89 lines
3.9 KiB
Python
89 lines
3.9 KiB
Python
"""Unified CLI entrypoint for AlphaX Agent ｜ Crypto jobs."""
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import argparse
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from app.services import altcoin_confirm, altcoin_screener, event_driven_screener, price_tracker, review_engine, sentiment_monitor
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def build_parser():
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parser = argparse.ArgumentParser(description="AlphaX Agent ｜ Crypto unified CLI")
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subparsers = parser.add_subparsers(dest="command", required=True)
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screener = subparsers.add_parser("screener", help="运行粗筛/细筛")
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screener.add_argument("--compact", action="store_true", help="输出紧凑 JSON")
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confirm = subparsers.add_parser("confirm", help="运行确认流程")
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confirm.add_argument("--compact", action="store_true", help="输出紧凑 JSON")
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tracker = subparsers.add_parser("tracker", help="运行价格跟踪")
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review = subparsers.add_parser("review", help="运行复盘")
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review.add_argument("--compact", action="store_true", help="输出紧凑 JSON")
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review.add_argument("--no-push", action="store_true", help="只运行复盘，不发飞书")
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event = subparsers.add_parser("event", help="运行事件驱动筛选")
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event.add_argument("--no-process-existing", action="store_true", help="只处理本轮新采集事件")
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sentiment = subparsers.add_parser("sentiment", help="运行舆情任务")
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sentiment.add_argument("--collect", action="store_true", help="采集并存储")
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sentiment.add_argument("--check", action="store_true", help="输出舆情异动")
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sentiment.add_argument("--scores", action="store_true", help="输出评分")
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llm = subparsers.add_parser("llm-insights", help="异步生成 LLM 缓存解释")
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llm.add_argument("--scope", choices=["recommendations", "sentiment", "sentiment-events", "review"], default="recommendations")
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llm.add_argument("--limit", type=int, default=30)
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return parser
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def main():
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parser = build_parser()
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args = parser.parse_args()
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if args.command == "screener":
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return altcoin_screener.main(compact=args.compact)
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if args.command == "confirm":
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return altcoin_confirm.main(compact=args.compact)
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if args.command == "tracker":
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return price_tracker.main()
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if args.command == "review":
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return review_engine.run_review(push_enabled=not args.no_push, compact=args.compact)
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if args.command == "event":
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result = event_driven_screener.run_once(process_existing=not args.no_process_existing)
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print(event_driven_screener.json.dumps(result, ensure_ascii=False, indent=2, default=str))
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return result
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if args.command == "sentiment":
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if args.collect:
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result = sentiment_monitor.collect_and_store()
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print(sentiment_monitor.json.dumps(result, ensure_ascii=False))
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return result
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if args.scores:
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result = sentiment_monitor.get_sentiment_scores()
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print(sentiment_monitor.json.dumps(result, ensure_ascii=False, indent=2))
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return result
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holdings = sentiment_monitor.get_active_holdings()
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alerts = sentiment_monitor.get_sentiment_alert(holdings=holdings)
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if args.check:
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print(sentiment_monitor.json.dumps(alerts, ensure_ascii=False, indent=2))
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return alerts
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result = {
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"alerts": alerts,
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"sentiment_scores": sentiment_monitor.get_sentiment_scores(),
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"holdings_count": len(holdings),
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"check_time": sentiment_monitor.datetime.now().isoformat(),
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}
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print(sentiment_monitor.json.dumps(result, ensure_ascii=False, indent=2))
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return result
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if args.command == "llm-insights":
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from app.services import llm_insights
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result = llm_insights.run(scope=args.scope, limit=args.limit)
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print(sentiment_monitor.json.dumps(result, ensure_ascii=False, indent=2))
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return result
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parser.error(f"unknown command: {args.command}")
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if __name__ == "__main__":
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main()
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