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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
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‎docs/docs.json

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}
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]
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},
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{
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"tab": "Enterprise",
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"groups": [
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{
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"group": "Getting Started",
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"pages": [
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"enterprise/introduction"
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]
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},
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{
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"group": "How-To Guides",
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"pages": [
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"enterprise/guides/build-crew",
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"enterprise/guides/deploy-crew",
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"enterprise/guides/kickoff-crew",
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"enterprise/guides/update-crew",
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"enterprise/guides/use-crew-api",
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"enterprise/guides/enable-crew-studio"
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]
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},
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{
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"group": "Features",
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"pages": [
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"enterprise/features/tool-repository",
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"enterprise/features/webhook-streaming",
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"enterprise/features/traces"
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]
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},
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{
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"group": "Resources",
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"pages": [
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"enterprise/resources/frequently-asked-questions"
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]
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}
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]
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},
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{
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"tab": "Examples",
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"groups": [

‎docs/enterprise/features/tool-repository.mdx

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---
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title: Tool Repository
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description: "Using the Tool Repository to manage your tools"
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icon: "toolbox"
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---
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## Overview
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The Tool Repository is a package manager for CrewAI tools. It allows users to publish, install, and manage tools that integrate with CrewAI crews and flows.
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Tools can be:
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- **Private**: accessible only within your organization (default)
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- **Public**: accessible to all CrewAI users if published with the `--public` flag
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The repository is not a version control system. Use Git to track code changes and enable collaboration.
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## Prerequisites
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Before using the Tool Repository, ensure you have:
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- A [CrewAI Enterprise](https://app.crewai.com) account
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- [CrewAI CLI](https://docs.crewai.com/concepts/cli#cli) installed
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- [Git](https://git-scm.com) installed and configured
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- Access permissions to publish or install tools in your CrewAI Enterprise organization
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## Installing Tools
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To install a tool:
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```bash
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crewai tool install <tool-name>
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```
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This installs the tool and adds it to `pyproject.toml`.
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## Creating and Publishing Tools
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To create a new tool project:
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```bash
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crewai tool create <tool-name>
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```
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This generates a scaffolded tool project locally.
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After making changes, initialize a Git repository and commit the code:
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```bash
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git init
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git add .
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git commit -m "Initial version"
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```
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To publish the tool:
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```bash
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crewai tool publish
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```
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By default, tools are published as private. To make a tool public:
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```bash
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crewai tool publish --public
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```
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For more details on how to build tools, see [Creating your own tools](https://docs.crewai.com/concepts/tools#creating-your-own-tools).
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## Updating Tools
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To update a published tool:
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1. Modify the tool locally
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2. Update the version in `pyproject.toml` (e.g., from `0.1.0` to `0.1.1`)
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3. Commit the changes and publish
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```bash
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git commit -m "Update version to 0.1.1"
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crewai tool publish
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```
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## Deleting Tools
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To delete a tool:
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1. Go to [CrewAI Enterprise](https://app.crewai.com)
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2. Navigate to **Tools**
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3. Select the tool
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4. Click **Delete**
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<Warning>
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Deletion is permanent. Deleted tools cannot be restored or re-installed.
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</Warning>
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## Security Checks
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Every published version undergoes automated security checks, and are only available to install after they pass.
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You can check the security check status of a tool at:
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`CrewAI Enterprise > Tools > Your Tool > Versions`
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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 API integration or troubleshooting.
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</Card>

‎docs/enterprise/features/traces.mdx

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---
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title: Traces
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description: "Using Traces to monitor your Crews"
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icon: "timeline"
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---
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## Overview
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Traces provide comprehensive visibility into your crew executions, helping you monitor performance, debug issues, and optimize your AI agent workflows.
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## What are Traces?
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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:
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- Agent thoughts and reasoning
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- Task execution details
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- Tool usage and outputs
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- Token consumption metrics
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- Execution times
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- Cost estimates
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<Frame>
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![Traces Overview](/images/enterprise/traces-overview.png)
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</Frame>
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## Accessing Traces
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<Steps>
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<Step title="Navigate to the Traces Tab">
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Once in your CrewAI Enterprise dashboard, click on the **Traces** to view all execution records.
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</Step>
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<Step title="Select an Execution">
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You'll see a list of all crew executions, sorted by date. Click on any execution to view its detailed trace.
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</Step>
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</Steps>
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## Understanding the Trace Interface
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The trace interface is divided into several sections, each providing different insights into your crew's execution:
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### 1. Execution Summary
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The top section displays high-level metrics about the execution:
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- **Total Tokens**: Number of tokens consumed across all tasks
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- **Prompt Tokens**: Tokens used in prompts to the LLM
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- **Completion Tokens**: Tokens generated in LLM responses
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- **Requests**: Number of API calls made
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- **Execution Time**: Total duration of the crew run
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- **Estimated Cost**: Approximate cost based on token usage
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<Frame>
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![Execution Summary](/images/enterprise/trace-summary.png)
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</Frame>
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### 2. Tasks & Agents
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This section shows all tasks and agents that were part of the crew execution:
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- Task name and agent assignment
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- Agents and LLMs used for each task
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- Status (completed/failed)
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- Individual execution time of the task
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<Frame>
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![Task List](/images/enterprise/trace-tasks.png)
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</Frame>
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### 3. Final Output
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Displays the final result produced by the crew after all tasks are completed.
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<Frame>
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![Final Output](/images/enterprise/final-output.png)
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</Frame>
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### 4. Execution Timeline
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A visual representation of when each task started and ended, helping you identify bottlenecks or parallel execution patterns.
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<Frame>
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![Execution Timeline](/images/enterprise/trace-timeline.png)
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</Frame>
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### 5. Detailed Task View
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When you click on a specific task in the timeline or task list, you'll see:
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<Frame>
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![Detailed Task View](/images/enterprise/trace-detailed-task.png)
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</Frame>
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- **Task Key**: Unique identifier for the task
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- **Task ID**: Technical identifier in the system
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- **Status**: Current state (completed/running/failed)
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- **Agent**: Which agent performed the task
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- **LLM**: Language model used for this task
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- **Start/End Time**: When the task began and completed
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- **Execution Time**: Duration of this specific task
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- **Task Description**: What the agent was instructed to do
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- **Expected Output**: What output format was requested
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- **Input**: Any input provided to this task from previous tasks
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- **Output**: The actual result produced by the agent
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## Using Traces for Debugging
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Traces are invaluable for troubleshooting issues with your crews:
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<Steps>
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<Step title="Identify Failure Points">
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When a crew execution doesn't produce the expected results, examine the trace to find where things went wrong. Look for:
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- Failed tasks
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- Unexpected agent decisions
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- Tool usage errors
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- Misinterpreted instructions
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<Frame>
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![Failure Points](/images/enterprise/failure.png)
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</Frame>
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</Step>
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<Step title="Optimize Performance">
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Use execution metrics to identify performance bottlenecks:
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- Tasks that took longer than expected
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- Excessive token usage
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- Redundant tool operations
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- Unnecessary API calls
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</Step>
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<Step title="Improve Cost Efficiency">
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Analyze token usage and cost estimates to optimize your crew's efficiency:
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- Consider using smaller models for simpler tasks
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- Refine prompts to be more concise
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- Cache frequently accessed information
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- Structure tasks to minimize redundant operations
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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">
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Contact our support team for assistance with trace analysis or any other CrewAI Enterprise features.
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</Card>

‎docs/enterprise/features/webhook-streaming.mdx

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---
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title: Webhook Streaming
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description: "Using Webhook Streaming to stream events to your webhook"
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icon: "webhook"
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---
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## Overview
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Enterprise Event Streaming lets you receive real-time webhook updates about your crews and flows deployed to
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CrewAI Enterprise, such as model calls, tool usage, and flow steps.
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## Usage
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When using the Kickoff API, include a `webhooks` object to your request, for example:
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```json
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{
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"inputs": {"foo": "bar"},
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"webhooks": {
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"events": ["crew_kickoff_started", "llm_call_started"],
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"url": "https://your.endpoint/webhook",
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"realtime": false,
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"authentication": {
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"strategy": "bearer",
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"token": "my-secret-token"
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}
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}
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}
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```
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If `realtime` is set to `true`, each event is delivered individually and immediately, at the cost of crew/flow performance.
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## Webhook Format
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Each webhook sends a list of events:
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```json
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{
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"events": [
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{
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"id": "event-id",
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"execution_id": "crew-run-id",
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"timestamp": "2025-02-16T10:58:44.965Z",
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"type": "llm_call_started",
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"data": {
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"model": "gpt-4",
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"messages": [
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{"role": "system", "content": "You are an assistant."},
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{"role": "user", "content": "Summarize this article."}
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]
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}
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}
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]
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}
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```
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The `data` object structure varies by event type. Refer to the [event list](https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events) on GitHub.
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As requests are sent over HTTP, the order of events can't be guaranteed. If you need ordering, use the `timestamp` field.
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## Supported Events
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CrewAI supports both system events and custom events in Enterprise Event Streaming. These events are sent to your configured webhook endpoint during crew and flow execution.
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- `crew_kickoff_started`
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- `crew_step_started`
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- `crew_step_completed`
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- `crew_execution_completed`
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- `llm_call_started`
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- `llm_call_completed`
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- `tool_usage_started`
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- `tool_usage_completed`
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- `crew_test_failed`
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- *...and others*
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Event names match the internal event bus. See [GitHub source](https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events) for the full list.
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You can emit your own custom events, and they will be delivered through the webhook stream alongside system events.
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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 webhook integration or troubleshooting.
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</Card>

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