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ActiveBlockference
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ActiveBlockference
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# ActiveBlockference ActiveBlockference is a CPU-oriented Active Inference library for deterministic, discrete-state radCAD and cadCAD grid simulations. It provides strict YAML/TOML configuration, canonical `(y, x)` dynamics, persisted diagnostics, rendered artefacts, and fail-closed validation. [](https://github.com/ActiveInferenceInstitute/ActiveBlockference/actions/workflows/ci.yml) [](https://raw.githubusercontent.com/ActiveInferenceInstitute/ActiveBlockference/main/LICENSE) ## Quick start ```bash uv sync --locked --extra dev uv run pytest uv run ruff check blockference tests uv run python scripts/release_check.py uv run blockference pipeline --config configs/smoke.yml --output-root output ``` The CLI has three explicit commands: ```bash blockference run --config configs/example.yml blockference pipeline --config configs/example.yml --output-root output blockference validation --run-dir output/gridworld_example ``` The pipeline emits `config.yml`, CSV trajectory and per-step diagnostics, JSON summary/model/policies, an NPZ model archive, PNG visualisations, a GIF, a log, `manifest.json`, and one aggregate `validation_report.json`. Parquet is an optional additional format; CSV and JSON remain required. A non-empty run directory is refused unless `--reuse` is supplied explicitly. For single-agent runs, `simulation.initial_state` remains the compatibility default. For multi-agent runs (`n_agents > 1`) the simultaneous-transition environment requires a unique starting cell per agent, so use `simulation.initial_states` with one distinct coordinate per agent; a multi-agent run without it fails fast with an explicit error. A seeded run owns its random generator and does not alter the caller's global random state. The grid implementation is self-contained. Install `active-blockference[pymdp]` only when using the optional `BlockferenceAgent` adapter; install `active-blockference[research]` for the explicitly selected OpenAI GRTs provider. Offline tests and the release gate never require either extra. ## Reliability and contracts * All JSON, CSV, NPZ, config, model, and render artefacts are published **atomically** through a sibling temporary file and renamed into place, so an interrupted run can never leave a partially written file (a leftover temp file is flagged as drift by validation). * `ValidationReport.ok` and `PipelineResult.ok` certify **software and artefact integrity only** — never the empirical adequacy of a scientific hypothesis. * `blockference.io.parse_trajectory_records` normalizes a persisted trajectory into typed, deterministically ordered `TrajectoryRecord` values so backend (radCAD vs cadCAD) and persistence round-trips are compared on values, not stringified cells. * `GridWorld` conforms to the `blockference.envs.DiscreteEnvironment` protocol (state identity, observations, simultaneous actions, collision resolution, and lossless `serialize`/`load`), so future environments can be added behind the same contract instead of special-casing the grid. ## Python API ```python from blockference import ExperimentConfig, GridWorld, run_pipeline config = ExperimentConfig.from_dict({ "name": "demo", "seed": 42, "grid": {"dimension": 3, "planning_length": 2, "affordances": ["UP", "RIGHT", "STAY"]}, "simulation": {"timesteps": 10, "runs": 1, "n_agents": 2, "target": [2, 2], "initial_states": [[0, 0], [1, 1]]}, }) result = run_pipeline(config) assert result.ok world = GridWorld(3, {0: (0, 0), 1: (1, 1)}) world.step({0: 1, 1: 0}) ``` ## Repository map * `blockference/` — installable library and CLI. * `configs/` — strict YAML/TOML examples. * `docs/` — architecture, theory, API, and pipeline contracts. * `notebooks/` — executable current-API teaching notebooks. * `GRTs/` — optional provider-based local research workflow. * `tests/` — unit, integration, artefact, and notebook checks. See [`docs/README.md`](docs/README.md) for the documentation index, [`docs/api.md`](docs/api.md), [`docs/pipeline.md`](docs/pipeline.md), and [`docs/development.md`](docs/development.md) for the complete contracts and workflow. Contributions are described in [`docs/contributing.md`](docs/contributing.md); security issues are reported privately per [`SECURITY.md`](SECURITY.md); the repository is released under the [MIT License](LICENSE).
