AI 线索评分实战：用 Jev 构建类型化评分与 CRM 分流

type LeadState = {
  company: string;
  employees: number;
  title: string;
  message: string;
  pricing_page_views_7d: number;
};

// 策略写在应用代码里，而不是 prompt 中
const AUTO_ROUTE_MIN_SCORE = 3;
const AUTO_ROUTE_MIN_CONFIDENCE = 0.85;

export async function scoreLead(lead: LeadState) {
  const response = await fetch("https://api.typesafe.ai/v1/jev/evaluate", {
    method: "POST",
    headers: { "Content-Type": "application/json" },
    body: JSON.stringify({
      state: lead,
      questions: {
        priority: {
          type: "score",
          instructions: "评估销售跟进优先级",
          criteria: {
            "1": "匹配度低",
            "2": "可能匹配",
            "3": "匹配度高",
            "4": "立即跟进",
          },
        },
        is_hot_lead: {
          type: "noul",
          instructions: "是否应在一个工作小时内通知销售？",
        },
        segment: {
          type: "choice",
          instructions: "判定 CRM 客户分层",
          criteria: {
            enterprise: "500 人以上",
            mid_market: "50-499 人",
            smb: "50 人以下",
          },
        },
      },
    }),
  });
  if (!response.ok) throw new Error("Jev evaluate failed");
  const data = await response.json();

  const { priority, is_hot_lead, segment } = data;
  const confident = priority.confidence >= AUTO_ROUTE_MIN_CONFIDENCE;

  if (priority.answer >= AUTO_ROUTE_MIN_SCORE && confident) {
    return {
      route: is_hot_lead.answer ? "page_rep_now" : "crm_auto",
      priority: priority.answer,
      segment: segment.answer,
      confidence: priority.confidence,
    };
  }
  // 评分或置信度低于阈值 → 进入 SDR 人工复核队列
  return {
    route: "sdr_review",
    priority: priority.answer,
    segment: segment.answer,
    confidence: priority.confidence,
  };
}

// 典型路径：单条线索 ~95ms，仅输入计费，0% schema 错误

import requests

JEV_ENDPOINT = "https://api.typesafe.ai/v1/jev/evaluate"
AUTO_ROUTE_MIN_SCORE = 3
AUTO_ROUTE_MIN_CONFIDENCE = 0.85

QUESTIONS = {
    "priority": {
        "type": "score",
        "instructions": "评估销售跟进优先级",
        "criteria": {
            "1": "匹配度低",
            "2": "可能匹配",
            "3": "匹配度高",
            "4": "立即跟进",
        },
    },
    "is_hot_lead": {
        "type": "noul",
        "instructions": "是否应在一个工作小时内通知销售？",
    },
}

def score_lead(lead: dict) -> dict:
    resp = requests.post(
        JEV_ENDPOINT,
        json={"state": lead, "questions": QUESTIONS},
        timeout=5,
    )
    resp.raise_for_status()
    result = resp.json()
    priority = result["priority"]
    hot = result["is_hot_lead"]

    if (
        priority["answer"] >= AUTO_ROUTE_MIN_SCORE
        and priority["confidence"] >= AUTO_ROUTE_MIN_CONFIDENCE
    ):
        route = "page_rep_now" if hot["answer"] else "crm_auto"
    else:
        route = "sdr_review"

    return {
        "lead_id": lead.get("id"),
        "priority": priority["answer"],
        "confidence": priority["confidence"],
        "route": route,
    }

def score_batch(leads: list[dict]) -> list[dict]:
    # ~95ms/条：夜间同步 1 万条线索约 16 分钟跑完，
    # 且远低于 CRM API 速率限制。
    return [score_lead(lead) for lead in leads]