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Installation

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Step 1: Install the package

Proto-tools requires Python 3.10+:
bash
pip install git+https://github.com/evo-design/proto-tools.git
A direct PyPI install (pip install proto-tools) will be available soon.
If you are developing or contributing to this project, follow the setup instructions in CONTRIBUTING.md instead.

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Step 2: Configure storage (optional)

All persistent data (model weights and tool environments) is cached under the PROTO_HOME directory on first use (defaults to ~/.proto/). To customize the storage location, you can specify a path via the following environment variable:
bash
# Add to your shell profile:
export PROTO_HOME=/path/to/your/proto_home
For shared filesystems, model weights can be reused to avoid downloading duplicate copies. The PROTO_MODEL_CACHE environment variable lets you point just the weights at that shared location (sharing tool environments is not recommended): export PROTO_MODEL_CACHE=/path/to/shared/weights. See Storage guide for all details and options.

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Step 3: Gated model access (optional)

Some tools use gated models that require accepting a license / terms-of-use. Two access flows depending on how the upstream author publishes weights:
ModelSourceAccess
ESM3HuggingFace: EvolutionaryScale/esm3-sm-open-v1Accept EvolutionaryScale license, then authenticate with HF (see below)
AlphaGenomeHuggingFace: google/alphagenome-all-foldsAccept Google DeepMind terms, then authenticate with HF (see below)
AlphaFold3DeepMind request form: google-deepmind/alphafold3#obtaining-model-parametersSubmit DeepMind’s form; if approved, you can download the weights archive and place at $PROTO_HOME/proto_model_cache/alphafold3/ (or set PROTO_ALPHAFOLD3_WEIGHTS_DIR). See proto_tools/tools/structure_prediction/alphafold3/README.md for the full weights-setup flow.
For HuggingFace-gated models:
  1. Create a HuggingFace account
  2. Visit each model page above and accept the license/terms
  3. Install the HuggingFace CLI and log in: 
    curl -LsSf https://hf.co/cli/install.sh | bash
hf auth login
    Or set the token directly in your environment: 
    export HF_TOKEN=hf_...
You’re all set up! To learn what features are available in the library, check out the guides — four short notebooks covering tool environments, persistent execution, device management, and parallel multi-GPU runs.
You’re all set! Head over to the Quickstart to run your first tool, or browse the tool catalog to see what’s available.