migration: preserve screener and tracking slice

2026-07-31 03:57:07 +08:00
parent cf2aad28ec
commit 4bab921d14
28 changed files with 4810 additions and 4152 deletions
@@ -0,0 +1,146 @@
+from __future__ import annotations
+
+import json
+import time
+import urllib.error
+import urllib.request
+from typing import Any
+
+from screener import FACTOR_FIELDS, REGIMES
+
+
+class LLMCompilerError(RuntimeError):
+    pass
+
+
+def test_llm_connection(
+    api_key: str,
+    base_url: str,
+    model: str,
+    timeout: int = 30,
+) -> dict[str, Any]:
+    if not api_key or not model:
+        raise LLMCompilerError("API Key 或模型未配置。")
+    endpoint = f"{base_url.rstrip('/')}/chat/completions"
+    payload = json.dumps(
+        {
+            "model": model,
+            "messages": [{"role": "user", "content": "只回复 OK"}],
+            "stream": False,
+        },
+        ensure_ascii=False,
+    ).encode("utf-8")
+    request = urllib.request.Request(
+        endpoint,
+        data=payload,
+        headers={
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {api_key}",
+            "User-Agent": "XiaobaiReviewWeb/0.5",
+        },
+        method="POST",
+    )
+    started = time.perf_counter()
+    try:
+        with urllib.request.urlopen(request, timeout=timeout) as response:
+            result = json.loads(response.read().decode("utf-8"))
+        reply = str(result["choices"][0]["message"]["content"]).strip()
+    except urllib.error.HTTPError as exc:
+        raise LLMCompilerError(_http_error_message(exc)) from exc
+    except (urllib.error.URLError, TimeoutError, json.JSONDecodeError, KeyError, IndexError) as exc:
+        raise LLMCompilerError(f"模型连接测试失败：{exc}") from exc
+    return {
+        "ok": True,
+        "model": model,
+        "reply": reply[:100],
+        "latency_ms": round((time.perf_counter() - started) * 1000),
+    }
+
+
+def compile_strategy_with_llm(
+    prompt: str,
+    regime: str,
+    api_key: str,
+    base_url: str,
+    model: str,
+    timeout: int = 45,
+) -> dict[str, Any]:
+    if not api_key or not model:
+        raise LLMCompilerError("尚未配置 LLM API Key 或模型。")
+    endpoint = f"{base_url.rstrip('/')}/chat/completions"
+    schema = {
+        "name": "策略名称",
+        "description": "策略说明",
+        "regimes": [regime],
+        "formula": {
+            "universe": {"exclude_st": True, "listed_days_min": 120},
+            "filters": [{"field": "return_5d", "op": ">=", "value": 0}],
+            "score": [{"field": "sector_strength", "weight": 0.3, "direction": "desc"}],
+            "limit": 15,
+            "min_score": 0.55,
+        },
+    }
+    system_prompt = (
+        "你是A股量化策略编译器。只输出JSON对象，不输出Markdown。"
+        "不得生成Python、SQL、网络请求或未提供的因子。"
+        f"当前市场阶段为{REGIMES.get(regime, regime)}。"
+        f"可用因子为：{json.dumps(FACTOR_FIELDS, ensure_ascii=False)}。"
+        "运算符只能使用 >, >=, <, <=, ==, !=, between, in。"
+        "score权重均大于0且不超过1，direction只能是asc或desc。"
+        "退潮和冰点策略必须提高门槛并允许结果为空。"
+        f"严格遵循以下结构：{json.dumps(schema, ensure_ascii=False)}"
+    )
+    payload = json.dumps(
+        {
+            "model": model,
+            "messages": [
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": prompt[:3000]},
+            ],
+            "stream": False,
+        },
+        ensure_ascii=False,
+    ).encode("utf-8")
+    request = urllib.request.Request(
+        endpoint,
+        data=payload,
+        headers={
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {api_key}",
+            "User-Agent": "XiaobaiReviewWeb/0.4",
+        },
+        method="POST",
+    )
+    try:
+        with urllib.request.urlopen(request, timeout=timeout) as response:
+            result = json.loads(response.read().decode("utf-8"))
+        content = result["choices"][0]["message"]["content"].strip()
+        if content.startswith("```"):
+            content = content.strip("`")
+            if content.startswith("json"):
+                content = content[4:].strip()
+        compiled = json.loads(content)
+    except urllib.error.HTTPError as exc:
+        raise LLMCompilerError(_http_error_message(exc).replace("模型连接测试", "LLM 策略编译")) from exc
+    except (urllib.error.URLError, TimeoutError, json.JSONDecodeError, KeyError, IndexError) as exc:
+        raise LLMCompilerError(f"LLM 策略编译失败：{exc}") from exc
+    compiled["compiler"] = "llm"
+    compiled["model"] = model
+    return compiled
+
+
+def _http_error_message(exc: urllib.error.HTTPError) -> str:
+    detail = ""
+    try:
+        payload = json.loads(exc.read().decode("utf-8", errors="replace"))
+        error = payload.get("error")
+        if isinstance(error, dict):
+            detail = str(error.get("message") or error.get("code") or "")
+        elif error:
+            detail = str(error)
+        elif payload.get("message"):
+            detail = str(payload["message"])
+    except (json.JSONDecodeError, OSError):
+        detail = ""
+    suffix = f"：{detail[:300]}" if detail else ""
+    return f"模型连接测试失败（HTTP {exc.code}）{suffix}"