50b1c3f9a9
后端新增规则资产版本管理和规则文件 CRUD 接口，优化风险 规则生成模板执行和员工数据模型字段，知识库 RAG 增强本 地回退和文档提取能力，清理旧风险规则文件统一由生成引擎 管理，前端审计页面增加运行时调试面板和规则资产编辑交互， 补充单元测试覆盖。
105 lines
4.0 KiB
Python
105 lines
4.0 KiB
Python
from __future__ import annotations
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import json
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from datetime import datetime, timedelta, timezone
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from typing import Any
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from sqlalchemy import func, select
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from sqlalchemy.orm import Session
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from app.core.logging import get_logger
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from app.models.financial_record import ExpenseClaim
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from app.services.runtime_chat import RuntimeChatService
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logger = get_logger("app.services.hermes_expense_report")
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class HermesExpenseReportService:
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def __init__(self, db: Session) -> None:
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self.db = db
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self.chat_service = RuntimeChatService(db)
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def generate_weekly_report(self, log_id: str | None = None) -> None:
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logger.info("Starting Hermes weekly expense report generation...")
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# 1. 聚合数据
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aggregated_data = self._aggregate_recent_expenses(days=7)
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if not aggregated_data.get("total_amount"):
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logger.info("No expense data in the last 7 days. Skipping report.")
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return
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# 2. 传入大模型分析
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report_markdown = self._generate_insights_with_llm(aggregated_data)
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if not report_markdown:
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logger.warning("Failed to generate expense report from LLM.")
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return
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# 3. 模拟发送报告
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self._deliver_report(report_markdown, log_id)
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logger.info("Hermes weekly expense report generation completed.")
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def _aggregate_recent_expenses(self, days: int = 7) -> dict[str, Any]:
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target_date = datetime.now(timezone.utc) - timedelta(days=days)
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# 基础过滤：最近N天且不是驳回状态的单据
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base_filter = [
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ExpenseClaim.occurred_at >= target_date,
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ExpenseClaim.status != "rejected"
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]
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# 1. 按部门汇总
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dept_stmt = select(
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ExpenseClaim.department_name,
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func.sum(ExpenseClaim.amount).label("total")
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).where(*base_filter).group_by(ExpenseClaim.department_name)
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dept_results = self.db.execute(dept_stmt).all()
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by_department = {row.department_name or "Unknown": float(row.total or 0) for row in dept_results}
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# 2. 按类目汇总
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type_stmt = select(
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ExpenseClaim.expense_type,
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func.sum(ExpenseClaim.amount).label("total")
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).where(*base_filter).group_by(ExpenseClaim.expense_type)
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type_results = self.db.execute(type_stmt).all()
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by_expense_type = {row.expense_type or "Unknown": float(row.total or 0) for row in type_results}
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# 3. 总花费
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total_amount = sum(by_department.values())
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return {
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"period": f"Last {days} days",
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"total_amount": total_amount,
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"by_department": by_department,
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"by_expense_type": by_expense_type
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}
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def _generate_insights_with_llm(self, data: dict[str, Any]) -> str | None:
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system_prompt = (
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"你是公司的财务分析专家。请根据提供的最近期业务开销数据，撰写一份简洁有力的【高管费控洞察周报】。\n"
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"要求：\n"
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"1. 不要机械地罗列数字，要像人一样指出异常（例如：哪个部门花钱最多？打车费是不是异常高？）。\n"
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"2. 给出 1 条削减成本的实操建议。\n"
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"3. 纯 Markdown 格式输出，不超过 300 字。"
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)
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messages = [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": f"开销统计数据：\n{json.dumps(data, ensure_ascii=False, indent=2)}"}
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]
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response = self.chat_service.complete(
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messages,
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max_tokens=800,
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temperature=0.4
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)
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return response
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def _deliver_report(self, report_markdown: str, log_id: str | None) -> None:
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# TODO: 未来在这里接入企微/钉钉机器人或邮件发送接口
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logger.info(f"\n================ Hermes Weekly Report [LogID: {log_id}] ================\n"
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f"{report_markdown}\n"
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f"==========================================================================")
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