refactor: unify data preparations and research input snapshots

backend/tests/research_fake.py

@@ -22,7 +22,7 @@ def research_step(text, returns, history):
             return "get_backtest_results", {"run_id": run_id}
         data = content(returns[-1])
         return f"已读取本次研究的 {data['total']} 条真实保存结果；缺失 Sharpe 仍为未知。"
-    if context.get("unsaved_field_selection") and not context.get("template_input_id"):
+    if context.get("unsaved_field_selection") and not context.get("input_snapshot_id"):
         return "请先保存字段选择，再点击用此输入研究。"
     if not returns:
         return "get_backtest_capabilities", {}
@@ -30,39 +30,23 @@ def research_step(text, returns, history):
     data = content(last)
     if "error" in data:
         return f"研究尚未完成：{data['error']}"
-    scope = context.get("catalog_scope") or {
-        "instrument_type": "EQUITY",
-        "region": "USA",
-        "universe": "TOP3000",
-        "delay": 1,
-    }
     if last.tool_name == "get_backtest_capabilities":
-        if context.get("template_input_id"):
+        if context.get("input_snapshot_id"):
             return "get_research_input", {
-                "input_id": context["template_input_id"],
+                "input_id": context["input_snapshot_id"],
                 "field_type": "MATRIX",
                 "limit": 1,
             }
-        return "search_catalog", {"filters": {**scope, "q": "TEST_FIN", "limit": 1}}
-    if last.tool_name == "search_catalog":
-        if data["dataset_id"] is None:
-            return "search_catalog", {
-                "dataset_id": data["items"][0]["id"],
-                "filters": {**scope, "field_type": "MATRIX", "limit": 1},
-            }
-        return "prepare_research_input", {
-            "scope": scope,
-            "dataset_id": data["dataset_id"],
-            "collection_version": data["collection_version"],
-            "field_ids": [data["items"][0]["id"]],
-        }
+        return "search_data_preparations", {"limit": 1}
+    if last.tool_name == "search_data_preparations":
+        return "prepare_research_input", {"items": [{"id": data["items"][0]["id"], "version": data["items"][0]["version"]}]}
     if last.tool_name in ("get_research_input", "prepare_research_input"):
-        field = data["items"][0]
+        field = next(f for f in data["items"] if f["field_type"] == "MATRIX")
         saved_scope = data["scope"]
         return "prepare_research_backtest", {
             "name": "Chatbox 数据集研究",
             "hypothesis": "验证所选合成字段的横截面排序信号",
-            "template_input_id": data["id"],
+            "input_snapshot_id": data["id"],
             "candidates": [
                 {
                     "client_item_id": "research-1",