cuvis-ai-schemas
Lightweight schema definitions for the cuvis-ai ecosystem.
Overview
cuvis-ai-schemas is a centralized, dependency-light package of schema definitions used across the cuvis-ai ecosystem. It enables type-safe communication between services without heavy runtime requirements.
Key points:
- Minimal deps (pydantic + pyyaml)
- Full Pydantic validation
- Optional extras for proto, torch, numpy, lightning, testing
Installation
uv add cuvis-ai-schemas
uv add "cuvis-ai-schemas[proto]"
uv add "cuvis-ai-schemas[full]"
Extras:
proto: gRPC and protobuf supporttorch: PyTorch dtype handling (validation only)numpy: NumPy array supportlightning: PyTorch Lightning training configstesting: Hypothesis strategies + round-trip assertions (cuvis_ai_schemas.testing)full: All featuresdev: Development dependencies
Usage
from cuvis_ai_schemas.pipeline import PipelineConfig, NodeConfig
pipeline = PipelineConfig(
nodes=[NodeConfig(name="node_1", class_name="my_pkg.DataLoader", hparams={"batch_size": 32})],
connections=[],
)
pipeline_json = pipeline.to_json()
pipeline = PipelineConfig.from_json(pipeline_json)
Development
uv sync --all-extras --dev
uv run pytest tests/ -v
uv run ruff check cuvis_ai_schemas/ tests/
uv run ruff format cuvis_ai_schemas/ tests/
uv run mypy cuvis_ai_schemas/
Contributing
Contributions are welcome. Please:
- Ensure tests pass
- Run ruff format and ruff check
- Keep type hints and update docs as needed
License
Licensed under the Apache License 2.0. See LICENSE for details.
1 maintainer
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