feat: Vector retrieval matches tables

Author: XiaJunjie2020

backend/apps/chat/task/llm.py

@@ -419,7 +419,8 @@ def select_datasource(self):
         full_thinking_text = ''
         full_text = ''
         if not ignore_auto_select:
-            if settings.TABLE_EMBEDDING_ENABLED:
+            if settings.TABLE_EMBEDDING_ENABLED and (
+                    not self.current_assistant or (self.current_assistant and self.current_assistant.type != 1)):
                 ds = get_ds_embedding(self.session, self.current_user, _ds_list, self.out_ds_instance,
                                       self.chat_question.question, self.current_assistant)
                 yield {'content': '{"id":' + str(ds.get('id')) + '}'}

backend/apps/system/crud/assistant.py

@@ -173,8 +173,8 @@ def get_db_schema(self, ds_id: int, question: str, embedding: bool = True) -> st
             tables.append(t_obj)
 
         # do table embedding
-        if embedding and tables and settings.TABLE_EMBEDDING_ENABLED:
-            tables = get_table_embedding(tables, question)
+        # if embedding and tables and settings.TABLE_EMBEDDING_ENABLED:
+        #     tables = get_table_embedding(tables, question)
 
         if tables:
             for s in tables:

backend/common/core/config.py

@@ -105,7 +105,7 @@ def SQLALCHEMY_DATABASE_URI(self) -> PostgresDsn | str:
     PG_POOL_RECYCLE: int = 3600
     PG_POOL_PRE_PING: bool = True
 
-    TABLE_EMBEDDING_ENABLED: bool = False
+    TABLE_EMBEDDING_ENABLED: bool = True
     TABLE_EMBEDDING_COUNT: int = 10