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Install the plexe library using pip. Choose the installation method that best suits your needs.

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Standard Installation

This installs the core plexe library along with common dependencies needed for most tasks, excluding large deep learning libraries.
This includes libraries like pandas, scikit-learn, xgboost, litellm, and smolagents.

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Lightweight Installation

For minimal dependencies, suitable if you only need the basic structure or plan to install other dependencies manually.
This installs only the absolute minimum required packages to run the core agent logic, without data handling or specific ML libraries. Use this if you are managing dependencies tightly in a constrained environment.

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Installation with Deep Learning Support

To include optional deep learning libraries like TensorFlow and PyTorch (CPU versions by default), use the [all] extra. This is needed if you expect Plexe to generate models using these frameworks.
This installs everything in the standard installation plus tensorflow-cpu and torch.
If you require GPU support for TensorFlow or PyTorch, you will need to install the appropriate GPU-enabled versions separately after installing plexe[all]. Consult the official TensorFlow and PyTorch documentation for GPU installation instructions specific to your system and CUDA version.

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Verifying Installation

After installation, you can verify it by importing plexe in a Python interpreter:

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Setting API Keys

Remember to set the necessary API keys for your chosen LLM provider(s) as environment variables.
Refer to the LiteLLM Providers documentation for the correct environment variable names.