Installation¶

ChemGraph requires Python 3.11 or newer. Use a virtual environment because its scientific dependencies may conflict with packages in other projects.

Install from PyPI¶

python -m venv .venv
source .venv/bin/activate              # Windows: .venv\Scripts\activate
python -m pip install --upgrade pip
python -m pip install chemgraph

Prefer uv? Use it to create the same environment and install ChemGraph:

uv venv
source .venv/bin/activate              # Windows: .venv\Scripts\activate
uv pip install chemgraph

Confirm that the command-line entry point and model registry load:

chemgraph --help
chemgraph models

The core installation includes the agent framework, ASE, RDKit, MACE, EMT, the Streamlit dependencies, and the general MCP server. MACE downloads model weights when first used; start with EMT if you need an offline calculator smoke test.

Install from source¶

Use a source checkout for the Streamlit interface, examples, documentation, or development:

git clone https://github.com/argonne-lcf/ChemGraph.git
cd ChemGraph
python -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -e .

With uv, the equivalent development setup is:

uv venv
source .venv/bin/activate
uv pip install -e .

Optional extras¶

Install only the integrations needed by your workflow:

Extra	Install command	Adds
`calculators`	`pip install "chemgraph[calculators]"`	TBLite
`uma`	`pip install "chemgraph[uma]"`	UMA through fairchem-core
`ui`	`pip install "chemgraph[ui]"`	Additional UI dependencies
`rag`	`pip install "chemgraph[rag]"`	Document ingestion and vector stores
`xanes`	`pip install "chemgraph[xanes]"`	XANES workflow dependencies
`docking`	`pip install "chemgraph[docking]"`	Meeko docking preparation
`parsl`	`pip install "chemgraph[parsl]"`	Parsl execution
`ensemble_launcher`	`pip install "chemgraph[ensemble_launcher]"`	ALCF ensemble launcher
`globus_compute`	`pip install "chemgraph[globus_compute]"`	Globus Compute execution
`academy`	`pip install "chemgraph[academy]"`	Academy multi-agent runtime
`codex`	Source checkout: `pip install -e ".[codex]"`	Experimental Codex subscription route

Extras can be combined:

python -m pip install "chemgraph[academy,parsl,globus_compute]"

UMA environment

UMA's e3nn requirements can conflict with the MACE stack in the core environment. A separate virtual environment is the safest setup for UMA.

External programs¶

Some integrations are Python adapters, not bundled simulation programs:

ORCA and NWChem must be installed and configured for ASE separately.
FDMNES is required for local XANES execution; set FDMNES_EXE.
AutoDock Vina is normally installed from conda-forge for docking.
Site-specific gRASPA and HPC modules require executables, schedulers, and filesystem paths available at the target facility.

Conda environments¶

If an integration needs compiled or external dependencies, create a clean environment first and install ChemGraph with pip inside it:

conda create -n chemgraph python=3.11
conda activate chemgraph
python -m pip install chemgraph

Docker¶

Docker avoids a local Python installation and provides CLI, Streamlit, MCP, and Jupyter-oriented images. See Docker for commands, ports, credential forwarding, and artifact volumes.

Next step¶

Continue with the quickstart, then configure a provider in Models and authentication.