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docs: add CrewAI Enterprise docs (#2691)
* Add enterprise deployment documentation to CLI docs * Update CrewAI Enterprise documentation with comprehensive guides for Traces, Tool Repository, Webhook Streaming, and FAQ structure * Add Enterprise documentation images * Update Enterprise introduction with visual CardGroups and Steps components
This commit is contained in:
Tony Kipkemboi
43
docs/enterprise/guides/build-crew.mdx
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43
docs/enterprise/guides/build-crew.mdx
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@@ -0,0 +1,43 @@
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---
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title: "Build Crew"
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description: "A Crew is a group of agents that work together to complete a task."
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icon: "people-arrows"
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---
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<Tip>
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[CrewAI Enterprise](https://app.crewai.com) streamlines the process of **creating**, **deploying**, and **managing** your AI agents in production environments.
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</Tip>
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## Getting Started
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<iframe
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width="100%"
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height="400"
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src="https://www.youtube.com/embed/d1Yp8eeknDk?si=tIxnTRI5UlyCp3z_"
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title="Building Crews with CrewAI CLI"
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frameborder="0"
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style={{ borderRadius: '10px' }}
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
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allowfullscreen
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></iframe>
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### Installation and Setup
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<Card title="Follow Standard Installation" icon="wrench" href="/installation">
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Follow our standard installation guide to set up CrewAI CLI and create your first project.
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</Card>
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### Building Your Crew
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<Card title="Quickstart Tutorial" icon="rocket" href="/quickstart">
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Follow our quickstart guide to create your first agent crew using YAML configuration.
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</Card>
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## Support and Resources
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For Enterprise-specific support or questions, contact our dedicated support team at [support@crewai.com](mailto:support@crewai.com).
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<Card title="Schedule a Demo" icon="calendar" href="mailto:support@crewai.com">
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Book time with our team to learn more about Enterprise features and how they can benefit your organization.
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</Card>
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216
docs/enterprise/guides/deploy-crew.mdx
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216
docs/enterprise/guides/deploy-crew.mdx
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---
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title: "Deploy Crew"
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description: "Deploy your local CrewAI project to the Enterprise platform"
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icon: "cloud-arrow-up"
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---
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## Option 1: CLI Deployment
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<Tip>
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This video tutorial walks you through the process of deploying your locally developed CrewAI project to the CrewAI Enterprise platform,
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transforming it into a production-ready API endpoint.
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</Tip>
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<iframe
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width="100%"
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height="400"
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src="https://www.youtube.com/embed/3EqSV-CYDZA"
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title="Deploying a Crew to CrewAI Enterprise"
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frameborder="0"
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style={{ borderRadius: '10px' }}
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
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allowfullscreen
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></iframe>
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## Prerequisites
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Before starting the deployment process, make sure you have:
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- A CrewAI project built locally ([follow our quickstart guide](/quickstart) if you haven't created one yet)
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- Your code pushed to a GitHub repository
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- The latest version of the CrewAI CLI installed (`uv tool install crewai`)
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<Note>
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For a quick reference project, you can clone our example repository at [github.com/tonykipkemboi/crewai-latest-ai-development](https://github.com/tonykipkemboi/crewai-latest-ai-development).
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</Note>
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### Step 1: Authenticate with the Enterprise Platform
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First, you need to authenticate your CLI with the CrewAI Enterprise platform:
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```bash
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# If you already have a CrewAI Enterprise account
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crewai login
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# If you're creating a new account
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crewai signup
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```
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When you run either command, the CLI will:
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1. Display a URL and a unique device code
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2. Open your browser to the authentication page
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3. Prompt you to confirm the device
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4. Complete the authentication process
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Upon successful authentication, you'll see a confirmation message in your terminal!
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### Step 2: Create a Deployment
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From your project directory, run:
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```bash
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crewai deploy create
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```
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This command will:
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1. Detect your GitHub repository information
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2. Identify environment variables in your local `.env` file
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3. Securely transfer these variables to the Enterprise platform
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4. Create a new deployment with a unique identifier
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On successful creation, you'll see a message like:
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```shell
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Deployment created successfully!
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Name: your_project_name
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Deployment ID: 01234567-89ab-cdef-0123-456789abcdef
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Current Status: Deploy Enqueued
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```
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### Step 3: Monitor Deployment Progress
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Track the deployment status with:
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```bash
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crewai deploy status
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```
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For detailed logs of the build process:
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```bash
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crewai deploy logs
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```
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<Tip>
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The first deployment typically takes 10-15 minutes as it builds the container images. Subsequent deployments are much faster.
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</Tip>
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### Additional CLI Commands
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The CrewAI CLI offers several commands to manage your deployments:
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```bash
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# List all your deployments
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crewai deploy list
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# Get the status of your deployment
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crewai deploy status
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# View the logs of your deployment
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crewai deploy logs
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# Push updates after code changes
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crewai deploy push
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# Remove a deployment
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crewai deploy remove <deployment_id>
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```
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## Option 2: Deploy Directly via Web Interface
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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.
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### Step 1: Pushing to GitHub
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First, you need to push your crew to a GitHub repository. If you haven't created a crew yet, you can [follow this tutorial](/quickstart).
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### Step 2: Connecting GitHub to CrewAI Enterprise
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1. Log in to [CrewAI Enterprise](https://app.crewai.com)
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2. Click on the button "Connect GitHub"
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<Frame>
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</Frame>
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### Step 3: Select the Repository
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After connecting your GitHub account, you'll be able to select which repository to deploy:
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<Frame>
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</Frame>
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### Step 4: Set Environment Variables
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Before deploying, you'll need to set up your environment variables to connect to your LLM provider or other services:
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1. You can add variables individually or in bulk
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2. Enter your environment variables in `KEY=VALUE` format (one per line)
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<Frame>
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</Frame>
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### Step 5: Deploy Your Crew
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1. Click the "Deploy" button to start the deployment process
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2. You can monitor the progress through the progress bar
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3. The first deployment typically takes around 10-15 minutes; subsequent deployments will be faster
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<Frame>
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</Frame>
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Once deployment is complete, you'll see:
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- Your crew's unique URL
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- A Bearer token to protect your crew API
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- A "Delete" button if you need to remove the deployment
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### Interact with Your Deployed Crew
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Once deployment is complete, you can access your crew through:
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1. **REST API**: The platform generates a unique HTTPS endpoint with these key routes:
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- `/inputs`: Lists the required input parameters
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- `/kickoff`: Initiates an execution with provided inputs
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- `/status/{kickoff_id}`: Checks the execution status
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2. **Web Interface**: Visit [app.crewai.com](https://app.crewai.com) to access:
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- **Status tab**: View deployment information, API endpoint details, and authentication token
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- **Run tab**: Visual representation of your crew's structure
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- **Executions tab**: History of all executions
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- **Metrics tab**: Performance analytics
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- **Traces tab**: Detailed execution insights
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### Trigger an Execution
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From the Enterprise dashboard, you can:
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1. Click on your crew's name to open its details
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2. Select "Trigger Crew" from the management interface
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3. Enter the required inputs in the modal that appears
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4. Monitor progress as the execution moves through the pipeline
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## Monitoring and Analytics
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The Enterprise platform provides comprehensive observability features:
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- **Execution Management**: Track active and completed runs
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- **Traces**: Detailed breakdowns of each execution
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- **Metrics**: Token usage, execution times, and costs
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- **Timeline View**: Visual representation of task sequences
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## Advanced Features
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The Enterprise platform also offers:
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- **Environment Variables Management**: Securely store and manage API keys
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- **LLM Connections**: Configure integrations with various LLM providers
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- **Custom Tools Repository**: Create, share, and install tools
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- **Crew Studio**: Build crews through a chat interface without writing code
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<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
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Contact our support team for assistance with deployment issues or questions about the Enterprise platform.
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</Card>
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166
docs/enterprise/guides/enable-crew-studio.mdx
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166
docs/enterprise/guides/enable-crew-studio.mdx
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---
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title: "Enable Crew Studio"
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description: "Enabling Crew Studio on CrewAI Enterprise"
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icon: "comments"
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---
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<Tip>
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Crew Studio is a powerful **no-code/low-code** tool that allows you to quickly scaffold or build Crews through a conversational interface.
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</Tip>
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## What is Crew Studio?
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Crew Studio is an innovative way to create AI agent crews without writing code.
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<Frame>
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</Frame>
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With Crew Studio, you can:
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- Chat with the Crew Assistant to describe your problem
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- Automatically generate agents and tasks
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- Select appropriate tools
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- Configure necessary inputs
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- Generate downloadable code for customization
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- Deploy directly to the CrewAI Enterprise platform
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## Configuration Steps
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Before you can start using Crew Studio, you need to configure your LLM connections:
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<Steps>
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<Step title="Set Up LLM Connection">
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Go to the **LLM Connections** tab in your CrewAI Enterprise dashboard and create a new LLM connection.
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<Note>
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Feel free to use any LLM provider you want that is supported by CrewAI.
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</Note>
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Configure your LLM connection:
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- Enter a `Connection Name` (e.g., `OpenAI`)
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- Select your model provider: `openai` or `azure`
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- Select models you'd like to use in your Studio-generated Crews
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- We recommend at least `gpt-4o`, `o1-mini`, and `gpt-4o-mini`
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- Add your API key as an environment variable:
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- For OpenAI: Add `OPENAI_API_KEY` with your API key
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- For Azure OpenAI: Refer to [this article](https://blog.crewai.com/configuring-azure-openai-with-crewai-a-comprehensive-guide/) for configuration details
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- Click `Add Connection` to save your configuration
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<Frame>
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</Frame>
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</Step>
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<Step title="Verify Connection Added">
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Once you complete the setup, you'll see your new connection added to the list of available connections.
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<Frame>
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</Frame>
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</Step>
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<Step title="Configure LLM Defaults">
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In the main menu, go to **Settings → Defaults** and configure the LLM Defaults settings:
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- Select default models for agents and other components
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- Set default configurations for Crew Studio
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Click `Save Settings` to apply your changes.
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<Frame>
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</Frame>
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</Step>
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</Steps>
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## Using Crew Studio
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Now that you've configured your LLM connection and default settings, you're ready to start using Crew Studio!
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<Steps>
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<Step title="Access Studio">
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Navigate to the **Studio** section in your CrewAI Enterprise dashboard.
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</Step>
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<Step title="Start a Conversation">
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Start a conversation with the Crew Assistant by describing the problem you want to solve:
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```md
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I need a crew that can research the latest AI developments and create a summary report.
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```
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The Crew Assistant will ask clarifying questions to better understand your requirements.
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</Step>
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<Step title="Review Generated Crew">
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Review the generated crew configuration, including:
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- Agents and their roles
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- Tasks to be performed
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- Required inputs
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- Tools to be used
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This is your opportunity to refine the configuration before proceeding.
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</Step>
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<Step title="Deploy or Download">
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Once you're satisfied with the configuration, you can:
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- Download the generated code for local customization
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- Deploy the crew directly to the CrewAI Enterprise platform
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- Modify the configuration and regenerate the crew
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</Step>
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<Step title="Test Your Crew">
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After deployment, test your crew with sample inputs to ensure it performs as expected.
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</Step>
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</Steps>
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<Tip>
|
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For best results, provide clear, detailed descriptions of what you want your crew to accomplish. Include specific inputs and expected outputs in your description.
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</Tip>
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## Example Workflow
|
||||
|
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Here's a typical workflow for creating a crew with Crew Studio:
|
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<Steps>
|
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<Step title="Describe Your Problem">
|
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Start by describing your problem:
|
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|
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```md
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I need a crew that can analyze financial news and provide investment recommendations
|
||||
```
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</Step>
|
||||
|
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<Step title="Answer Questions">
|
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Respond to clarifying questions from the Crew Assistant to refine your requirements.
|
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</Step>
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<Step title="Review the Plan">
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Review the generated crew plan, which might include:
|
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|
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- A Research Agent to gather financial news
|
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- An Analysis Agent to interpret the data
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- A Recommendations Agent to provide investment advice
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</Step>
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|
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<Step title="Approve or Modify">
|
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Approve the plan or request changes if necessary.
|
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</Step>
|
||||
|
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<Step title="Download or Deploy">
|
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Download the code for customization or deploy directly to the platform.
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</Step>
|
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|
||||
<Step title="Test and Refine">
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Test your crew with sample inputs and refine as needed.
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</Step>
|
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</Steps>
|
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|
||||
<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.
|
||||
</Card>
|
||||
|
||||
186
docs/enterprise/guides/kickoff-crew.mdx
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186
docs/enterprise/guides/kickoff-crew.mdx
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|
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---
|
||||
title: "Kickoff Crew"
|
||||
description: "Kickoff a Crew on CrewAI Enterprise"
|
||||
icon: "flag-checkered"
|
||||
---
|
||||
|
||||
# Kickoff a Crew on CrewAI Enterprise
|
||||
|
||||
Once you've deployed your crew to the CrewAI Enterprise platform, you can kickoff executions through the web interface or the API. This guide covers both approaches.
|
||||
|
||||
## Method 1: Using the Web Interface
|
||||
|
||||
### Step 1: Navigate to Your Deployed Crew
|
||||
|
||||
1. Log in to [CrewAI Enterprise](https://app.crewai.com)
|
||||
2. Click on the crew name from your projects list
|
||||
3. You'll be taken to the crew's detail page
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### Step 2: Initiate Execution
|
||||
|
||||
From your crew's detail page, you have two options to kickoff an execution:
|
||||
|
||||
#### Option A: Quick Kickoff
|
||||
|
||||
1. Click the `Kickoff` link in the Test Endpoints section
|
||||
2. Enter the required input parameters for your crew in the JSON editor
|
||||
3. Click the `Send Request` button
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
#### Option B: Using the Visual Interface
|
||||
|
||||
1. Click the `Run` tab in the crew detail page
|
||||
2. Enter the required inputs in the form fields
|
||||
3. Click the `Run Crew` button
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### Step 3: Monitor Execution Progress
|
||||
|
||||
After initiating the execution:
|
||||
|
||||
1. You'll receive a response containing a `kickoff_id` - **copy this ID**
|
||||
2. This ID is essential for tracking your execution
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### Step 4: Check Execution Status
|
||||
|
||||
To monitor the progress of your execution:
|
||||
|
||||
1. Click the "Status" endpoint in the Test Endpoints section
|
||||
2. Paste the `kickoff_id` into the designated field
|
||||
3. Click the "Get Status" button
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
The status response will show:
|
||||
- Current execution state (`running`, `completed`, etc.)
|
||||
- Details about which tasks are in progress
|
||||
- Any outputs produced so far
|
||||
|
||||
### Step 5: View Final Results
|
||||
|
||||
Once execution is complete:
|
||||
|
||||
1. The status will change to `completed`
|
||||
2. You can view the full execution results and outputs
|
||||
3. For a more detailed view, check the `Executions` tab in the crew detail page
|
||||
|
||||
## Method 2: Using the API
|
||||
|
||||
You can also kickoff crews programmatically using the CrewAI Enterprise REST API.
|
||||
|
||||
### Authentication
|
||||
|
||||
All API requests require a bearer token for authentication:
|
||||
|
||||
```bash
|
||||
curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
|
||||
```
|
||||
|
||||
Your bearer token is available on the Status tab of your crew's detail page.
|
||||
|
||||
### Checking Crew Health
|
||||
|
||||
Before executing operations, you can verify that your crew is running properly:
|
||||
|
||||
```bash
|
||||
curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
|
||||
```
|
||||
|
||||
A successful response will return a message indicating the crew is operational:
|
||||
|
||||
```
|
||||
Healthy%
|
||||
```
|
||||
|
||||
### Step 1: Retrieve Required Inputs
|
||||
|
||||
First, determine what inputs your crew requires:
|
||||
|
||||
```bash
|
||||
curl -X GET \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
https://your-crew-url.crewai.com/inputs
|
||||
```
|
||||
|
||||
The response will be a JSON object containing an array of required input parameters, for example:
|
||||
|
||||
```json
|
||||
{"inputs":["topic","current_year"]}
|
||||
```
|
||||
|
||||
This example shows that this particular crew requires two inputs: `topic` and `current_year`.
|
||||
|
||||
### Step 2: Kickoff Execution
|
||||
|
||||
Initiate execution by providing the required inputs:
|
||||
|
||||
```bash
|
||||
curl -X POST \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
-d '{"inputs": {"topic": "AI Agent Frameworks", "current_year": "2025"}}' \
|
||||
https://your-crew-url.crewai.com/kickoff
|
||||
```
|
||||
|
||||
The response will include a `kickoff_id` that you'll need for tracking:
|
||||
|
||||
```json
|
||||
{"kickoff_id":"abcd1234-5678-90ef-ghij-klmnopqrstuv"}
|
||||
```
|
||||
|
||||
### Step 3: Check Execution Status
|
||||
|
||||
Monitor the execution progress using the kickoff_id:
|
||||
|
||||
```bash
|
||||
curl -X GET \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
https://your-crew-url.crewai.com/status/abcd1234-5678-90ef-ghij-klmnopqrstuv
|
||||
```
|
||||
|
||||
## Handling Executions
|
||||
|
||||
### Long-Running Executions
|
||||
|
||||
For executions that may take a long time:
|
||||
|
||||
1. Consider implementing a polling mechanism to check status periodically
|
||||
2. Use webhooks (if available) for notification when execution completes
|
||||
3. Implement error handling for potential timeouts
|
||||
|
||||
### Execution Context
|
||||
|
||||
The execution context includes:
|
||||
|
||||
- Inputs provided at kickoff
|
||||
- Environment variables configured during deployment
|
||||
- Any state maintained between tasks
|
||||
|
||||
### Debugging Failed Executions
|
||||
|
||||
If an execution fails:
|
||||
|
||||
1. Check the "Executions" tab for detailed logs
|
||||
2. Review the "Traces" tab for step-by-step execution details
|
||||
3. Look for LLM responses and tool usage in the trace details
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with execution issues or questions about the Enterprise platform.
|
||||
</Card>
|
||||
|
||||
89
docs/enterprise/guides/update-crew.mdx
Normal file
89
docs/enterprise/guides/update-crew.mdx
Normal file
@@ -0,0 +1,89 @@
|
||||
---
|
||||
title: "Update Crew"
|
||||
description: "Updating a Crew on CrewAI Enterprise"
|
||||
icon: "pencil"
|
||||
---
|
||||
|
||||
<Note>
|
||||
After deploying your crew to CrewAI Enterprise, you may need to make updates to the code, security settings, or configuration.
|
||||
This guide explains how to perform these common update operations.
|
||||
</Note>
|
||||
|
||||
## Why Update Your Crew?
|
||||
|
||||
CrewAI won't automatically pick up GitHub updates by default, so you'll need to manually trigger updates, unless you checked the `Auto-update` option when deploying your crew.
|
||||
|
||||
There are several reasons you might want to update your crew deployment:
|
||||
- You want to update the code with a latest commit you pushed to GitHub
|
||||
- You want to reset the bearer token for security reasons
|
||||
- You want to update environment variables
|
||||
|
||||
## 1. Updating Your Crew Code for a Latest Commit
|
||||
|
||||
When you've pushed new commits to your GitHub repository and want to update your deployment:
|
||||
|
||||
1. Navigate to your crew in the CrewAI Enterprise platform
|
||||
2. Click on the `Re-deploy` button on your crew details page
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
This will trigger an update that you can track using the progress bar. The system will pull the latest code from your repository and rebuild your deployment.
|
||||
|
||||
## 2. Resetting Bearer Token
|
||||
|
||||
If you need to generate a new bearer token (for example, if you suspect the current token might have been compromised):
|
||||
|
||||
1. Navigate to your crew in the CrewAI Enterprise platform
|
||||
2. Find the `Bearer Token` section
|
||||
3. Click the `Reset` button next to your current token
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
<Warning>
|
||||
Resetting your bearer token will invalidate the previous token immediately. Make sure to update any applications or scripts that are using the old token.
|
||||
</Warning>
|
||||
|
||||
## 3. Updating Environment Variables
|
||||
|
||||
To update the environment variables for your crew:
|
||||
|
||||
1. First access the deployment page by clicking on your crew's name
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
2. Locate the `Environment Variables` section (you will need to click the `Settings` icon to access it)
|
||||
3. Edit the existing variables or add new ones in the fields provided
|
||||
4. Click the `Update` button next to each variable you modify
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
5. Finally, click the `Update Deployment` button at the bottom of the page to apply the changes
|
||||
|
||||
<Note>
|
||||
Updating environment variables will trigger a new deployment, but this will only update the environment configuration and not the code itself.
|
||||
</Note>
|
||||
|
||||
## After Updating
|
||||
|
||||
After performing any update:
|
||||
|
||||
1. The system will rebuild and redeploy your crew
|
||||
2. You can monitor the deployment progress in real-time
|
||||
3. Once complete, test your crew to ensure the changes are working as expected
|
||||
|
||||
<Tip>
|
||||
If you encounter any issues after updating, you can view deployment logs in the platform or contact support for assistance.
|
||||
</Tip>
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with updating your crew or troubleshooting deployment issues.
|
||||
</Card>
|
||||
|
||||
319
docs/enterprise/guides/use-crew-api.mdx
Normal file
319
docs/enterprise/guides/use-crew-api.mdx
Normal file
@@ -0,0 +1,319 @@
|
||||
---
|
||||
title: "Trigger Deployed Crew API"
|
||||
description: "Using your deployed crew's API on CrewAI Enterprise"
|
||||
icon: "arrow-up-right-from-square"
|
||||
---
|
||||
|
||||
Once you have deployed your crew to CrewAI Enterprise, it automatically becomes available as a REST API. This guide explains how to interact with your crew programmatically.
|
||||
|
||||
## API Basics
|
||||
|
||||
Your deployed crew exposes several endpoints that allow you to:
|
||||
1. Discover required inputs
|
||||
2. Start crew executions
|
||||
3. Monitor execution status
|
||||
4. Receive results
|
||||
|
||||
### Authentication
|
||||
|
||||
All API requests require a bearer token for authentication, which is generated when you deploy your crew:
|
||||
|
||||
```bash
|
||||
curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com/...
|
||||
```
|
||||
|
||||
<Tip>
|
||||
You can find your bearer token in the Status tab of your crew's detail page in the CrewAI Enterprise dashboard.
|
||||
</Tip>
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
## Available Endpoints
|
||||
|
||||
Your crew API provides three main endpoints:
|
||||
|
||||
| Endpoint | Method | Description |
|
||||
|----------|--------|-------------|
|
||||
| `/inputs` | GET | Lists all required inputs for crew execution |
|
||||
| `/kickoff` | POST | Starts a crew execution with provided inputs |
|
||||
| `/status/{kickoff_id}` | GET | Retrieves the status and results of an execution |
|
||||
|
||||
## GET /inputs
|
||||
|
||||
The inputs endpoint allows you to discover what parameters your crew requires:
|
||||
|
||||
```bash
|
||||
curl -X GET \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
https://your-crew-url.crewai.com/inputs
|
||||
```
|
||||
|
||||
### Response
|
||||
|
||||
```json
|
||||
{
|
||||
"inputs": ["budget", "interests", "duration", "age"]
|
||||
}
|
||||
```
|
||||
|
||||
This response indicates that your crew expects four input parameters: `budget`, `interests`, `duration`, and `age`.
|
||||
|
||||
## POST /kickoff
|
||||
|
||||
The kickoff endpoint starts a new crew execution:
|
||||
|
||||
```bash
|
||||
curl -X POST \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
-d '{
|
||||
"inputs": {
|
||||
"budget": "1000 USD",
|
||||
"interests": "games, tech, ai, relaxing hikes, amazing food",
|
||||
"duration": "7 days",
|
||||
"age": "35"
|
||||
}
|
||||
}' \
|
||||
https://your-crew-url.crewai.com/kickoff
|
||||
```
|
||||
|
||||
### Request Parameters
|
||||
|
||||
| Parameter | Type | Required | Description |
|
||||
|-----------|------|----------|-------------|
|
||||
| `inputs` | Object | Yes | Key-value pairs of all required inputs |
|
||||
| `meta` | Object | No | Additional metadata to pass to the crew |
|
||||
| `taskWebhookUrl` | String | No | Callback URL executed after each task |
|
||||
| `stepWebhookUrl` | String | No | Callback URL executed after each agent thought |
|
||||
| `crewWebhookUrl` | String | No | Callback URL executed when the crew finishes |
|
||||
|
||||
### Example with Webhooks
|
||||
|
||||
```json
|
||||
{
|
||||
"inputs": {
|
||||
"budget": "1000 USD",
|
||||
"interests": "games, tech, ai, relaxing hikes, amazing food",
|
||||
"duration": "7 days",
|
||||
"age": "35"
|
||||
},
|
||||
"meta": {
|
||||
"requestId": "user-request-12345",
|
||||
"source": "mobile-app"
|
||||
},
|
||||
"taskWebhookUrl": "https://your-server.com/webhooks/task",
|
||||
"stepWebhookUrl": "https://your-server.com/webhooks/step",
|
||||
"crewWebhookUrl": "https://your-server.com/webhooks/crew"
|
||||
}
|
||||
```
|
||||
|
||||
### Response
|
||||
|
||||
```json
|
||||
{
|
||||
"kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv"
|
||||
}
|
||||
```
|
||||
|
||||
The `kickoff_id` is used to track and retrieve the execution results.
|
||||
|
||||
## GET /status/{kickoff_id}
|
||||
|
||||
The status endpoint allows you to check the progress and results of a crew execution:
|
||||
|
||||
```bash
|
||||
curl -X GET \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
https://your-crew-url.crewai.com/status/abcd1234-5678-90ef-ghij-klmnopqrstuv
|
||||
```
|
||||
|
||||
### Response Structure
|
||||
|
||||
The response structure will vary depending on the execution state:
|
||||
|
||||
#### In Progress
|
||||
|
||||
```json
|
||||
{
|
||||
"status": "running",
|
||||
"current_task": "research_task",
|
||||
"progress": {
|
||||
"completed_tasks": 0,
|
||||
"total_tasks": 2
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### Completed
|
||||
|
||||
```json
|
||||
{
|
||||
"status": "completed",
|
||||
"result": {
|
||||
"output": "Comprehensive travel itinerary...",
|
||||
"tasks": [
|
||||
{
|
||||
"task_id": "research_task",
|
||||
"output": "Research findings...",
|
||||
"agent": "Researcher",
|
||||
"execution_time": 45.2
|
||||
},
|
||||
{
|
||||
"task_id": "planning_task",
|
||||
"output": "7-day itinerary plan...",
|
||||
"agent": "Trip Planner",
|
||||
"execution_time": 62.8
|
||||
}
|
||||
]
|
||||
},
|
||||
"execution_time": 108.5
|
||||
}
|
||||
```
|
||||
|
||||
## Webhook Integration
|
||||
|
||||
When you provide webhook URLs in your kickoff request, the system will make POST requests to those URLs at specific points in the execution:
|
||||
|
||||
### taskWebhookUrl
|
||||
|
||||
Called when each task completes:
|
||||
|
||||
```json
|
||||
{
|
||||
"kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv",
|
||||
"task_id": "research_task",
|
||||
"status": "completed",
|
||||
"output": "Research findings...",
|
||||
"agent": "Researcher",
|
||||
"execution_time": 45.2
|
||||
}
|
||||
```
|
||||
|
||||
### stepWebhookUrl
|
||||
|
||||
Called after each agent thought or action:
|
||||
|
||||
```json
|
||||
{
|
||||
"kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv",
|
||||
"task_id": "research_task",
|
||||
"agent": "Researcher",
|
||||
"step_type": "thought",
|
||||
"content": "I should first search for popular destinations that match these interests..."
|
||||
}
|
||||
```
|
||||
|
||||
### crewWebhookUrl
|
||||
|
||||
Called when the entire crew execution completes:
|
||||
|
||||
```json
|
||||
{
|
||||
"kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv",
|
||||
"status": "completed",
|
||||
"result": {
|
||||
"output": "Comprehensive travel itinerary...",
|
||||
"tasks": [
|
||||
{
|
||||
"task_id": "research_task",
|
||||
"output": "Research findings...",
|
||||
"agent": "Researcher",
|
||||
"execution_time": 45.2
|
||||
},
|
||||
{
|
||||
"task_id": "planning_task",
|
||||
"output": "7-day itinerary plan...",
|
||||
"agent": "Trip Planner",
|
||||
"execution_time": 62.8
|
||||
}
|
||||
]
|
||||
},
|
||||
"execution_time": 108.5,
|
||||
"meta": {
|
||||
"requestId": "user-request-12345",
|
||||
"source": "mobile-app"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Best Practices
|
||||
|
||||
### Handling Long-Running Executions
|
||||
|
||||
Crew executions can take anywhere from seconds to minutes depending on their complexity. Consider these approaches:
|
||||
|
||||
1. **Webhooks (Recommended)**: Set up webhook endpoints to receive notifications when the execution completes
|
||||
2. **Polling**: Implement a polling mechanism with exponential backoff
|
||||
3. **Client-Side Timeout**: Set appropriate timeouts for your API requests
|
||||
|
||||
### Error Handling
|
||||
|
||||
The API may return various error codes:
|
||||
|
||||
| Code | Description | Recommended Action |
|
||||
|------|-------------|-------------------|
|
||||
| 401 | Unauthorized | Check your bearer token |
|
||||
| 404 | Not Found | Verify your crew URL and kickoff_id |
|
||||
| 422 | Validation Error | Ensure all required inputs are provided |
|
||||
| 500 | Server Error | Contact support with the error details |
|
||||
|
||||
### Sample Code
|
||||
|
||||
Here's a complete Python example for interacting with your crew API:
|
||||
|
||||
```python
|
||||
import requests
|
||||
import time
|
||||
|
||||
# Configuration
|
||||
CREW_URL = "https://your-crew-url.crewai.com"
|
||||
BEARER_TOKEN = "your-crew-token"
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {BEARER_TOKEN}",
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
# 1. Get required inputs
|
||||
response = requests.get(f"{CREW_URL}/inputs", headers=HEADERS)
|
||||
required_inputs = response.json()["inputs"]
|
||||
print(f"Required inputs: {required_inputs}")
|
||||
|
||||
# 2. Start crew execution
|
||||
payload = {
|
||||
"inputs": {
|
||||
"budget": "1000 USD",
|
||||
"interests": "games, tech, ai, relaxing hikes, amazing food",
|
||||
"duration": "7 days",
|
||||
"age": "35"
|
||||
}
|
||||
}
|
||||
|
||||
response = requests.post(f"{CREW_URL}/kickoff", headers=HEADERS, json=payload)
|
||||
kickoff_id = response.json()["kickoff_id"]
|
||||
print(f"Execution started with ID: {kickoff_id}")
|
||||
|
||||
# 3. Poll for results
|
||||
MAX_RETRIES = 30
|
||||
POLL_INTERVAL = 10 # seconds
|
||||
for i in range(MAX_RETRIES):
|
||||
print(f"Checking status (attempt {i+1}/{MAX_RETRIES})...")
|
||||
response = requests.get(f"{CREW_URL}/status/{kickoff_id}", headers=HEADERS)
|
||||
data = response.json()
|
||||
|
||||
if data["status"] == "completed":
|
||||
print("Execution completed!")
|
||||
print(f"Result: {data['result']['output']}")
|
||||
break
|
||||
elif data["status"] == "error":
|
||||
print(f"Execution failed: {data.get('error', 'Unknown error')}")
|
||||
break
|
||||
else:
|
||||
print(f"Status: {data['status']}, waiting {POLL_INTERVAL} seconds...")
|
||||
time.sleep(POLL_INTERVAL)
|
||||
```
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with API integration or troubleshooting.
|
||||
</Card>
|
||||
Reference in New Issue
Block a user