alphax/app/cli.py

"""Unified CLI entrypoint for AlphaX Agent jobs."""

import argparse
import sys

from app.services import altcoin_confirm, altcoin_screener, event_driven_screener, live_trading_smoke, market_overview, onchain_monitor, paper_trader, price_streamer, price_tracker, review_engine, sentiment_monitor


def build_parser():
    parser = argparse.ArgumentParser(description="AlphaX Agent unified CLI")
    subparsers = parser.add_subparsers(dest="command", required=True)

    screener = subparsers.add_parser("screener", help="运行粗筛/细筛")
    screener.add_argument("--compact", action="store_true", help="输出紧凑 JSON")

    confirm = subparsers.add_parser("confirm", help="运行确认流程")
    confirm.add_argument("--compact", action="store_true", help="输出紧凑摘要 JSON")
    confirm.add_argument("--verbose", action="store_true", help="输出完整确认上下文，仅排查时使用")
    confirm.add_argument("--limit", type=int, default=None, help="本轮最多确认的候选数量")
    confirm.add_argument("--max-seconds", type=int, default=None, help="本轮最大运行秒数")

    tracker = subparsers.add_parser("tracker", help="运行价格跟踪")

    paper = subparsers.add_parser("paper-trader", help="运行模拟交易账本同步")
    paper.add_argument("--limit", type=int, default=100, help="本轮最多处理的可执行推荐数量")

    subparsers.add_parser("price-streamer", help="运行 websocket 实时价格流")
    subparsers.add_parser("market", help="采集全市场快照")

    review = subparsers.add_parser("review", help="运行复盘")
    review.add_argument("--compact", action="store_true", help="输出紧凑 JSON")
    review.add_argument("--no-push", action="store_true", help="只运行复盘，不发飞书")

    event = subparsers.add_parser("event", help="运行事件驱动筛选")
    event.add_argument("--no-process-existing", action="store_true", help="只处理本轮新采集事件")
    event.add_argument("--limit", type=int, default=None, help="单轮最多处理事件数")
    event.add_argument("--max-seconds", type=int, default=None, help="单轮最大运行秒数")

    sentiment = subparsers.add_parser("sentiment", help="运行舆情任务")
    sentiment.add_argument("--collect", action="store_true", help="采集并存储")
    sentiment.add_argument("--check", action="store_true", help="输出舆情异动")
    sentiment.add_argument("--scores", action="store_true", help="输出评分")

    onchain = subparsers.add_parser("onchain", help="运行链上追踪任务")
    onchain.add_argument("--limit", type=int, default=60, help="本轮最多处理的 token 映射数量")

    llm = subparsers.add_parser("llm-insights", help="异步生成 LLM 缓存解释")
    llm.add_argument("--scope", choices=["recommendations", "sentiment", "sentiment-events", "review"], default="recommendations")
    llm.add_argument("--limit", type=int, default=30)

    live_smoke = subparsers.add_parser("live-trading-smoke", help="运行 Binance 合约接口 smoke test")
    live_smoke.add_argument("--account-id", type=int, required=True, help="live_trade_accounts.id")
    live_smoke.add_argument("--symbol", default="BTC/USDT", help="测试交易对")
    live_smoke.add_argument("--notional-usdt", type=float, default=10.0, help="测试名义金额，默认 10U")
    live_smoke.add_argument("--leverage", type=float, default=1.0, help="测试杠杆，默认 1x")

    repair_strategy = subparsers.add_parser("repair-strategy-direction", help="修复策略方向与交易方向不一致的推荐数据")
    repair_strategy.add_argument("--limit", type=int, default=500, help="最多扫描的 recommendation 数量")
    repair_strategy.add_argument("--dry-run", action="store_true", help="只预览不写库")

    reset_strategy = subparsers.add_parser("reset-strategy-samples", help="清理已下线策略的历史样本")
    reset_strategy.add_argument("--scope", choices=["legacy-strategies"], required=True)
    reset_strategy.add_argument("--confirm", required=True, help="必须传 CLEAN_LEGACY_STRATEGY_SAMPLES")
    reset_strategy.add_argument("--no-backup", action="store_true", help="跳过 pg_dump 备份，仅用于测试")

    return parser


def main():
    parser = build_parser()
    args = parser.parse_args()

    if args.command == "screener":
        return altcoin_screener.main(compact=args.compact)
    if args.command == "confirm":
        return altcoin_confirm.main(compact=args.compact, verbose=args.verbose, limit=args.limit, max_seconds=args.max_seconds)
    if args.command == "tracker":
        return price_tracker.main()
    if args.command == "paper-trader":
        return paper_trader.main(limit=args.limit)
    if args.command == "price-streamer":
        return price_streamer.main()
    if args.command == "market":
        result = market_overview.collect_market_snapshot()
        print(sentiment_monitor.json.dumps(result, ensure_ascii=False, indent=2))
        return result
    if args.command == "review":
        return review_engine.run_review(push_enabled=not args.no_push, compact=args.compact)
    if args.command == "event":
        result = event_driven_screener.run_once(
            process_existing=not args.no_process_existing,
            limit=args.limit,
            max_seconds=args.max_seconds,
        )
        print(event_driven_screener.json.dumps(result, ensure_ascii=False, indent=2, default=str))
        return result
    if args.command == "sentiment":
        if args.collect:
            result = sentiment_monitor.collect_and_store()
            print(sentiment_monitor.json.dumps(result, ensure_ascii=False))
            return result
        if args.scores:
            result = sentiment_monitor.get_sentiment_scores()
            print(sentiment_monitor.json.dumps(result, ensure_ascii=False, indent=2))
            return result
        holdings = sentiment_monitor.get_active_holdings()
        alerts = sentiment_monitor.get_sentiment_alert(holdings=holdings)
        if args.check:
            print(sentiment_monitor.json.dumps(alerts, ensure_ascii=False, indent=2))
            return alerts
        result = {
            "alerts": alerts,
            "sentiment_scores": sentiment_monitor.get_sentiment_scores(),
            "holdings_count": len(holdings),
            "check_time": sentiment_monitor.datetime.now().isoformat(),
        }
        print(sentiment_monitor.json.dumps(result, ensure_ascii=False, indent=2))
        return result
    if args.command == "onchain":
        return onchain_monitor.run_once(limit=args.limit)
    if args.command == "llm-insights":
        from app.services import llm_insights

        result = llm_insights.run(scope=args.scope, limit=args.limit)
        print(sentiment_monitor.json.dumps(result, ensure_ascii=False, indent=2))
        return result
    if args.command == "live-trading-smoke":
        return live_trading_smoke.main(
            account_id=args.account_id,
            symbol=args.symbol,
            notional_usdt=args.notional_usdt,
            leverage=args.leverage,
        )
    if args.command == "repair-strategy-direction":
        from app.db.strategy_direction_repair import repair_strategy_direction_mismatches

        result = repair_strategy_direction_mismatches(limit=args.limit, dry_run=args.dry_run)
        print(sentiment_monitor.json.dumps(result, ensure_ascii=False, indent=2))
        return result
    if args.command == "reset-strategy-samples":
        from app.db.strategy_sample_cleanup import cleanup_legacy_strategy_samples

        result = cleanup_legacy_strategy_samples(confirm=args.confirm, create_backup=not args.no_backup)
        print(sentiment_monitor.json.dumps(result, ensure_ascii=False, indent=2))
        return result

    parser.error(f"unknown command: {args.command}")


if __name__ == "__main__":
    try:
        main()
    except Exception as exc:
        try:
            from app.db.system_logs import record_exception

            command = " ".join(sys.argv[1:]) or "unknown"
            record_exception(exc, source="cli", context={"argv": sys.argv, "command": command})
        except Exception:
            pass
        raise