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0432429 5edd704 0432429 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 | """Deterministic task execution for awarded Agent 11 work.
The auction decides who receives work. This module only validates award/task
lineage, resolves required upstream inputs, invokes an approved deterministic
handler, and validates the resulting typed WorkProduct.
Handlers own substantive synthetic content only. They cannot choose their own
award, task, worker identity, capability, or work-product identifier.
"""
from __future__ import annotations
from collections.abc import Callable, Mapping
from dataclasses import dataclass
from datetime import datetime
from hashlib import sha256
from pydantic import ValidationError
from .models import FailureClass, TaskAnnouncement, TaskAward, WorkProduct
from .registry import PeerRegistry
class ExecutionError(ValueError):
"""Bounded execution failure suitable for conversion into TaskFailure."""
def __init__(self, message: str, *, failure_class: FailureClass) -> None:
super().__init__(message)
self.failure_class = failure_class
@dataclass(frozen=True)
class HandlerOutput:
"""Untrusted substantive payload returned by an execution handler.
The executor converts this payload into the strict WorkProduct contract.
Keeping handler output separate lets validation catch malformed handler
behavior before a work product is admitted downstream.
"""
title: str
summary: str
findings: tuple[str, ...]
evidence_ids: tuple[str, ...]
@dataclass(frozen=True)
class ExecutionContext:
"""Read-only context supplied to one approved deterministic handler."""
announcement: TaskAnnouncement
award: TaskAward
required_inputs: tuple[WorkProduct, ...]
TaskHandler = Callable[[ExecutionContext], HandlerOutput]
class DeterministicTaskExecutor:
"""Execute an awarded task through an allowlisted deterministic handler."""
def __init__(
self,
registry: PeerRegistry,
*,
handlers: Mapping[str, TaskHandler] | None = None,
) -> None:
self._registry = registry
self._handlers = dict(default_handlers() if handlers is None else handlers)
def execute(
self,
*,
announcement: TaskAnnouncement,
award: TaskAward,
completed_at: datetime,
available_inputs: tuple[WorkProduct, ...] = (),
) -> WorkProduct:
"""Validate lineage, run one handler, and return a strict work product."""
self._validate_award(announcement=announcement, award=award)
required_inputs = self._resolve_required_inputs(
announcement=announcement,
available_inputs=available_inputs,
)
handler = self._handlers.get(announcement.requested_capability)
if handler is None:
raise ExecutionError(
f"no approved handler for capability {announcement.requested_capability}",
failure_class=FailureClass.POLICY_REJECTION,
)
context = ExecutionContext(
announcement=announcement,
award=award,
required_inputs=required_inputs,
)
try:
output = handler(context)
except ExecutionError:
raise
except Exception as exc: # deterministic containment boundary
raise ExecutionError(
f"handler raised {type(exc).__name__}: {exc}",
failure_class=FailureClass.EXECUTION_ERROR,
) from exc
if not isinstance(output, HandlerOutput):
raise ExecutionError(
"handler returned an unsupported output type",
failure_class=FailureClass.INVALID_OUTPUT,
)
try:
return WorkProduct(
work_product_id=self._work_product_id(announcement, award),
award_id=award.award_id,
auction_id=announcement.auction_id,
task_id=announcement.task_id,
auction_round=announcement.auction_round,
agent_id=award.awarded_agent_id,
capability=announcement.requested_capability,
title=output.title,
summary=output.summary,
findings=output.findings,
evidence_ids=output.evidence_ids,
completed_at=completed_at,
)
except ValidationError as exc:
raise ExecutionError(
f"handler output failed WorkProduct validation: {exc.errors()[0]['msg']}",
failure_class=FailureClass.INVALID_OUTPUT,
) from exc
def _validate_award(
self,
*,
announcement: TaskAnnouncement,
award: TaskAward,
) -> None:
if award.auction_id != announcement.auction_id:
raise ExecutionError(
"award auction_id does not match announcement",
failure_class=FailureClass.POLICY_REJECTION,
)
if award.task_id != announcement.task_id:
raise ExecutionError(
"award task_id does not match announcement",
failure_class=FailureClass.POLICY_REJECTION,
)
if award.auction_round != announcement.auction_round:
raise ExecutionError(
"award auction_round does not match announcement",
failure_class=FailureClass.POLICY_REJECTION,
)
profile = self._registry.get(award.awarded_agent_id)
if profile is None:
raise ExecutionError(
"awarded agent is not registered",
failure_class=FailureClass.POLICY_REJECTION,
)
capability_score = profile.score_for(announcement.requested_capability)
if capability_score is None:
raise ExecutionError(
"awarded agent is not registered for the requested capability",
failure_class=FailureClass.POLICY_REJECTION,
)
if capability_score < announcement.minimum_capability_score:
raise ExecutionError(
"awarded agent capability is below the task minimum",
failure_class=FailureClass.POLICY_REJECTION,
)
@staticmethod
def _resolve_required_inputs(
*,
announcement: TaskAnnouncement,
available_inputs: tuple[WorkProduct, ...],
) -> tuple[WorkProduct, ...]:
by_id: dict[str, WorkProduct] = {}
for product in available_inputs:
if product.work_product_id in by_id:
raise ExecutionError(
f"duplicate available input {product.work_product_id}",
failure_class=FailureClass.DEPENDENCY_FAILURE,
)
by_id[product.work_product_id] = product
missing = [
input_id
for input_id in announcement.required_input_ids
if input_id not in by_id
]
if missing:
raise ExecutionError(
f"missing required input work products: {', '.join(missing)}",
failure_class=FailureClass.DEPENDENCY_FAILURE,
)
return tuple(by_id[input_id] for input_id in announcement.required_input_ids)
@staticmethod
def _work_product_id(
announcement: TaskAnnouncement,
award: TaskAward,
) -> str:
material = (
f"{announcement.auction_id}|{announcement.task_id}|"
f"{announcement.auction_round}|{award.awarded_agent_id}"
)
digest = sha256(material.encode("utf-8")).hexdigest()[:20]
return f"work:{digest}"
def default_handlers() -> dict[str, TaskHandler]:
"""Return the five deterministic synthetic due-diligence handlers."""
return {
"market_research": _market_research_handler,
"financial_analysis": _financial_analysis_handler,
"operating_risk": _operating_risk_handler,
"evidence_verification": _evidence_verification_handler,
"executive_synthesis": _executive_synthesis_handler,
}
def _market_research_handler(context: ExecutionContext) -> HandlerOutput:
return HandlerOutput(
title="Synthetic Market Attractiveness Review",
summary=(
"Meridian Industrial Systems operates in a fictional niche with stable end-market "
"demand, fragmented competition, and moderate customer switching friction."
),
findings=(
"Fictional end-market demand is stable rather than hyper-growth dependent.",
"Competition is fragmented enough to support differentiated positioning.",
"Customer switching friction appears moderate and supports recurring relationships.",
),
evidence_ids=("evidence.market.1", "evidence.market.2", "evidence.market.3"),
)
def _financial_analysis_handler(context: ExecutionContext) -> HandlerOutput:
return HandlerOutput(
title="Synthetic Financial Quality Review",
summary=(
"The fictional target shows recurring revenue characteristics, positive cash "
"conversion, and margins that are healthy but sensitive to integration execution."
),
findings=(
"Synthetic recurring revenue quality is stronger than one-time project revenue.",
"Synthetic free-cash conversion remains positive across the reviewed period.",
"Margin durability depends on maintaining procurement and labor discipline.",
),
evidence_ids=("evidence.finance.1", "evidence.finance.2", "evidence.finance.3"),
)
def _operating_risk_handler(context: ExecutionContext) -> HandlerOutput:
return HandlerOutput(
title="Synthetic Operating Risk Review",
summary=(
"The principal fictional execution risks are supplier concentration, integration "
"complexity, and dependence on a small group of experienced operators."
),
findings=(
"Supplier concentration creates a bounded but material continuity risk.",
"Integration complexity could temporarily pressure service quality and margins.",
"Key-person dependence should be reduced before aggressive post-close scaling.",
),
evidence_ids=("evidence.risk.1", "evidence.risk.2", "evidence.risk.3"),
)
def _evidence_verification_handler(context: ExecutionContext) -> HandlerOutput:
return HandlerOutput(
title="Synthetic Evidence Verification Review",
summary=(
"The synthetic diligence evidence is internally consistent enough for continued "
"review, while several claims still warrant explicit confirmation before a final bid."
),
findings=(
"Key synthetic claims have at least one corroborating evidence record.",
"No material contradiction is present in the synthetic evidence set.",
"Open verification items should remain visible rather than being silently resolved.",
),
evidence_ids=("evidence.verify.1", "evidence.verify.2", "evidence.verify.3"),
)
def _executive_synthesis_handler(context: ExecutionContext) -> HandlerOutput:
upstream_count = len(context.required_inputs)
upstream_titles = tuple(product.title for product in context.required_inputs)
integrated_note = (
f"Integrated {upstream_count} validated upstream work products."
if upstream_count
else "No upstream work products were required for this synthetic execution."
)
title_note = (
f" Reviewed inputs: {', '.join(upstream_titles)}."
if upstream_titles
else ""
)
return HandlerOutput(
title="Synthetic Executive Due-Diligence Synthesis",
summary=(
"The fictional acquisition case supports continued diligence rather than an "
f"unconditional proceed decision. {integrated_note}{title_note}"
),
findings=(
"Market and financial characteristics support continued diligence.",
"Operating and evidence risks remain decision-relevant and should stay explicit.",
"The synthetic recommendation is to proceed only to the next diligence stage.",
),
evidence_ids=("evidence.synthesis.1", "evidence.synthesis.2"),
)
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