from __future__ import annotations

from typing import Any

import httpx

from ..settings import settings


def _rule_based_summary(query: str, retrieved: list[dict[str, Any]]) -> dict[str, Any]:
    top = retrieved[:3]
    bullets = []
    for r in top:
        pid = r.get("product_id") or r.get("id") or "-"
        title = r.get("title") or ""
        follow = r.get("follow_score")
        life = r.get("lifecycle")
        bullets.append(f"- {pid} {title}（跟卖指数={follow} 生命周期={life}）")
    return {
        "mode": "rules_only",
        "query": query,
        "retrieved": retrieved,
        "answer": "基于当前向量库/指标的规则摘要：\n" + "\n".join(bullets),
    }


def generate_insight(query: str, product_id: str | None, top_k: int) -> dict[str, Any]:
    """
    这里先做“可运行的最小闭环”：
    - 向量检索（尚未实现时返回空）
    - 有 OPENAI_API_KEY 则调用 LLM，输出结构化建议
    - 否则返回规则引擎摘要
    """
    # TODO: 接入向量库检索（Milvus/Azure 等）。先保留协议，保证前端可用。
    retrieved: list[dict[str, Any]] = []

    if not settings.openai_api_key:
        return _rule_based_summary(query, retrieved)

    prompt = f"""你是电商数据分析与选品决策助手。
用户问题：{query}

请输出一个“发现爆款 -> 数据验证 -> 决策跟卖”的闭环建议，包含：
1) 结论摘要（3-5条）
2) 数据证据（引用关键指标：销量/增速/竞争/生命周期）
3) 风险点与反例（至少3条）
4) 可执行动作（选品、备货、投流、供应链）
如果没有足够数据，请明确说明缺口，并给出最小补充数据清单。
"""

    headers = {"Authorization": f"Bearer {settings.openai_api_key}"}
    payload = {
        "model": settings.openai_model,
        "input": prompt,
    }

    try:
        with httpx.Client(timeout=30.0) as client:
            r = client.post("https://api.openai.com/v1/responses", headers=headers, json=payload)
            r.raise_for_status()
            data = r.json()
        text = ""
        for item in data.get("output", []):
            for c in item.get("content", []):
                if c.get("type") in ("output_text", "text"):
                    text += c.get("text", "")
        return {"mode": "llm", "query": query, "retrieved": retrieved, "answer": text.strip()}
    except Exception as e:
        out = _rule_based_summary(query, retrieved)
        out["mode"] = "rules_fallback"
        out["error"] = str(e)
        return out