v0.1.0: CRM/ERP 系统内测版本 - 安全加固完成
- Docker bridge 网络隔离（8000 端口封死） - Gunicorn 4 Worker 多进程 - Alembic 数据库迁移基线 - 日志轮转 20m×3 - JWT 密钥 + DB 密码 + CORS 收紧 - 3-2-1 备份链路（NAS + R740-B 冷备） - 连接池 pool_pre_ping + pool_recycle=3600
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hankin
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# -*- coding: utf-8 -*-
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"""
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AI 工作流服务 (Dify BaaS 版本)
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事件驱动的异步 AI 任务：从客户沟通日志中自动提取标签和生成跟进待办。
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架构要点：
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- 此函数由 FastAPI BackgroundTasks 调用，运行在独立的后台线程中
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- 必须使用独立的 DB Session 生命周期，严禁与主请求共享 Session
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- AI 调用通过 Dify 平台 API（非直连大模型）
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- AI 解析失败时静默降级（记录日志），绝不抛出异常导致主线程崩溃
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"""
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import json
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import logging
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import uuid
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from app.core.dify_client import dify_client
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from app.core.database import AsyncSessionLocal
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from app.models.crm_business import CustomerTag, FollowUpToDo
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from app.core.config import settings
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logger = logging.getLogger("ai_workflow")
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async def process_log_with_ai(
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log_id: uuid.UUID,
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content: str,
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customer_id: uuid.UUID,
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) -> None:
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"""
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后台 AI 任务：分析沟通日志，提取标签和待办。
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*** 关键约束 ***
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此函数在 BackgroundTasks 中执行，必须：
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1. 使用独立的 AsyncSession（不与主请求共享）
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2. 内部捕获所有异常，不向外抛出
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3. AI 返回格式异常时静默降级
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"""
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logger.info("开始 AI 处理: log_id=%s, customer_id=%s", log_id, customer_id)
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if not settings.DIFY_LOG_APP_API_KEY:
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logger.error("DIFY_LOG_APP_API_KEY 未配置，跳过 AI 处理")
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return
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# ---- 独立的 DB Session 生命周期 ----
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async with AsyncSessionLocal() as db:
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try:
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# Step 1: 调用 Dify 日志分析 Workflow App
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# *** inputs 的键名必须与 Dify 后台配置的变量名对齐 ***
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# 在 Dify 后台的 Workflow 编排中，需定义输入变量 "log_content"
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workflow_outputs = await dify_client.call_workflow(
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api_key=settings.DIFY_LOG_APP_API_KEY,
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inputs={"log_content": content},
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)
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if not workflow_outputs:
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logger.warning("Dify 返回空响应，跳过入库 (log_id=%s)", log_id)
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return
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# Workflow 返回的是 dict，序列化为 JSON 字符串以兼容现有解析管线
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if isinstance(workflow_outputs, dict):
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raw_response = json.dumps(workflow_outputs, ensure_ascii=False)
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else:
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raw_response = str(workflow_outputs)
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logger.debug("Dify Workflow 原始返回: %s", raw_response[:500])
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# Step 2: 解析 JSON 响应 (容错)
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json_str = _extract_json(raw_response)
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result = json.loads(json_str)
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tags: list[str] = result.get("tags", [])
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next_task: str = result.get("next_task", "")
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# Step 3: 写入标签 (最多 3 个)
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if tags:
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for tag_name in tags[:3]:
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tag_name = tag_name.strip()
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if not tag_name:
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continue
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tag = CustomerTag(
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customer_id=customer_id,
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tag_name=tag_name,
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)
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db.add(tag)
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logger.info("写入 %d 个标签: %s", len(tags[:3]), tags[:3])
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# Step 4: 写入跟进待办
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if next_task and next_task.strip():
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todo = FollowUpToDo(
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customer_id=customer_id,
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task_desc=next_task.strip(),
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status="pending",
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)
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db.add(todo)
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logger.info("写入待办: %s", next_task.strip()[:100])
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await db.commit()
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logger.info("AI 处理完成: log_id=%s", log_id)
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except json.JSONDecodeError as e:
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logger.error(
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"Dify 返回 JSON 解析失败 (log_id=%s): %s | 原始响应: %s",
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log_id, e, raw_response[:300],
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)
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await db.rollback()
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except Exception as e:
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logger.error(
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"AI 后台任务异常 (log_id=%s): %s",
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log_id, e, exc_info=True,
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)
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await db.rollback()
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def _extract_json(text: str) -> str:
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"""
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从 Dify/LLM 响应中提取 JSON 字符串。
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处理常见的"包裹"行为：
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- 直接返回 JSON
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- 用 ```json ... ``` 包裹
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- 在 JSON 前后加解释文字
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"""
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text = text.strip()
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# 尝试提取 ```json ... ``` 代码块
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if "```json" in text:
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start = text.index("```json") + len("```json")
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end = text.index("```", start)
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return text[start:end].strip()
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if "```" in text:
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start = text.index("```") + len("```")
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end = text.index("```", start)
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return text[start:end].strip()
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# 尝试找到第一个 { 和最后一个 }
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first_brace = text.find("{")
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last_brace = text.rfind("}")
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if first_brace != -1 and last_brace != -1 and last_brace > first_brace:
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return text[first_brace:last_brace + 1]
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# 原样返回，让 json.loads 报错触发容错
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return text
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# -*- coding: utf-8 -*-
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"""
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销售数据分析服务 (Dify BaaS 版本)
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基于 SQL 预聚合的销售漏斗统计 + Dify AI 驱动的复盘报告生成。
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"""
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import logging
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from datetime import datetime, timezone
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from sqlalchemy import func, select, extract, case
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.config import settings
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from app.core.dify_client import dify_client
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from app.models.crm_business import SalesOpportunity
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logger = logging.getLogger("analytics")
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# ============================================================
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# 1. SQL 预聚合：销售漏斗指标
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# ============================================================
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async def get_sales_metrics(db: AsyncSession) -> list[dict]:
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"""
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按当月统计各销售阶段的机会数量和总金额。
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使用 SQLAlchemy GROUP BY 聚合查询，在数据库层面完成计算。
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"""
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now = datetime.now(timezone.utc)
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stmt = (
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select(
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SalesOpportunity.stage,
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func.count(SalesOpportunity.id).label("count"),
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func.coalesce(func.sum(SalesOpportunity.amount), 0).label("total_amount"),
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)
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.where(
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extract("year", SalesOpportunity.created_at) == now.year,
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extract("month", SalesOpportunity.created_at) == now.month,
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)
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.group_by(SalesOpportunity.stage)
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.order_by(
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case(
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(SalesOpportunity.stage == "意向", 1),
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(SalesOpportunity.stage == "谈判", 2),
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(SalesOpportunity.stage == "成交", 3),
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(SalesOpportunity.stage == "流失", 4),
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else_=5,
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)
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)
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)
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result = await db.execute(stmt)
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rows = result.all()
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metrics = [
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{
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"stage": row.stage,
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"count": row.count,
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"total_amount": float(row.total_amount),
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}
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for row in rows
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]
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logger.info("当月销售指标: %s", metrics)
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return metrics
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# ============================================================
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# 2. Dify AI 复盘报告生成
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# ============================================================
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async def generate_monthly_report(db: AsyncSession) -> dict:
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"""
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生成当月销售复盘报告：
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1. SQL 预聚合获取真实数据指标
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2. 将结构化数据通过 inputs 传给 Dify 报告 App
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3. 直接返回 Dify 生成的报告文本
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:return: {"metrics": [...], "report": "Dify 生成的报告文本"}
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"""
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# Step 1: 获取真实销售数据
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metrics = await get_sales_metrics(db)
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if not metrics:
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return {
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"metrics": [],
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"report": "当月暂无销售机会数据，无法生成复盘报告。",
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}
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# Step 2: 将数据序列化为 Dify 可消费的文本格式
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# *** inputs 的键名必须与 Dify 后台配置的变量名对齐 ***
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# 在 Dify 后台的报告 App 编排中，需定义输入变量 "metrics_data"
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metrics_text = "\n".join(
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f"- {m['stage']}: {m['count']} 个机会, 总金额 ¥{m['total_amount']:,.2f}"
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for m in metrics
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)
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total_count = sum(m["count"] for m in metrics)
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total_amount = sum(m["total_amount"] for m in metrics)
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metrics_text += f"\n- 合计: {total_count} 个机会, 总金额 ¥{total_amount:,.2f}"
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# Step 3: 调用 Dify 报告 App
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if not settings.DIFY_REPORT_APP_API_KEY:
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logger.error("DIFY_REPORT_APP_API_KEY 未配置")
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return {
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"metrics": metrics,
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"report": "AI 报告服务未配置，请联系管理员。",
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}
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# 动态生成 Dify 后台所需的必填参数 report_period
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now = datetime.now(timezone.utc)
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report_period = f"{now.year}年{now.month:02d}月"
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report_text = await dify_client.call_text_generator(
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api_key=settings.DIFY_REPORT_APP_API_KEY,
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inputs={"metrics_data": metrics_text, "report_period": report_period},
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)
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if not report_text:
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report_text = "AI 报告生成失败，请稍后重试或检查 Dify 服务状态。"
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logger.info("月度复盘报告生成完成 (%d 字)", len(report_text))
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return {
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"metrics": metrics,
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"report": report_text,
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}
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