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feat(engine): 添加运行时上下文支持并重构工具迭代限制

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添加 RuntimeContext 类用于捕获模型运行时的日期时间信息，
包括UTC时间、本地时间和时区信息，并在系统提示中显示这些信息。

同时增加最大上下文消息数和工具迭代次数的配置选项，
将验证服务从引擎加载器中移除，并更新相关的数据结构和接口。

BREAKING CHANGE: 移除了验证服务，相关字段被替换为证据状态和接受状态。

- 添加 RuntimeContext 类和相关渲染方法
- 增加 max_context_messages 和 max_tool_iterations 配置
- 移除 ValidationService 相关代码
- 更新消息记录中的验证状态字段
- 添加原始工具调用检测和回退处理
This commit is contained in:
steven_li
2026-05-26 11:18:35 +08:00
parent 16347caf5e
commit 6e9e74d1ee
57 changed files with 5710 additions and 1582 deletions
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536
app-instance/backend/beaver/services/agent_service.py
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@ -29,9 +29,9 @@ from beaver.tasks import (
TaskEvidencePacket,
TaskExecutionPlan,
TaskRecord,
ValidationResult,
render_task_evidence,
)
from beaver.tasks.service import normalize_acceptance_type
NOTIFICATION_SESSION_ID = "notify:default:scheduled"
@ -60,11 +60,19 @@ class AgentService:
) -> None:
self.profile = profile or AgentProfile()
self.loader = loader or EngineLoader(workspace=workspace, config_path=config_path)
self._apply_configured_profile_defaults()
self._loop: AgentLoop | None = None
self._run_task: asyncio.Task[None] | None = None
self._main_agent_router = MainAgentRouter()
self._runtime_services: dict[str, Any] = {}
def _apply_configured_profile_defaults(self) -> None:
defaults = self.loader.config.agents_defaults
if defaults.max_context_messages is not None:
self.profile.max_context_messages = max(1, defaults.max_context_messages)
if defaults.max_tool_iterations is not None:
self.profile.max_tool_iterations = max(0, defaults.max_tool_iterations)
def create_loop(self) -> AgentLoop:
"""创建并缓存当前 service 使用的 AgentLoop。"""
@ -232,7 +240,7 @@ class AgentService:
Scheduled jobs are product-level Tasks, not hidden one-off agent turns.
This entry bypasses the main-agent classifier and forces Task mode so
every trigger produces a TaskRecord, validation, feedback state, and a
every trigger produces a TaskRecord, evidence, acceptance state, and a
run_id that the scheduled-task history can link to.
"""
@ -280,9 +288,9 @@ class AgentService:
result.run_id,
{
"message_type": "scheduled_reply",
"scheduled_job_id": job.id,
"scheduled_run_id": run.scheduled_run_id,
"cron_job_name": job.name,
"scheduled_job_id": cron_job_id,
"scheduled_run_id": scheduled_run_id,
"cron_job_name": cron_job_name,
"mode": "notification",
},
)
@ -403,15 +411,15 @@ class AgentService:
},
)
async def submit_feedback(
async def submit_acceptance(
self,
*,
session_id: str,
run_id: str,
feedback_type: str,
acceptance_type: str,
comment: str | None = None,
) -> dict[str, Any]:
"""Record chat feedback for the internal task linked to a run."""
"""Record user acceptance for the internal task linked to a run."""
loaded = self.create_loop().boot()
task_service = self._require_loaded(loaded, "task_service")
@ -419,32 +427,31 @@ class AgentService:
if task is None or task.session_id != session_id:
raise ValueError(f"No internal task found for run_id={run_id!r}")
normalized = feedback_type.strip().lower()
if normalized not in {"satisfied", "revise", "abandon"}:
raise ValueError("feedback_type must be one of: satisfied, revise, abandon")
normalized = normalize_acceptance_type(acceptance_type)
legacy_feedback_type = "satisfied" if normalized == "accept" else normalized
already_recorded = any(
item.get("run_id") == run_id and item.get("feedback_type") == normalized
item.get("run_id") == run_id and item.get("acceptance_type") == normalized
for item in task.feedback
)
conflicting_feedback = next(
conflicting_acceptance = next(
(
item
for item in task.feedback
if item.get("run_id") == run_id and item.get("feedback_type") != normalized
if item.get("run_id") == run_id and item.get("acceptance_type") != normalized
),
None,
)
if conflicting_feedback is not None:
if conflicting_acceptance is not None:
raise ValueError(
f"Feedback for run_id={run_id!r} was already recorded as "
f"{conflicting_feedback.get('feedback_type')!r}"
f"Acceptance for run_id={run_id!r} was already recorded as "
f"{conflicting_acceptance.get('acceptance_type')!r}"
)
if task.status in {"closed", "abandoned"} and not already_recorded:
raise ValueError(f"Task {task.task_id} is already finalized as {task.status!r}")
updated = task if already_recorded else task_service.add_feedback(
updated = task if already_recorded else task_service.add_acceptance(
task.task_id,
feedback_type=normalized,
acceptance_type=normalized,
comment=comment,
run_id=run_id,
)
@ -455,7 +462,8 @@ class AgentService:
{
"task_id": updated.task_id,
"task_status": updated.status,
"feedback_state": normalized,
"acceptance_state": normalized,
"feedback_state": legacy_feedback_type,
},
)
if not already_recorded:
@ -463,10 +471,11 @@ class AgentService:
session_id,
run_id=run_id,
role="system",
event_type="task_feedback_recorded",
event_type="task_acceptance_recorded",
event_payload={
"task_id": task.task_id,
"feedback_type": normalized,
"acceptance_type": normalized,
"feedback_type": legacy_feedback_type,
"comment": comment,
"task_status": updated.status,
},
@ -475,35 +484,36 @@ class AgentService:
)
generated_candidates = []
validation = ValidationResult.from_dict(updated.validation_result)
if not already_recorded:
run_memory_store = self._require_loaded(loaded, "run_memory_store")
feedback_payload = {
"feedback_type": normalized,
acceptance_payload = {
"acceptance_type": normalized,
"feedback_type": legacy_feedback_type,
"comment": comment or "",
"task_status": updated.status,
"final_accepted_run_id": updated.metadata.get("final_accepted_run_id"),
}
run_memory_store.update_run_record(
run_id,
success=normalized == "satisfied",
feedback=feedback_payload,
success=normalized == "accept",
feedback=acceptance_payload,
)
run_memory_store.update_skill_effects_for_run(
run_id,
success=normalized == "satisfied",
feedback_score=self._feedback_score_for_learning(normalized, validation),
success=normalized == "accept",
feedback_score=self._acceptance_score_for_learning(normalized),
notes=(comment or normalized).strip(),
)
skill_learning_service = self._require_loaded(loaded, "skill_learning_service")
skill_learning_service.rescore_skill_versions()
if already_recorded:
generated_candidates = []
elif normalized == "satisfied" and validation is not None and validation.accepted:
elif normalized == "accept":
generated_candidates = [
item.to_dict()
for item in skill_learning_service.build_learning_candidates_for_task(
updated.task_id,
trigger_run_id=run_id,
final_accepted_run_id=run_id,
)
]
elif normalized == "abandon":
@ -514,7 +524,8 @@ class AgentService:
event_type="task_failure_evidence_recorded",
event_payload={
"task_id": updated.task_id,
"feedback_type": normalized,
"acceptance_type": normalized,
"feedback_type": legacy_feedback_type,
"comment": comment or "",
"task_status": updated.status,
"durable_memory_written": False,
@ -528,10 +539,28 @@ class AgentService:
"run_id": run_id,
"task_id": updated.task_id,
"task_status": updated.status,
"feedback_type": normalized,
"acceptance_type": normalized,
"feedback_type": legacy_feedback_type,
"learning_candidates": generated_candidates,
}
async def submit_feedback(
self,
*,
session_id: str,
run_id: str,
feedback_type: str,
comment: str | None = None,
) -> dict[str, Any]:
"""Backward-compatible wrapper for older clients."""
return await self.submit_acceptance(
session_id=session_id,
run_id=run_id,
acceptance_type=feedback_type,
comment=comment,
)
async def _process_with_main_agent(
self,
message: str,
@ -591,7 +620,7 @@ class AgentService:
else active_task
)
if active_task is not None and decision.action == "revise_task" and task.task_id == active_task.task_id:
task = self._record_revision_feedback_for_task(
task = self._record_revision_acceptance_for_task(
loaded,
task=task,
session_id=session_id,
@ -599,7 +628,7 @@ class AgentService:
)
return await self._run_task_mode(message, runner=runner, kwargs=kwargs, task=task)
def _record_revision_feedback_for_task(
def _record_revision_acceptance_for_task(
self,
loaded: Any,
*,
@ -607,9 +636,9 @@ class AgentService:
session_id: str,
comment: str,
) -> TaskRecord:
"""Mark the latest feedback-eligible run as revised before continuing a task."""
"""Mark the latest acceptance-eligible run as revised before continuing a task."""
if task.status not in {"awaiting_feedback", "needs_revision"}:
if task.status not in {"awaiting_acceptance", "needs_revision"}:
return task
run_id = next((item for item in reversed(task.run_ids) if item), None)
if not run_id:
@ -617,15 +646,15 @@ class AgentService:
existing = next((item for item in task.feedback if item.get("run_id") == run_id), None)
if existing is not None:
if existing.get("feedback_type") != "revise":
if existing.get("acceptance_type") != "revise":
return task
updated = task
already_recorded = True
else:
task_service = self._require_loaded(loaded, "task_service")
updated = task_service.add_feedback(
updated = task_service.add_acceptance(
task.task_id,
feedback_type="revise",
acceptance_type="revise",
comment=comment,
run_id=run_id,
)
@ -638,6 +667,7 @@ class AgentService:
{
"task_id": updated.task_id,
"task_status": updated.status,
"acceptance_state": "revise",
"feedback_state": "revise",
},
)
@ -648,9 +678,10 @@ class AgentService:
session_id,
run_id=run_id,
role="system",
event_type="task_feedback_recorded",
event_type="task_acceptance_recorded",
event_payload={
"task_id": updated.task_id,
"acceptance_type": "revise",
"feedback_type": "revise",
"comment": comment,
"task_status": updated.status,
@ -659,12 +690,12 @@ class AgentService:
content=comment,
context_visible=False,
)
validation = ValidationResult.from_dict(updated.validation_result)
run_memory_store = self._require_loaded(loaded, "run_memory_store")
run_memory_store.update_run_record(
run_id,
success=False,
feedback={
"acceptance_type": "revise",
"feedback_type": "revise",
"comment": comment,
"task_status": updated.status,
@ -673,7 +704,7 @@ class AgentService:
run_memory_store.update_skill_effects_for_run(
run_id,
success=False,
feedback_score=self._feedback_score_for_learning("revise", validation),
feedback_score=self._acceptance_score_for_learning("revise"),
notes=comment.strip() or "revise",
)
skill_learning_service = self._require_loaded(loaded, "skill_learning_service")
@ -690,236 +721,185 @@ class AgentService:
) -> AgentRunResult:
loaded = self.create_loop().boot()
task_service = self._require_loaded(loaded, "task_service")
validation_service = self._require_loaded(loaded, "validation_service")
task_execution_planner = self._require_loaded(loaded, "task_execution_planner")
session_manager = self._require_loaded(loaded, "session_manager")
run_memory_store = self._require_loaded(loaded, "run_memory_store")
last_result: AgentRunResult | None = None
latest_validation: ValidationResult | None = None
base_execution_context = kwargs.get("execution_context")
provider_bundle = kwargs.get("provider_bundle") or self._make_provider_bundle_for_task(loaded, kwargs)
kwargs = dict(kwargs)
team_provider_bundle_factory = kwargs.pop("team_provider_bundle_factory", None)
kwargs["provider_bundle"] = provider_bundle
for attempt_index in (1, 2):
task_service.start_run(task.task_id, user_message=message, attempt_index=attempt_index)
plan = await task_execution_planner.plan(
attempt_index = int(task.metadata.get("latest_attempt_index") or 0) + 1
task_service.start_run(task.task_id, user_message=message, attempt_index=attempt_index)
plan = await task_execution_planner.plan(
task=task,
user_message=message,
attempt_index=attempt_index,
provider_bundle=provider_bundle,
)
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_execution_planned",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
**plan.to_event_payload(),
},
)
team_summaries: list[str] = []
team_execution_context = ""
team_result: TeamRunResult | None = None
if plan.is_team:
team_result, team_error = await self._run_team_for_task(
plan,
task=task,
user_message=message,
attempt_index=attempt_index,
latest_validation=latest_validation,
provider_bundle=provider_bundle,
parent_session_id=kwargs["session_id"],
provider_bundle_factory=team_provider_bundle_factory
or self._build_team_provider_bundle_factory(loaded, kwargs),
)
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_execution_planned",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
**plan.to_event_payload(),
},
)
team_summaries: list[str] = []
team_execution_context = ""
team_result: TeamRunResult | None = None
if plan.is_team:
team_result, team_error = await self._run_team_for_task(
plan,
task=task,
parent_session_id=kwargs["session_id"],
provider_bundle_factory=team_provider_bundle_factory
or self._build_team_provider_bundle_factory(loaded, kwargs),
if team_result is not None:
team_summaries = [self._team_summary_for_validation(team_result)]
team_packet = TaskEvidencePacket(
task_id=task.task_id,
attempt_index=attempt_index,
main_run=None,
team_runs=self._team_run_evidence(team_result),
team_node_results=list(team_result.node_results),
final_output="",
)
team_execution_context = self._join_context(
self._team_execution_context(plan, team_result),
"Rendered team evidence:\n" + render_task_evidence(team_packet),
)
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_team_run_completed" if team_result.success else "task_team_run_failed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
"node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
"team_run_ids": team_result.run_ids,
"team_success": team_result.success,
"node_results": self._team_node_results_for_event(plan, team_result),
"reason": plan.reason,
"error": None if team_result.success else "one or more team nodes failed",
},
)
else:
team_summaries = [f"Team execution failed: {team_error}"]
team_execution_context = self._failed_team_execution_context(plan, team_error or "unknown error")
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_team_run_failed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
"node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
"team_run_ids": [],
"team_success": False,
"reason": plan.reason,
"error": team_error,
},
)
if team_result is not None:
team_summaries = [self._team_summary_for_validation(team_result)]
team_packet = TaskEvidencePacket(
task_id=task.task_id,
attempt_index=attempt_index,
main_run=None,
team_runs=self._team_run_evidence(team_result),
team_node_results=list(team_result.node_results),
final_output="",
)
team_execution_context = self._join_context(
self._team_execution_context(plan, team_result),
"Rendered team evidence:\n" + render_task_evidence(team_packet),
)
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_team_run_completed" if team_result.success else "task_team_run_failed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
"node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
"team_run_ids": team_result.run_ids,
"team_success": team_result.success,
"node_results": self._team_node_results_for_event(plan, team_result),
"reason": plan.reason,
"error": None if team_result.success else "one or more team nodes failed",
},
)
else:
team_summaries = [f"Team execution failed: {team_error}"]
team_execution_context = self._failed_team_execution_context(plan, team_error or "unknown error")
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_team_run_failed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
"node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
"team_run_ids": [],
"team_success": False,
"reason": plan.reason,
"error": team_error,
},
)
attempt_kwargs = dict(kwargs)
attempt_kwargs.update(
{
"task_id": task.task_id,
"task_mode": True,
"attempt_index": attempt_index,
"allow_candidate_generation": False,
}
)
if attempt_index == 2 and latest_validation is not None:
revision_context = latest_validation.recommended_revision_prompt.strip()
if revision_context:
attempt_kwargs["execution_context"] = self._join_context(
base_execution_context,
f"Task validation revision request:\n{revision_context}",
team_execution_context,
)
elif team_execution_context:
attempt_kwargs["execution_context"] = self._join_context(base_execution_context, team_execution_context)
if plan.is_team and team_execution_context:
attempt_kwargs["include_tools"] = False
attempt_kwargs["max_tool_iterations"] = 0
attempt_kwargs["skill_selection_context"] = self._build_skill_selection_context(
task=task,
user_message=message,
attempt_index=attempt_index,
latest_validation=latest_validation,
plan=plan,
team_summaries=team_summaries,
)
result = await runner(message, **attempt_kwargs)
last_result = result
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_synthesis_completed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"main_run_id": result.run_id,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
},
)
task = task_service.append_run(
task.task_id,
result.run_id,
skill_names=self._skill_names_for_run(loaded, result.run_id),
)
evidence_packet = self._build_task_evidence_packet(
session_manager=session_manager,
task=task,
attempt_index=attempt_index,
result=result,
team_result=team_result,
)
evidence_text = render_task_evidence(evidence_packet)
validation = await validation_service.validate_task_result(
task=task,
user_message=message,
final_output=result.output_text,
evidence_packet=evidence_packet,
evidence_text=evidence_text,
transcript_excerpt=self._run_excerpt(session_manager, result.session_id, result.run_id),
tool_summaries=self._tool_summaries(session_manager, result.session_id, result.run_id),
team_summaries=team_summaries,
provider_bundle=provider_bundle,
)
latest_validation = validation
has_usable_answer = bool(result.output_text.strip()) and (
"Tool loop stopped after reaching the configured iteration limit." not in result.output_text
)
task = task_service.record_validation(
task.task_id,
result.run_id,
validation,
final_attempt=(
attempt_index == 2
or validation.status in {"accepted", "insufficient_evidence", "validator_error"}
),
has_usable_answer=has_usable_answer,
)
run_memory_store.update_run_record(result.run_id, validation_result=validation.to_dict())
session_manager.update_latest_assistant_event_payload(
result.session_id,
result.run_id,
{
"task_id": task.task_id,
"task_status": task.status,
"validation_status": "passed" if validation.accepted else "failed",
},
)
validation_debug = {
"evidence_run_ids": [
item.run_id for item in [evidence_packet.main_run, *evidence_packet.team_runs] if item is not None
],
"evidence_session_ids": [
item.session_id
for item in [evidence_packet.main_run, *evidence_packet.team_runs]
if item is not None
],
"tool_result_count": sum(
len(item.tool_results)
for item in [evidence_packet.main_run, *evidence_packet.team_runs]
if item is not None
),
"evidence_length": len(evidence_text),
attempt_kwargs = dict(kwargs)
attempt_kwargs.update(
{
"task_id": task.task_id,
"task_mode": True,
"attempt_index": attempt_index,
"allow_candidate_generation": False,
}
retry_scheduled = validation.status == "rejected" and attempt_index == 1
session_manager.append_message(
result.session_id,
run_id=result.run_id,
role="system",
event_type="task_validation_snapshotted",
event_payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"validation_result": validation.to_dict(),
"validation_debug": validation_debug,
"retry_scheduled": retry_scheduled,
},
content=validation.recommended_revision_prompt or None,
context_visible=False,
)
if retry_scheduled:
session_manager.set_run_context_visible(result.session_id, result.run_id, False)
result.task_id = task.task_id
result.task_status = task.status
result.validation_result = validation.to_dict()
if not retry_scheduled:
return result
)
if team_execution_context:
attempt_kwargs["execution_context"] = self._join_context(base_execution_context, team_execution_context)
if plan.is_team and team_execution_context:
attempt_kwargs["include_tools"] = False
attempt_kwargs["max_tool_iterations"] = 0
attempt_kwargs["skill_selection_context"] = self._build_skill_selection_context(
task=task,
user_message=message,
attempt_index=attempt_index,
plan=plan,
team_summaries=team_summaries,
)
if last_result is None: # pragma: no cover - defensive
raise RuntimeError("Task mode did not produce a run result")
return last_result
result = await runner(message, **attempt_kwargs)
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_synthesis_completed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"main_run_id": result.run_id,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
},
)
task = task_service.append_run(
task.task_id,
result.run_id,
skill_names=self._skill_names_for_run(loaded, result.run_id),
)
evidence_packet = self._build_task_evidence_packet(
session_manager=session_manager,
task=task,
attempt_index=attempt_index,
result=result,
team_result=team_result,
)
evidence_text = render_task_evidence(evidence_packet)
evidence_debug = {
"evidence_run_ids": [
item.run_id for item in [evidence_packet.main_run, *evidence_packet.team_runs] if item is not None
],
"evidence_session_ids": [
item.session_id
for item in [evidence_packet.main_run, *evidence_packet.team_runs]
if item is not None
],
"tool_result_count": sum(
len(item.tool_results)
for item in [evidence_packet.main_run, *evidence_packet.team_runs]
if item is not None
),
"evidence_length": len(evidence_text),
}
session_manager.update_latest_assistant_event_payload(
result.session_id,
result.run_id,
{
"task_id": task.task_id,
"task_status": task.status,
"evidence_status": "recorded",
},
)
session_manager.append_message(
result.session_id,
run_id=result.run_id,
role="system",
event_type="task_evidence_recorded",
event_payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"evidence_debug": evidence_debug,
},
content=None,
context_visible=False,
)
result.task_id = task.task_id
result.task_status = task.status
result.validation_result = None
return result
async def _run_team_for_task(
self,
@ -986,12 +966,10 @@ class AgentService:
return []
@staticmethod
def _feedback_score_for_learning(feedback_type: str, validation: ValidationResult | None) -> float:
if feedback_type == "satisfied":
if validation is not None:
return max(0.0, min(1.0, float(validation.score)))
def _acceptance_score_for_learning(acceptance_type: str) -> float:
if acceptance_type == "accept":
return 1.0
if feedback_type == "revise":
if acceptance_type == "revise":
return 0.5
return 0.0
@ -1001,12 +979,11 @@ class AgentService:
task: TaskRecord,
user_message: str,
attempt_index: int,
latest_validation: ValidationResult | None = None,
plan: TaskExecutionPlan | None = None,
team_summaries: list[str] | None = None,
) -> str:
phase = f"attempt_{attempt_index}"
if latest_validation is not None:
if task.feedback and task.feedback[-1].get("acceptance_type") == "revise":
phase = f"revision_attempt_{attempt_index}"
elif plan is not None and plan.is_team:
phase = f"team_synthesis_attempt_{attempt_index}"
@ -1027,24 +1004,14 @@ class AgentService:
)
else:
sections.append("Previously activated skills:\nNone")
if latest_validation is not None:
validation_lines = [
f"accepted: {latest_validation.accepted}",
f"score: {latest_validation.score}",
]
if latest_validation.issues:
validation_lines.append("issues:\n" + "\n".join(f"- {item}" for item in latest_validation.issues))
if latest_validation.missing_requirements:
validation_lines.append(
"missing requirements:\n"
+ "\n".join(f"- {item}" for item in latest_validation.missing_requirements)
)
if latest_validation.recommended_revision_prompt:
validation_lines.append(
"recommended revision:\n"
+ latest_validation.recommended_revision_prompt
)
sections.append("Validation feedback:\n" + "\n".join(validation_lines))
if task.feedback:
history_lines = []
for item in task.feedback[-5:]:
kind = item.get("acceptance_type") or item.get("feedback_type")
comment = item.get("comment") or ""
run_id = item.get("run_id") or ""
history_lines.append(f"- {kind} run={run_id}: {comment}".strip())
sections.append("Task acceptance history:\n" + "\n".join(history_lines))
if plan is not None:
plan_lines = [
f"mode: {plan.mode}",
@ -1313,7 +1280,8 @@ class AgentService:
"inbound_metadata": dict(inbound.metadata),
"task_id": getattr(result, "task_id", None),
"task_status": getattr(result, "task_status", None),
"validation_result": getattr(result, "validation_result", None),
"evidence_status": "recorded" if getattr(result, "task_id", None) else None,
"validation_result": None,
},
)