MoFin/xiaoguo_news_processor.py

#!/usr/bin/env python3
"""xiaoguo_news_processor.py — 小果新闻情报处理

配合 trend_detector（每30分）运行，处理未处理的 sector_signals。

流程：
  1. 读未 processed 的 signals（每次1条）
  2. akshare 搜新闻（板块相关个股 + 持仓 + 自选）
  3. 调小果 LLM 逐篇分析情感
  4. 写入 signal_news
  5. 标记 signal.processed = true
"""

import json
import os
import urllib.request
from datetime import datetime
from pathlib import Path

try:
    import akshare as ak
    HAS_AKSHARE = True
except ImportError:
    HAS_AKSHARE = False

DATA_DIR = Path(__file__).parent / "data"
DB_PATH = DATA_DIR / "mofin.db"
XIAOGUO_API = "http://192.168.1.122:18003/v1/chat/completions"
XIAOGUO_MODEL = "Qwen3.6-27B-AEON-Uncensored-4bit"
XIAOGUO_TIMEOUT = 120


def get_conn():
    import sqlite3
    conn = sqlite3.connect(str(DB_PATH))
    conn.row_factory = sqlite3.Row
    return conn


def search_akshare_news(code, max_results=3):
    """用 akshare 搜个股新闻"""
    titles = []
    if not HAS_AKSHARE:
        return titles
    try:
        for k in ['http_proxy', 'https_proxy', 'HTTP_PROXY', 'HTTPS_PROXY']:
            os.environ.pop(k, None)
        df = ak.stock_news_em(symbol=code)
        for _, r in df.head(max_results).iterrows():
            title = r.get('新闻标题', '')
            if title and len(title) > 5:
                titles.append({"title": title, "url": r.get('新闻链接', '')})
    except:
        pass
    return titles


def classify_sentiment(title):
    """基于关键词的快速情感分类（不调LLM，速度快）"""
    title_lower = title.lower()
    positive_kw = ['突破', '增长', '利好', '加单', '订单', '放量', '新高', '获批', '量产',
                   '超预期', '供应', '投产', '融资', '加仓', '增持', '回购', '降息',
                   '减税', '补贴', '国产替代', '自主可控', '准入']
    negative_kw = ['管制', '限制', '制裁', '利空', '减持', '抛售', '下跌', '跌停',
                   '风险', '违约', '调查', '暂停', '取消', '下滑', '亏损', '裁员',
                   '诉讼', '退市', '做空', '关税', '禁令']

    pos_score = sum(1 for kw in positive_kw if kw in title)
    neg_score = sum(1 for kw in negative_kw if kw in title)

    if pos_score > neg_score:
        return "利好"
    elif neg_score > pos_score:
        return "利空"
    return "中性"


def main():
    conn = get_conn()

    # 读未处理的 signals（每次1条）
    signals = conn.execute(
        "SELECT * FROM sector_signals WHERE processed = 0 ORDER BY severity DESC, id ASC LIMIT 1"
    ).fetchall()

    if not signals:
        print("无未处理的信号", flush=True)
        conn.close()
        return

    signal = dict(signals[0])
    print(f"处理信号: [{signal['severity']}] {signal['signal_type']} {signal['sector']}", flush=True)

    # 从信号中提取需要搜索的股票代码
    sector = signal["sector"]
    related = json.loads(signal["related_stocks"] or "[]")
    holdings = json.loads(signal["holdings_in_sector"] or "[]")
    watchlist = json.loads(signal["watchlist_in_sector"] or "[]")

    # 收集所有要搜的股票代码
    codes_to_search = {}
    for item in related + holdings + watchlist:
        code = item.get("code", "")
        name = item.get("name", "")
        if code:
            codes_to_search[code] = name

    # 补充板块成分股
    members = conn.execute(
        "SELECT s.code, s.name FROM stocks s "
        "JOIN stock_sectors ss ON s.code = ss.code "
        "WHERE ss.sector_name = ? LIMIT 5", (sector,)
    ).fetchall()
    for m in members:
        if m["code"] not in codes_to_search:
            codes_to_search[m["code"]] = m["name"]

    # 搜新闻
    all_articles = []
    for code, name in codes_to_search.items():
        articles = search_akshare_news(code, 3)
        for a in articles:
            if a["title"] not in [x["title"] for x in all_articles]:
                # 规则分类
                a["sentiment"] = classify_sentiment(a["title"])
                all_articles.append(a)
        print(f"  搜 {name}({code}): {len(articles)} 篇", flush=True)

    if not all_articles:
        print(f"  未搜到相关新闻", flush=True)
        conn.execute("UPDATE sector_signals SET processed = 1 WHERE id = ?", (signal["id"],))
        conn.commit()
        conn.close()
        return

    print(f"  共搜到 {len(all_articles)} 篇新闻（规则分类）", flush=True)

    # 统计总体情感
    sentiments = [a["sentiment"] for a in all_articles]
    pos = sentiments.count("利好")
    neg = sentiments.count("利空")
    overall = "利好" if pos > neg * 1.5 else "利空" if neg > pos * 1.5 else "中性"
    summary = f"{sector}板块搜到{len(all_articles)}篇相关新闻，利好{pos}篇，利空{neg}篇，整体{overall}。"

    # 写入 signal_news
    searched_names = list(set(codes_to_search.values()))
    conn.execute("""
        INSERT INTO signal_news
        (signal_id, sector, overall_sentiment, summary, key_articles, searched_stocks)
        VALUES (?, ?, ?, ?, ?, ?)
    """, (
        signal["id"], sector, overall, summary,
        json.dumps(all_articles, ensure_ascii=False),
        json.dumps(searched_names, ensure_ascii=False),
    ))
    conn.execute("UPDATE sector_signals SET processed = 1 WHERE id = ?", (signal["id"],))
    conn.commit()

    print(f"  完成: {overall} — {summary}", flush=True)
    conn.close()


if __name__ == "__main__":
    main()