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CrewAI CLI Documentation

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
  • -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.

Terminal
crewai run

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. 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:

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