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21 Commits

Author SHA1 Message Date
Rip&Tear
5bddfc6782 fix: replace unsafe ast.literal_eval() with secure alternative to prevent code injection
- Remove unsafe ast.literal_eval() usage in _validate_tool_input method
- Implement _safe_literal_parse() with strict input validation
- Add dangerous pattern detection to block __import__, exec, eval, lambda, etc.
- Support limited Python literal syntax (strings, numbers, booleans, None, lists, dicts)
- Only allow specific safe characters in input
- Maintain backward compatibility for valid tool inputs

Fixes security vulnerability where malicious tool_input could execute arbitrary Python code.

Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
2025-10-12 19:33:28 +08:00
Rip&Tear
5e3f2e7be2 test 2025-10-12 16:59:57 +08:00
Rip&Tear
02c808eaae test: trigger local k8s deployment 2025-10-12 16:59:21 +08:00
Greyson LaLonde
7b550ebfe8 fix: inject tool repository credentials in crewai run command
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2025-10-10 15:00:04 -04:00
Greyson LaLonde
29919c2d81 fix: revert bad cron sched
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This reverts commit b71c88814f.
2025-10-09 13:52:25 -04:00
Greyson LaLonde
b71c88814f fix: correct cron schedule to run every 5 days at specific dates 2025-10-09 13:10:45 -04:00
Rip&Tear
cb8bcfe214 docs: update security policy for vulnerability reporting
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- Revised the security policy to clarify the reporting process for vulnerabilities.
- Added detailed sections on scope, reporting requirements, and our commitment to addressing reported issues.
- Emphasized the importance of not disclosing vulnerabilities publicly and provided guidance on how to report them securely.
- Included a new section on coordinated disclosure and safe harbor provisions for ethical reporting.

Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
2025-10-09 00:57:57 -04:00
Lorenze Jay
13a514f8be chore: update crewAI and crewAI-tools dependencies to version 0.203.0 and 0.76.0 respectively (#3674)
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- Updated the `crewai-tools` dependency in `pyproject.toml` and `uv.lock` to version 0.76.0.
- Updated the `crewai` version in `__init__.py` to 0.203.0.
- Updated the dependency versions in the crew, flow, and tool templates to reflect the new `crewai` version.
2025-10-08 14:34:51 -07:00
Lorenze Jay
316b1cea69 docs: add guide for capturing telemetry logs in CrewAI AMP (#3673)
- Introduced a new documentation page detailing how to capture telemetry logs from CrewAI AMP deployments.
- Updated the main documentation to include the new guide in the enterprise section.
- Added prerequisites and step-by-step instructions for configuring OTEL collector setup.
- Included an example image for OTEL log collection capture to Datadog.
2025-10-08 14:06:10 -07:00
Lorenze Jay
6f2e39c0dd feat: enhance knowledge and guardrail event handling in Agent class (#3672)
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* feat: enhance knowledge event handling in Agent class

- Updated the Agent class to include task context in knowledge retrieval events.
- Emitted new events for knowledge retrieval and query processes, capturing task and agent details.
- Refactored knowledge event classes to inherit from a base class for better structure and maintainability.
- Added tracing for knowledge events in the TraceCollectionListener to improve observability.

This change improves the tracking and management of knowledge queries and retrievals, facilitating better debugging and performance monitoring.

* refactor: remove task_id from knowledge event emissions in Agent class

- Removed the task_id parameter from various knowledge event emissions in the Agent class to streamline event handling.
- This change simplifies the event structure and focuses on the essential context of knowledge retrieval and query processes.

This refactor enhances the clarity of knowledge events and aligns with the recent improvements in event handling.

* surface association for guardrail events

* fix: improve LLM selection logic in converter

- Updated the logic for selecting the LLM in the convert_with_instructions function to handle cases where the agent may not have a function_calling_llm attribute.
- This change ensures that the converter can still function correctly by falling back to the standard LLM if necessary, enhancing robustness and preventing potential errors.

This fix improves the reliability of the conversion process when working with different agent configurations.

* fix test

* fix: enforce valid LLM instance requirement in converter

- Updated the convert_with_instructions function to ensure that a valid LLM instance is provided by the agent.
- If neither function_calling_llm nor the standard llm is available, a ValueError is raised, enhancing error handling and robustness.
- Improved error messaging for conversion failures to provide clearer feedback on issues encountered during the conversion process.

This change strengthens the reliability of the conversion process by ensuring that agents are properly configured with a valid LLM.
2025-10-08 11:53:13 -07:00
Lucas Gomide
8d93361cb3 docs: add missing /resume files (#3661)
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2025-10-07 12:21:27 -04:00
Lucas Gomide
54ec245d84 docs: clarify webhook URL parameter in HITL workflows (#3660) 2025-10-07 12:06:11 -04:00
Vidit Ostwal
f589ab9b80 chore: load json tool input before console output
Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
2025-10-07 10:18:28 -04:00
Greyson LaLonde
fadb59e0f0 chore: add scheduled cache rebuild to prevent expiration
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2025-10-06 11:45:28 -04:00
Greyson LaLonde
1a60848425 chore: remove crewAI.excalidraw file 2025-10-06 11:03:55 -04:00
Greyson LaLonde
0135163040 chore: remove mkdocs cache directory
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Remove obsolete .cache directory from mkdocs-material social plugin as the project no longer uses mkdocs for documentation.
2025-10-05 21:41:09 -04:00
Greyson LaLonde
dac5d6d664 fix: use system PATH for Docker binary instead of hardcoded path 2025-10-05 21:36:05 -04:00
Rip&Tear
f0f94f2540 fix: add CodeQL configuration to properly exclude template directories (#3641) 2025-10-06 08:21:51 +08:00
Tony Kipkemboi
bf9e0423f2 chore(docs): bring AMP doc refresh from release/v1.0.0 into main (#3637)
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* WIP: v1 docs (#3626)

(cherry picked from commit d46e20fa09bcd2f5916282f5553ddeb7183bd92c)

* docs: parity for all translations

* docs: full name of acronym AMP

* docs: fix lingering unused code

* docs: expand contextual options in docs.json

* docs: add contextual action to request feature on GitHub

* chore: tidy docs formatting
2025-10-02 11:36:04 -04:00
Lorenze Jay
f47e0c82c4 Add tracing documentation and enable tracing feature in CrewAI
- Introduced a new documentation page for CrewAI Tracing, detailing setup and usage.
- Updated the main documentation to include the new tracing page in the observability section.
- Added example code snippets for enabling tracing in both Crews and Flows.
- Included instructions for global tracing configuration via environment variables.
- Added a new image for the CrewAI Tracing interface.
2025-10-02 07:33:18 -04:00
Doug Guthrie
eabced321c Add braintrust docs (#3628)
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* Add braintrust docs

* Add more things

* fix eval command

* Add missing crewai-tools import

* Allow for dynamic inputs
2025-10-01 14:38:22 -04:00
1366 changed files with 19286 additions and 58080 deletions

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21
.github/codeql/codeql-config.yml vendored Normal file
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@@ -0,0 +1,21 @@
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

63
.github/security.md vendored
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@@ -1,27 +1,50 @@
## CrewAI Security Vulnerability Reporting Policy
## CrewAI Security Policy
CrewAI prioritizes the security of our software products, services, and GitHub repositories. To promptly address vulnerabilities, follow these steps for reporting security issues:
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.
### Reporting Process
Do **not** report vulnerabilities via public GitHub issues.
### Scope
Email all vulnerability reports directly to:
**security@crewai.com**
We welcome reports for vulnerabilities that could impact:
### Required Information
To help us quickly validate and remediate the issue, your report must include:
- CrewAI-maintained source code and repositories
- CrewAI-operated infrastructure and services
- Official CrewAI releases, packages, and distributions
- **Vulnerability Type:** Clearly state the vulnerability type (e.g., SQL injection, XSS, privilege escalation).
- **Affected Source Code:** Provide full file paths and direct URLs (branch, tag, or commit).
- **Reproduction Steps:** Include detailed, step-by-step instructions. Screenshots are recommended.
- **Special Configuration:** Document any special settings or configurations required to reproduce.
- **Proof-of-Concept (PoC):** Provide exploit or PoC code (if available).
- **Impact Assessment:** Clearly explain the severity and potential exploitation scenarios.
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.
### Our Response
- We will acknowledge receipt of your report promptly via your provided email.
- Confirmed vulnerabilities will receive priority remediation based on severity.
- Patches will be released as swiftly as possible following verification.
### How to Report
### Reward Notice
Currently, we do not offer a bug bounty program. Rewards, if issued, are discretionary.
- **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.

View File

@@ -7,6 +7,8 @@ on:
paths:
- "uv.lock"
- "pyproject.toml"
schedule:
- cron: "0 0 */5 * *" # Run every 5 days at midnight UTC to prevent cache expiration
workflow_dispatch:
permissions:

View File

@@ -15,11 +15,11 @@ on:
push:
branches: [ "main" ]
paths-ignore:
- "lib/crewai/src/crewai/cli/templates/**"
- "src/crewai/cli/templates/**"
pull_request:
branches: [ "main" ]
paths-ignore:
- "lib/crewai/src/crewai/cli/templates/**"
- "src/crewai/cli/templates/**"
jobs:
analyze:
@@ -73,6 +73,7 @@ jobs:
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.

View File

@@ -52,10 +52,10 @@ jobs:
- name: Run Ruff on Changed Files
if: ${{ steps.changed-files.outputs.files != '' }}
run: |
echo "${{ steps.changed-files.outputs.files }}" \
| tr ' ' '\n' \
| grep -v 'src/crewai/cli/templates/' \
| xargs -I{} uv run ruff check "{}"
echo "${{ steps.changed-files.outputs.files }}" \
| tr ' ' '\n' \
| grep -v 'src/crewai/cli/templates/' \
| xargs -I{} uv run ruff check "{}"
- name: Save uv caches
if: steps.cache-restore.outputs.cache-hit != 'true'

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

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@@ -8,14 +8,6 @@ permissions:
env:
OPENAI_API_KEY: fake-api-key
PYTHONUNBUFFERED: 1
BRAVE_API_KEY: fake-brave-key
SNOWFLAKE_USER: fake-snowflake-user
SNOWFLAKE_PASSWORD: fake-snowflake-password
SNOWFLAKE_ACCOUNT: fake-snowflake-account
SNOWFLAKE_WAREHOUSE: fake-snowflake-warehouse
SNOWFLAKE_DATABASE: fake-snowflake-database
SNOWFLAKE_SCHEMA: fake-snowflake-schema
EMBEDCHAIN_DB_URI: sqlite:///test.db
jobs:
tests:
@@ -64,13 +56,13 @@ jobs:
- 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}"
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"
@@ -82,8 +74,8 @@ jobs:
# echo "No test changes detected, using cached test durations for optimal splitting"
# DURATIONS_ARG="--durations-path=${DURATION_FILE}"
# fi
cd lib/crewai && uv run pytest \
uv run pytest \
--block-network \
--timeout=30 \
-vv \
@@ -94,19 +86,6 @@ jobs:
-n auto \
--maxfail=3
- name: Run tool tests (group ${{ matrix.group }} of 8)
run: |
cd lib/crewai-tools && uv run pytest \
--block-network \
--timeout=30 \
-vv \
--splits 8 \
--group ${{ matrix.group }} \
--durations=10 \
-n auto \
--maxfail=3
- name: Save uv caches
if: steps.cache-restore.outputs.cache-hit != 'true'
uses: actions/cache/save@v4

1
.gitignore vendored
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@@ -2,6 +2,7 @@
.pytest_cache
__pycache__
dist/
lib/
.env
assets/*
.idea

View File

@@ -6,16 +6,14 @@ repos:
entry: uv run ruff check
language: system
types: [python]
exclude: ^lib/crewai/
- id: ruff-format
name: ruff-format
entry: uv run ruff format
language: system
types: [python]
exclude: ^lib/crewai/
- id: mypy
name: mypy
entry: uv run mypy
language: system
types: [python]
exclude: ^lib/crewai/
exclude: ^tests/

View File

@@ -62,9 +62,9 @@
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 Enterprise Suite
# CrewAI AMP Suite
CrewAI Enterprise Suite is a comprehensive bundle tailored for organizations that require secure, scalable, and easy-to-manage agent-driven automation.
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)
@@ -76,9 +76,9 @@ You can try one part of the suite the [Crew Control Plane for free](https://app.
- **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 Enterprise on-premise or in the cloud, depending on your security and compliance requirements.
- **On-premise and Cloud Deployment Options**: Deploy CrewAI AMP on-premise or in the cloud, depending on your security and compliance requirements.
CrewAI Enterprise is designed for enterprises seeking a powerful, reliable solution to transform complex business processes into efficient,
CrewAI AMP is designed for enterprises seeking a powerful, reliable solution to transform complex business processes into efficient,
intelligent automations.
## Table of contents
@@ -674,9 +674,9 @@ CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/b
### Enterprise Features
- [What additional features does CrewAI Enterprise offer?](#q-what-additional-features-does-crewai-enterprise-offer)
- [Is CrewAI Enterprise available for cloud and on-premise deployments?](#q-is-crewai-enterprise-available-for-cloud-and-on-premise-deployments)
- [Can I try CrewAI Enterprise for free?](#q-can-i-try-crewai-enterprise-for-free)
- [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?
@@ -732,17 +732,17 @@ A: Check out practical examples in the [CrewAI-examples repository](https://gith
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 Enterprise offer?
### Q: What additional features does CrewAI AMP offer?
A: CrewAI Enterprise provides advanced features such as a unified control plane, real-time observability, secure integrations, advanced security, actionable insights, and dedicated 24/7 enterprise support.
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 Enterprise available for cloud and on-premise deployments?
### Q: Is CrewAI AMP available for cloud and on-premise deployments?
A: Yes, CrewAI Enterprise supports both cloud-based and on-premise deployment options, allowing enterprises to meet their specific security and compliance requirements.
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 Enterprise for free?
### Q: Can I try CrewAI AMP for free?
A: Yes, you can explore part of the CrewAI Enterprise Suite by accessing the [Crew Control Plane](https://app.crewai.com) 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?
@@ -762,7 +762,7 @@ A: CrewAI is highly scalable, supporting simple automations and large-scale ente
### Q: Does CrewAI offer debugging and monitoring tools?
A: Yes, CrewAI Enterprise includes advanced debugging, tracing, and real-time observability features, simplifying the management and troubleshooting of your automations.
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?
@@ -775,3 +775,4 @@ A: Yes, CrewAI provides extensive beginner-friendly tutorials, courses, and docu
### 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.
# test

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View File

@@ -9,7 +9,22 @@
},
"favicon": "/images/favicon.svg",
"contextual": {
"options": ["copy", "view", "chatgpt", "claude"]
"options": [
"copy",
"view",
"chatgpt",
"claude",
"perplexity",
"mcp",
"cursor",
"vscode",
{
"title": "Request a feature",
"description": "Join the discussion on GitHub to request a new feature",
"icon": "plus",
"href": "https://github.com/crewAIInc/crewAI/issues/new/choose"
}
]
},
"navigation": {
"languages": [
@@ -256,8 +271,10 @@
{
"group": "Observability",
"pages": [
"en/observability/tracing",
"en/observability/overview",
"en/observability/arize-phoenix",
"en/observability/braintrust",
"en/observability/langdb",
"en/observability/langfuse",
"en/observability/langtrace",
@@ -287,6 +304,7 @@
"en/learn/force-tool-output-as-result",
"en/learn/hierarchical-process",
"en/learn/human-input-on-execution",
"en/learn/human-in-the-loop",
"en/learn/kickoff-async",
"en/learn/kickoff-for-each",
"en/learn/llm-connections",
@@ -303,7 +321,7 @@
]
},
{
"tab": "Enterprise",
"tab": "AMP",
"icon": "briefcase",
"groups": [
{
@@ -379,6 +397,7 @@
"en/enterprise/guides/kickoff-crew",
"en/enterprise/guides/update-crew",
"en/enterprise/guides/enable-crew-studio",
"en/enterprise/guides/capture_telemetry_logs",
"en/enterprise/guides/azure-openai-setup",
"en/enterprise/guides/tool-repository",
"en/enterprise/guides/react-component-export",
@@ -403,6 +422,7 @@
"en/api-reference/introduction",
"en/api-reference/inputs",
"en/api-reference/kickoff",
"en/api-reference/resume",
"en/api-reference/status"
]
}
@@ -667,6 +687,7 @@
"pages": [
"pt-BR/observability/overview",
"pt-BR/observability/arize-phoenix",
"pt-BR/observability/braintrust",
"pt-BR/observability/langdb",
"pt-BR/observability/langfuse",
"pt-BR/observability/langtrace",
@@ -695,6 +716,7 @@
"pt-BR/learn/force-tool-output-as-result",
"pt-BR/learn/hierarchical-process",
"pt-BR/learn/human-input-on-execution",
"pt-BR/learn/human-in-the-loop",
"pt-BR/learn/kickoff-async",
"pt-BR/learn/kickoff-for-each",
"pt-BR/learn/llm-connections",
@@ -711,7 +733,7 @@
]
},
{
"tab": "Enterprise",
"tab": "AMP",
"icon": "briefcase",
"groups": [
{
@@ -807,6 +829,7 @@
"pt-BR/api-reference/introduction",
"pt-BR/api-reference/inputs",
"pt-BR/api-reference/kickoff",
"pt-BR/api-reference/resume",
"pt-BR/api-reference/status"
]
}
@@ -1049,7 +1072,6 @@
"ko/tools/cloud-storage/overview",
"ko/tools/cloud-storage/s3readertool",
"ko/tools/cloud-storage/s3writertool",
"ko/tools/cloud-storage/bedrockinvokeagenttool",
"ko/tools/cloud-storage/bedrockkbretriever"
]
},
@@ -1080,6 +1102,7 @@
"pages": [
"ko/observability/overview",
"ko/observability/arize-phoenix",
"ko/observability/braintrust",
"ko/observability/langdb",
"ko/observability/langfuse",
"ko/observability/langtrace",
@@ -1108,6 +1131,7 @@
"ko/learn/force-tool-output-as-result",
"ko/learn/hierarchical-process",
"ko/learn/human-input-on-execution",
"ko/learn/human-in-the-loop",
"ko/learn/kickoff-async",
"ko/learn/kickoff-for-each",
"ko/learn/llm-connections",
@@ -1218,6 +1242,7 @@
"ko/api-reference/introduction",
"ko/api-reference/inputs",
"ko/api-reference/kickoff",
"ko/api-reference/resume",
"ko/api-reference/status"
]
}

View File

@@ -1,29 +1,29 @@
---
title: "Introduction"
description: "Complete reference for the CrewAI Enterprise REST API"
description: "Complete reference for the CrewAI AMP REST API"
icon: "code"
mode: "wide"
---
# CrewAI Enterprise API
# CrewAI AMP API
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.
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.
## Quick Start
<Steps>
<Step title="Get Your API Credentials">
Navigate to your crew's detail page in the CrewAI Enterprise dashboard and copy your Bearer Token from the Status tab.
Navigate to your crew's detail page in the CrewAI AMP 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 +46,7 @@ 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 Enterprise dashboard.
You can find both token types in the Status tab of your crew's detail page in the CrewAI AMP dashboard.
</Tip>
## Base URL
@@ -62,7 +62,7 @@ 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 +82,12 @@ The API uses standard HTTP status codes:
## Interactive Testing
<Info>
**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.
**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.
</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 +104,7 @@ 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

View File

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

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@@ -20,7 +20,7 @@ Think of an agent as a specialized team member with specific skills, expertise,
</Tip>
<Note type="info" title="Enterprise Enhancement: Visual Agent Builder">
CrewAI 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.
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.
![Visual Agent Builder Screenshot](/images/enterprise/crew-studio-interface.png)

View File

@@ -5,7 +5,7 @@ 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>
<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
@@ -186,9 +186,9 @@ def crew(self) -> Crew:
### 10. Deploy
Deploy the crew or flow to [CrewAI Enterprise](https://app.crewai.com).
Deploy the crew or flow to [CrewAI AMP](https://app.crewai.com).
- **Authentication**: You need to be authenticated to deploy to CrewAI Enterprise.
- **Authentication**: You need to be authenticated to deploy to CrewAI AMP.
You can login or create an account with:
```shell Terminal
crewai login
@@ -203,7 +203,7 @@ Deploy the crew or flow to [CrewAI Enterprise](https://app.crewai.com).
### 11. Organization Management
Manage your CrewAI Enterprise organizations.
Manage your CrewAI AMP organizations.
```shell Terminal
crewai org [COMMAND] [OPTIONS]
@@ -227,17 +227,17 @@ crewai org switch <organization_id>
```
<Note>
You must be authenticated to CrewAI Enterprise to use these organization management commands.
You must be authenticated to CrewAI AMP 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 Enterprise.
- **Deploy the Crew**: Once you are authenticated, you can deploy your crew or flow to CrewAI AMP.
```shell Terminal
crewai deploy push
```
- Initiates the deployment process on the CrewAI Enterprise platform.
- Initiates the deployment process on the CrewAI AMP 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 Enterprise to use these organization managem
```shell Terminal
crewai deploy remove
```
This deletes the deployment from the CrewAI Enterprise platform.
This deletes the deployment from the CrewAI AMP platform.
- **Help Command**: You can get help with the CLI with:
```shell Terminal
@@ -270,7 +270,7 @@ You must be authenticated to CrewAI Enterprise to use these organization managem
```
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 Enterprise](http://app.crewai.com) using the 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.
<iframe
className="w-full aspect-video rounded-xl"
@@ -283,7 +283,7 @@ Watch this video tutorial for a step-by-step demonstration of deploying your cre
### 11. Login
Authenticate with CrewAI Enterprise using a secure device code flow (no email entry required).
Authenticate with CrewAI AMP using a secure device code flow (no email entry required).
```shell Terminal
crewai login
@@ -354,7 +354,7 @@ crewai config reset
#### Available Configuration Parameters
- `enterprise_base_url`: Base URL of the CrewAI Enterprise instance
- `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
@@ -370,7 +370,7 @@ crewai config list
Example output:
| Setting | Value | Description |
| :------------------ | :----------------------- | :---------------------------------------------------------- |
| enterprise_base_url | https://app.crewai.com | Base URL of the CrewAI Enterprise instance |
| 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) |

View File

@@ -20,7 +20,7 @@ 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 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.
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.
![Prompt Tracing Dashboard](/images/enterprise/traces-overview.png)

View File

@@ -14,7 +14,7 @@ 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 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.
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.
![Task Builder Screenshot](/images/enterprise/crew-studio-interface.png)

View File

@@ -17,7 +17,7 @@ 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 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.
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.
The Enterprise Tools Repository includes:
- Pre-built connectors for popular enterprise systems
@@ -208,7 +208,7 @@ 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

View File

@@ -102,5 +102,3 @@ Once deployed, you can view the automation details and have the **Options** drop
Stream real-time events and updates to your systems.
</Card>
</CardGroup>

View File

@@ -86,5 +86,3 @@ Once published, you can view the automation details and have the **Options** dro
Export a React Component.
</Card>
</CardGroup>

View File

@@ -28,7 +28,7 @@ The Marketplace provides a curated surface for discovering integrations, interna
![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 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
@@ -44,5 +44,3 @@ you can use them locally or refine them to your needs.
Store, share, and reuse agent definitions across teams and projects.
</Card>
</CardGroup>

View File

@@ -7,16 +7,16 @@ mode: "wide"
## Overview
RBAC in CrewAI Enterprise enables secure, scalable access management through a combination of organizationlevel roles and automationlevel visibility controls.
RBAC in CrewAI AMP enables secure, scalable access management through a combination of organizationlevel roles and automationlevel visibility controls.
<Frame>
<img src="/images/enterprise/users_and_roles.png" alt="RBAC overview in CrewAI Enterprise" />
<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.
Each member in your CrewAI workspace is assigned a role, which determines their access across various features.
You can:
@@ -28,7 +28,7 @@ You can configure users and roles in Settings → Roles.
<Steps>
<Step title="Open Roles settings">
Go to <b>Settings → Roles</b> in CrewAI Enterprise.
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.
@@ -93,12 +93,10 @@ The organization owner always has access. In private mode, only whitelisted user
</Tip>
<Frame>
<img src="/images/enterprise/visibility.png" alt="Automation Visibility settings in CrewAI Enterprise" />
<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>

View File

@@ -188,10 +188,10 @@ Tools & Integrations is the central hub for connecting thirdparty apps and ma
## Internal Tools
Create custom tools locally, publish them on CrewAI Enterprise Tool Repository and use them in your agents.
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 Enterprise account by running this command:
Before running the commands below, make sure you log in to your CrewAI AMP account by running this command:
```bash
crewai login
```
@@ -209,13 +209,13 @@ Tools & Integrations is the central hub for connecting thirdparty apps and ma
```
</Step>
<Step title="Publish">
Publish the tool to the CrewAI Enterprise Tool Repository.
Publish the tool to the CrewAI AMP Tool Repository.
```bash
crewai tool publish
```
</Step>
<Step title="Install">
Install the tool from the CrewAI Enterprise Tool Repository.
Install the tool from the CrewAI AMP Tool Repository.
```bash
crewai tool install your-tool
```
@@ -247,4 +247,3 @@ Tools & Integrations is the central hub for connecting thirdparty apps and ma
Automate workflows and integrate with external platforms and services.
</Card>
</CardGroup>

View File

@@ -11,7 +11,7 @@ Traces provide comprehensive visibility into your crew executions, helping you m
## What are Traces?
Traces in CrewAI Enterprise are detailed execution records that capture every aspect of your crew's operation, from initial inputs to final outputs. They record:
Traces in CrewAI AMP are detailed execution records that capture every aspect of your crew's operation, from initial inputs to final outputs. They record:
- Agent thoughts and reasoning
- Task execution details
@@ -28,9 +28,9 @@ Traces in CrewAI Enterprise are detailed execution records that capture every as
<Steps>
<Step title="Navigate to the Traces Tab">
Once in your CrewAI Enterprise dashboard, click on the **Traces** to view all execution records.
Once in your CrewAI AMP dashboard, click on the **Traces** to view all execution records.
</Step>
<Step title="Select an Execution">
You'll see a list of all crew executions, sorted by date. Click on any execution to view its detailed trace.
</Step>
@@ -112,7 +112,7 @@ Traces are invaluable for troubleshooting issues with your crews:
<Steps>
<Step title="Identify Failure Points">
When a crew execution doesn't produce the expected results, examine the trace to find where things went wrong. Look for:
- Failed tasks
- Unexpected agent decisions
- Tool usage errors
@@ -122,19 +122,19 @@ Traces are invaluable for troubleshooting issues with your crews:
![Failure Points](/images/enterprise/failure.png)
</Frame>
</Step>
<Step title="Optimize Performance">
Use execution metrics to identify performance bottlenecks:
- Tasks that took longer than expected
- Excessive token usage
- Redundant tool operations
- Unnecessary API calls
</Step>
<Step title="Improve Cost Efficiency">
Analyze token usage and cost estimates to optimize your crew's efficiency:
- Consider using smaller models for simpler tasks
- Refine prompts to be more concise
- Cache frequently accessed information
@@ -153,5 +153,5 @@ CrewAI batches trace uploads to reduce overhead on high-volume runs:
This yields more stable tracing under load while preserving detailed task/agent telemetry.
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
Contact our support team for assistance with trace analysis or any other CrewAI Enterprise features.
</Card>
Contact our support team for assistance with trace analysis or any other CrewAI AMP features.
</Card>

View File

@@ -7,8 +7,8 @@ mode: "wide"
## Overview
Enterprise Event Streaming lets you receive real-time webhook updates about your crews and flows deployed to
CrewAI Enterprise, such as model calls, tool usage, and flow steps.
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
@@ -151,7 +151,7 @@ CrewAI supports both system events and custom events in Enterprise Event Streami
### Reasoning Events:
- `agent_reasoning_started`
- `agent_reasoning_completed`
- `agent_reasoning_completed`
- `agent_reasoning_failed`
Event names match the internal event bus. See GitHub for the full list of events.
@@ -165,4 +165,4 @@ You can emit your own custom events, and they will be delivered through the webh
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
Contact our support team for assistance with webhook integration or troubleshooting.
</Card>
</CardGroup>
</CardGroup>

View File

@@ -1,11 +1,11 @@
---
title: "Triggers Overview"
description: "Understand how CrewAI Enterprise triggers work, how to manage them, and where to find integration-specific playbooks"
description: "Understand how CrewAI AMP triggers work, how to manage them, and where to find integration-specific playbooks"
icon: "face-smile"
mode: "wide"
---
CrewAI Enterprise triggers connect your automations to real-time events across the tools your teams already use. Instead of polling systems or relying on manual kickoffs, triggers listen for changes—new emails, calendar updates, CRM status changes—and immediately launch the crew or flow you specify.
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)
@@ -250,6 +250,6 @@ def delegate_to_crew(self, crewai_trigger_payload: dict = None):
Automation triggers transform your CrewAI deployments into responsive, event-driven systems that can seamlessly integrate with your existing business processes and tools.
<Card title="CrewAI Enterprise Trigger Examples" href="https://github.com/crewAIInc/crewai-enterprise-trigger-examples" icon="github">
<Card title="CrewAI AMP Trigger Examples" href="https://github.com/crewAIInc/crewai-enterprise-trigger-examples" icon="github">
Check them out on GitHub!
</Card>
</Card>

View File

@@ -19,8 +19,8 @@ This guide walks you through connecting Azure OpenAI with Crew Studio for seamle
</Frame>
</Step>
<Step title="Configure CrewAI Enterprise Connection">
4. In another tab, open `CrewAI Enterprise > LLM Connections`. Name your LLM Connection, select Azure as the provider, and choose the same model you selected in Azure.
<Step title="Configure CrewAI AMP Connection">
4. In another tab, open `CrewAI AMP > LLM Connections`. Name your LLM Connection, select Azure as the provider, and choose the same model you selected in Azure.
5. On the same page, add environment variables from step 3:
- One named `AZURE_DEPLOYMENT_TARGET_URL` (using the Target URI). The URL should look like this: https://your-deployment.openai.azure.com/openai/deployments/gpt-4o/chat/completions?api-version=2024-08-01-preview
- Another named `AZURE_API_KEY` (using the Key).
@@ -28,7 +28,7 @@ This guide walks you through connecting Azure OpenAI with Crew Studio for seamle
</Step>
<Step title="Set Default Configuration">
7. In `CrewAI Enterprise > Settings > Defaults > Crew Studio LLM Settings`, set the new LLM Connection and model as defaults.
7. In `CrewAI AMP > Settings > Defaults > Crew Studio LLM Settings`, set the new LLM Connection and model as defaults.
</Step>
<Step title="Configure Network Access">
@@ -49,4 +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

@@ -7,7 +7,7 @@ mode: "wide"
## Overview
[CrewAI Enterprise](https://app.crewai.com) streamlines the process of **creating**, **deploying**, and **managing** your AI agents in production environments.
[CrewAI AMP](https://app.crewai.com) streamlines the process of **creating**, **deploying**, and **managing** your AI agents in production environments.
## Getting Started

View File

@@ -0,0 +1,35 @@
---
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>

View File

@@ -1,12 +1,12 @@
---
title: "Deploy Crew"
description: "Deploying a Crew on CrewAI Enterprise"
description: "Deploying a Crew on CrewAI AMP"
icon: "rocket"
mode: "wide"
---
<Note>
After creating a crew locally or through Crew Studio, the next step is deploying it to the CrewAI Enterprise platform. This guide covers multiple deployment methods to help you choose the best approach for your workflow.
After creating a crew locally or through Crew Studio, the next step is deploying it to the CrewAI AMP platform. This guide covers multiple deployment methods to help you choose the best approach for your workflow.
</Note>
## Prerequisites
@@ -39,10 +39,10 @@ The CLI provides the fastest way to deploy locally developed crews to the Enterp
</Step>
<Step title="Authenticate with the Enterprise Platform">
First, you need to authenticate your CLI with the CrewAI Enterprise platform:
First, you need to authenticate your CLI with the CrewAI AMP platform:
```bash
# If you already have a CrewAI Enterprise account, or want to create one:
# If you already have a CrewAI AMP account, or want to create one:
crewai login
```
@@ -124,7 +124,7 @@ The CrewAI CLI offers several commands to manage your deployments:
## Option 2: Deploy Directly via Web Interface
You can also deploy your crews directly through the CrewAI Enterprise web interface by connecting your GitHub account. This approach doesn't require using the CLI on your local machine.
You can also deploy your crews directly through the CrewAI AMP web interface by connecting your GitHub account. This approach doesn't require using the CLI on your local machine.
<Steps>
@@ -134,9 +134,9 @@ You can also deploy your crews directly through the CrewAI Enterprise web interf
</Step>
<Step title="Connecting GitHub to CrewAI Enterprise">
<Step title="Connecting GitHub to CrewAI AMP">
1. Log in to [CrewAI Enterprise](https://app.crewai.com)
1. Log in to [CrewAI AMP](https://app.crewai.com)
2. Click on the button "Connect GitHub"
<Frame>
@@ -190,7 +190,7 @@ You can also deploy your crews directly through the CrewAI Enterprise web interf
## ⚠️ Environment Variable Security Requirements
<Warning>
**Important**: CrewAI Enterprise has security restrictions on environment variable names that can cause deployment failures if not followed.
**Important**: CrewAI AMP has security restrictions on environment variable names that can cause deployment failures if not followed.
</Warning>
### Blocked Environment Variable Patterns

View File

@@ -1,17 +1,17 @@
---
title: "Enable Crew Studio"
description: "Enabling Crew Studio on CrewAI Enterprise"
description: "Enabling Crew Studio on CrewAI AMP"
icon: "comments"
mode: "wide"
---
<Tip>
Crew Studio is a powerful **no-code/low-code** tool that allows you to quickly scaffold or build Crews through a conversational interface.
Crew Studio is a powerful **no-code/low-code** tool that allows you to quickly scaffold or build Crews through a conversational interface.
</Tip>
## What is Crew Studio?
Crew Studio is an innovative way to create AI agent crews without writing code.
Crew Studio is an innovative way to create AI agent crews without writing code.
<Frame>
![Crew Studio Interface](/images/enterprise/crew-studio-interface.png)
@@ -24,7 +24,7 @@ With Crew Studio, you can:
- Select appropriate tools
- Configure necessary inputs
- Generate downloadable code for customization
- Deploy directly to the CrewAI Enterprise platform
- Deploy directly to the CrewAI AMP platform
## Configuration Steps
@@ -32,14 +32,14 @@ Before you can start using Crew Studio, you need to configure your LLM connectio
<Steps>
<Step title="Set Up LLM Connection">
Go to the **LLM Connections** tab in your CrewAI Enterprise dashboard and create a new LLM connection.
Go to the **LLM Connections** tab in your CrewAI AMP dashboard and create a new LLM connection.
<Note>
Feel free to use any LLM provider you want that is supported by CrewAI.
</Note>
Configure your LLM connection:
- Enter a `Connection Name` (e.g., `OpenAI`)
- Select your model provider: `openai` or `azure`
- Select models you'd like to use in your Studio-generated Crews
@@ -48,28 +48,28 @@ Before you can start using Crew Studio, you need to configure your LLM connectio
- For OpenAI: Add `OPENAI_API_KEY` with your API key
- For Azure OpenAI: Refer to [this article](https://blog.crewai.com/configuring-azure-openai-with-crewai-a-comprehensive-guide/) for configuration details
- Click `Add Connection` to save your configuration
<Frame>
![LLM Connection Configuration](/images/enterprise/llm-connection-config.png)
</Frame>
</Step>
<Step title="Verify Connection Added">
Once you complete the setup, you'll see your new connection added to the list of available connections.
<Frame>
![Connection Added](/images/enterprise/connection-added.png)
</Frame>
</Step>
<Step title="Configure LLM Defaults">
In the main menu, go to **Settings → Defaults** and configure the LLM Defaults settings:
- Select default models for agents and other components
- Set default configurations for Crew Studio
Click `Save Settings` to apply your changes.
<Frame>
![LLM Defaults Configuration](/images/enterprise/llm-defaults.png)
</Frame>
@@ -82,38 +82,38 @@ Now that you've configured your LLM connection and default settings, you're read
<Steps>
<Step title="Access Studio">
Navigate to the **Studio** section in your CrewAI Enterprise dashboard.
Navigate to the **Studio** section in your CrewAI AMP dashboard.
</Step>
<Step title="Start a Conversation">
Start a conversation with the Crew Assistant by describing the problem you want to solve:
```md
I need a crew that can research the latest AI developments and create a summary report.
```
The Crew Assistant will ask clarifying questions to better understand your requirements.
</Step>
<Step title="Review Generated Crew">
Review the generated crew configuration, including:
- Agents and their roles
- Tasks to be performed
- Required inputs
- Tools to be used
This is your opportunity to refine the configuration before proceeding.
</Step>
<Step title="Deploy or Download">
Once you're satisfied with the configuration, you can:
- Download the generated code for local customization
- Deploy the crew directly to the CrewAI Enterprise platform
- Deploy the crew directly to the CrewAI AMP platform
- Modify the configuration and regenerate the crew
</Step>
<Step title="Test Your Crew">
After deployment, test your crew with sample inputs to ensure it performs as expected.
</Step>
@@ -130,38 +130,37 @@ Here's a typical workflow for creating a crew with Crew Studio:
<Steps>
<Step title="Describe Your Problem">
Start by describing your problem:
```md
I need a crew that can analyze financial news and provide investment recommendations
```
</Step>
<Step title="Answer Questions">
Respond to clarifying questions from the Crew Assistant to refine your requirements.
</Step>
<Step title="Review the Plan">
Review the generated crew plan, which might include:
- A Research Agent to gather financial news
- An Analysis Agent to interpret the data
- A Recommendations Agent to provide investment advice
</Step>
<Step title="Approve or Modify">
Approve the plan or request changes if necessary.
</Step>
<Step title="Download or Deploy">
Download the code for customization or deploy directly to the platform.
</Step>
<Step title="Test and Refine">
Test your crew with sample inputs and refine as needed.
</Step>
</Steps>
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
Contact our support team for assistance with Crew Studio or any other CrewAI Enterprise features.
Contact our support team for assistance with Crew Studio or any other CrewAI AMP features.
</Card>

View File

@@ -15,7 +15,7 @@ Use the Gmail Trigger to kick off your deployed crews when Gmail events happen i
## Enabling the Gmail Trigger
1. Open your deployment in CrewAI Enterprise
1. Open your deployment in CrewAI AMP
2. Go to the **Triggers** tab
3. Locate **Gmail** and switch the toggle to enable
@@ -55,7 +55,7 @@ The Gmail payload will be available via the standard context mechanisms. See the
### Sample payloads & crews
The [CrewAI Enterprise Trigger Examples repository](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/gmail) includes:
The [CrewAI AMP Trigger Examples repository](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/gmail) includes:
- `new-email-payload-1.json` / `new-email-payload-2.json` — production-style new message alerts with matching crews in `new-email-crew.py`
- `thread-updated-sample-1.json` — follow-up messages on an existing thread, processed by `gmail-alert-crew.py`

View File

@@ -15,7 +15,7 @@ Use the Google Calendar trigger to launch automations whenever calendar events c
## Enabling the Google Calendar Trigger
1. Open your deployment in CrewAI Enterprise
1. Open your deployment in CrewAI AMP
2. Go to the **Triggers** tab
3. Locate **Google Calendar** and switch the toggle to enable

View File

@@ -15,7 +15,7 @@ Trigger your automations when files are created, updated, or removed in Google D
## Enabling the Google Drive Trigger
1. Open your deployment in CrewAI Enterprise
1. Open your deployment in CrewAI AMP
2. Go to the **Triggers** tab
3. Locate **Google Drive** and switch the toggle to enable

View File

@@ -5,22 +5,22 @@ 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.
This guide provides a step-by-step process to set up HubSpot triggers for CrewAI AMP, enabling you to initiate crews directly from HubSpot Workflows.
## Prerequisites
- A CrewAI Enterprise account
- A CrewAI AMP account
- A HubSpot account with the [HubSpot Workflows](https://knowledge.hubspot.com/workflows/create-workflows) feature
## Setup Steps
<Steps>
<Step title="Connect your HubSpot account with CrewAI Enterprise">
- Log in to your `CrewAI Enterprise account > Triggers`
<Step title="Connect your HubSpot account with CrewAI AMP">
- Log in to your `CrewAI AMP account > Triggers`
- Select `HubSpot` from the list of available triggers
- Choose the HubSpot account you want to connect with CrewAI Enterprise
- Follow the on-screen prompts to authorize CrewAI Enterprise access to your HubSpot account
- A confirmation message will appear once HubSpot is successfully connected with CrewAI Enterprise
- Choose the HubSpot account you want to connect with CrewAI AMP
- Follow the on-screen prompts to authorize CrewAI AMP access to your HubSpot account
- A confirmation message will appear once HubSpot is successfully connected with CrewAI AMP
</Step>
<Step title="Create a HubSpot Workflow">
- Log in to your `HubSpot account > Automations > Workflows > New workflow`
@@ -61,4 +61,4 @@ You can jump-start development with the [HubSpot examples in the trigger reposit
Each crew demonstrates how to parse HubSpot record fields, enrich context, and return structured insights.
For more detailed information on available actions and customization options, refer to the [HubSpot Workflows Documentation](https://knowledge.hubspot.com/workflows/create-workflows).
For more detailed information on available actions and customization options, refer to the [HubSpot Workflows Documentation](https://knowledge.hubspot.com/workflows/create-workflows).

View File

@@ -40,6 +40,28 @@ Human-In-The-Loop (HITL) is a powerful approach that combines artificial intelli
<Frame>
<img src="/images/enterprise/crew-resume-endpoint.png" alt="Crew Resume Endpoint" />
</Frame>
<Warning>
**Critical: Webhook URLs Must Be Provided Again**:
You **must** provide the same webhook URLs (`taskWebhookUrl`, `stepWebhookUrl`, `crewWebhookUrl`) in the resume call that you used in the kickoff call. Webhook configurations are **NOT** automatically carried over from kickoff - they must be explicitly included in the resume request to continue receiving notifications for task completion, agent steps, and crew completion.
</Warning>
Example resume call with webhooks:
```bash
curl -X POST {BASE_URL}/resume \
-H "Authorization: Bearer YOUR_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"execution_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv",
"task_id": "research_task",
"human_feedback": "Great work! Please add more details.",
"is_approve": true,
"taskWebhookUrl": "https://your-server.com/webhooks/task",
"stepWebhookUrl": "https://your-server.com/webhooks/step",
"crewWebhookUrl": "https://your-server.com/webhooks/crew"
}'
```
<Warning>
**Feedback Impact on Task Execution**:
It's crucial to exercise care when providing feedback, as the entire feedback content will be incorporated as additional context for further task executions.
@@ -76,4 +98,4 @@ HITL workflows are particularly valuable for:
- Complex decision-making scenarios
- Sensitive or high-stakes operations
- Creative tasks requiring human judgment
- Compliance and regulatory reviews
- Compliance and regulatory reviews

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