From 086ea38076bb1c18f2b82bb3f6562e9e3567422b Mon Sep 17 00:00:00 2001 From: agent-7e3bbc424e07835b Date: Sun, 19 Apr 2026 19:50:26 +0200 Subject: [PATCH] build(agent): new-agents-2#7e3bbc iteration --- AGENTS.md | 10 ++ .../__init__.py | 5 +- .../contracts.py | 102 +++++++----------- .../dsl.py | 69 ++++++++++++ .../solver.py | 58 +++++----- 5 files changed, 151 insertions(+), 93 deletions(-) create mode 100644 src/catopt_category_theoretic_compositional/dsl.py diff --git a/AGENTS.md b/AGENTS.md index 949781b..f9bbf8d 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -19,3 +19,13 @@ Guidance for contributors - Do not change the MVP skeleton without explicit intent to expand functionality. - Ensure test.sh remains executable and tests cover basic import/build scenarios. - Update AGENTS.md as the architecture evolves. + +New MVP scaffolds (current status): +- Added lightweight DSL primitives (src/catopt_category_theoretic_compositional/dsl.py) +- Added minimal contracts primitives (src/catopt_category_theoretic_compositional/contracts.py) +- Added a tiny solver kernel (src/catopt_category_theoretic_compositional/solver.py) +- Exposed new API in package __init__ (LocalProblem, SharedVariables, PlanDelta, admm_update) + +How to explore: +- Import surface: from catopt_category_theoretic_compositional import LocalProblem, SharedVariables, PlanDelta, admm_update +- Use admm_update(local, shared) as a tiny, deterministic update example. diff --git a/src/catopt_category_theoretic_compositional/__init__.py b/src/catopt_category_theoretic_compositional/__init__.py index 9b3682d..e1e3c3e 100644 --- a/src/catopt_category_theoretic_compositional/__init__.py +++ b/src/catopt_category_theoretic_compositional/__init__.py @@ -8,7 +8,10 @@ single utility function used by the test suite. from __future__ import annotations -__all__ = ["add"] +from .dsl import LocalProblem, SharedVariables, PlanDelta +from .solver import admm_update + +__all__ = ["add", "LocalProblem", "SharedVariables", "PlanDelta", "admm_update"] def add(a: int, b: int) -> int: diff --git a/src/catopt_category_theoretic_compositional/contracts.py b/src/catopt_category_theoretic_compositional/contracts.py index beb6cb3..08b5d78 100644 --- a/src/catopt_category_theoretic_compositional/contracts.py +++ b/src/catopt_category_theoretic_compositional/contracts.py @@ -1,90 +1,62 @@ -"""CatOpt Contracts: Minimal primitives for Local Problems and exchanges. +"""Contracts: lightweight data-contract primitives for CatOpt (minimal). -This module provides lightweight dataclasses that sketch the API surface -for CatOpt's data contracts. The goal is to be expressive enough for MVP wiring -without pulling in heavy dependencies. +These dataclasses are intentionally small and import-time friendly to keep +the MVP stable while enabling eventual extensions for privacy contracts, +audits, and governance. """ from __future__ import annotations -from dataclasses import dataclass, asdict -from typing import Any, Dict, List, Optional +from dataclasses import dataclass, asdict, field +from typing import Dict, Optional import json @dataclass -class LocalProblem: - """Represents a device-level optimization problem. - - - variables: a map of decision variables and their current values/roles - - objective: a serializable representation of the local objective - - constraints: list of constraints (expressions or callables in a real system) - - privacy_preferences: optional hints for privacy-preserving exchanges - """ - - variables: Dict[str, Any] - objective: Any - constraints: List[Any] - privacy_preferences: Optional[Dict[str, Any]] = None +class LocalProblemContract: + id: str + domain: str + objective: str + constraints: list[str] def to_json(self) -> str: - return json.dumps(asdict(self), default=str) + return json.dumps(asdict(self)) + + @classmethod + def from_json(cls, payload: str) -> "LocalProblemContract": + data = json.loads(payload) + return cls(id=data["id"], domain=data.get("domain", ""), objective=data.get("objective", ""), constraints=data.get("constraints", [])) @dataclass -class SharedVariables: - """Variables shared across agents for coordination (e.g., aggregates).""" - - variables: Dict[str, Any] +class SharedVariablesContract: version: int - contract_id: str - encryption_schema: Optional[str] = None + contract_id: Optional[str] = None + payload: Dict[str, float] = field(default_factory=dict) def to_json(self) -> str: - return json.dumps(asdict(self), default=str) + return json.dumps(asdict(self)) + + @classmethod + def from_json(cls, payload: str) -> "SharedVariablesContract": + data = json.loads(payload) + return cls(version=data["version"], contract_id=data.get("contract_id"), payload=data.get("payload", {})) @dataclass -class DualVariables: - """Lagrange-like multipliers used in coordination.""" - - multipliers: Dict[str, float] - - def to_json(self) -> str: - return json.dumps(asdict(self), default=str) - - -@dataclass -class PlanDelta: - """Proposed updates to the local problem in a delta-sync step.""" - - delta: Dict[str, Any] - timestamp: float +class PlanDeltaContract: + delta: Dict[str, float] + timestamp: str author: str - contract_id: str - privacy_budget: Optional[Dict[str, Any]] = None - proofs: Optional[List[str]] = None + contract_id: Optional[str] = None def to_json(self) -> str: - return json.dumps(asdict(self), default=str) + return json.dumps(asdict(self)) + + @classmethod + def from_json(cls, payload: str) -> "PlanDeltaContract": + data = json.loads(payload) + return cls(delta=data["delta"], timestamp=data["timestamp"], author=data["author"], contract_id=data.get("contract_id")) -@dataclass -class AuditLog: - """Immutable-ish audit log for governance and replay protection.""" - - entries: List[Dict[str, Any]] - - def to_json(self) -> str: - return json.dumps(asdict(self), default=str) - - -@dataclass -class PolicyBlock: - """Safety and data-exposure policy block attached to exchanges.""" - - safety_constraints: List[str] - data_exposure_rules: List[str] - - def to_json(self) -> str: - return json.dumps(asdict(self), default=str) +__all__ = ["LocalProblemContract", "SharedVariablesContract", "PlanDeltaContract"] diff --git a/src/catopt_category_theoretic_compositional/dsl.py b/src/catopt_category_theoretic_compositional/dsl.py new file mode 100644 index 0000000..75e294d --- /dev/null +++ b/src/catopt_category_theoretic_compositional/dsl.py @@ -0,0 +1,69 @@ +"""CatOpt DSL primitives (minimal MVP scaffolding). + +This module provides lightweight, serializable representations for the local +optimization problems and exchange artifacts that participate in the +CatOpt protocol. It is intentionally small but stable to enable safe expansion +in future iterations. +""" + +from __future__ import annotations + +from dataclasses import dataclass, field, asdict +from typing import Dict, List, Optional +import json + + +@dataclass +class LocalProblem: + id: str + domain: str + objective: str + constraints: List[str] = field(default_factory=list) + variables: Optional[Dict[str, float]] = None + + def to_json(self) -> str: + return json.dumps(asdict(self)) + + @classmethod + def from_json(cls, payload: str) -> "LocalProblem": + data = json.loads(payload) + return cls( + id=data["id"], + domain=data.get("domain", "unknown"), + objective=data.get("objective", ""), + constraints=data.get("constraints", []), + variables=data.get("variables"), + ) + + +@dataclass +class SharedVariables: + version: int + signals: Dict[str, float] = field(default_factory=dict) + + def to_json(self) -> str: + return json.dumps(asdict(self)) + + @classmethod + def from_json(cls, payload: str) -> "SharedVariables": + data = json.loads(payload) + return cls(version=data["version"], signals=data.get("signals", {})) + + +@dataclass +class PlanDelta: + delta: Dict[str, float] + timestamp: str + author: str + contract_id: Optional[str] = None + + def to_json(self) -> str: + return json.dumps(asdict(self)) + + @classmethod + def from_json(cls, payload: str) -> "PlanDelta": + data = json.loads(payload) + return cls(delta=data["delta"], timestamp=data["timestamp"], author=data["author"], contract_id=data.get("contract_id")) + + +__all__ = ["LocalProblem", "SharedVariables", "PlanDelta"] diff --git a/src/catopt_category_theoretic_compositional/solver.py b/src/catopt_category_theoretic_compositional/solver.py index 27ad3d2..f03db91 100644 --- a/src/catopt_category_theoretic_compositional/solver.py +++ b/src/catopt_category_theoretic_compositional/solver.py @@ -1,37 +1,41 @@ -"""Tiny ADMM-inspired solver placeholder for CatOpt MVP.""" +"""A tiny, placeholder ADMM-like solver kernel for CatOpt MVP. + +This module provides a minimal function that demonstrates an update step +between a LocalProblem (DSL) and SharedVariables (contracts). The logic is +deliberately simple to keep the MVP stable while offering a hook for future +expansion. +""" from __future__ import annotations -from typing import Dict, Any, Tuple - -from .contracts import LocalProblem, SharedVariables, DualVariables +from typing import Dict +from .dsl import LocalProblem, SharedVariables -def admm_step(local: LocalProblem, shared: SharedVariables, dual: DualVariables) -> Tuple[LocalProblem, SharedVariables, DualVariables]: - """Perform a toy ADMM step. +def admm_update(local: LocalProblem, shared: SharedVariables, rho: float = 1.0) -> LocalProblem: + """Perform a tiny, deterministic ADMM-like update of a local problem. - This is a non-production placeholder that demonstrates the kind of update - you would wire into the MVP. It does not solve the problem; it simply - demonstrates structure and state transitions for local and shared data. + This is a stub implementation intended for demonstration and testing. It + updates a simple primal variable if present, otherwise initializes it. """ - # Very naive placeholder: push a tiny, deterministic adjustment to a variable - # indicating progress in coordination. In a real solver, you'd compute proximal - # updates, dual ascent steps, and consensus enforcement here. - if local.variables: - key = next(iter(local.variables)) - val = local.variables[key] - try: - local.variables[key] = val # no-op baseline; real code would update - except Exception: - pass + # Copy local to avoid mutating input (functional style). + updated = LocalProblem( + id=local.id, + domain=local.domain, + objective=local.objective, + constraints=list(local.constraints), + variables=dict(local.variables) if local.variables is not None else {}, + ) - # Update a dummy shared signal (e.g., a mean of a shared variable) - for k, v in list(shared.variables.items()): - if isinstance(v, (int, float)): - shared.variables[k] = v * 1.0 # no change; placeholder + # Simple, deterministic update to a hypothetical primal variable. + primal = 0.0 + if not isinstance(updated.variables, dict): + updated.variables = {} + if isinstance(updated.variables, dict): + primal = updated.variables.get("primal", 0.0) + updated.variables["primal"] = primal + 0.5 * rho - # Update duals trivially - for k in list(dual.multipliers.keys()): - dual.multipliers[k] = dual.multipliers[k] + return updated - return local, shared, dual + +__all__ = ["admm_update"]