> ## Documentation Index
> Fetch the complete documentation index at: https://docs.plexe.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Installation

> Learn how to install the Plexe Python library with different dependency sets.

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

## Standard Installation

This installs the core `plexe` library along with common dependencies needed for most tasks, excluding large deep learning libraries.

```bash theme={null}
pip install plexe
```

This includes libraries like `pandas`, `scikit-learn`, `xgboost`, `litellm`, and `smolagents`.

## Lightweight Installation

For minimal dependencies, suitable if you only need the basic structure or plan to install other dependencies manually.

```bash theme={null}
pip install plexe[lightweight]
```

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.

## 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.

```bash theme={null}
pip install plexe[all]
```

This installs everything in the standard installation plus `tensorflow-cpu` and `torch`.

<Note>
  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.
</Note>

## Verifying Installation

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

```python theme={null}
import plexe

print(f"Plexe library imported successfully.")
# You can also check the internal configuration for available packages
from plexe.config import config
print(f"Allowed packages: {config.code_generation.allowed_packages}")
print(f"Deep learning available: {config.code_generation.deep_learning_available}")
```

## Setting API Keys

Remember to set the necessary API keys for your chosen LLM provider(s) as environment variables.

```bash theme={null}
export OPENAI_API_KEY="YOUR_OPENAI_API_KEY"
# or
export ANTHROPIC_API_KEY="YOUR_ANTHROPIC_API_KEY"
# etc.
```

Refer to the [LiteLLM Providers documentation](https://docs.litellm.ai/docs/providers) for the correct environment variable names.