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docker-and-data-setup

docker-and-data-setup

Plan AlphaFold Docker execution, database/model-parameter acquisition, update flows, and safe dry-run command construction without starting containers or downloads.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: docker-and-data-setup description: "Plan AlphaFold Docker execution, database/model-parameter acquisition, update flows, and safe dry-run command construction without starting containers or downloads." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Docker and Data Setup

Use this sub-skill when an AlphaFold task is about installation prerequisites, Docker image/run planning, GPU runtime checks, database and model-parameter layout, full-vs-reduced database choices, data updates, or safe construction of setup commands.

Do not run Docker builds, Docker containers, database downloads, or model-parameter downloads automatically. AlphaFold setup commonly requires hundreds of GB to multiple TB of storage, network transfer, a Docker daemon, and GPU/container runtime access; treat those operations as user-supervised external work.

Fast Routing

  • For Docker prerequisites, image build planning, GPU runtime signals, mount mapping, and dry-run launcher command construction, read references/docker-workflow.md and use scripts/plan_docker_command.py.
  • For database/model-parameter acquisition, expected data directory layout, full vs reduced mode, and incremental update ordering, read references/data-layout.md and use scripts/plan_data_downloads.py.
  • For setup failures such as repo-nested data directories, missing aria2c/rsync, missing NVIDIA runtime, permissions, database-preset mismatches, and GPU relax instability, read references/troubleshooting.md.
  • For FASTA content/schema validation, route to input-data-and-formats; this sub-skill only checks filesystem path and basename constraints needed for Docker planning.
  • For prediction flag semantics, model-output files, confidence interpretation, or direct run_alphafold execution, route to prediction-cli and outputs-and-confidence.

Safe Helper Usage

Run only the bundled helpers below during agent-driven setup planning:

python sub-skills/docker-and-data-setup/scripts/plan_docker_command.py --help
python sub-skills/docker-and-data-setup/scripts/plan_data_downloads.py --help

The helpers only inspect local paths and print plans. Any Docker build/run command or official downloader command they describe is a user-supervised external operation, not an agent-run validation step.

Minimum Public Facts

  • Public package/distribution version covered here: alphafold 2.3.2.
  • Public Python requirement from package metadata: Python >=3.10.
  • Docker launcher dependencies are absl-py==1.0.0 and docker==5.0.0, but the bundled command planner does not import docker.
  • Full prediction setups require external genetic databases, model parameters, HMMER/HH-suite/Kalign tooling inside the runtime environment, and typically a Linux host with NVIDIA GPU/container runtime support.
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