users/app/api/rfm/analyze/route.ts

import { NextResponse } from "next/server"
import { analyzeUser, type AnalyzeInput } from "@/services/rfm-engine"
import { generateText } from "ai"
import { openai } from "@ai-sdk/openai"

/**
 * 可选 AI 标签增强：
 * - 使用 AI SDK (generateText + openai("gpt-4o"))，符合统一标准 [^1]
 * - 无 OPENAI_API_KEY 时自动跳过，保持稳定
 */
async function aiTagging(chat_logs?: string[]) {
  const text = (chat_logs ?? []).slice(0, 8).join("。")
  if (!text) return null
  if (!process.env.OPENAI_API_KEY) return null
  try {
    const { text: out } = await generateText({
      model: openai("gpt-4o"),
      system:
        "请根据用户聊天片段输出JSON，字段：emotion(积极|中性|消极), intent(弱意图|中等意图|强意图), behavior(数组，中文标签最多3个)。只输出JSON。",
      prompt: `聊天片段：${text}`,
      // @ts-expect-error ai sdk typings are flexible in Next.js
      maxTokens: 200,
    })
    const json = JSON.parse(out.trim())
    return json
  } catch {
    return null
  }
}

export async function POST(req: Request) {
  try {
    const body = await req.json()
    const inputs: AnalyzeInput[] = Array.isArray(body) ? body : [body]
    const useAI = (Array.isArray(body) ? (body as any).useAI : (body as any)?.useAI) ?? false

    const results = []
    for (const input of inputs) {
      const base = analyzeUser(input)
      if (useAI) {
        const ai = await aiTagging(input.chat_logs)
        if (ai) {
          base.tags.emotion = ai.emotion ?? base.tags.emotion
          base.tags.intent = ai.intent ?? base.tags.intent
          if (Array.isArray(ai.behavior)) {
            base.tags.behavior = Array.from(new Set([...(base.tags.behavior ?? []), ...ai.behavior]))
          }
        }
      }
      results.push(base)
    }
    return NextResponse.json({ success: true, data: results })
  } catch (e: any) {
    return NextResponse.json({ success: false, error: e?.message || "Invalid input" }, { status: 400 })
  }
}