from __future__ import annotations from dataclasses import dataclass from datetime import UTC, datetime from time import perf_counter from typing import Any from sqlalchemy import func, select from sqlalchemy.orm import Session from app.core.agent_enums import ( AgentAssetStatus, AgentAssetType, AgentName, AgentPermissionLevel, AgentRunSource, AgentRunStatus, AgentToolType, ) from app.core.logging import get_logger from app.models.financial_record import ( AccountsPayableRecord, AccountsReceivableRecord, ExpenseClaim, ) from app.schemas.agent_asset import AgentAssetListItem, AgentAssetRead from app.schemas.ontology import OntologyParseRequest, OntologyParseResult from app.schemas.orchestrator import ( OrchestratorRequest, OrchestratorResponse, OrchestratorTraceSummary, ) from app.schemas.user_agent import UserAgentRequest, UserAgentResponse from app.services.agent_assets import AgentAssetService from app.services.agent_conversations import AgentConversationService from app.services.expense_claims import ExpenseClaimService from app.services.agent_foundation import AgentFoundationService from app.services.agent_runs import AgentRunService from app.services.ontology import SemanticOntologyService from app.services.user_agent import UserAgentService logger = get_logger("app.services.orchestrator") SCENARIO_TO_DOMAIN = { "expense": "expense", "accounts_receivable": "ar", "accounts_payable": "ap", "knowledge": "knowledge", "unknown": "system", } @dataclass(slots=True) class ExecutionOutcome: status: str result: dict[str, Any] degraded: bool tool_count: int failed_tool_count: int class OrchestratorService: def __init__(self, db: Session) -> None: self.db = db self.asset_service = AgentAssetService(db) self.conversation_service = AgentConversationService(db) self.expense_claim_service = ExpenseClaimService(db) self.run_service = AgentRunService(db) self.ontology_service = SemanticOntologyService(db) self.user_agent_service = UserAgentService(db) def run(self, payload: OrchestratorRequest) -> OrchestratorResponse: AgentFoundationService(self.db).ensure_foundation_ready() context_json = dict(payload.context_json or {}) conversation_id = str(payload.conversation_id or "").strip() or None conversation = None if payload.source == AgentRunSource.USER_MESSAGE.value: conversation = self.conversation_service.get_or_create_conversation( conversation_id=conversation_id, user_id=payload.user_id, source=payload.source, context_json=context_json, ) conversation_id = conversation.conversation_id context_json = self.conversation_service.hydrate_context_json( conversation=conversation, context_json=context_json, ) route_json: dict[str, Any] = { "orchestrated_by": AgentName.ORCHESTRATOR.value, "stage": "created", } if conversation_id: route_json["conversation_id"] = conversation_id run = self.run_service.create_run( agent=AgentName.ORCHESTRATOR.value, source=payload.source, user_id=payload.user_id, task_id=payload.task_id, ontology_json={}, route_json=route_json, permission_level=AgentPermissionLevel.READ.value, status=AgentRunStatus.RUNNING.value, result_summary="Orchestrator 已接收请求。", ) try: message, task_asset = self._resolve_message(payload) if conversation is not None: self.conversation_service.append_message( conversation_id=conversation.conversation_id, role="user", content=message, run_id=run.run_id, message_json={ "attachment_names": context_json.get("attachment_names", []), "attachment_count": context_json.get("attachment_count", 0), "ocr_summary": context_json.get("ocr_summary", ""), }, ) ontology = self.ontology_service.parse_for_run( OntologyParseRequest( query=message, user_id=payload.user_id, context_json=context_json, ), run_id=run.run_id, ) if context_json.get("simulate_orchestrator_exception"): raise RuntimeError("simulated orchestrator exception") selected_agent, route_reason = self._select_agent(payload, ontology) capabilities = self._select_capabilities( payload=payload, ontology=ontology, task_asset=task_asset, ) selected_capability_codes = self._flatten_capability_codes(capabilities) requires_confirmation = ( ontology.permission.level == AgentPermissionLevel.APPROVAL_REQUIRED.value ) route_json = { "orchestrated_by": AgentName.ORCHESTRATOR.value, "stage": "routed", "selected_agent": selected_agent, "route_reason": route_reason, "selected_capability_codes": selected_capability_codes, "ontology_run_id": ontology.run_id, } if ontology.permission.level == AgentPermissionLevel.FORBIDDEN.value: outcome = ExecutionOutcome( status=AgentRunStatus.BLOCKED.value, result={ "message": ontology.permission.reason, "clarification_question": ontology.clarification_question, "degraded": False, }, degraded=False, tool_count=0, failed_tool_count=0, ) selected_agent = None route_reason = "permission_forbidden" route_json["stage"] = "blocked" route_json["route_reason"] = route_reason elif ontology.clarification_required: if selected_agent == AgentName.USER_AGENT.value and ontology.scenario == "expense": clarification_response = self.user_agent_service.respond( UserAgentRequest( run_id=run.run_id, user_id=payload.user_id, message=payload.message or "", ontology=ontology, context_json=context_json, tool_payload={"clarification_required": True}, selected_capability_codes=selected_capability_codes, degraded=False, requires_confirmation=requires_confirmation, ) ) clarification_result = self._build_user_agent_result( clarification_response, degraded=False, ) clarification_result.update( { "clarification_required": True, "missing_slots": ontology.missing_slots, "ambiguity": ontology.ambiguity, "parse_strategy": ontology.parse_strategy, } ) outcome = ExecutionOutcome( status=AgentRunStatus.BLOCKED.value, result=clarification_result, degraded=False, tool_count=0, failed_tool_count=0, ) else: outcome = ExecutionOutcome( status=AgentRunStatus.BLOCKED.value, result={ "message": ontology.clarification_question or "需要补充更多上下文。", "clarification_required": True, "missing_slots": ontology.missing_slots, "ambiguity": ontology.ambiguity, "parse_strategy": ontology.parse_strategy, "degraded": False, }, degraded=False, tool_count=0, failed_tool_count=0, ) route_reason = "clarification_required" route_json["stage"] = "clarification" route_json["route_reason"] = route_reason elif selected_agent == AgentName.HERMES.value: outcome = self._execute_hermes( payload=payload, run_id=run.run_id, ontology=ontology, capabilities=capabilities, requires_confirmation=requires_confirmation, task_asset=task_asset, context_json=context_json, ) else: outcome = self._execute_user_agent( payload=payload, run_id=run.run_id, ontology=ontology, capabilities=capabilities, requires_confirmation=requires_confirmation, context_json=context_json, ) final_status = ( AgentRunStatus.BLOCKED.value if requires_confirmation and outcome.status == AgentRunStatus.SUCCEEDED.value and ontology.permission.level == AgentPermissionLevel.APPROVAL_REQUIRED.value else outcome.status ) response_status = self._normalize_response_status(final_status) result_message = ( str(outcome.result.get("message", "")).strip() or "Orchestrator 执行完成。" ) trace_summary = OrchestratorTraceSummary( scenario=ontology.scenario, intent=ontology.intent, tool_count=outcome.tool_count, failed_tool_count=outcome.failed_tool_count, selected_capability_codes=selected_capability_codes, degraded=outcome.degraded, ) self.run_service.update_run( run.run_id, agent=selected_agent or AgentName.ORCHESTRATOR.value, ontology_json=self._build_ontology_json(ontology), route_json={ **route_json, "requires_confirmation": requires_confirmation, "degraded": outcome.degraded, }, permission_level=ontology.permission.level, status=final_status, result_summary=result_message, error_message=None, finished_at=datetime.now(UTC), ) if conversation is not None and conversation_id: draft_payload = outcome.result.get("draft_payload") self.conversation_service.update_state( conversation_id=conversation_id, run_id=run.run_id, scenario=ontology.scenario, intent=ontology.intent, context_json=context_json, draft_payload=draft_payload if isinstance(draft_payload, dict) else None, ) self.conversation_service.append_message( conversation_id=conversation_id, role="assistant", content=result_message, run_id=run.run_id, message_json={ "status": final_status, "scenario": ontology.scenario, "intent": ontology.intent, "attachment_names": context_json.get("attachment_names", []), "attachment_count": context_json.get("attachment_count", 0), "draft_payload": draft_payload if isinstance(draft_payload, dict) else None, "orchestrator_payload": { "run_id": run.run_id, "conversation_id": conversation_id, "selected_agent": selected_agent, "route_reason": route_reason, "permission_level": ontology.permission.level, "status": response_status, "requires_confirmation": requires_confirmation, "trace_summary": trace_summary.model_dump(), "result": outcome.result, }, }, ) return OrchestratorResponse( run_id=run.run_id, conversation_id=conversation_id, selected_agent=selected_agent, route_reason=route_reason, permission_level=ontology.permission.level, status=response_status, result=outcome.result, requires_confirmation=requires_confirmation, trace_summary=trace_summary, ) except Exception as exc: logger.exception("Orchestrator run failed run_id=%s", run.run_id) self.run_service.update_run( run.run_id, agent=AgentName.ORCHESTRATOR.value, route_json={**route_json, "stage": "failed"}, status=AgentRunStatus.FAILED.value, result_summary="Orchestrator 执行失败。", error_message=str(exc), finished_at=datetime.now(UTC), ) if conversation is not None and conversation_id: self.conversation_service.update_state( conversation_id=conversation_id, run_id=run.run_id, scenario=None, intent=None, context_json=context_json, draft_payload=None, ) self.conversation_service.append_message( conversation_id=conversation_id, role="assistant", content=f"Orchestrator 执行失败：{exc}", run_id=run.run_id, message_json={"status": AgentRunStatus.FAILED.value}, ) return OrchestratorResponse( run_id=run.run_id, conversation_id=conversation_id, selected_agent=None, route_reason="orchestrator_exception", permission_level=AgentPermissionLevel.READ.value, status="failed", result={"message": f"Orchestrator 执行失败：{exc}"}, requires_confirmation=False, trace_summary=OrchestratorTraceSummary( scenario="unknown", intent="query", tool_count=0, failed_tool_count=0, selected_capability_codes=[], degraded=False, ), ) def _resolve_message( self, payload: OrchestratorRequest, ) -> tuple[str, AgentAssetRead | None]: task_asset = None if payload.task_id: task_asset = self.asset_service.get_asset(payload.task_id) if payload.message and payload.message.strip(): return payload.message.strip(), task_asset if task_asset is not None: description = str(task_asset.description or "").strip() scenario_text = " ".join(str(item) for item in task_asset.scenario_json) message = f"{task_asset.name} {description} {scenario_text}".strip() return message, task_asset if payload.source == AgentRunSource.SCHEDULE.value: return "定时风险巡检任务", task_asset raise ValueError("message 或 task_id 至少需要提供一个。") @staticmethod def _select_agent( payload: OrchestratorRequest, ontology: OntologyParseResult, ) -> tuple[str, str]: if payload.source == AgentRunSource.SCHEDULE.value: return AgentName.HERMES.value, "schedule_source_defaults_to_hermes" if payload.source == AgentRunSource.SYSTEM_EVENT.value and ontology.intent == "risk_check": return AgentName.HERMES.value, "system_event_risk_check_routes_to_hermes" if ontology.intent == "risk_check" and payload.source == AgentRunSource.SCHEDULE.value: return AgentName.HERMES.value, "scheduled_risk_check_routes_to_hermes" if ontology.intent in {"query", "explain", "draft", "compare", "operate"}: return AgentName.USER_AGENT.value, f"{ontology.intent}_routes_to_user_agent" return AgentName.USER_AGENT.value, "user_message_defaults_to_user_agent" def _select_capabilities( self, *, payload: OrchestratorRequest, ontology: OntologyParseResult, task_asset: AgentAssetRead | None, ) -> dict[str, list[AgentAssetListItem | AgentAssetRead]]: domain_value = SCENARIO_TO_DOMAIN.get(ontology.scenario) rules = self._rank_assets( self.asset_service.list_assets( asset_type=AgentAssetType.RULE.value, status=AgentAssetStatus.ACTIVE.value, domain=domain_value if domain_value not in {"knowledge", "system"} else None, ), ontology, ) skills = self._rank_assets( self.asset_service.list_assets( asset_type=AgentAssetType.SKILL.value, status=AgentAssetStatus.ACTIVE.value, domain=domain_value if domain_value not in {"system"} else None, ), ontology, ) mcps = self._rank_assets( self.asset_service.list_assets( asset_type=AgentAssetType.MCP.value, status=AgentAssetStatus.ACTIVE.value, ), ontology, ) tasks: list[AgentAssetListItem | AgentAssetRead] = [] if task_asset is not None and task_asset.status == AgentAssetStatus.ACTIVE.value: tasks.append(task_asset) elif payload.source == AgentRunSource.SCHEDULE.value: tasks = self._rank_assets( self.asset_service.list_assets( asset_type=AgentAssetType.TASK.value, status=AgentAssetStatus.ACTIVE.value, ), ontology, ) return { "rules": rules, "skills": skills, "mcps": mcps, "tasks": tasks, } def _execute_user_agent( self, *, payload: OrchestratorRequest, run_id: str, ontology: OntologyParseResult, capabilities: dict[str, list[AgentAssetListItem | AgentAssetRead]], requires_confirmation: bool, context_json: dict[str, Any], ) -> ExecutionOutcome: selected_capability_codes = self._flatten_capability_codes(capabilities) if requires_confirmation: response, degraded = self._invoke_tool( run_id=run_id, tool_type=AgentToolType.LLM.value, tool_name="user_agent.confirmation_placeholder", request_json={ "message": payload.message, "permission_level": ontology.permission.level, }, context_json=context_json, executor=lambda: { "confirmation_title": "操作需要确认", "message": f"{ontology.permission.reason} 当前仅返回确认摘要，不直接执行动作。", }, fallback_factory=lambda exc: { "confirmation_title": "操作需要确认", "message": f"确认摘要生成失败，已阻断自动执行：{exc}", }, ) return ExecutionOutcome( status=AgentRunStatus.BLOCKED.value, result={**response, "degraded": degraded}, degraded=degraded, tool_count=1, failed_tool_count=1 if degraded else 0, ) next_step = self._resolve_next_step(ontology, payload.source) if next_step == "query_database": tool_payload, degraded = self._invoke_tool( run_id=run_id, tool_type=AgentToolType.DATABASE.value, tool_name=self._database_tool_name(ontology.scenario), request_json=self._build_ontology_json(ontology), context_json=context_json, executor=lambda: self._build_database_answer(ontology), fallback_factory=lambda exc: { "message": f"数据库查询暂时不可用，已返回降级说明：{exc}", "degraded": True, }, ) result = self._build_user_agent_result( self.user_agent_service.respond( UserAgentRequest( run_id=run_id, user_id=payload.user_id, message=payload.message or "", ontology=ontology, context_json=context_json, tool_payload=tool_payload, selected_capability_codes=selected_capability_codes, degraded=degraded, requires_confirmation=requires_confirmation, ) ), degraded=degraded, ) return ExecutionOutcome( status=AgentRunStatus.SUCCEEDED.value, result=result, degraded=degraded, tool_count=1, failed_tool_count=1 if degraded else 0, ) if next_step == "search_knowledge": tool_payload, degraded = self._invoke_tool( run_id=run_id, tool_type=AgentToolType.DATABASE.value, tool_name="knowledge.search", request_json=self._build_ontology_json(ontology), context_json=context_json, executor=lambda: self._build_knowledge_answer(ontology, capabilities), fallback_factory=lambda exc: { "message": f"知识检索暂时不可用，建议稍后重试：{exc}", "degraded": True, }, ) result = self._build_user_agent_result( self.user_agent_service.respond( UserAgentRequest( run_id=run_id, user_id=payload.user_id, message=payload.message or "", ontology=ontology, context_json=context_json, tool_payload=tool_payload, selected_capability_codes=selected_capability_codes, degraded=degraded, requires_confirmation=requires_confirmation, ) ), degraded=degraded, ) return ExecutionOutcome( status=AgentRunStatus.SUCCEEDED.value, result=result, degraded=degraded, tool_count=1, failed_tool_count=1 if degraded else 0, ) if next_step == "run_rule": tool_payload, degraded = self._invoke_tool( run_id=run_id, tool_type=AgentToolType.RULE_ENGINE.value, tool_name=self._rule_tool_name(capabilities), request_json=self._build_ontology_json(ontology), context_json=context_json, executor=lambda: self._build_rule_answer(ontology), fallback_factory=lambda exc: { "message": f"规则检查暂时不可用，已返回人工复核建议：{exc}", "degraded": True, }, ) result = self._build_user_agent_result( self.user_agent_service.respond( UserAgentRequest( run_id=run_id, user_id=payload.user_id, message=payload.message or "", ontology=ontology, context_json=context_json, tool_payload=tool_payload, selected_capability_codes=selected_capability_codes, degraded=degraded, requires_confirmation=requires_confirmation, ) ), degraded=degraded, ) return ExecutionOutcome( status=AgentRunStatus.SUCCEEDED.value, result=result, degraded=degraded, tool_count=1, failed_tool_count=1 if degraded else 0, ) tool_type = AgentToolType.LLM.value tool_name = "user_agent.draft_placeholder" executor = lambda: { "message": ( f"已生成 {ontology.scenario} 场景草稿，" "占位能力后续由 Day 5 User Agent 接管。" ), "draft_only": True, } fallback_factory = lambda exc: { "message": f"草稿生成暂时不可用，请稍后再试：{exc}", "degraded": True, } if ontology.scenario == "expense": tool_type = AgentToolType.DATABASE.value tool_name = "database.expense_claims.upsert_draft" executor = lambda: self.expense_claim_service.upsert_draft_from_ontology( run_id=run_id, user_id=payload.user_id, message=payload.message or "", ontology=ontology, context_json=context_json, ) fallback_factory = lambda exc: { "message": f"报销草稿落库失败，请稍后再试：{exc}", "degraded": True, } tool_payload, degraded = self._invoke_tool( run_id=run_id, tool_type=tool_type, tool_name=tool_name, request_json=self._build_ontology_json(ontology), context_json=context_json, executor=executor, fallback_factory=fallback_factory, ) result = self._build_user_agent_result( self.user_agent_service.respond( UserAgentRequest( run_id=run_id, user_id=payload.user_id, message=payload.message or "", ontology=ontology, context_json=context_json, tool_payload=tool_payload, selected_capability_codes=selected_capability_codes, degraded=degraded, requires_confirmation=requires_confirmation, ) ), degraded=degraded, ) return ExecutionOutcome( status=AgentRunStatus.SUCCEEDED.value, result=result, degraded=degraded, tool_count=1, failed_tool_count=1 if degraded else 0, ) def _execute_hermes( self, *, payload: OrchestratorRequest, run_id: str, ontology: OntologyParseResult, capabilities: dict[str, list[AgentAssetListItem | AgentAssetRead]], requires_confirmation: bool, task_asset: AgentAssetRead | None, context_json: dict[str, Any], ) -> ExecutionOutcome: if requires_confirmation: return ExecutionOutcome( status=AgentRunStatus.BLOCKED.value, result={ "message": "Hermes 不会自动执行需要确认的高风险动作，已阻断。", "degraded": False, }, degraded=False, tool_count=0, failed_tool_count=0, ) rule_response, rule_degraded = self._invoke_tool( run_id=run_id, tool_type=AgentToolType.RULE_ENGINE.value, tool_name=self._rule_tool_name(capabilities), request_json=self._build_ontology_json(ontology), context_json=context_json, executor=lambda: self._build_rule_answer(ontology), fallback_factory=lambda exc: { "message": f"规则巡检失败，已降级为待人工复核：{exc}", "degraded": True, }, ) mcp_response, mcp_degraded = self._invoke_tool( run_id=run_id, tool_type=AgentToolType.MCP.value, tool_name=self._mcp_tool_name(capabilities), request_json={ "task_code": task_asset.code if task_asset is not None else "", "scenario": ontology.scenario, }, context_json=context_json, executor=lambda: self._build_mcp_answer(task_asset, ontology), fallback_factory=lambda exc: { "message": f"MCP 调用失败，已使用缓存快照降级：{exc}", "fallback": "used_cached_snapshot", }, ) degraded = rule_degraded or mcp_degraded failed_tool_count = int(rule_degraded) + int(mcp_degraded) result = { "message": self._build_hermes_message( task_asset=task_asset, ontology=ontology, rule_response=rule_response, mcp_response=mcp_response, degraded=degraded, ), "report_type": task_asset.code if task_asset is not None else "hermes_runtime", "degraded": degraded, } return ExecutionOutcome( status=AgentRunStatus.SUCCEEDED.value, result=result, degraded=degraded, tool_count=2, failed_tool_count=failed_tool_count, ) @staticmethod def _resolve_next_step(ontology: OntologyParseResult, source: str) -> str: if ontology.clarification_required: return "ask_clarification" if ontology.intent == "draft": return "create_draft" if ontology.scenario == "knowledge" or ontology.intent == "explain": return "search_knowledge" if ontology.intent == "risk_check" or source == AgentRunSource.SCHEDULE.value: return "run_rule" if ontology.intent in {"query", "compare"}: return "query_database" return "create_draft" @staticmethod def _flatten_capability_codes( capabilities: dict[str, list[AgentAssetListItem | AgentAssetRead]], ) -> list[str]: codes: list[str] = [] for items in capabilities.values(): for item in items[:2]: if item.code not in codes: codes.append(item.code) return codes def _rank_assets( self, items: list[AgentAssetListItem], ontology: OntologyParseResult, ) -> list[AgentAssetListItem]: def score(item: AgentAssetListItem) -> tuple[int, str]: item_tags = {str(value) for value in item.scenario_json or []} weight = 0 if ontology.scenario in item_tags: weight += 3 if ontology.intent in item_tags: weight += 2 for risk_flag in ontology.risk_flags: if risk_flag in item_tags: weight += 4 return weight, item.code ranked = sorted(items, key=score, reverse=True) if not ranked: return [] scored = [item for item in ranked if score(item)[0] > 0] return scored or ranked[:1] def _invoke_tool( self, *, run_id: str, tool_type: str, tool_name: str, request_json: dict[str, Any], context_json: dict[str, Any], executor, fallback_factory, ) -> tuple[dict[str, Any], bool]: started = perf_counter() try: self._maybe_raise_simulated_failure(tool_type, context_json) response = executor() duration_ms = int((perf_counter() - started) * 1000) self.run_service.record_tool_call( run_id=run_id, tool_type=tool_type, tool_name=tool_name, request_json=request_json, response_json=response, status="succeeded", duration_ms=duration_ms, ) return response, False except Exception as exc: duration_ms = int((perf_counter() - started) * 1000) response = fallback_factory(exc) self.run_service.record_tool_call( run_id=run_id, tool_type=tool_type, tool_name=tool_name, request_json=request_json, response_json=response, status="failed", duration_ms=duration_ms, error_message=str(exc), ) return response, True @staticmethod def _maybe_raise_simulated_failure(tool_type: str, context_json: dict[str, Any]) -> None: expected = str(context_json.get("simulate_tool_failure") or "").strip().lower() if not expected: return if expected == tool_type.lower(): raise RuntimeError(f"simulated {tool_type} failure") def _build_database_answer(self, ontology: OntologyParseResult) -> dict[str, Any]: if ontology.scenario == "expense": count_stmt = select(func.count()).select_from(ExpenseClaim) amount_stmt = select( func.coalesce(func.sum(ExpenseClaim.amount), 0) ).select_from(ExpenseClaim) employee_names = [ item.normalized_value for item in ontology.entities if item.type == "employee" ] if employee_names: count_stmt = count_stmt.where(ExpenseClaim.employee_name.in_(employee_names)) amount_stmt = amount_stmt.where(ExpenseClaim.employee_name.in_(employee_names)) total_count = int(self.db.scalar(count_stmt) or 0) total_amount = float(self.db.scalar(amount_stmt) or 0) return { "record_count": total_count, "total_amount": round(total_amount, 2), } if ontology.scenario == "accounts_receivable": total_count = int( self.db.scalar( select(func.count()).select_from(AccountsReceivableRecord) ) or 0 ) total_amount = float( self.db.scalar( select(func.coalesce(func.sum(AccountsReceivableRecord.amount_outstanding), 0)) ) or 0 ) return { "record_count": total_count, "outstanding_amount": round(total_amount, 2), } total_count = int( self.db.scalar(select(func.count()).select_from(AccountsPayableRecord)) or 0 ) total_amount = float( self.db.scalar( select(func.coalesce(func.sum(AccountsPayableRecord.amount_outstanding), 0)) ) or 0 ) return { "record_count": total_count, "outstanding_amount": round(total_amount, 2), } @staticmethod def _build_user_query_result( ontology: OntologyParseResult, response: dict[str, Any], ) -> dict[str, Any]: if ontology.scenario == "expense": return { "message": ( f"已路由到 User Agent，占位查询结果：命中 {response['record_count']} 笔报销，" f"金额合计 {response['total_amount']} 元。" ), "data": response, } if ontology.scenario == "accounts_receivable": return { "message": ( f"已路由到 User Agent，占位查询结果：命中 {response['record_count']} 条应收，" f"未回款金额 {response['outstanding_amount']} 元。" ), "data": response, } return { "message": ( f"已路由到 User Agent，占位查询结果：命中 {response['record_count']} 条应付，" f"待付金额 {response['outstanding_amount']} 元。" ), "data": response, } @staticmethod def _build_user_agent_result( response: UserAgentResponse, *, degraded: bool, ) -> dict[str, Any]: result = { "message": response.answer, "answer": response.answer, "citations": [item.model_dump() for item in response.citations], "suggested_actions": [item.model_dump() for item in response.suggested_actions], "risk_flags": response.risk_flags, "requires_confirmation": response.requires_confirmation, "degraded": degraded, } if response.draft_payload is not None: result["draft_payload"] = response.draft_payload.model_dump() if response.review_payload is not None: result["review_payload"] = response.review_payload.model_dump() return result @staticmethod def _build_knowledge_answer( ontology: OntologyParseResult, capabilities: dict[str, list[AgentAssetListItem | AgentAssetRead]], ) -> dict[str, Any]: referenced = [item.code for item in capabilities["rules"][:1]] or [ "knowledge.policy.default" ] return { "message": f"已路由到 User Agent，占位知识结果：建议先查看 {', '.join(referenced)}。", "references": referenced, } @staticmethod def _build_rule_answer(ontology: OntologyParseResult) -> dict[str, Any]: risk_text = ( "、".join(ontology.risk_flags) if ontology.risk_flags else "未识别到明确风险标签" ) return { "message": f"已完成占位规则检查，风险标签：{risk_text}。", "risk_flags": ontology.risk_flags, } @staticmethod def _build_mcp_answer( task_asset: AgentAssetRead | None, ontology: OntologyParseResult, ) -> dict[str, Any]: return { "message": ( f"已调用占位 MCP 快照，任务={task_asset.code if task_asset else 'none'}，" f"scenario={ontology.scenario}。" ), "snapshot": "stubbed", } @staticmethod def _build_hermes_message( *, task_asset: AgentAssetRead | None, ontology: OntologyParseResult, rule_response: dict[str, Any], mcp_response: dict[str, Any], degraded: bool, ) -> str: task_code = task_asset.code if task_asset is not None else "task.unspecified" suffix = "，其中部分能力已降级。" if degraded else "。" return ( f"Hermes 占位执行完成：任务 {task_code}，" f"场景 {ontology.scenario}，规则结果={rule_response.get('message', '')}，" f"MCP 结果={mcp_response.get('message', '')}{suffix}" ) @staticmethod def _database_tool_name(scenario: str) -> str: if scenario == "expense": return "database.expense_claims.lookup" if scenario == "accounts_receivable": return "database.accounts_receivable.lookup" return "database.accounts_payable.lookup" @staticmethod def _rule_tool_name( capabilities: dict[str, list[AgentAssetListItem | AgentAssetRead]], ) -> str: if capabilities["rules"]: return capabilities["rules"][0].code return "rule_engine.default_risk_check" @staticmethod def _mcp_tool_name( capabilities: dict[str, list[AgentAssetListItem | AgentAssetRead]], ) -> str: if capabilities["mcps"]: return capabilities["mcps"][0].code return "mcp.default_snapshot" @staticmethod def _build_ontology_json(ontology: OntologyParseResult) -> dict[str, Any]: return { "scenario": ontology.scenario, "intent": ontology.intent, "entities": [item.model_dump() for item in ontology.entities], "time_range": ontology.time_range.model_dump(), "metrics": [item.model_dump() for item in ontology.metrics], "constraints": [item.model_dump() for item in ontology.constraints], "risk_flags": ontology.risk_flags, "permission": ontology.permission.model_dump(), } @staticmethod def _normalize_response_status(status: str) -> str: if status == AgentRunStatus.FAILED.value: return "failed" if status == AgentRunStatus.BLOCKED.value: return "blocked" return "succeeded"