feat: add Super Alpha research, management and MCP workflows

backend/app/backtests/service.py

@@ -93,7 +93,7 @@ class Backtests:
 
     async def capabilities(self):
         return {
-            "alpha_types": ["REGULAR"],
+            "alpha_types": ["REGULAR", "SUPER"],
             "languages": ["FASTEXPR"],
             "instrument_types": ["EQUITY"],
             "settings_schema": Candidate.model_json_schema(),
@@ -111,6 +111,8 @@ class Backtests:
         from ..research.expressions import analyze
         if not body.preparation_refs and not body.input_ids:
             return
+        if any(c.alpha_type == "SUPER" for c in body.candidates):
+            raise HTTPException(422, "SUPER 组件快照不能使用字段数据准备集合")
         await Preparations(self.db).bind(body)
         snapshots = [await Preparations(self.db).snapshot(i) for i in body.input_ids]
         for candidate in body.candidates:
@@ -221,6 +223,8 @@ class Backtests:
                 if len(candidates) != len(selection):
                     raise HTTPException(422, "选择包含不属于当前草稿的候选")
             data = {"name": draft.name, "source": draft.source, "candidates": candidates}
+        from ..superalpha.service import validate_source
+        await validate_source(self.db, data["source"], data["candidates"])
         candidates = DraftInput.model_validate(data).model_dump(mode="json")["candidates"]
         config = await self.db.get(BacktestConfig, 1)
         groups = defaultdict(list)
@@ -253,6 +257,9 @@ class Backtests:
         for indices in groups.values():
             local_batches = []
             for index in indices:
+                if candidates[index]["alpha_type"] == "SUPER":
+                    batches.append([index])
+                    continue
                 batch = next(
                     (
                         b
@@ -352,6 +359,7 @@ class Backtests:
                         ordinal=i,
                         client_item_id=c.client_item_id,
                         expression=c.expression,
+                        alpha_type=c.alpha_type, selection=c.selection, combo=c.combo,
                         settings=c.settings.model_dump(),
                         fingerprint=fingerprint(c.platform_input()),
                     )
@@ -360,8 +368,10 @@ class Backtests:
         await self.db.flush()
         return await self.run(run.id)
 
-    async def runs(self, limit=25, offset=0, source=None, reference=None, research_id=None, q="", sort="created_at", direction="desc"):
+    async def runs(self, limit=25, offset=0, source=None, reference=None, research_id=None, q="", sort="created_at", direction="desc", alpha_type=None):
         query = select(BacktestRun)
+        if alpha_type:
+            query = query.where(BacktestRun.id.in_(select(BacktestItem.run_id).where(BacktestItem.alpha_type == alpha_type)))
         if q:
             query = query.where(BacktestRun.name.contains(q, autoescape=True))
         column = {"name": BacktestRun.name, "created_at": BacktestRun.created_at}[sort]
@@ -460,7 +470,7 @@ class Backtests:
                             for k in (
                                 "id",
                                 "client_item_id",
-                                "expression",
+                                "expression", "alpha_type", "selection", "combo",
                                 "settings",
                                 "attempt_id",
                                 "platform_status",
@@ -610,7 +620,8 @@ class Backtests:
                     source=Source.model_validate({**run.source, "parent_run_id": run.id}),
                     candidates=[
                         Candidate(
-                            client_item_id=r.client_item_id, expression=r.expression, settings=r.settings
+                            client_item_id=r.client_item_id, expression=r.expression, settings=r.settings,
+                            alpha_type=r.alpha_type, selection=r.selection, combo=r.combo
                         )
                         for r in selected
                     ],