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Documentation Index

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Foundation requires Python 3.7 or later. No GPU is needed to run the simulation; a GPU is only required if you plan to accelerate RL training with WarpDrive.

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Install via pip

The quickest way to install Foundation is from PyPI: 
pip install ai-economist
This installs version 1.7.1 along with all required dependencies (NumPy, SciPy, Pandas, Matplotlib, and others listed in requirements.txt).

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Install from source

Installing from source lets you edit the framework code and run the included tutorials.
1

Clone the repository

git clone https://github.com/salesforce/ai-economist
2

Create and activate a conda environment

conda create --name ai-economist python=3.7 --yes
conda activate ai-economist
Add the following alias to your ~/.bashrc or ~/.bash_profile for quick access:
alias aiecon="conda activate ai-economist; cd <local path to ai-economist>"
Then run aiecon once to activate the environment and change to the project directory.
3

Install the package

Choose one of the two approaches:
cd ai-economist
pip install -e .
The editable install (-e .) is recommended because it keeps the installed package in sync with any source edits you make.
4

Verify the installation

conda activate ai-economist
python -c "import ai_economist"
No output means the import succeeded. If you see an ImportError, double-check that the conda environment is active and that the install step completed without errors.

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Optional: GPU-accelerated training with WarpDrive

Foundation integrates with WarpDrive, a high-throughput multi-agent RL framework that runs thousands of environment rollouts in parallel on a single GPU. To enable WarpDrive support, install the extra package: 
pip install rl-warp-drive
WarpDrive requires a CUDA-capable GPU. It is not needed to run or explore Foundation simulations—only for large-scale GPU training.

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Dependencies

The key runtime dependencies installed by pip install ai-economist are:
PackageVersionPurpose
numpy1.21.0Array operations throughout the simulation
scipy1.6.3Statistical distributions and signal processing
pandas1.2.4Dataset handling (COVID-19 data)
matplotlib3.2.1Visualization utilities
pyyaml5.4.1Configuration file parsing
All pinned versions are in requirements.txt.

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