build(agent): molt-d#cb502d iteration
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"""CosmosMesh MVP: Privacy-Preserving Federated Mission Planning (Skeleton)
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"""CosmosMesh MVP packages
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This package provides a minimal, well-typed scaffold for a federated optimization
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stack used in CosmosMesh MVP initiatives. It intentionally implements a small,
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expressive optimizer skeleton (an ADMM-lite solver) to bootstrap testing,
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interfacing, and integration with adapters. The goal is to offer a safe, minimal
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yet realistic surface for rapid iteration while preserving the project's public
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API semantics.
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Lightweight scaffolding for a CatOpt-style bridge and two starter adapters
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to bootstrap CosmosMesh privacy-preserving federated mission planning.
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"""
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from .admm_lite import ADMMLiteSolver
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from .catopt_bridge import CatOptBridge
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from .contract_registry import ContractRegistry
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from .dsl_sketch import LocalProblemDSL, SharedVariablesDSL, DualVariablesDSL, PlanDeltaDSL
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from .catopt_bridge import (
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LocalProblem,
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SharedVariables,
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DualVariables,
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PlanDelta,
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CatOptBridge,
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)
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__all__ = [
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"ADMMLiteSolver",
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"LocalProblem",
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"SharedVariables",
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"DualVariables",
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"PlanDelta",
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"CatOptBridge",
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"ContractRegistry",
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"LocalProblemDSL",
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"SharedVariablesDSL",
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"DualVariablesDSL",
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"PlanDeltaDSL",
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]
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from __future__ import annotations
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from typing import Any, Dict
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from cosmosmesh_privacy_preserving_federated.catopt_bridge import LocalProblem, SharedVariables, DualVariables
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class HabitatModuleAdapter:
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"""Minimal habitat module adapter scaffold.
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Provides a tiny interface consistent with the Rover adapter to demonstrate
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end-to-end flow in the MVP. This is intentionally lightweight.
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"""
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def __init__(self) -> None:
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pass
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def read_state(self) -> Dict[str, Any]:
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return {"life_support": {"oxygen": 21.0, "co2": 0.04}, "status": "ok"}
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def expose_local_problem_data(self) -> LocalProblem:
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lp = LocalProblem(
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id="lp_habitat_1",
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objective="balance_life_support",
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variables={"heater": 0.5},
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constraints=["power<=100"],
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version=1,
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)
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return lp
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def apply_command(self, command: Dict[str, Any]) -> Dict[str, Any]:
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return {"ack": True, "command": command}
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from __future__ import annotations
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from typing import Any, Dict
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from cosmosmesh_privacy_preserving_federated.catopt_bridge import LocalProblem, SharedVariables, DualVariables
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class RoverPlannerAdapter:
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"""Minimal rover planner adapter scaffold.
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Exposes a tiny interface used by the MVP to demonstrate problem translation
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and command application. This is intentionally lightweight.
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"""
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def __init__(self) -> None:
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pass
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def read_state(self) -> Dict[str, Any]:
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# Placeholder rover state; in a real system this would query sensors.
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return {"battery": 78, "position": [0.0, 0.0], "status": "idle"}
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def expose_local_problem_data(self) -> LocalProblem:
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# Return a toy LocalProblem instance for the MVP demo.
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lp = LocalProblem(
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id="lp_rover_1",
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objective="minimize_energy",
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variables={"task": "survey"},
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constraints=["battery>=20"],
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version=1,
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)
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return lp
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def apply_command(self, command: Dict[str, Any]) -> Dict[str, Any]:
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# Accept a command and return an acknowledgment. This is a stub.
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return {"ack": True, "command": command}
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"""CatOpt bridge (MVP): CosmosMesh primitives <-> CatOpt-like representation.
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This module provides a tiny, domain-agnostic translator that maps CosmosMesh MVP
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primitives (LocalProblem, SharedVariables, DualVariables, PlanDelta) to a
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canonical CatOpt-like representation consisting of Objects, Morphisms, and
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Functors. It is intentionally lightweight to bootstrap cross-domain MVP testing
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without introducing heavy dependencies.
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"""
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from __future__ import annotations
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from typing import Any, Dict
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from dataclasses import dataclass, asdict
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from typing import Any, Dict, List, Optional
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from .dsl_sketch import LocalProblemDSL, SharedVariablesDSL, PlanDeltaDSL
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@dataclass
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class LocalProblem:
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id: str
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objective: str
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variables: Dict[str, Any]
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constraints: List[str]
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version: int = 1
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@dataclass
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class SharedVariables:
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name: str
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value: Any
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timestamp: float
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@dataclass
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class DualVariables:
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name: str
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value: Any
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@dataclass
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class PlanDelta:
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delta_id: str
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changes: Dict[str, Any]
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timestamp: float
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class GraphOfContracts:
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"""Simple in-memory registry for contract schemas and versions."""
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def __init__(self) -> None:
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self._contracts: Dict[str, Dict[str, Any]] = {}
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def register(self, name: str, version: str, schema: Optional[Dict[str, Any]] = None) -> None:
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self._contracts[name] = {"version": version, "schema": schema or {}}
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def get(self, name: str) -> Optional[Dict[str, Any]]:
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return self._contracts.get(name)
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def all(self) -> Dict[str, Dict[str, Any]]:
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return self._contracts
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class CatOptBridge:
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"""Lightweight translator between CosmosMesh primitives and CatOpt-like signals.
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"""Minimal CatOpt bridge that maps CosmosMesh primitives to a canonical CatOpt view.
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The bridge does not implement real secure transport or cryptography; it merely
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provides a stable, versioned mapping surface that downstream adapters can rely on
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for MVP interoperability.
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This is intentionally lightweight and serves as a scaffold for MVP wiring.
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"""
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def __init__(self) -> None:
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# Simple in-memory registry of versions for contracts lived in this bridge
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self._registry: Dict[str, str] = {
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"LocalProblem": "0.1",
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"SharedVariables": "0.1",
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"DualVariables": "0.1",
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"PlanDelta": "0.1",
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}
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self._registry = GraphOfContracts()
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def contract_version(self, contract_name: str) -> str:
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return self._registry.get(contract_name, "0.0")
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# Contract registry helpers
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def register_contract(self, name: str, version: str, schema: Optional[Dict[str, Any]] = None) -> None:
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self._registry.register(name, version, schema)
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# --- Translation helpers (minimal stubs) ---
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def to_catopt_object(self, lp: LocalProblemDSL) -> Dict[str, Any]:
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"""Translate a LocalProblem DSL instance to a CatOpt Object.
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def get_contract(self, name: str) -> Optional[Dict[str, Any]]:
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return self._registry.get(name)
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The output is a simple dictionary suitable for JSON-like transport.
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"""
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return {
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"type": "LocalProblemObject",
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"version": self.contract_version("LocalProblem"),
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"payload": {
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"agent_id": lp.agent_id,
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"variables": lp.variables,
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"objective": lp.objective,
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"constraints": lp.constraints,
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def all_contracts(self) -> Dict[str, Dict[str, Any]]:
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return self._registry.all()
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# Translation primitives (annotation-friendly, minimal)
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def to_catopt(self, lp: LocalProblem, sv: SharedVariables, dv: DualVariables) -> Dict[str, Any]:
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"""Translate CosmosMesh primitives into a minimal CatOpt-like representation."""
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catopt = {
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"Objects": {
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"LocalProblem": asdict(lp),
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},
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"Morphisms": {
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"SharedVariables": asdict(sv),
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"DualVariables": asdict(dv),
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},
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"Functors": {
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# Placeholder for adapter bindings (empty by default)
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},
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}
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return catopt
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def from_catopt_object(self, payload: Dict[str, Any]) -> LocalProblemDSL:
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"""Reverse-translate a CatOpt Object payload back into a LocalProblemDSL.
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def from_catopt(self, catopt: Dict[str, Any]) -> Dict[str, Any]:
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"""Minimal reverse-translation from CatOpt-like representation to a dictionary.
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This is intentionally permissive for MVP testing; adapters can extend as needed.
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This is intentionally permissive for MVP; it merely returns the input structure
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in a normalized dict form for downstream processing.
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"""
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p = payload.get("payload", {})
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return LocalProblemDSL(
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agent_id=str(p.get("agent_id", "unknown")),
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objective=p.get("objective", ""),
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variables=p.get("variables", []),
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constraints=p.get("constraints", []),
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)
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return dict(catopt)
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def to_plan_delta(self, delta: PlanDeltaDSL) -> Dict[str, Any]:
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"""Serialize a PlanDelta to a canonical CatOpt-like signal."""
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return {
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"type": "PlanDelta",
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"version": self.contract_version("PlanDelta"),
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"payload": delta.dict(),
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}
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def __repr__(self) -> str:
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return f"<CatOptBridge contracts={list(self._registry.keys())}>"
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__all__ = [
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"LocalProblem",
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"SharedVariables",
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"DualVariables",
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"PlanDelta",
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"GraphOfContracts",
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"CatOptBridge",
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]
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