diff --git a/README.md b/README.md index cbca2a3..97fdfb7 100644 --- a/README.md +++ b/README.md @@ -41,6 +41,16 @@ Public artifacts - Python modules in src/cosmosmesh_privacy_preserving_federated_ and src/cosmosmesh_privacy_preserving_federated_/catopt_bridge.py - Tests in tests/ (smoke test for basic arithmetic) - READY_TO_PUBLISH flag to be created when ready for publication + +CatOpt MVP Bridge (Overview) +- The MVP includes a lightweight CatOpt bridge that maps CosmosMesh primitives to a CatOpt-like representation (Objects/Morphisms/Functors). +- Core components: + - src/cosmosmesh_privacy_preserving_federated/catopt_bridge.py: translator skeleton for LocalProblem, SharedVariables, DualVariables, PlanDelta + - src/cosmosmesh_privacy_preserving_federated/dsl_sketch.py: lightweight DSL scaffolding for MVP primitives + - src/cosmosmesh_privacy_preserving_federated/contract_registry.py: minimal contract registry +- Reference adapters (toy scaffolds) added under src/cosmosmesh_privacy_preserving_federated_/reference_adapter.py to illustrate how rover and habitat domain adapters would interface with the bridge +- A tiny Graph-of-Contracts registry supports versioning for LocalProblem/SharedVariables/DualVariables/PlanDelta contracts +- Next steps (optional): TLS transport adapters, secure aggregation, and governance ledger integration # CosmosMesh MVP: Privacy-Preserving Federated Mission Planning This repository contains a minimal MVP scaffold for privacy-preserving, offline-first, multi-agent mission planning in deep-space fleets. It includes a tiny ADMM-lite solver and contract primitives, plus a CatOpt-style interoperability bridge for cross-domain experimentation. diff --git a/src/cosmosmesh_privacy_preserving_federated_/reference_adapter.py b/src/cosmosmesh_privacy_preserving_federated_/reference_adapter.py new file mode 100644 index 0000000..3843d4f --- /dev/null +++ b/src/cosmosmesh_privacy_preserving_federated_/reference_adapter.py @@ -0,0 +1,110 @@ +"""Prototype reference adapters for CosmosMesh CatOpt MVP. + +This module provides lightweight, self-contained adapters that demonstrate +how two domain agents (rover planner and habitat module) could interact with +the CatOpt bridge and the MVP primitives defined in the core package. + +The implementations are intentionally minimal and safe: they do not depend on +external transport or cryptography. They serve as a scaffold for downstream +team integrations and for validating end-to-end data shapes and contract +bindings. +""" + +from __future__ import annotations + +from typing import Dict, Any + +# Lightweight local DSL definitions (stand-ins for MVP scaffolding). +from dataclasses import dataclass +@dataclass +class LocalProblemDSL: + agent_id: str + objective: str + variables: list + constraints: list + + def dict(self) -> dict: + return { + "agent_id": self.agent_id, + "objective": self.objective, + "variables": self.variables, + "constraints": self.constraints, + } + +@dataclass +class SharedVariablesDSL: + signals: dict + version: str = "0.1" + + def dict(self) -> dict: + return {"signals": self.signals, "version": self.version} + +@dataclass +class PlanDeltaDSL: + delta_id: str + changes: dict + timestamp: str | None = None + + def dict(self) -> dict: + return {"delta_id": self.delta_id, "changes": self.changes, "timestamp": self.timestamp} +from cosmosmesh_privacy_preserving_federated_.catopt_bridge import CatOptBridge +from cosmosmesh_privacy_preserving_federated_.protocol import LocalProblem, SharedVariables, DualVariables + + +class RoverPlannerAdapter: + """Toy rover planner adapter demonstrating binding with the CatOpt bridge.""" + + def __init__(self) -> None: + self.bridge = CatOptBridge() + + def readState(self) -> Dict[str, Any]: + # Minimal example of agent state that could be fed into the bridge + lp = LocalProblem(variables={"x": 1.0, "y": 2.0, "z": 0.0}, objective="maximize_delivery_quality", constraints=["0 <= x <= 10"]) + sv = SharedVariables(signals={"share": 0.5}) + dv = DualVariables(multipliers={"lambda": 0.1}) + catopt = self.bridge.to_catopt(lp, sv, dv) + return {"type": "CatOpt", "payload": catopt} + + def exposeLocalProblemData(self) -> Dict[str, Any]: + lp = LocalProblem(variables={"x": 0.5, "y": 1.5}, objective="min_energy", constraints=["x+y <= 2"]) + sv = SharedVariables(signals={"share": 0.2}) + dv = DualVariables(multipliers={"lambda": 0.05}) + return self.bridge.to_catopt(lp, sv, dv) + + def applyCommand(self, command: Dict[str, Any]) -> Dict[str, Any]: + # Echo back the received command as an acknowledgment; simple delta object + delta = PlanDeltaDSL(delta_id=command.get("delta_id", "delta-000"), changes=command.get("changes", {})) + lp = LocalProblem(variables={}, objective="default", constraints=[]) + sv = SharedVariables(signals={}) + dv = DualVariables(multipliers={}) + # Return a canonical container via the bridge for testing pipelines + return self.bridge.to_catopt(lp, sv, dv) + + +class HabitatModuleAdapter: + """Toy habitat module adapter scaffold.""" + + def __init__(self) -> None: + self.bridge = CatOptBridge() + + def readState(self) -> Dict[str, Any]: + sv = SharedVariables(signals={"temperature": 22.0, "humidity": 45.0}) + lp = LocalProblem(variables={"a": 1.0}, objective="maximize survivability", constraints=["a>=0"]) + dv = DualVariables(multipliers={"gamma": 0.1}) + return self.bridge.to_catopt(lp, sv, dv) + + def exposeLocalProblemData(self) -> Dict[str, Any]: + lp = LocalProblem(variables={"a": 2.0}, objective="maximize survivability", constraints=["a >= 0"]) + sv = SharedVariables(signals={"temperature": 21.0}) + dv = DualVariables(multipliers={"delta": 0.3}) + return self.bridge.to_catopt(lp, sv, dv) + + def applyCommand(self, command: Dict[str, Any]) -> Dict[str, Any]: + delta = PlanDeltaDSL(delta_id=command.get("delta_id", "hab-delta-1"), changes={}) + lp = LocalProblem(variables={}, objective="default", constraints=[]) + sv = SharedVariables(signals={}) + dv = DualVariables(multipliers={}) + return self.bridge.to_catopt(lp, sv, dv) + + +__all__ = ["RoverPlannerAdapter", "HabitatModuleAdapter"]