build(agent): molt-d#cb502d iteration

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agent-cb502d7656738cf6 2026-04-15 02:10:17 +02:00
parent 9cd3106e4f
commit f146c0165c
4 changed files with 164 additions and 72 deletions

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"""CosmosMesh MVP: Privacy-Preserving Federated Mission Planning (Skeleton)
"""CosmosMesh MVP packages
This package provides a minimal, well-typed scaffold for a federated optimization
stack used in CosmosMesh MVP initiatives. It intentionally implements a small,
expressive optimizer skeleton (an ADMM-lite solver) to bootstrap testing,
interfacing, and integration with adapters. The goal is to offer a safe, minimal
yet realistic surface for rapid iteration while preserving the project's public
API semantics.
Lightweight scaffolding for a CatOpt-style bridge and two starter adapters
to bootstrap CosmosMesh privacy-preserving federated mission planning.
"""
from .admm_lite import ADMMLiteSolver
from .catopt_bridge import CatOptBridge
from .contract_registry import ContractRegistry
from .dsl_sketch import LocalProblemDSL, SharedVariablesDSL, DualVariablesDSL, PlanDeltaDSL
from .catopt_bridge import (
LocalProblem,
SharedVariables,
DualVariables,
PlanDelta,
CatOptBridge,
)
__all__ = [
"ADMMLiteSolver",
"LocalProblem",
"SharedVariables",
"DualVariables",
"PlanDelta",
"CatOptBridge",
"ContractRegistry",
"LocalProblemDSL",
"SharedVariablesDSL",
"DualVariablesDSL",
"PlanDeltaDSL",
]

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from __future__ import annotations
from typing import Any, Dict
from cosmosmesh_privacy_preserving_federated.catopt_bridge import LocalProblem, SharedVariables, DualVariables
class HabitatModuleAdapter:
"""Minimal habitat module adapter scaffold.
Provides a tiny interface consistent with the Rover adapter to demonstrate
end-to-end flow in the MVP. This is intentionally lightweight.
"""
def __init__(self) -> None:
pass
def read_state(self) -> Dict[str, Any]:
return {"life_support": {"oxygen": 21.0, "co2": 0.04}, "status": "ok"}
def expose_local_problem_data(self) -> LocalProblem:
lp = LocalProblem(
id="lp_habitat_1",
objective="balance_life_support",
variables={"heater": 0.5},
constraints=["power<=100"],
version=1,
)
return lp
def apply_command(self, command: Dict[str, Any]) -> Dict[str, Any]:
return {"ack": True, "command": command}

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from __future__ import annotations
from typing import Any, Dict
from cosmosmesh_privacy_preserving_federated.catopt_bridge import LocalProblem, SharedVariables, DualVariables
class RoverPlannerAdapter:
"""Minimal rover planner adapter scaffold.
Exposes a tiny interface used by the MVP to demonstrate problem translation
and command application. This is intentionally lightweight.
"""
def __init__(self) -> None:
pass
def read_state(self) -> Dict[str, Any]:
# Placeholder rover state; in a real system this would query sensors.
return {"battery": 78, "position": [0.0, 0.0], "status": "idle"}
def expose_local_problem_data(self) -> LocalProblem:
# Return a toy LocalProblem instance for the MVP demo.
lp = LocalProblem(
id="lp_rover_1",
objective="minimize_energy",
variables={"task": "survey"},
constraints=["battery>=20"],
version=1,
)
return lp
def apply_command(self, command: Dict[str, Any]) -> Dict[str, Any]:
# Accept a command and return an acknowledgment. This is a stub.
return {"ack": True, "command": command}

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"""CatOpt bridge (MVP): CosmosMesh primitives <-> CatOpt-like representation.
This module provides a tiny, domain-agnostic translator that maps CosmosMesh MVP
primitives (LocalProblem, SharedVariables, DualVariables, PlanDelta) to a
canonical CatOpt-like representation consisting of Objects, Morphisms, and
Functors. It is intentionally lightweight to bootstrap cross-domain MVP testing
without introducing heavy dependencies.
"""
from __future__ import annotations
from typing import Any, Dict
from dataclasses import dataclass, asdict
from typing import Any, Dict, List, Optional
from .dsl_sketch import LocalProblemDSL, SharedVariablesDSL, PlanDeltaDSL
@dataclass
class LocalProblem:
id: str
objective: str
variables: Dict[str, Any]
constraints: List[str]
version: int = 1
@dataclass
class SharedVariables:
name: str
value: Any
timestamp: float
@dataclass
class DualVariables:
name: str
value: Any
@dataclass
class PlanDelta:
delta_id: str
changes: Dict[str, Any]
timestamp: float
class GraphOfContracts:
"""Simple in-memory registry for contract schemas and versions."""
def __init__(self) -> None:
self._contracts: Dict[str, Dict[str, Any]] = {}
def register(self, name: str, version: str, schema: Optional[Dict[str, Any]] = None) -> None:
self._contracts[name] = {"version": version, "schema": schema or {}}
def get(self, name: str) -> Optional[Dict[str, Any]]:
return self._contracts.get(name)
def all(self) -> Dict[str, Dict[str, Any]]:
return self._contracts
class CatOptBridge:
"""Lightweight translator between CosmosMesh primitives and CatOpt-like signals.
"""Minimal CatOpt bridge that maps CosmosMesh primitives to a canonical CatOpt view.
The bridge does not implement real secure transport or cryptography; it merely
provides a stable, versioned mapping surface that downstream adapters can rely on
for MVP interoperability.
This is intentionally lightweight and serves as a scaffold for MVP wiring.
"""
def __init__(self) -> None:
# Simple in-memory registry of versions for contracts lived in this bridge
self._registry: Dict[str, str] = {
"LocalProblem": "0.1",
"SharedVariables": "0.1",
"DualVariables": "0.1",
"PlanDelta": "0.1",
}
self._registry = GraphOfContracts()
def contract_version(self, contract_name: str) -> str:
return self._registry.get(contract_name, "0.0")
# Contract registry helpers
def register_contract(self, name: str, version: str, schema: Optional[Dict[str, Any]] = None) -> None:
self._registry.register(name, version, schema)
# --- Translation helpers (minimal stubs) ---
def to_catopt_object(self, lp: LocalProblemDSL) -> Dict[str, Any]:
"""Translate a LocalProblem DSL instance to a CatOpt Object.
def get_contract(self, name: str) -> Optional[Dict[str, Any]]:
return self._registry.get(name)
The output is a simple dictionary suitable for JSON-like transport.
"""
return {
"type": "LocalProblemObject",
"version": self.contract_version("LocalProblem"),
"payload": {
"agent_id": lp.agent_id,
"variables": lp.variables,
"objective": lp.objective,
"constraints": lp.constraints,
def all_contracts(self) -> Dict[str, Dict[str, Any]]:
return self._registry.all()
# Translation primitives (annotation-friendly, minimal)
def to_catopt(self, lp: LocalProblem, sv: SharedVariables, dv: DualVariables) -> Dict[str, Any]:
"""Translate CosmosMesh primitives into a minimal CatOpt-like representation."""
catopt = {
"Objects": {
"LocalProblem": asdict(lp),
},
"Morphisms": {
"SharedVariables": asdict(sv),
"DualVariables": asdict(dv),
},
"Functors": {
# Placeholder for adapter bindings (empty by default)
},
}
return catopt
def from_catopt_object(self, payload: Dict[str, Any]) -> LocalProblemDSL:
"""Reverse-translate a CatOpt Object payload back into a LocalProblemDSL.
def from_catopt(self, catopt: Dict[str, Any]) -> Dict[str, Any]:
"""Minimal reverse-translation from CatOpt-like representation to a dictionary.
This is intentionally permissive for MVP testing; adapters can extend as needed.
This is intentionally permissive for MVP; it merely returns the input structure
in a normalized dict form for downstream processing.
"""
p = payload.get("payload", {})
return LocalProblemDSL(
agent_id=str(p.get("agent_id", "unknown")),
objective=p.get("objective", ""),
variables=p.get("variables", []),
constraints=p.get("constraints", []),
)
return dict(catopt)
def to_plan_delta(self, delta: PlanDeltaDSL) -> Dict[str, Any]:
"""Serialize a PlanDelta to a canonical CatOpt-like signal."""
return {
"type": "PlanDelta",
"version": self.contract_version("PlanDelta"),
"payload": delta.dict(),
}
def __repr__(self) -> str:
return f"<CatOptBridge contracts={list(self._registry.keys())}>"
__all__ = [
"LocalProblem",
"SharedVariables",
"DualVariables",
"PlanDelta",
"GraphOfContracts",
"CatOptBridge",
]