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feat/cli-i
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.github/workflows/mkdocs.yml
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.github/workflows/mkdocs.yml
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name: Deploy MkDocs
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name: Deploy MkDocs
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on:
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on:
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release:
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types: [published]
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push:
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branches:
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- main
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permissions:
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permissions:
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contents: write
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contents: write
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1
.github/workflows/stale.yml
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.github/workflows/stale.yml
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stale-pr-message: 'This PR is stale because it has been open for 45 days with no activity.'
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stale-pr-message: 'This PR is stale because it has been open for 45 days with no activity.'
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days-before-pr-stale: 45
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days-before-pr-stale: 45
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days-before-pr-close: -1
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days-before-pr-close: -1
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operations-per-run: 500
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# CrewAI CLI Documentation
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The CrewAI CLI provides a set of commands to interact with CrewAI, allowing you to create, train, run, and manage crews and pipelines.
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## Installation
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To use the CrewAI CLI, make sure you have CrewAI & Poetry installed:
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```
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pip install crewai poetry
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```
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## Basic Usage
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The basic structure of a CrewAI CLI command is:
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```
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crewai [COMMAND] [OPTIONS] [ARGUMENTS]
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```
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## Available Commands
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### 1. create
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Create a new crew or pipeline.
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```
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crewai create [OPTIONS] TYPE NAME
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```
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- `TYPE`: Choose between "crew" or "pipeline"
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- `NAME`: Name of the crew or pipeline
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- `--router`: (Optional) Create a pipeline with router functionality
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Example:
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```
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crewai create crew my_new_crew
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crewai create pipeline my_new_pipeline --router
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```
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### 2. version
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Show the installed version of CrewAI.
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```
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crewai version [OPTIONS]
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```
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- `--tools`: (Optional) Show the installed version of CrewAI tools
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Example:
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```
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crewai version
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crewai version --tools
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```
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### 3. train
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Train the crew for a specified number of iterations.
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```
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crewai train [OPTIONS]
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```
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- `-n, --n_iterations INTEGER`: Number of iterations to train the crew (default: 5)
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- `-f, --filename TEXT`: Path to a custom file for training (default: "trained_agents_data.pkl")
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Example:
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```
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crewai train -n 10 -f my_training_data.pkl
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```
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### 4. replay
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Replay the crew execution from a specific task.
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```
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crewai replay [OPTIONS]
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```
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- `-t, --task_id TEXT`: Replay the crew from this task ID, including all subsequent tasks
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Example:
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```
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crewai replay -t task_123456
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```
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### 5. log_tasks_outputs
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Retrieve your latest crew.kickoff() task outputs.
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```
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crewai log_tasks_outputs
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```
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### 6. reset_memories
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Reset the crew memories (long, short, entity, latest_crew_kickoff_outputs).
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```
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crewai reset_memories [OPTIONS]
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```
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- `-l, --long`: Reset LONG TERM memory
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- `-s, --short`: Reset SHORT TERM memory
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- `-e, --entities`: Reset ENTITIES memory
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- `-k, --kickoff-outputs`: Reset LATEST KICKOFF TASK OUTPUTS
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- `-a, --all`: Reset ALL memories
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Example:
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```
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crewai reset_memories --long --short
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crewai reset_memories --all
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```
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### 7. test
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Test the crew and evaluate the results.
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```
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crewai test [OPTIONS]
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```
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- `-n, --n_iterations INTEGER`: Number of iterations to test the crew (default: 3)
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- `-m, --model TEXT`: LLM Model to run the tests on the Crew (default: "gpt-4o-mini")
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Example:
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```
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crewai test -n 5 -m gpt-3.5-turbo
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```
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### 8. run
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Run the crew.
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```
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crewai run
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```
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## Note
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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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Reference in New Issue
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