/example", "en/examples/cookbooks"]
}
]
},
{
"tab": "Changelog",
"icon": "clock",
"groups": [
{
"group": "Release Notes",
"pages": ["en/changelog"]
}
]
}
]
},
@@ -377,20 +411,21 @@
"icon": "discourse"
},
{
"anchor": "Crew GPT",
"href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
"icon": "robot"
"anchor": "Blog",
"href": "https://blog.crewai.com",
"icon": "newspaper"
},
{
"anchor": "Lançamentos",
"href": "https://github.com/crewAIInc/crewAI/releases",
"icon": "tag"
"anchor": "CrewGPT",
"href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
"icon": "robot"
}
]
},
"tabs": [
{
"tab": "Documentação",
"icon": "book-open",
"groups": [
{
"group": "Começando",
@@ -405,18 +440,22 @@
"pages": [
{
"group": "Estratégia",
"icon": "compass",
"pages": ["pt-BR/guides/concepts/evaluating-use-cases"]
},
{
"group": "Agentes",
"icon": "user",
"pages": ["pt-BR/guides/agents/crafting-effective-agents"]
},
{
"group": "Crews",
"icon": "users",
"pages": ["pt-BR/guides/crews/first-crew"]
},
{
"group": "Flows",
"icon": "code-branch",
"pages": [
"pt-BR/guides/flows/first-flow",
"pt-BR/guides/flows/mastering-flow-state"
@@ -424,6 +463,7 @@
},
{
"group": "Avançado",
"icon": "gear",
"pages": [
"pt-BR/guides/advanced/customizing-prompts",
"pt-BR/guides/advanced/fingerprinting"
@@ -469,6 +509,7 @@
"pt-BR/tools/overview",
{
"group": "Arquivo & Documento",
"icon": "folder-open",
"pages": [
"pt-BR/tools/file-document/overview",
"pt-BR/tools/file-document/filereadtool",
@@ -486,6 +527,7 @@
},
{
"group": "Web Scraping & Navegação",
"icon": "globe",
"pages": [
"pt-BR/tools/web-scraping/overview",
"pt-BR/tools/web-scraping/scrapewebsitetool",
@@ -504,6 +546,7 @@
},
{
"group": "Pesquisa",
"icon": "magnifying-glass",
"pages": [
"pt-BR/tools/search-research/overview",
"pt-BR/tools/search-research/serperdevtool",
@@ -519,6 +562,7 @@
},
{
"group": "Dados",
"icon": "database",
"pages": [
"pt-BR/tools/database-data/overview",
"pt-BR/tools/database-data/mysqltool",
@@ -531,6 +575,7 @@
},
{
"group": "IA & Machine Learning",
"icon": "brain",
"pages": [
"pt-BR/tools/ai-ml/overview",
"pt-BR/tools/ai-ml/dalletool",
@@ -544,16 +589,26 @@
},
{
"group": "Cloud & Armazenamento",
"icon": "cloud",
"pages": [
"pt-BR/tools/cloud-storage/overview",
"pt-BR/tools/cloud-storage/s3readertool",
"pt-BR/tools/cloud-storage/s3writertool",
"pt-BR/tools/cloud-storage/bedrockinvokeagenttool",
"pt-BR/tools/cloud-storage/bedrockkbretriever"
]
},
{
"group": "Automação & Integração",
"group": "Integrações",
"icon": "plug",
"pages": [
"pt-BR/tools/tool-integrations/overview",
"pt-BR/tools/tool-integrations/bedrockinvokeagenttool",
"pt-BR/tools/tool-integrations/crewaiautomationtool"
]
},
{
"group": "Automação",
"icon": "bolt",
"pages": [
"pt-BR/tools/automation/overview",
"pt-BR/tools/automation/apifyactorstool",
@@ -613,6 +668,7 @@
},
{
"tab": "Enterprise",
"icon": "briefcase",
"groups": [
{
"group": "Começando",
@@ -680,6 +736,7 @@
},
{
"tab": "Referência da API",
"icon": "magnifying-glass",
"groups": [
{
"group": "Começando",
@@ -694,12 +751,23 @@
},
{
"tab": "Exemplos",
"icon": "code",
"groups": [
{
"group": "Exemplos",
"pages": ["pt-BR/examples/example", "pt-BR/examples/cookbooks"]
}
]
},
{
"tab": "Notas de Versão",
"icon": "clock",
"groups": [
{
"group": "Notas de Versão",
"pages": ["pt-BR/changelog"]
}
]
}
]
},
@@ -718,20 +786,21 @@
"icon": "discourse"
},
{
"anchor": "Crew GPT",
"href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
"icon": "robot"
"anchor": "블로그",
"href": "https://blog.crewai.com",
"icon": "newspaper"
},
{
"anchor": "릴리스",
"href": "https://github.com/crewAIInc/crewAI/releases",
"icon": "tag"
"anchor": "CrewGPT",
"href": "https://chatgpt.com/g/g-qqTuUWsBY-crewai-assistant",
"icon": "robot"
}
]
},
"tabs": [
{
"tab": "기술 문서",
"icon": "book-open",
"groups": [
{
"group": "시작 안내",
@@ -742,18 +811,22 @@
"pages": [
{
"group": "전략",
"icon": "compass",
"pages": ["ko/guides/concepts/evaluating-use-cases"]
},
{
"group": "에이전트 (Agents)",
"icon": "user",
"pages": ["ko/guides/agents/crafting-effective-agents"]
},
{
"group": "크루 (Crews)",
"icon": "users",
"pages": ["ko/guides/crews/first-crew"]
},
{
"group": "플로우 (Flows)",
"icon": "code-branch",
"pages": [
"ko/guides/flows/first-flow",
"ko/guides/flows/mastering-flow-state"
@@ -761,6 +834,7 @@
},
{
"group": "고급",
"icon": "gear",
"pages": [
"ko/guides/advanced/customizing-prompts",
"ko/guides/advanced/fingerprinting"
@@ -806,6 +880,7 @@
"ko/tools/overview",
{
"group": "파일 & 문서",
"icon": "folder-open",
"pages": [
"ko/tools/file-document/overview",
"ko/tools/file-document/filereadtool",
@@ -825,6 +900,7 @@
},
{
"group": "웹 스크래핑 & 브라우징",
"icon": "globe",
"pages": [
"ko/tools/web-scraping/overview",
"ko/tools/web-scraping/scrapewebsitetool",
@@ -844,6 +920,7 @@
},
{
"group": "검색 및 연구",
"icon": "magnifying-glass",
"pages": [
"ko/tools/search-research/overview",
"ko/tools/search-research/serperdevtool",
@@ -865,6 +942,7 @@
},
{
"group": "데이터베이스 & 데이터",
"icon": "database",
"pages": [
"ko/tools/database-data/overview",
"ko/tools/database-data/mysqltool",
@@ -879,6 +957,7 @@
},
{
"group": "인공지능 & 머신러닝",
"icon": "brain",
"pages": [
"ko/tools/ai-ml/overview",
"ko/tools/ai-ml/dalletool",
@@ -892,6 +971,7 @@
},
{
"group": "클라우드 & 스토리지",
"icon": "cloud",
"pages": [
"ko/tools/cloud-storage/overview",
"ko/tools/cloud-storage/s3readertool",
@@ -901,7 +981,17 @@
]
},
{
"group": "자동화 & 통합",
"group": "통합",
"icon": "plug",
"pages": [
"ko/tools/tool-integrations/overview",
"ko/tools/tool-integrations/bedrockinvokeagenttool",
"ko/tools/tool-integrations/crewaiautomationtool"
]
},
{
"group": "자동화",
"icon": "bolt",
"pages": [
"ko/tools/automation/overview",
"ko/tools/automation/apifyactorstool",
@@ -962,6 +1052,7 @@
},
{
"tab": "엔터프라이즈",
"icon": "briefcase",
"groups": [
{
"group": "시작 안내",
@@ -1028,6 +1119,7 @@
},
{
"tab": "API 레퍼런스",
"icon": "magnifying-glass",
"groups": [
{
"group": "시작 안내",
@@ -1042,12 +1134,23 @@
},
{
"tab": "예시",
"icon": "code",
"groups": [
{
"group": "예시",
"pages": ["ko/examples/example", "ko/examples/cookbooks"]
}
]
},
{
"tab": "변경 로그",
"icon": "clock",
"groups": [
{
"group": "릴리스 노트",
"pages": ["ko/changelog"]
}
]
}
]
}
@@ -1057,15 +1160,23 @@
"light": "/images/crew_only_logo.png",
"dark": "/images/crew_only_logo.png"
},
"fonts": {
"family": "Inter"
},
"appearance": {
"default": "dark",
"strict": false
"default": "system",
"strict": false,
"layout": "sidenav"
},
"background": {
"decoration": "grid"
},
"navbar": {
"links": [
{
"label": "Start Cloud Trial",
"href": "https://app.crewai.com"
"href": "https://app.crewai.com",
"icon": "arrow-up-right-from-square"
}
],
"primary": {
@@ -1084,7 +1195,20 @@
}
},
"seo": {
"indexing": "all"
"indexing": "all",
"metatags": {
"og:type": "website",
"og:site_name": "CrewAI Documentation",
"og:image": "https://docs.crewai.com/images/crew_only_logo.png",
"twitter:card": "summary_large_image",
"twitter:site": "@crewAIInc",
"keywords": "AI agents, multi-agent systems, CrewAI, artificial intelligence, automation, Python framework, agent collaboration, AI workflows"
}
},
"feedback": {
"enabled": true,
"thumbsRating": true,
"suggestEdit": true
},
"redirects": [
{
@@ -1105,7 +1229,7 @@
},
{
"source": "/changelog",
"destination": "https://github.com/crewAIInc/crewAI/releases"
"destination": "/en/changelog"
},
{
"source": "/telemetry",

View File

@@ -2,6 +2,7 @@
title: "GET /inputs"
description: "Get required inputs for your crew"
openapi: "/enterprise-api.en.yaml GET /inputs"
mode: "wide"
---

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

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@@ -2,6 +2,7 @@
title: "POST /kickoff"
description: "Start a crew execution"
openapi: "/enterprise-api.en.yaml POST /kickoff"
mode: "wide"
---

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@@ -2,6 +2,7 @@
title: "GET /status/{kickoff_id}"
description: "Get execution status"
openapi: "/enterprise-api.en.yaml GET /status/{kickoff_id}"
mode: "wide"
---

1763
docs/en/changelog.mdx Normal file

File diff suppressed because it is too large Load Diff

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

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@@ -2,6 +2,7 @@
title: CLI
description: Learn how to use the CrewAI CLI to interact with CrewAI.
icon: terminal
mode: "wide"
---
<Warning>Since release 0.140.0, CrewAI Enterprise started a process of migrating their login provider. As such, the authentication flow via CLI was updated. Users that use Google to login, or that created their account after July 3rd, 2025 will be unable to log in with older versions of the `crewai` library.</Warning>
@@ -282,7 +283,7 @@ Watch this video tutorial for a step-by-step demonstration of deploying your cre
allowfullscreen
></iframe>
### 12. Login
### 11. Login
Authenticate with CrewAI Enterprise using a secure device code flow (no email entry required).
@@ -300,7 +301,7 @@ Notes:
- 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
### 13. API Keys
### 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.
@@ -328,7 +329,7 @@ See the following link for each provider's key name:
* [LiteLLM Providers](https://docs.litellm.ai/docs/providers)
### 14. Configuration Management
### 13. Configuration Management
Manage CLI configuration settings for CrewAI.
@@ -369,19 +370,15 @@ crewai config list
```
Example output:
```
CrewAI CLI Configuration
┏━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Setting ┃ Value ┃ Description ┃
┡━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ enterprise_base_url│ https://app.crewai.com │ Base URL of the CrewAI Enterprise instance
org_name │ Not set │ Name of the currently active organization │
org_uuid │ Not set │ UUID of the currently active organization
oauth2_provider │ workos │ OAuth2 provider used for authentication (e.g., workos, okta, auth0).
│ oauth2_audience │ client_01YYY │ OAuth2 audience value, typically used to identify the target API or resource. │
│ oauth2_client_id │ client_01XXX │ OAuth2 client ID issued by the provider, used during authentication requests. │
│ oauth2_domain │ login.crewai.com │ OAuth2 provider's domain (e.g., your-org.auth0.com) used for issuing tokens. │
```
| Setting | Value | Description |
| :------------------ | :----------------------- | :---------------------------------------------------------- |
| enterprise_base_url | https://app.crewai.com | Base URL of the CrewAI Enterprise instance |
| org_name | Not set | Name of the currently active organization |
| org_uuid | Not set | UUID of the currently active organization |
| oauth2_provider | workos | OAuth2 provider (e.g., workos, okta, auth0) |
| oauth2_audience | client_01YYY | Audience identifying the target API/resource |
| oauth2_client_id | client_01XXX | OAuth2 client ID issued by the provider |
| oauth2_domain | login.crewai.com | Provider domain (e.g., your-org.auth0.com) |
Set the enterprise base URL:
```shell Terminal

View File

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

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

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@@ -2,6 +2,7 @@
title: 'Event Listeners'
description: 'Tap into CrewAI events to build custom integrations and monitoring'
icon: spinner
mode: "wide"
---
## Overview

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@@ -2,6 +2,7 @@
title: Flows
description: Learn how to create and manage AI workflows using CrewAI Flows.
icon: arrow-progress
mode: "wide"
---
## Overview

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@@ -2,6 +2,7 @@
title: Knowledge
description: What is knowledge in CrewAI and how to use it.
icon: book
mode: "wide"
---
## Overview

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@@ -2,6 +2,7 @@
title: 'LLMs'
description: 'A comprehensive guide to configuring and using Large Language Models (LLMs) in your CrewAI projects'
icon: 'microchip-ai'
mode: "wide"
---
## Overview

View File

@@ -2,11 +2,12 @@
title: Memory
description: Leveraging memory systems in the CrewAI framework to enhance agent capabilities.
icon: database
mode: "wide"
---
## Overview
The CrewAI framework provides a sophisticated memory system designed to significantly enhance AI agent capabilities. CrewAI offers **three distinct memory approaches** that serve different use cases:
The CrewAI framework provides a sophisticated memory system designed to significantly enhance AI agent capabilities. CrewAI offers **two distinct memory approaches** that serve different use cases:
1. **Basic Memory System** - Built-in short-term, long-term, and entity memory
2. **External Memory** - Standalone external memory providers

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

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

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

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@@ -2,6 +2,7 @@
title: Tasks
description: Detailed guide on managing and creating tasks within the CrewAI framework.
icon: list-check
mode: "wide"
---
## Overview

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

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

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@@ -2,6 +2,7 @@
title: Training
description: Learn how to train your CrewAI agents by giving them feedback early on and get consistent results.
icon: dumbbell
mode: "wide"
---
## Overview

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@@ -2,6 +2,7 @@
title: 'Agent Repositories'
description: 'Learn how to use Agent Repositories to share and reuse your agents across teams and projects'
icon: 'database'
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.

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

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@@ -2,6 +2,7 @@
title: Integrations
description: "Connected applications for your agents to take actions."
icon: "plug"
mode: "wide"
---
## Overview

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

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@@ -2,6 +2,7 @@
title: Tool Repository
description: "Using the Tool Repository to manage your tools"
icon: "toolbox"
mode: "wide"
---
## Overview

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@@ -2,6 +2,7 @@
title: Traces
description: "Using Traces to monitor your Crews"
icon: "timeline"
mode: "wide"
---
## Overview

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@@ -2,6 +2,7 @@
title: Webhook Streaming
description: "Using Webhook Streaming to stream events to your webhook"
icon: "webhook"
mode: "wide"
---
## Overview
@@ -62,16 +63,96 @@ As requests are sent over HTTP, the order of events can't be guaranteed. If you
CrewAI supports both system events and custom events in Enterprise Event Streaming. These events are sent to your configured webhook endpoint during crew and flow execution.
- `crew_kickoff_started`
- `crew_step_started`
- `crew_step_completed`
- `crew_execution_completed`
- `llm_call_started`
- `llm_call_completed`
- `tool_usage_started`
- `tool_usage_completed`
- `crew_test_failed`
- *...and others*
### Flow Events:
- 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 source](https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events) for the full list.

View File

@@ -2,6 +2,7 @@
title: "Automation Triggers"
description: "Automatically execute your CrewAI workflows when specific events occur in connected integrations"
icon: "bolt"
mode: "wide"
---
Automation triggers enable you to automatically run your CrewAI deployments when specific events occur in your connected integrations, creating powerful event-driven workflows that respond to real-time changes in your business systems.

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

View File

@@ -2,6 +2,7 @@
title: "Build Crew"
description: "A Crew is a group of agents that work together to complete a task."
icon: "people-arrows"
mode: "wide"
---
## Overview

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

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

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@@ -2,6 +2,7 @@
title: "HubSpot Trigger"
description: "Trigger CrewAI crews directly from HubSpot Workflows"
icon: "hubspot"
mode: "wide"
---
This guide provides a step-by-step process to set up HubSpot triggers for CrewAI Enterprise, enabling you to initiate crews directly from HubSpot Workflows.

View File

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

View File

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

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

View File

@@ -2,6 +2,7 @@
title: "Salesforce Trigger"
description: "Trigger CrewAI crews from Salesforce workflows for CRM automation"
icon: "salesforce"
mode: "wide"
---
CrewAI Enterprise can be triggered from Salesforce to automate customer relationship management workflows and enhance your sales operations.

View File

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

View File

@@ -2,6 +2,7 @@
title: "Team Management"
description: "Learn how to invite and manage team members in your CrewAI Enterprise organization"
icon: "users"
mode: "wide"
---
As an administrator of a CrewAI Enterprise account, you can easily invite new team members to join your organization. This guide will walk you through the process step-by-step.

View File

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

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

View File

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

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

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

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

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title: GitHub Integration
description: "Repository and issue management with GitHub integration for CrewAI."
icon: "github"
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---
## Overview

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title: Gmail Integration
description: "Email and contact management with Gmail integration for CrewAI."
icon: "envelope"
mode: "wide"
---
## Overview

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title: Google Calendar Integration
description: "Event and schedule management with Google Calendar integration for CrewAI."
icon: "calendar"
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---
## Overview

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title: Google Sheets Integration
description: "Spreadsheet data synchronization with Google Sheets integration for CrewAI."
icon: "google"
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---
## Overview

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title: "HubSpot Integration"
description: "Manage companies and contacts in HubSpot with CrewAI."
icon: "briefcase"
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---
## Overview

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title: Jira Integration
description: "Issue tracking and project management with Jira integration for CrewAI."
icon: "bug"
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---
## Overview

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title: Linear Integration
description: "Software project and bug tracking with Linear integration for CrewAI."
icon: "list-check"
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---
## Overview

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title: Notion Integration
description: "Page and database management with Notion integration for CrewAI."
icon: "book"
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---
## Overview

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title: Salesforce Integration
description: "CRM and sales automation with Salesforce integration for CrewAI."
icon: "salesforce"
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---
## Overview

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title: Shopify Integration
description: "E-commerce and online store management with Shopify integration for CrewAI."
icon: "shopify"
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## Overview

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title: Slack Integration
description: "Team communication and collaboration with Slack integration for CrewAI."
icon: "slack"
mode: "wide"
---
## Overview

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title: Stripe Integration
description: "Payment processing and subscription management with Stripe integration for CrewAI."
icon: "stripe"
mode: "wide"
---
## Overview

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title: Zendesk Integration
description: "Customer support and helpdesk management with Zendesk integration for CrewAI."
icon: "headset"
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## Overview

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title: "CrewAI Enterprise"
description: "Deploy, monitor, and scale your AI agent workflows"
icon: "globe"
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## Introduction

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title: FAQs
description: "Frequently asked questions about CrewAI Enterprise"
icon: "circle-question"
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---
<AccordionGroup>

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title: CrewAI Cookbooks
description: Feature-focused quickstarts and notebooks for learning patterns fast.
icon: book
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## Quickstarts & Demos

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title: CrewAI Examples
description: Explore curated examples organized by Crews, Flows, Integrations, and Notebooks.
icon: rocket-launch
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---
## Crews

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

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title: Fingerprinting
description: Learn how to use CrewAI's fingerprinting system to uniquely identify and track components throughout their lifecycle.
icon: fingerprint
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## Overview

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title: Crafting Effective Agents
description: Learn best practices for designing powerful, specialized AI agents that collaborate effectively to solve complex problems.
icon: robot
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## The Art and Science of Agent Design

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

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title: Build Your First Crew
description: Step-by-step tutorial to create a collaborative AI team that works together to solve complex problems.
icon: users-gear
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---
## Unleashing the Power of Collaborative AI

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

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title: Mastering Flow State Management
description: A comprehensive guide to managing, persisting, and leveraging state in CrewAI Flows for building robust AI applications.
icon: diagram-project
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## Understanding the Power of State in Flows

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title: Installation
description: Get started with CrewAI - Install, configure, and build your first AI crew
icon: wrench
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## Video Tutorial

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title: Introduction
description: Build AI agent teams that work together to tackle complex tasks
icon: handshake
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---
# What is CrewAI?

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

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title: Bring your own agent
description: Learn how to bring your own agents that work within a Crew.
icon: robots
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---
Interoperability is a core concept in CrewAI. This guide will show you how to bring your own agents that work within a Crew.

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title: Coding Agents
description: Learn how to enable your CrewAI Agents to write and execute code, and explore advanced features for enhanced functionality.
icon: rectangle-code
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## Introduction

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title: Conditional Tasks
description: Learn how to use conditional tasks in a crewAI kickoff
icon: diagram-subtask
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---
## Introduction

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

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title: Custom LLM Implementation
description: Learn how to create custom LLM implementations in CrewAI.
icon: code
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---
## Overview

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title: Custom Manager Agent
description: Learn how to set a custom agent as the manager in CrewAI, providing more control over task management and coordination.
icon: user-shield
mode: "wide"
---
# Setting a Specific Agent as Manager in CrewAI

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title: Customize Agents
description: A comprehensive guide to tailoring agents for specific roles, tasks, and advanced customizations within the CrewAI framework.
icon: user-pen
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---
## Customizable Attributes

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title: "Image Generation with DALL-E"
description: "Learn how to use DALL-E for AI-powered image generation in your CrewAI projects"
icon: "image"
mode: "wide"
---
CrewAI supports integration with OpenAI's DALL-E, allowing your AI agents to generate images as part of their tasks. This guide will walk you through how to set up and use the DALL-E tool in your CrewAI projects.

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title: Force Tool Output as Result
description: Learn how to force tool output as the result in an Agent's task in CrewAI.
icon: wrench-simple
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## Introduction

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title: Hierarchical Process
description: A comprehensive guide to understanding and applying the hierarchical process within your CrewAI projects, updated to reflect the latest coding practices and functionalities.
icon: sitemap
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---
## Introduction

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

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title: Human Input on Execution
description: Integrating CrewAI with human input during execution in complex decision-making processes and leveraging the full capabilities of the agent's attributes and tools.
icon: user-check
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---
## Human input in agent execution

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title: Kickoff Crew Asynchronously
description: Kickoff a Crew Asynchronously
icon: rocket-launch
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---
## Introduction

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title: Kickoff Crew for Each
description: Kickoff Crew for Each Item in a List
icon: at
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---
## Introduction

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title: Connect to any LLM
description: Comprehensive guide on integrating CrewAI with various Large Language Models (LLMs) using LiteLLM, including supported providers and configuration options.
icon: brain-circuit
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---
## Connect CrewAI to LLMs

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title: 'Strategic LLM Selection Guide'
description: 'Strategic framework for choosing the right LLM for your CrewAI AI agents and writing effective task and agent definitions'
icon: 'brain-circuit'
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---
## The CrewAI Approach to LLM Selection

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title: Using Multimodal Agents
description: Learn how to enable and use multimodal capabilities in your agents for processing images and other non-text content within the CrewAI framework.
icon: video
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---
## Using Multimodal Agents

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title: "Overview"
description: "Learn how to build, customize, and optimize your CrewAI applications with comprehensive guides and tutorials"
icon: "face-smile"
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---
## Learn CrewAI

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