mirror of
https://ghfast.top/https://github.com/aeroxw/tick-stock-panel.git
synced 2026-09-12 16:44:15 +08:00
shy3130
697c27bb02
- 市场环境: 新增情绪周期6阶段(冰点/启动/主升/高潮/退潮/修复, 连板梯队驱动, EMA平滑+2日确认+弱档否决, 平均段长9.7天)与概念/行业主线排名(涨停梯队聚合, 可配置宽基/风格标签过滤); 市场环境页重构, regime 透明加列, 与5档state并存 - 挖掘: 因子与策略挖掘全链路(API/worker/进程锁/候选库/前端工作台/文档), 周度调度默认关闭且永不自动发布 - 回测: 财务快照因子(点时口径), 批量回测预计算共享下期收益, 信号路径矩阵列依赖展开修复(consecutive_limit_ups 缺列报错) - 数据/性能: enriched 生成与预热治理, 重任务限流, 行情/K线缓存复用, 时区修复 - 测试: 后端全量 914 通过; GUI 黑盒验证截图存证 gui-test-screenshots/
432 lines
18 KiB
Python
432 lines
18 KiB
Python
"""AI 策略生成器 — 读取策略开发文档 + 调用 LLM 生成策略代码。
|
||
|
||
职责: 接收用户自然语言描述 → 读取 prompts/strategy-guide.md → 调用 LLM → 返回策略代码。
|
||
不知道: 引擎内部、API、前端、配置持久化、回测。
|
||
"""
|
||
from __future__ import annotations
|
||
|
||
import ast
|
||
import logging
|
||
import math
|
||
import re
|
||
from pathlib import Path
|
||
|
||
from app.indicators.pipeline import ENRICHED_COLUMNS
|
||
from app.strategy.scoring import VIRTUAL_SCORING_DEPENDENCIES
|
||
|
||
logger = logging.getLogger(__name__)
|
||
|
||
# 策略开发精简指南路径 (随 backend/app 打包进 Docker, 避免 .dockerignore 排除 docs/ 导致运行时缺失)
|
||
GUIDE_PATH = Path(__file__).resolve().parent / "prompts" / "strategy-guide-compact.md"
|
||
|
||
_SYSTEM_PREFIX = """你是A股量化策略设计专家。根据用户描述的需求，参考下方的《策略开发指南》生成一个完整的策略Python文件。
|
||
|
||
文件与范围铁律（不可违反）:
|
||
1. 只创建这一个策略文件：只生成一个 .py 文件，绝不创建多文件、不拆分模块、不跨文件引用
|
||
2. 绝不触碰项目源码：不要写任何会修改 backend/、docs/、frontend/ 等现有文件的代码；不要 import os/sys/pathlib 等文件系统模块
|
||
3. 不得放入内置策略目录：AI 生成的策略只属于 data/strategies/ai/，文件名/ID 用 ai_ 前缀；内置目录 backend/app/strategy/builtin/ 由项目维护，AI 不得染指
|
||
4. polars 策略只 import polars 和 datetime；matrix_native 策略只允许 import numpy 以及 from app.backtest.matrix import 所需矩阵协议和算子
|
||
|
||
要求:
|
||
1. 用户可能调整的策略阈值通过 META["params"] 暴露，每项使用 id/label/type/default/min/max/step；公式常数、固定窗口边界、布尔开关不必强行参数化
|
||
2. 遵循指南中的文件结构，但优先贴合用户规则，不要为了套模板歪曲策略含义
|
||
3. ENTRY_SIGNALS/EXIT_SIGNALS 根据策略逻辑自行选择匹配的信号列，不要照搬示例
|
||
4. scoring 权重根据策略核心逻辑定制，总和 = 1.0；键只能使用指南中的真实数值字段或受控虚拟评分字段 ma20_bias，不得创造条件名称作为评分列
|
||
5. 优先使用 Polars 表达式、窗口函数、聚合和 with_columns/filter 实现，避免逐行/逐股 Python 循环；只有表达式难以描述的复杂状态机才使用 partition_by/to_dicts
|
||
6. 直接输出Python代码，不要输出其他内容
|
||
7. 元数据必须使用模块顶层的 META = {...} 或 META: dict = {...}，不得省略或改名；并且必须定义所选执行后端要求的策略入口
|
||
|
||
--- 策略开发指南 ---
|
||
|
||
"""
|
||
|
||
_META_NAMES = ("META", "STRATEGY_META", "meta")
|
||
_FENCED_CODE_RE = re.compile(
|
||
r"```(?P<language>[^\n`]*)\r?\n(?P<code>.*?)```",
|
||
re.DOTALL,
|
||
)
|
||
_POLARS_ENTRYPOINT_ERROR = "找不到策略入口函数 filter() 或 filter_history()"
|
||
_MATRIX_ENTRYPOINT_ERROR = "找不到 Matrix 策略入口 MATRIX_STRATEGY"
|
||
|
||
_POLARS_SCORING_FIELDS = frozenset(
|
||
name
|
||
for name in ENRICHED_COLUMNS
|
||
if name not in {"symbol", "date", "name"} and not name.startswith("signal_")
|
||
) | frozenset(VIRTUAL_SCORING_DEPENDENCIES)
|
||
_MATRIX_SCORING_FIELDS = frozenset({
|
||
"open", "high", "low", "close", "volume", "amount", "turnover_rate",
|
||
"total_shares", "float_shares", "consecutive_limit_ups",
|
||
"consecutive_limit_downs", "prev_close", "change_pct", "change_amount",
|
||
"amplitude", "ma5", "ma10", "ma20", "ma30", "ma60", "boll_upper",
|
||
"boll_lower", "high_60d", "low_60d", "momentum_5d", "momentum_10d",
|
||
"momentum_20d", "momentum_30d", "momentum_60d", "annual_vol_20d",
|
||
"rsi_6", "rsi_14", "rsi_24", "vol_ratio_5d", "ma20_bias",
|
||
})
|
||
|
||
|
||
def _top_level_assignment(
|
||
tree: ast.Module,
|
||
name: str,
|
||
) -> tuple[ast.Name, ast.expr | None] | None:
|
||
for node in tree.body:
|
||
if isinstance(node, ast.Assign):
|
||
target = next(
|
||
(item for item in node.targets
|
||
if isinstance(item, ast.Name) and item.id == name),
|
||
None,
|
||
)
|
||
if target is not None:
|
||
return target, node.value
|
||
elif isinstance(node, ast.AnnAssign) \
|
||
and isinstance(node.target, ast.Name) \
|
||
and node.target.id == name:
|
||
return node.target, node.value
|
||
return None
|
||
|
||
|
||
def find_meta_assignment(code: str) -> tuple[ast.Name, ast.Dict] | None:
|
||
"""Find a supported module-level META assignment without executing code."""
|
||
tree = ast.parse(code)
|
||
for name in _META_NAMES:
|
||
found = _top_level_assignment(tree, name)
|
||
if found is not None:
|
||
target, value = found
|
||
if not isinstance(value, ast.Dict):
|
||
raise ValueError(f"{name} 必须是字面量字典")
|
||
return target, value
|
||
return None
|
||
|
||
|
||
def _strategy_execution_backend(tree: ast.Module, meta: dict | None = None) -> str:
|
||
found = _top_level_assignment(tree, "EXECUTION_BACKEND")
|
||
if found is not None:
|
||
try:
|
||
value = ast.literal_eval(found[1])
|
||
except (ValueError, SyntaxError):
|
||
value = None
|
||
if isinstance(value, str):
|
||
return value
|
||
if isinstance(meta, dict) and isinstance(meta.get("execution_backend"), str):
|
||
return meta["execution_backend"]
|
||
if any(
|
||
isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef))
|
||
and node.name == "filter_history"
|
||
for node in tree.body
|
||
):
|
||
return "python_history_legacy"
|
||
return "polars_expr"
|
||
|
||
|
||
def _strategy_entrypoint_error(code: str, meta: dict | None = None) -> str | None:
|
||
tree = ast.parse(code)
|
||
if _strategy_execution_backend(tree, meta) == "matrix_native":
|
||
return None if _top_level_assignment(tree, "MATRIX_STRATEGY") else _MATRIX_ENTRYPOINT_ERROR
|
||
has_polars_entrypoint = any(
|
||
isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef))
|
||
and node.name in {"filter", "filter_history"}
|
||
for node in tree.body
|
||
)
|
||
return None if has_polars_entrypoint else _POLARS_ENTRYPOINT_ERROR
|
||
|
||
|
||
class AIStrategyGenerator:
|
||
"""AI 策略生成器"""
|
||
|
||
def __init__(self) -> None:
|
||
self._guide_cache: str | None = None
|
||
|
||
def _get_guide(self) -> str:
|
||
if self._guide_cache is None:
|
||
if GUIDE_PATH.exists():
|
||
self._guide_cache = GUIDE_PATH.read_text(encoding="utf-8")
|
||
else:
|
||
logger.warning("strategy guide not found at %s", GUIDE_PATH)
|
||
self._guide_cache = ""
|
||
return self._guide_cache
|
||
|
||
async def generate(self, user_prompt: str) -> dict:
|
||
"""根据用户描述生成策略代码
|
||
|
||
Returns: {"code": str, "meta": dict, "valid": bool, "error": str | None}
|
||
"""
|
||
guide = self._get_guide()
|
||
|
||
# 调用 LLM
|
||
code = await self._call_llm(user_prompt, guide)
|
||
result = self.validate_code(code)
|
||
if self.needs_structural_repair(result):
|
||
return await self.repair_code(result["code"], result["error"])
|
||
return result
|
||
|
||
async def stream(self, user_prompt: str):
|
||
"""Yield generated strategy code deltas from the configured AI provider."""
|
||
from app.services.ai_provider import stream_ai_text
|
||
|
||
guide = self._get_guide()
|
||
async for chunk in stream_ai_text(
|
||
[
|
||
{"role": "system", "content": _SYSTEM_PREFIX + guide},
|
||
{"role": "user", "content": user_prompt},
|
||
],
|
||
temperature=0.3,
|
||
max_tokens=3000,
|
||
):
|
||
yield chunk
|
||
|
||
def validate_code(self, code: str) -> dict:
|
||
code = self._extract_code_block(code)
|
||
|
||
# 验证
|
||
try:
|
||
self._validate_safety(code)
|
||
except SyntaxError as e:
|
||
return {
|
||
"code": code,
|
||
"meta": {},
|
||
"valid": False,
|
||
"error": f"Python 语法错误: {e.msg}",
|
||
}
|
||
except ValueError as e:
|
||
return {
|
||
"code": code,
|
||
"meta": {},
|
||
"valid": False,
|
||
"error": str(e),
|
||
}
|
||
|
||
# 试加载获取 META
|
||
try:
|
||
meta = self._extract_meta(code)
|
||
except Exception as e:
|
||
return {
|
||
"code": code,
|
||
"meta": {},
|
||
"valid": False,
|
||
"error": f"解析META失败: {e}",
|
||
}
|
||
|
||
entrypoint_error = _strategy_entrypoint_error(code, meta)
|
||
if entrypoint_error:
|
||
return {
|
||
"code": code,
|
||
"meta": meta,
|
||
"valid": False,
|
||
"error": entrypoint_error,
|
||
}
|
||
|
||
try:
|
||
self._validate_meta_semantics(code, meta)
|
||
except ValueError as e:
|
||
return {
|
||
"code": code,
|
||
"meta": meta,
|
||
"valid": False,
|
||
"error": str(e),
|
||
}
|
||
|
||
return {
|
||
"code": code,
|
||
"meta": meta,
|
||
"valid": True,
|
||
"error": None,
|
||
}
|
||
|
||
@staticmethod
|
||
def needs_structural_repair(result: dict) -> bool:
|
||
error = result.get("error") or ""
|
||
return error.startswith("解析META失败:") or error in {
|
||
_POLARS_ENTRYPOINT_ERROR,
|
||
_MATRIX_ENTRYPOINT_ERROR,
|
||
} or error.startswith(("META.params", "META.scoring"))
|
||
|
||
@staticmethod
|
||
def _validate_meta_semantics(code: str, meta: dict) -> None:
|
||
params = meta.get("params", [])
|
||
if isinstance(params, (list, tuple)):
|
||
for index, item in enumerate(params):
|
||
if isinstance(item, dict) and not str(item.get("id") or "").strip():
|
||
raise ValueError(f"META.params[{index}] 缺少非空 id")
|
||
|
||
scoring = meta.get("scoring", {})
|
||
if not isinstance(scoring, dict):
|
||
raise ValueError("META.scoring 必须是字典")
|
||
if not scoring:
|
||
return
|
||
|
||
for name, weight in scoring.items():
|
||
if not isinstance(name, str) or not name:
|
||
raise ValueError("META.scoring 字段名必须是非空字符串")
|
||
if isinstance(weight, bool) or not isinstance(weight, (int, float)) \
|
||
or not math.isfinite(float(weight)) or weight < 0:
|
||
raise ValueError(f"META.scoring[{name!r}] 权重必须是非负有限数值")
|
||
total_weight = sum(float(weight) for weight in scoring.values())
|
||
if not math.isclose(total_weight, 1.0, rel_tol=0.0, abs_tol=1e-6):
|
||
raise ValueError("META.scoring 权重总和必须为 1.0")
|
||
|
||
backend = _strategy_execution_backend(ast.parse(code), meta)
|
||
if backend == "python_history_legacy":
|
||
return
|
||
allowed = _MATRIX_SCORING_FIELDS if backend == "matrix_native" else _POLARS_SCORING_FIELDS
|
||
unknown = sorted(set(scoring) - set(allowed))
|
||
if unknown:
|
||
raise ValueError(
|
||
f"META.scoring 引用了不可用字段: {unknown}; "
|
||
"请使用真实数值字段或受控虚拟字段 ma20_bias"
|
||
)
|
||
|
||
async def repair_code(self, code: str, error: str) -> dict:
|
||
"""Ask the model once for a complete replacement after a structural error."""
|
||
try:
|
||
backend = _strategy_execution_backend(ast.parse(code))
|
||
except SyntaxError:
|
||
backend = "polars_expr"
|
||
if backend == "matrix_native":
|
||
entrypoint_requirement = (
|
||
'保留 EXECUTION_BACKEND = "matrix_native"，定义 MATRIX_STRATEGY，'
|
||
"不得添加 filter() 或 filter_history()"
|
||
)
|
||
else:
|
||
entrypoint_requirement = (
|
||
"保留原执行后端，并定义对应的 filter() 或 filter_history()"
|
||
)
|
||
prompt = f"""上一次生成的策略代码未通过结构校验。
|
||
|
||
校验错误：{error}
|
||
|
||
请输出修复后的完整策略 Python 文件。必须保留原策略意图和参数，使用模块顶层
|
||
META = {{...}}，{entrypoint_requirement}。只输出完整 Python 代码。
|
||
|
||
上一次代码：
|
||
```python
|
||
{code}
|
||
```"""
|
||
repaired = await self._call_llm(prompt, self._get_guide())
|
||
return self.validate_code(repaired)
|
||
|
||
async def _call_llm(self, user_prompt: str, guide: str) -> str:
|
||
"""Call the configured AI provider and return generated strategy code."""
|
||
from app.services.ai_provider import generate_ai_text
|
||
|
||
content = await generate_ai_text(
|
||
[
|
||
{"role": "system", "content": _SYSTEM_PREFIX + guide},
|
||
{"role": "user", "content": user_prompt},
|
||
],
|
||
temperature=0.3,
|
||
max_tokens=3000,
|
||
)
|
||
return self._extract_code_block(content)
|
||
|
||
@staticmethod
|
||
def _extract_code_block(content: str) -> str:
|
||
blocks = list(_FENCED_CODE_RE.finditer(content))
|
||
for match in blocks:
|
||
candidate = match.group("code").strip()
|
||
try:
|
||
found = find_meta_assignment(candidate)
|
||
if found is not None:
|
||
meta = ast.literal_eval(found[1])
|
||
if isinstance(meta, dict) and _strategy_entrypoint_error(candidate, meta) is None:
|
||
return candidate
|
||
except (SyntaxError, ValueError):
|
||
continue
|
||
for match in blocks:
|
||
if match.group("language").strip().lower() in {"python", "py"}:
|
||
return match.group("code").strip()
|
||
if blocks:
|
||
return blocks[0].group("code").strip()
|
||
return content.strip()
|
||
|
||
# import 白名单: Polars 与矩阵策略只开放执行协议所需模块。
|
||
# 白名单而非黑名单 — 黑名单挡不住 ctypes/importlib/builtins/pickle 等未列出的危险模块。
|
||
_ALLOWED_IMPORT_MODULES = frozenset({
|
||
"polars",
|
||
"numpy",
|
||
"app.backtest.matrix",
|
||
"app.strategy.builtin.factor_rank_research",
|
||
"datetime",
|
||
"__future__",
|
||
})
|
||
|
||
@classmethod
|
||
def _validate_safety(
|
||
cls,
|
||
code: str,
|
||
*,
|
||
extra_allowed_import_modules: frozenset[str] = frozenset(),
|
||
extra_allowed_calls: frozenset[str] = frozenset(),
|
||
) -> None:
|
||
"""AST 级安全检查: import 白名单 + 危险内建调用拦截 + dunder 遍历拦截。
|
||
|
||
注意: AST 名单不是真正的沙箱, 只能拦截常见攻击模式。真正的隔离需要
|
||
在受限子进程里执行策略 (后续 P0)。此处拦截已知的逃逸技巧:
|
||
- __globals__ / __builtins__ / __class__ / __subclasses__ / __mro__ 等属性访问
|
||
- ["__import__"] / ["__builtins__"] 等字符串下标访问
|
||
"""
|
||
tree = ast.parse(code)
|
||
|
||
allowed_import_modules = cls._ALLOWED_IMPORT_MODULES | extra_allowed_import_modules
|
||
forbidden_calls = {
|
||
"open", "exec", "eval", "compile", "__import__",
|
||
"globals", "locals", "vars", "dir", "getattr",
|
||
"setattr", "delattr", "type", "input", "breakpoint",
|
||
} - extra_allowed_calls
|
||
|
||
def _module_allowed(module: str) -> bool:
|
||
return (
|
||
module in allowed_import_modules
|
||
or module.split(".", 1)[0] in allowed_import_modules
|
||
)
|
||
|
||
# dunder 属性名: 访问这些属性可逃逸出策略沙箱拿到 os/subprocess 等
|
||
forbidden_dunder_attrs = {
|
||
"__globals__", "__builtins__", "__class__", "__subclasses__",
|
||
"__mro__", "__bases__", "__base__", "__dict__", "__code__",
|
||
"__import__", "__loader__", "__spec__", "__wrapped__",
|
||
}
|
||
# 字符串下标访问的危险名: x["__builtins__"] / x["__import__"]
|
||
forbidden_subscript_strs = {
|
||
"__builtins__", "__import__", "__globals__",
|
||
}
|
||
|
||
for node in ast.walk(tree):
|
||
if isinstance(node, ast.Import):
|
||
for alias in node.names:
|
||
if not _module_allowed(alias.name):
|
||
raise ValueError(f"禁止 import {alias.name} (不在策略安全白名单)")
|
||
if isinstance(node, ast.ImportFrom):
|
||
mod = node.module or ""
|
||
if not _module_allowed(mod):
|
||
raise ValueError(f"禁止 from {node.module} import (不在策略安全白名单)")
|
||
if isinstance(node, ast.Call):
|
||
if isinstance(node.func, ast.Name) and node.func.id in forbidden_calls:
|
||
raise ValueError(f"禁止调用 {node.func.id}()")
|
||
# 拦截 dunder 属性访问: x.__globals__ / ().__class__ 等
|
||
if isinstance(node, ast.Attribute) and node.attr in forbidden_dunder_attrs:
|
||
raise ValueError(f"禁止访问属性 {node.attr} (策略不允许 dunder 遍历逃逸)")
|
||
# 拦截字符串下标访问危险名: x["__builtins__"]
|
||
if isinstance(node, ast.Subscript):
|
||
sl = node.slice
|
||
if isinstance(sl, ast.Constant) and isinstance(sl.value, str) \
|
||
and sl.value in forbidden_subscript_strs:
|
||
raise ValueError(f"禁止下标访问 {sl.value} (策略不允许 dunder 遍历逃逸)")
|
||
|
||
@staticmethod
|
||
def _extract_meta(code: str) -> dict:
|
||
"""从代码字符串中提取 META 字典（不执行代码, 仅接受字面量）
|
||
|
||
兼容两种声明: META = {...} (Assign) 和 META: dict = {...} (AnnAssign)。
|
||
与 api.strategy._find_meta_dict 保持同一套匹配逻辑。
|
||
"""
|
||
found = find_meta_assignment(code)
|
||
if found is None:
|
||
raise ValueError("找不到 META 字典")
|
||
_, value = found
|
||
try:
|
||
meta = ast.literal_eval(value)
|
||
except (ValueError, SyntaxError) as e:
|
||
raise ValueError(f"META 必须是纯字面量字典: {e}") from e
|
||
if not isinstance(meta, dict):
|
||
raise ValueError("META 必须是纯字面量字典")
|
||
return meta
|