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CLI for authoring and running SWEAP benchmark tasks

Project description

SWEAP CLI

Command-line tooling for authoring, validating, and evaluating SWEAP benchmark tasks. Each task is a self-contained bundle containing repository metadata, guardrail tests, and a golden patch that can be reproduced locally or inside Modal sandboxes.

Quick Start

# optional: create a virtual environment
python3 -m venv .venv
source .venv/bin/activate

pip install --upgrade pip
pip install sweap-cli

# scaffold a new task bundle
task init --repo https://github.com/example/project.git --commit deadbeef

# iterate locally until guardrails behave as expected
task validate

# run the modal evaluation pipeline (baseline + model + patched verification)
task run --model codex

Required Credentials

  • SWEAP_API_URL and SWEAP_API_TOKEN for remote submissions and runs (request an API token from the SWEAP team).
  • OPENAI_API_KEY for Codex access (optional for local runs; mandatory for remote runs processed by our hosted worker).
  • modal CLI credentials (modal setup) if you plan to run Modal evaluations locally.

Add --runner node or --runner maven during task init to scaffold non-Python bundles. Use task validate --modal to reproduce validation inside Modal and task build to cache Modal environments for pytest bundles.

Core Commands

  • task init – scaffold manifests, guardrail directories, and dependency stubs.
  • task validate – run baseline vs. patched guardrails locally or in Modal.
  • task run – execute the full evaluation loop (baseline, model attempt, patched verification, optional full suite) locally or via the backend.
  • task submit – register/update tasks with the backend and upload bundle archives.
  • task build – prebuild Modal environments for pytest bundles.
  • task info / task fetch-bundle / task runs-get – inspect remote metadata, download bundles, and retrieve run artifacts.

See the CLI reference for detailed options.

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