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docs/concepts/training.mdx
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docs/concepts/training.mdx
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---
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title: Training
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description: Learn how to train your CrewAI agents by giving them feedback early on and get consistent results.
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icon: dumbbell
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---
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## Introduction
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The training feature in CrewAI allows you to train your AI agents using the command-line interface (CLI).
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By running the command `crewai train -n <n_iterations>`, you can specify the number of iterations for the training process.
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During training, CrewAI utilizes techniques to optimize the performance of your agents along with human feedback.
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This helps the agents improve their understanding, decision-making, and problem-solving abilities.
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### Training Your Crew Using the CLI
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To use the training feature, follow these steps:
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1. Open your terminal or command prompt.
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2. Navigate to the directory where your CrewAI project is located.
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3. Run the following command:
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```shell
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crewai train -n <n_iterations> <filename> (optional)
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```
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<Tip>
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Replace `<n_iterations>` with the desired number of training iterations and `<filename>` with the appropriate filename ending with `.pkl`.
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</Tip>
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### Training Your Crew Programmatically
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To train your crew programmatically, use the following steps:
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1. Define the number of iterations for training.
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2. Specify the input parameters for the training process.
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3. Execute the training command within a try-except block to handle potential errors.
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```python Code
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n_iterations = 2
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inputs = {"topic": "CrewAI Training"}
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filename = "your_model.pkl"
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try:
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YourCrewName_Crew().crew().train(
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n_iterations=n_iterations,
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inputs=inputs,
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filename=filename
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)
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except Exception as e:
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raise Exception(f"An error occurred while training the crew: {e}")
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```
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### Key Points to Note
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- **Positive Integer Requirement:** Ensure that the number of iterations (`n_iterations`) is a positive integer. The code will raise a `ValueError` if this condition is not met.
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- **Filename Requirement:** Ensure that the filename ends with `.pkl`. The code will raise a `ValueError` if this condition is not met.
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- **Error Handling:** The code handles subprocess errors and unexpected exceptions, providing error messages to the user.
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It is important to note that the training process may take some time, depending on the complexity of your agents and will also require your feedback on each iteration.
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Once the training is complete, your agents will be equipped with enhanced capabilities and knowledge, ready to tackle complex tasks and provide more consistent and valuable insights.
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Remember to regularly update and retrain your agents to ensure they stay up-to-date with the latest information and advancements in the field.
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Happy training with CrewAI! 🚀
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