9f7b8b46a3
Align planner, runtime rules, and policy assets so travel guidance matches the updated reimbursement workflow.
277 lines
13 KiB
Python
277 lines
13 KiB
Python
from __future__ import annotations
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import json
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from dataclasses import dataclass
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from datetime import date
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from typing import Any
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from app.schemas.steward import StewardPlanRequest
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from app.services.ontology_field_registry import normalize_ontology_form_values
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from app.services.runtime_chat import RuntimeChatService
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STEWARD_INTENT_FUNCTION_NAME = "submit_steward_intent_plan"
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@dataclass(frozen=True, slots=True)
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class StewardIntentAgentResult:
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payload: dict[str, Any]
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model_call_traces: list[dict[str, Any]]
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class StewardIntentAgent:
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"""使用大模型 function calling 识别小财管家的复合财务意图。"""
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def __init__(self, runtime_chat_service: RuntimeChatService) -> None:
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self.runtime_chat_service = runtime_chat_service
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self.last_call_traces: list[dict[str, Any]] = []
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def detect(
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self,
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request: StewardPlanRequest,
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*,
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base_date: date,
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canonical_fields: list[str],
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) -> StewardIntentAgentResult | None:
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result = self.runtime_chat_service.complete_with_tool_call(
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self._build_messages(request, base_date=base_date, canonical_fields=canonical_fields),
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tools=[self._build_intent_tool_schema(canonical_fields)],
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tool_choice={
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"type": "function",
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"function": {"name": STEWARD_INTENT_FUNCTION_NAME},
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},
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max_tokens=1800,
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temperature=0.1,
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timeout_seconds=45,
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max_attempts=1,
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)
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self.last_call_traces = result.calls_as_dicts()
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if result.tool_call is None or result.tool_call.name != STEWARD_INTENT_FUNCTION_NAME:
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return None
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return StewardIntentAgentResult(
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payload=result.tool_call.arguments,
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model_call_traces=self.last_call_traces,
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)
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@staticmethod
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def _build_messages(
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request: StewardPlanRequest,
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*,
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base_date: date,
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canonical_fields: list[str],
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) -> list[dict[str, Any]]:
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context_payload = {
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"message": request.message,
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"base_date": base_date.isoformat(),
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"client_now_iso": request.client_now_iso,
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"user_id": request.user_id,
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"canonical_ontology_fields": canonical_fields,
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"review_form_values": normalize_ontology_form_values(
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request.context_json.get("review_form_values")
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),
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"context_json": {
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key: value
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for key, value in request.context_json.items()
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if key
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in {
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"entry_source",
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"session_type",
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"role_codes",
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"username",
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"name",
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"department_name",
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"employee_grade",
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"employee_no",
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"client_timezone_offset_minutes",
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}
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},
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"attachments": [
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{
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"index": index + 1,
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"name": item.name,
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"media_type": item.media_type,
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"ocr_summary": item.ocr_summary,
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"ocr_fields": item.ocr_fields,
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}
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for index, item in enumerate(request.attachments)
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if item.name
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],
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}
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return [
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{
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"role": "system",
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"content": (
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"你是 X-Financial 的小财管家意图识别智能体。"
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"你必须通过 function calling 输出结构化计划，不能只返回普通文本。"
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"当前版本只支持 expense_application 和 reimbursement 两类任务；"
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"你只做识别、拆解、归集和确认点规划，不能执行入库、绑定附件或提交审批。"
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"用户描述未来出差、差旅计划、去某地几天、部署、支撑、拜访或会议安排时，"
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"即使没有出现“申请”两个字，也必须优先识别为 expense_application。"
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"用户描述已经发生的费用、昨天/前天费用、票据或明确报销诉求时，才识别为 reimbursement。"
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"如果用户只描述出差时间、地点和事由，但没有明确申请、报销、提交、保存草稿等动作，"
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"且无法从上下文判断流程方向，必须返回 pending_flow_confirmation.status=pending，"
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"candidate_flows 同时给出 travel_application 和 travel_reimbursement，tasks 保持空数组。"
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"所有 ontology_fields 只能使用调用方给出的 canonical_ontology_fields；"
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"如果输入里出现 occurred_date、transport_type、reason_value 等别名，必须映射为 canonical 字段。"
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"相对日期必须以 base_date 为准转换为明确日期。"
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"thinking_events 只能是面向用户的过程摘要，不能暴露内部推理链。"
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),
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},
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{
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"role": "user",
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"content": json.dumps(context_payload, ensure_ascii=False),
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},
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]
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@staticmethod
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def _build_intent_tool_schema(canonical_fields: list[str]) -> dict[str, Any]:
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return {
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"type": "function",
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"function": {
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"name": STEWARD_INTENT_FUNCTION_NAME,
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"description": "提交小财管家的复合财务意图识别结果。",
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"parameters": {
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"type": "object",
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"properties": {
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"thinking_events": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"stage": {"type": "string"},
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"title": {"type": "string"},
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"content": {"type": "string"},
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},
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"required": ["stage", "title", "content"],
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},
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},
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"tasks": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"task_type": {
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"type": "string",
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"enum": ["expense_application", "reimbursement"],
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},
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"title": {"type": "string"},
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"summary": {"type": "string"},
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"confidence": {
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"type": "number",
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"minimum": 0,
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"maximum": 1,
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},
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"ontology_fields": {
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"type": "object",
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"additionalProperties": {"type": "string"},
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},
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"missing_fields": {
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"type": "array",
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"items": {
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"type": "string",
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"enum": canonical_fields,
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},
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},
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},
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"required": [
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"task_type",
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"title",
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"summary",
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"confidence",
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"ontology_fields",
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"missing_fields",
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],
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},
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},
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"pending_flow_confirmation": {
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"type": "object",
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"properties": {
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"status": {
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"type": "string",
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"enum": ["none", "pending"],
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},
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"source_message": {"type": "string"},
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"reason": {"type": "string"},
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"candidate_flows": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"flow_id": {
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"type": "string",
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"enum": ["travel_application", "travel_reimbursement"],
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},
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"label": {"type": "string"},
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"confidence": {
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"type": "number",
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"minimum": 0,
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"maximum": 1,
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},
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"reason": {"type": "string"},
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"ontology_fields": {
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"type": "object",
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"additionalProperties": {"type": "string"},
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},
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"missing_fields": {
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"type": "array",
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"items": {
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"type": "string",
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"enum": canonical_fields,
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},
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},
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},
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"required": [
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"flow_id",
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"label",
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"confidence",
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"reason",
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"ontology_fields",
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"missing_fields",
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],
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},
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},
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},
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"required": ["status", "source_message", "reason", "candidate_flows"],
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},
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"attachment_groups": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"target_task_index": {
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"type": "integer",
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"minimum": 1,
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},
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"scene": {"type": "string"},
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"scene_label": {"type": "string"},
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"attachment_names": {
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"type": "array",
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"items": {"type": "string"},
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},
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"excluded_attachment_names": {
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"type": "array",
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"items": {"type": "string"},
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},
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"confidence": {
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"type": "number",
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"minimum": 0,
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"maximum": 1,
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},
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"rationale": {"type": "string"},
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},
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"required": [
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"scene",
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"scene_label",
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"attachment_names",
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"excluded_attachment_names",
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"confidence",
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"rationale",
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],
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},
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},
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},
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"required": ["thinking_events", "tasks", "attachment_groups"],
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},
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},
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}
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