feat: 增加 MCP 研究模板保存工具

2026-09-11 23:05:01 +08:00
parent 03a66546f3
commit f29063c9a2
13 changed files with 430 additions and 13 deletions
@@ -0,0 +1,60 @@
+"""Persist caller-authored templates with frozen local research evidence."""
+
+import math
+
+from sqlalchemy import select
+
+from ..models import BacktestItem, BacktestResult, ResearchAsset
+from ..research.assets import Assets
+from ..research.workspace_contracts import AssetWrite
+from .queries import item_summary
+
+
+async def create_template(db, args, principal):
+    """Save a new asset inside the caller's account-locked, idempotent transaction.
+
+    Args contain the external model's TemplateSpec and local source item IDs.
+    Return the versioned asset and theoretical combination count. Raise
+    ResearchError for name conflicts or missing/incomplete research evidence.
+    Stored evidence proves provenance, not profitability or platform eligibility;
+    schema validation does not validate every expanded FASTEXPR combination.
+    """
+    from .service import ResearchError
+
+    existing = await db.scalar(select(ResearchAsset).where(
+        ResearchAsset.kind == "template", ResearchAsset.name == args.template.name,
+    ).order_by(ResearchAsset.id).limit(1))
+    if existing:
+        raise ResearchError("TEMPLATE_NAME_CONFLICT", "模板名称已存在，请使用新名称；此工具不覆盖已有模板",
+                            affected_items=[{"template_id": existing.id, "version": existing.version}])
+    rows = (await db.execute(select(BacktestItem, BacktestResult).outerjoin(
+        BacktestResult, BacktestResult.item_id == BacktestItem.id,
+    ).where(BacktestItem.id.in_(args.source_item_ids)))).all()
+    found = {item.id: (item, result) for item, result in rows}
+    missing = [item_id for item_id in args.source_item_ids if item_id not in found]
+    if missing:
+        raise ResearchError("NOT_FOUND", "部分来源回测候选不存在", affected_items=missing)
+    incomplete = [item.id for item, result in rows if (
+        item.platform_status != "completed" or item.collection_status != "complete"
+        or item.persistence_status != "saved" or not result or not result.complete
+    )]
+    if incomplete:
+        raise ResearchError("SOURCE_NOT_READY", "来源候选须完成回测、结果采集和持久化，请先读取 get_backtest_results",
+                            affected_items=sorted(incomplete))
+    provenance = {
+        "source": {"kind": "mcp", "reference": args.reference},
+        "hypothesis": args.hypothesis,
+        "mcp_token_id": principal.token_id,
+        "admin_id": principal.admin_id,
+        "source_items": [item_summary(*found[item_id]) for item_id in args.source_item_ids],
+    }
+    asset = await Assets(db).save(AssetWrite(
+        kind="template", content=args.template.model_dump(mode="json"),
+    ), provenance=provenance)
+    return {
+        **asset, "template_id": asset["id"],
+        "combination_count": str(math.prod(len(v.values) for v in args.template.variables.values())),
+        "validation": {"structure": "valid", "source_evidence": "recorded",
+                       "expanded_candidates": "not_validated", "platform_semantics": "unknown"},
+        "next_step": "在模板工坊选择固定输入及模拟设置，展开并核验候选，再确认批量回测。",
+    }