yuxuanhui
149 lines
5.0 KiB
Python
149 lines
5.0 KiB
Python
"""Domain-owned AI capabilities; caller owns authorization and transactions."""
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from pydantic import Field
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from ..schemas import AlphaFilters, BulkInput, BulkUpdate, Contract, ResearchInput, ResearchUpdate
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from .capabilities import Capability, EmptyArgs
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class SearchArgs(Contract):
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filters: AlphaFilters = Field(default_factory=AlphaFilters)
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class AlphaArgs(Contract):
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alpha_id: str = Field(min_length=1, max_length=100, pattern=r"^[A-Za-z0-9_-]+$")
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class ResearchArgs(AlphaArgs):
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changes: ResearchInput
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async def search(ctx, args):
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data = await ctx.business.search_alphas(args.filters)
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return {**data, "filters": args.filters.model_dump(mode="json")}
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async def pnl(ctx, args):
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data = await ctx.business.get_alpha_pnl(args.alpha_id)
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points = data.pop("points")
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# Chart data is fetched by the UI; keep large series out of model context.
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series = data.pop("series", [])
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return {
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**data,
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"alpha_id": args.alpha_id,
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"count": len(points),
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"series": [{"id": item["id"], "label": item["label"]} for item in series],
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"first": points[0] if points else None,
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"last": points[-1] if points else None,
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"null_count": sum(p["value"] is None for p in points),
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}
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async def research_preview(ctx, ids, changes):
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"""Fix before/after values and versions using the same validation as execution."""
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targets, versions = [], {}
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for alpha_id in ids:
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before = (await ctx.business.get_alpha(alpha_id))["research"]
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after = {**before, **changes(before)}
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ResearchInput.model_validate({k: after[k] for k in ("note", "tags", "favorite", "state")})
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targets.append({"alpha_id": alpha_id, "before": before, "after": after})
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versions[alpha_id] = before["version"]
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return {"targets": targets, "versions": versions}
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async def preview_research(ctx, args):
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return await research_preview(
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ctx, [args.alpha_id], lambda before: args.changes.model_dump(exclude_unset=True)
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)
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async def preview_bulk(ctx, args):
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return await research_preview(
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ctx,
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args.alpha_ids,
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lambda before: {
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"tags": sorted((set(before["tags"]) | set(args.add_tags)) - set(args.remove_tags)),
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**({"state": args.state} if args.state else {}),
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},
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)
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async def update_research(ctx, args, preview):
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return await ctx.business.update_research(
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args.alpha_id,
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ResearchUpdate(
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**args.changes.model_dump(exclude_unset=True), version=preview["versions"][args.alpha_id]
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),
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)
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async def update_bulk(ctx, args, preview):
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return await ctx.business.bulk_update_research(
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BulkUpdate(**args.model_dump(), versions=preview["versions"])
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)
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INSTRUCTIONS = "缺失指标保持未知；Turnover 0.15 表示15%。陈述依据、Alpha ID 和数据时间，区分当前页与全部结果。\n只传需要修改的研究字段。批量操作固定ID，最多100个。不要自行扩大选中范围。"
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CAPABILITIES = (
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Capability(
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name="search_alphas",
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schema=SearchArgs,
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description="按明确筛选条件查询本地 Alpha。Turnover 0.15 表示 15%；支持分页，禁止把当前页当作全部结果。",
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label="查询 Alpha",
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renderer="alpha",
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effect="query",
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handler=search,
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),
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Capability(
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name="get_alpha_facets",
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schema=EmptyArgs,
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description="获取可用地区、类型、状态、标签与本地 Alpha 总数。",
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label="查询筛选选项",
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renderer="alpha",
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effect="query",
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handler=lambda ctx, args: ctx.business.get_alpha_facets(),
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),
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Capability(
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name="get_alpha",
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schema=AlphaArgs,
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description="读取指定 Alpha 的表达式、指标、已有检查和本地研究记录。",
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label="读取 Alpha",
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renderer="alpha",
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effect="query",
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handler=lambda ctx, args: ctx.business.get_alpha(args.alpha_id),
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),
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Capability(
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name="get_alpha_pnl",
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schema=AlphaArgs,
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description="读取指定 Alpha 的 PnL 缓存摘要。缺失缓存时说明情况，不自动刷新。",
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label="读取 PnL 缓存",
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renderer="alpha",
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effect="query",
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handler=pnl,
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),
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Capability(
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name="update_research",
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schema=ResearchArgs,
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description="提出指定 Alpha 的本地研究记录修改。仅传要修改的字段，等待用户在界面确认。",
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label="修改研究记录",
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renderer="alpha",
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effect="confirm",
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preview=preview_research,
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execute=update_research,
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refresh=("alphas",),
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),
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Capability(
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name="bulk_update_research",
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schema=BulkInput,
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description="提出固定 1–100 个 Alpha 的批量标签或研究状态修改，等待用户确认。",
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label="批量修改研究记录",
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renderer="alpha",
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effect="confirm",
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preview=preview_bulk,
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execute=update_bulk,
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refresh=("alphas",),
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),
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)
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