diff --git a/tests/test_qa_generator.py b/tests/test_qa_generator.py
new file mode 100644
index 00000000..f715a674
--- /dev/null
+++ b/tests/test_qa_generator.py
@@ -0,0 +1,71 @@
+import importlib
+import json
+import sys
+from types import ModuleType, SimpleNamespace
+
+import pytest
+from pandas import Timestamp
+
+from weclone.data.models import Message, QaPair
+
+
+def _load_data_processor(monkeypatch):
+    pii_module = ModuleType("weclone.core.PII.pii_detector")
+    pii_module.ChinesePIIDetector = object
+    pii_module.PIIDetector = object
+    monkeypatch.setitem(sys.modules, "weclone.core.PII.pii_detector", pii_module)
+
+    cleaning_module = ModuleType("weclone.data.clean.strategies")
+    cleaning_module.LLMCleaningStrategy = object
+    cleaning_module.OlineLLMCleaningStrategy = object
+    monkeypatch.setitem(sys.modules, "weclone.data.clean.strategies", cleaning_module)
+    monkeypatch.delitem(sys.modules, "weclone.data.qa_generator", raising=False)
+
+    return importlib.import_module("weclone.data.qa_generator").DataProcessor
+
+
+def test_save_result_updates_configured_dataset_file(tmp_path, monkeypatch):
+    DataProcessor = _load_data_processor(monkeypatch)
+    dataset_dir = tmp_path / "custom-dataset"
+    dataset_dir.mkdir()
+    dataset_path = dataset_dir / "current-chat.json"
+    dataset_path.write_text('[{"messages": [{"content": "stale data"}]}]', encoding="utf-8")
+    (dataset_dir / "dataset_info.json").write_text(
+        json.dumps({"custom-chat": {"file_name": "current-chat.json"}}),
+        encoding="utf-8",
+    )
+
+    processor = DataProcessor.__new__(DataProcessor)
+    processor.c = SimpleNamespace(dataset="custom-chat", dataset_dir=str(dataset_dir))
+    qa_pair = QaPair(
+        id=1,
+        time=Timestamp("2026-08-26T00:00:00"),
+        score=0,
+        messages=[Message(role="user", content="fresh data")],
+        images=[],
+        system="",
+    )
+    monkeypatch.chdir(tmp_path)
+
+    output_path = processor.save_result([qa_pair])
+
+    saved_data = json.loads(dataset_path.read_text(encoding="utf-8"))
+    assert saved_data[0]["messages"][0]["content"] == "fresh data"
+    assert output_path == str(dataset_path)
+    assert not (tmp_path / "dataset/res_csv/sft/sft-my.json").exists()
+
+
+def test_save_result_rejects_non_object_dataset_entry(tmp_path, monkeypatch):
+    DataProcessor = _load_data_processor(monkeypatch)
+    dataset_dir = tmp_path / "custom-dataset"
+    dataset_dir.mkdir()
+    (dataset_dir / "dataset_info.json").write_text(
+        json.dumps({"custom-chat": None}),
+        encoding="utf-8",
+    )
+
+    processor = DataProcessor.__new__(DataProcessor)
+    processor.c = SimpleNamespace(dataset="custom-chat", dataset_dir=str(dataset_dir))
+
+    with pytest.raises(ValueError, match="must define file_name"):
+        processor.save_result([])
diff --git a/weclone/data/qa_generator.py b/weclone/data/qa_generator.py
index e5a2d874..f9c409e0 100644
--- a/weclone/data/qa_generator.py
+++ b/weclone/data/qa_generator.py
@@ -146,11 +146,11 @@ def main(self):
         if self.enable_clean:
             self.clean_strategy.judge(qa_res)  # type: ignore
 
-        self.save_result(qa_res)
+        output_path = self.save_result(qa_res)
         self._execute_length_cdf_script()
 
         logger.success(
-            f"Chat record processing successful, obtained {len(qa_res)} data entries in total, saved to ./dataset/res_csv/sft/sft-my.json"
+            f"Chat record processing successful, obtained {len(qa_res)} data entries in total, saved to {output_path}"
         )
 
     def pre_parse_chat_dataset(self):
@@ -678,7 +678,7 @@ def load_file(self, file_path) -> List[ChatMessage]:
     def process_text(self, chat_message: ChatMessage):
         pass
 
-    def save_result(self, qa_res: List[QaPair]):
+    def save_result(self, qa_res: List[QaPair]) -> str:
         """
         Saves the list of QaPair objects to a JSON file after converting them to dictionaries.
 
@@ -697,13 +697,23 @@ def save_result(self, qa_res: List[QaPair]):
             }
             processed_qa_res.append(item_dict)
 
-        output_path = "./dataset/res_csv/sft/sft-my.json"
+        dataset_info_path = os.path.join(self.c.dataset_dir, "dataset_info.json")
+        with open(dataset_info_path, "r", encoding="utf-8") as f:
+            dataset_info = json.load(f)
+
+        dataset_entry = dataset_info.get(self.c.dataset) if isinstance(dataset_info, dict) else None
+        file_name = dataset_entry.get("file_name") if isinstance(dataset_entry, dict) else None
+        if not isinstance(file_name, str) or not file_name:
+            raise ValueError(f"Dataset '{self.c.dataset}' must define file_name in {dataset_info_path}")
+
+        output_path = os.path.join(self.c.dataset_dir, file_name)
         os.makedirs(os.path.dirname(output_path), exist_ok=True)
         with open(output_path, "w", encoding="utf-8") as f:
             json.dump(processed_qa_res, f, ensure_ascii=False, indent=4)
         logger.success(
             f"Chat record processing successful, {len(qa_res)} entries in total, saved to {output_path}"
         )
+        return output_path
 
 
 if __name__ == "__main__":