feat: Vector retrieval matches datasource

backend/apps/datasource/embedding/ds_embedding.py

@@ -8,6 +8,7 @@ from apps.ai_model.embedding import EmbeddingModelCache
 from apps.datasource.crud.datasource import get_table_schema
 from apps.datasource.models.datasource import CoreDatasource
 from common.core.deps import SessionDep, CurrentUser
+from common.utils.utils import SQLBotLogUtil
 
 
 def cosine_similarity(vec_a, vec_b):
@@ -50,7 +51,10 @@ def get_ds_embedding(session: SessionDep, current_user: CurrentUser, _ds_list, q
                 _list[index]['cosine_similarity'] = cosine_similarity(q_embedding, item)
 
             _list.sort(key=lambda x: x['cosine_similarity'], reverse=True)
-            print(len(_list))
+            # print(len(_list))
+            SQLBotLogUtil.info(json.dumps(
+                [{"id": ele.get("id"), "name": ele.get("name"), "cosine_similarity": ele.get("cosine_similarity")}
+                 for ele in _list]))
             ds = _list[0].get('ds')
             return {"id": ds.id, "name": ds.name, "description": ds.description}
         except Exception: