CLI ↗

crewai concept intermediate agents
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Summary: Learn how to use the CrewAI CLI to interact with CrewAI.

Original Documentation

Documentation Index#

Fetch the complete documentation index at: https://docs.crewai.com/llms.txt Use this file to discover all available pages before exploring further.

Learn how to use the CrewAI CLI to interact with CrewAI.

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.

Overview#

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

Installation#

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

pip install crewai

Basic Usage#

The basic structure of a CrewAI CLI command is:

crewai [COMMAND] [OPTIONS] [ARGUMENTS]

Available Commands#

1. Create#

Create a new crew or flow.

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

Example:

crewai create crew my_new_crew
crewai create flow my_new_flow

2. Version#

Show the installed version of CrewAI.

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

Example:

crewai version
crewai version --tools

3. Train#

Train the crew for a specified number of iterations.

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:

crewai train -n 10 -f my_training_data.pkl

4. Replay#

Replay the crew execution from a specific task.

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

Example:

crewai replay -t task_123456

5. Log-tasks-outputs#

Retrieve your latest crew.kickoff() task outputs.

crewai log-tasks-outputs

6. Reset-memories#

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

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:

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

7. Test#

Test the crew and evaluate the results.

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:

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

8. Run#

Run the crew or flow.

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.

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.

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
    )

10. Deploy#

Deploy the crew or flow to CrewAI AMP.

  • Authentication: You need to be authenticated to deploy to CrewAI AMP. You can login or create an account with:

    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.

    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.

11. Organization Management#

Manage your CrewAI AMP organizations.

crewai org [COMMAND] [OPTIONS]

Commands:#

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

You must be authenticated to CrewAI AMP 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 AMP.

    crewai deploy push
    • 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:

    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:

    crewai deploy logs

    This streams the deployment logs to your terminal.

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

    crewai deploy list

    This lists all your deployments.

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

    crewai deploy remove

    This deletes the deployment from the CrewAI AMP platform.

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

    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 AMP using the CLI.