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Overview

The CrewAI CLI provides a set of commands to interact with CrewAI, allowing you to create, train, run, and manage crews & flows.

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Installation

To use the CrewAI CLI, make sure you have CrewAI installed:

Terminal
pip install crewai

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Basic Usage

The basic structure of a CrewAI CLI command is:

Terminal
crewai [COMMAND] [OPTIONS] [ARGUMENTS]

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Available Commands

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1. Create

Create a new crew or flow.

Terminal
crewai create [OPTIONS] TYPE NAME
  • TYPE: Choose between “crew” or “flow”
  • NAME: Name of the crew or flow

Example:

Terminal
crewai create crew my_new_crew
crewai create flow my_new_flow

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2. Version

Show the installed version of CrewAI.

Terminal
crewai version [OPTIONS]
  • --tools: (Optional) Show the installed version of CrewAI tools

Example:

Terminal
crewai version
crewai version --tools

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3. Train

Train the crew for a specified number of iterations.

Terminal
crewai train [OPTIONS]
  • -n, --n_iterations INTEGER: Number of iterations to train the crew (default: 5)
  • -f, --filename TEXT: Path to a custom file for training (default: “trained_agents_data.pkl”)

Example:

Terminal
crewai train -n 10 -f my_training_data.pkl

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4. Replay

Replay the crew execution from a specific task.

Terminal
crewai replay [OPTIONS]
  • -t, --task_id TEXT: Replay the crew from this task ID, including all subsequent tasks

Example:

Terminal
crewai replay -t task_123456

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5. Log-tasks-outputs

Retrieve your latest crew.kickoff() task outputs.

Terminal
crewai log-tasks-outputs

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6. Reset-memories

Reset the crew memories (long, short, entity, latest_crew_kickoff_outputs).

Terminal
crewai reset-memories [OPTIONS]
  • -l, --long: Reset LONG TERM memory
  • -s, --short: Reset SHORT TERM memory
  • -e, --entities: Reset ENTITIES memory
  • -k, --kickoff-outputs: Reset LATEST KICKOFF TASK OUTPUTS
  • -kn, --knowledge: Reset KNOWLEDGE storage
  • -akn, --agent-knowledge: Reset AGENT KNOWLEDGE storage
  • -a, --all: Reset ALL memories

Example:

Terminal
crewai reset-memories --long --short
crewai reset-memories --all

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7. Test

Test the crew and evaluate the results.

Terminal
crewai test [OPTIONS]
  • -n, --n_iterations INTEGER: Number of iterations to test the crew (default: 3)
  • -m, --model TEXT: LLM Model to run the tests on the Crew (default: “gpt-4o-mini”)

Example:

Terminal
crewai test -n 5 -m gpt-3.5-turbo

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8. Run

Run the crew or flow.

Terminal
crewai run

Starting from version 0.103.0, the crewai run command can be used to run both standard crews and flows. For flows, it automatically detects the type from pyproject.toml and runs the appropriate command. This is now the recommended way to run both crews and flows.

Make sure to run these commands from the directory where your CrewAI project is set up. Some commands may require additional configuration or setup within your project structure.

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9. Chat

Starting in version 0.98.0, when you run the crewai chat command, you start an interactive session with your crew. The AI assistant will guide you by asking for necessary inputs to execute the crew. Once all inputs are provided, the crew will execute its tasks.

After receiving the results, you can continue interacting with the assistant for further instructions or questions.

Terminal
crewai chat

Ensure you execute these commands from your CrewAI project’s root directory.

IMPORTANT: Set the chat_llm property in your crew.py file to enable this command.

@crew
def crew(self) -> Crew:
    return Crew(
        agents=self.agents,
        tasks=self.tasks,
        process=Process.sequential,
        verbose=True,
        chat_llm="gpt-4o",  # LLM for chat orchestration
    )

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10. Deploy

Deploy the crew or flow to CrewAI Enterprise.

  • Authentication: You need to be authenticated to deploy to CrewAI Enterprise.

    Terminal
    crewai signup

    If you already have an account, you can login with:

    Terminal
    crewai login

  • Create a deployment: Once you are authenticated, you can create a deployment for your crew or flow from the root of your localproject.

    Terminal
    crewai deploy create
    • Reads your local project configuration.
    • Prompts you to confirm the environment variables (like OPENAI_API_KEY, SERPER_API_KEY) found locally. These will be securely stored with the deployment on the Enterprise platform. Ensure your sensitive keys are correctly configured locally (e.g., in a .env file) before running this.

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11. Organization Management

Manage your CrewAI Enterprise organizations.

Terminal
crewai org [COMMAND] [OPTIONS]

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Commands:

  • list: List all organizations you belong to
Terminal
crewai org list
  • current: Display your currently active organization
Terminal
crewai org current
  • switch: Switch to a specific organization
Terminal
crewai org switch <organization_id>

You must be authenticated to CrewAI Enterprise to use these organization management commands.

  • 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.

    Terminal
    crewai deploy push
    • Initiates the deployment process on the CrewAI Enterprise platform.
    • Upon successful initiation, it will output the Deployment created successfully! message along with the Deployment Name and a unique Deployment ID (UUID).

  • Deployment Status: You can check the status of your deployment with:

    Terminal
    crewai deploy status

    This fetches the latest deployment status of your most recent deployment attempt (e.g., Building Images for Crew, Deploy Enqueued, Online).

  • Deployment Logs: You can check the logs of your deployment with:

    Terminal
    crewai deploy logs

    This streams the deployment logs to your terminal.

  • List deployments: You can list all your deployments with:

    Terminal
    crewai deploy list

    This lists all your deployments.

  • Delete a deployment: You can delete a deployment with:

    Terminal
    crewai deploy remove

    This deletes the deployment from the CrewAI Enterprise platform.

  • Help Command: You can get help with the CLI with:

    Terminal
    crewai deploy --help

    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 using the CLI.

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11. API Keys

When running crewai create crew command, the CLI will first show you the top 5 most common LLM providers and ask you to select one.

Once you’ve selected an LLM provider, you will be prompted for API keys.

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Initial API key providers

The CLI will initially prompt for API keys for the following services:

  • OpenAI
  • Groq
  • Anthropic
  • Google Gemini
  • SambaNova

When you select a provider, the CLI will prompt you to enter your API key.

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Other Options

If you select option 6, you will be able to select from a list of LiteLLM supported providers.

When you select a provider, the CLI will prompt you to enter the Key name and the API key.

See the following link for each provider’s key name: