112 lines
4.4 KiB
Python
112 lines
4.4 KiB
Python
"""Service entrypoint for smart executor workflows."""
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from __future__ import annotations
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import os
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import sys
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from .. import smart_executor as smart_executor_module
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def run(argv: list[str] | None = None) -> int:
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argv = list(sys.argv[1:] if argv is None else argv)
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args, normalized_argv = smart_executor_module.parse_cli_args(argv)
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action = args.command.replace("-", "_")
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argv_tail = smart_executor_module.cli_action_args(args, action)
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decision_id = (
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args.decision_id
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or os.getenv("DECISION_ID")
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or smart_executor_module.default_decision_id(action, normalized_argv)
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)
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if args.dry_run:
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smart_executor_module.DRY_RUN = True
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previous = smart_executor_module.get_execution_state(decision_id)
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read_only_action = action in {"balance", "balances", "status"}
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if previous and previous.get("status") == "success" and not read_only_action:
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smart_executor_module.log(f"⚠️ decision_id={decision_id} 已执行成功，跳过重复执行")
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return 0
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try:
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ex = smart_executor_module.get_exchange()
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if read_only_action:
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if action in {"balance", "balances"}:
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smart_executor_module.command_balances(ex)
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else:
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smart_executor_module.command_status(ex)
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return 0
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decision_context = smart_executor_module.build_decision_context(ex, action, argv_tail, decision_id)
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if args.analysis:
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decision_context["analysis"] = args.analysis
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elif os.getenv("DECISION_ANALYSIS"):
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decision_context["analysis"] = os.getenv("DECISION_ANALYSIS")
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if args.reasoning:
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decision_context["reasoning"] = args.reasoning
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elif os.getenv("DECISION_REASONING"):
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decision_context["reasoning"] = os.getenv("DECISION_REASONING")
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smart_executor_module.record_execution_state(
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decision_id,
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{"status": "pending", "started_at": smart_executor_module.bj_now_iso(), "action": action, "args": argv_tail},
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)
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if action == "sell_all":
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result = smart_executor_module.action_sell_all(ex, args.symbol, decision_id, decision_context)
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elif action == "buy":
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result = smart_executor_module.action_buy(ex, args.symbol, float(args.amount_usdt), decision_id, decision_context)
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elif action == "rebalance":
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result = smart_executor_module.action_rebalance(ex, args.from_symbol, args.to_symbol, decision_id, decision_context)
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elif action == "hold":
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balances = smart_executor_module.fetch_balances(ex)
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positions = smart_executor_module.load_positions()
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market_snapshot = smart_executor_module.build_market_snapshot(ex)
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smart_executor_module.log_decision(
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{
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**decision_context,
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"balances_after": balances,
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"positions_after": positions,
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"market_snapshot": market_snapshot,
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"analysis": decision_context.get("analysis", "hold"),
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"reasoning": decision_context.get("reasoning", "hold"),
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"execution_result": {"status": "hold"},
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}
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)
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smart_executor_module.log("😴 决策: 持续持有，无操作")
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result = {"status": "hold"}
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else:
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raise RuntimeError(f"未知动作: {action}；请运行 --help 查看正确 CLI 用法")
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smart_executor_module.record_execution_state(
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decision_id,
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{
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"status": "success",
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"finished_at": smart_executor_module.bj_now_iso(),
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"action": action,
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"args": argv_tail,
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"result": result,
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},
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)
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smart_executor_module.log(f"✅ 执行完成 decision_id={decision_id}")
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return 0
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except Exception as exc:
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smart_executor_module.record_execution_state(
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decision_id,
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{
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"status": "failed",
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"finished_at": smart_executor_module.bj_now_iso(),
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"action": action,
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"args": argv_tail,
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"error": str(exc),
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},
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)
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smart_executor_module.log_error(
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"smart_executor",
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exc,
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decision_id=decision_id,
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action=action,
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args=argv_tail,
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)
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smart_executor_module.log(f"❌ 执行失败: {exc}")
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return 1
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