"""轻量 RAG：检索与个股/大盘相关的资讯，做情绪标注，作为 LLM 上下文降低幻觉。

当前为基于来源接口 + 关键词情绪的检索式上下文；后续可平滑升级为向量检索（embedding + 向量库）。
"""
from __future__ import annotations

import akshare_service as svc


def stock_news(symbol: str, limit: int = 5):
    """返回个股相关资讯（已带利好/利空标注）。"""
    try:
        data = svc.get_stock_news(symbol, limit=limit)
        return data.get("list", [])[:limit]
    except Exception:
        return []


def _senti_score(items):
    pos = sum(1 for x in items if x.get("sentiment") == "利好")
    neg = sum(1 for x in items if x.get("sentiment") == "利空")
    if pos > neg:
        return "利好", pos, neg
    if neg > pos:
        return "利空", pos, neg
    return "中性", pos, neg


def stock_context(symbol: str, limit: int = 5):
    """供 AI 诊断使用：检索资讯 + 汇总情绪。"""
    items = stock_news(symbol, limit)
    tone, pos, neg = _senti_score(items)
    block = ""
    if items:
        block = "近期相关资讯（检索）：\n" + "\n".join(
            f"- [{x.get('sentiment','中性')}] {x.get('title','')}（{x.get('time','')}）" for x in items)
    return {"items": items, "tone": tone, "pos": pos, "neg": neg, "block": block}