feat: integrate chatbox research with datasets and backtests

backend/tests/ai_fake.py

@@ -8,6 +8,8 @@ from uuid import uuid4
 from pydantic_ai.messages import ToolReturnPart, UserPromptPart
 from pydantic_ai.models.function import DeltaToolCall, FunctionModel
 
+from tests.research_fake import research_step
+
 
 async def fake_stream(messages, info):
     latest = max(
@@ -17,6 +19,16 @@ async def fake_stream(messages, info):
         str(p.content) for m in messages[latest:] for p in m.parts if isinstance(p, UserPromptPart)
     )
     returns = [p for m in messages[latest:] for p in m.parts if isinstance(p, ToolReturnPart)]
+    if any(marker in text for marker in ("研究此输入", "自行选字段研究", "解读研究结果")):
+        step = research_step(
+            text, returns, [p for m in messages for p in m.parts if isinstance(p, ToolReturnPart)]
+        )
+        if isinstance(step, str):
+            yield step
+        else:
+            name, args = step
+            yield {0: DeltaToolCall(name=name, json_args=json.dumps(args), tool_call_id=uuid4().hex)}
+        return
     if returns and returns[-1].tool_name == "prepare_backtest":
         content = returns[-1].content
         content = json.loads(content) if isinstance(content, str) else content