dekun
840e88daad
Key monitors use 5m close triggers with WeChat alerts and box/convergence auto orders; add pending-order worker, structured WeChat notify, AI settings/messages, session clock, CTP margin sizing, and dual-layer position limits. Co-authored-by: Cursor <cursoragent@cursor.com>
103 lines
4.0 KiB
Python
103 lines
4.0 KiB
Python
# Copyright (c) 2025-2026 马建军. All rights reserved.
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# 专有软件 — 未经授权禁止复制、传播、转售。
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# 严禁用于：带单/代客理财、向他人推荐期货品种或买卖建议、融资配资等业务。
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# 详见 LICENSE.zh-CN.txt 与 docs/软件购买与使用协议.md
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"""AI 接口：Ollama / OpenAI 兼容 API。"""
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from __future__ import annotations
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import json
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import logging
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from typing import Callable, Optional
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import requests
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logger = logging.getLogger(__name__)
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def is_ai_enabled(get_setting: Callable[[str, str], str]) -> bool:
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return (get_setting("ai_enabled", "0") or "0").strip() in ("1", "true", "yes")
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def get_ai_config(get_setting: Callable[[str, str], str]) -> dict:
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provider = (get_setting("ai_provider", "ollama") or "ollama").strip().lower()
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if provider not in ("ollama", "openai"):
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provider = "ollama"
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return {
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"enabled": is_ai_enabled(get_setting),
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"provider": provider,
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"ollama_base_url": (get_setting("ai_ollama_base_url", "http://127.0.0.1:11434") or "").strip().rstrip("/"),
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"ollama_model": (get_setting("ai_ollama_model", "qwen2.5:7b") or "qwen2.5:7b").strip(),
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"openai_base_url": (get_setting("ai_openai_base_url", "https://api.openai.com/v1") or "").strip().rstrip("/"),
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"openai_api_key": (get_setting("ai_openai_api_key", "") or "").strip(),
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"openai_model": (get_setting("ai_openai_model", "gpt-4o-mini") or "gpt-4o-mini").strip(),
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}
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def chat_completion(
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*,
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get_setting: Callable[[str, str], str],
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system_prompt: str,
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user_prompt: str,
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timeout: int = 120,
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) -> tuple[bool, str]:
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cfg = get_ai_config(get_setting)
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if not cfg["enabled"]:
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return False, "AI 未启用"
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provider = cfg["provider"]
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try:
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if provider == "ollama":
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url = f"{cfg['ollama_base_url']}/api/chat"
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payload = {
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"model": cfg["ollama_model"],
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"messages": [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt},
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],
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"stream": False,
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}
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resp = requests.post(url, json=payload, timeout=timeout)
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resp.raise_for_status()
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data = resp.json()
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msg = (data.get("message") or {}).get("content") or ""
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return True, (msg or "").strip() or "（AI 无回复）"
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url = f"{cfg['openai_base_url']}/chat/completions"
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headers = {
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"Authorization": f"Bearer {cfg['openai_api_key']}",
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"Content-Type": "application/json",
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}
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payload = {
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"model": cfg["openai_model"],
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"messages": [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt},
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],
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"temperature": 0.4,
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}
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resp = requests.post(url, headers=headers, json=payload, timeout=timeout)
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resp.raise_for_status()
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data = resp.json()
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choices = data.get("choices") or []
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if not choices:
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return False, "AI 返回为空"
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msg = (choices[0].get("message") or {}).get("content") or ""
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return True, (msg or "").strip() or "（AI 无回复）"
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except Exception as exc:
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logger.warning("AI chat failed (%s): %s", provider, exc)
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return False, f"AI 调用失败：{exc}"
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def analyze_trading_event(
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*,
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get_setting: Callable[[str, str], str],
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event_kind: str,
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payload: dict,
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) -> tuple[bool, str]:
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system = (
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"你是国内期货交易复盘助手。根据提供的结构化交易数据，"
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"用简洁中文给出 3～6 条要点：风险、纪律、改进建议。"
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"不要编造未提供的数据；金额单位为元。"
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)
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user = f"事件类型：{event_kind}\n\n数据：\n{json.dumps(payload, ensure_ascii=False, indent=2)}"
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return chat_completion(get_setting=get_setting, system_prompt=system, user_prompt=user)
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