fix(rag): Fix schema linking error (#1637)

dbgpt/rag/schemalinker/schema_linking.py

@@ -11,9 +11,9 @@
     ModelRequest,
 )
 from dbgpt.datasource.base import BaseConnector
+from dbgpt.rag.index.base import IndexStoreBase
 from dbgpt.rag.schemalinker.base_linker import BaseSchemaLinker
 from dbgpt.rag.summary.rdbms_db_summary import _parse_db_summary
-from dbgpt.serve.rag.connector import VectorStoreConnector
 from dbgpt.util.chat_util import run_async_tasks
 
 INSTRUCTION = """
@@ -46,21 +46,19 @@ def __init__(
         model_name: str,
         llm: LLMClient,
         top_k: int = 5,
-        vector_store_connector: Optional[VectorStoreConnector] = None,
-        **kwargs
+        index_store: Optional[IndexStoreBase] = None,
     ):
         """Create the schema linking instance.
 
         Args:
            connection (Optional[BaseConnector]): BaseConnector connection.
            llm (Optional[LLMClient]): base llm
         """
-        super().__init__(**kwargs)
         self._top_k = top_k
         self._connector = connector
         self._llm = llm
         self._model_name = model_name
-        self._vector_store_connector = vector_store_connector
+        self._index_store = index_store
 
     def _schema_linking(self, query: str) -> List:
         """Get all db schema info."""
@@ -71,11 +69,10 @@ def _schema_linking(self, query: str) -> List:
 
     def _schema_linking_with_vector_db(self, query: str) -> List[Chunk]:
         queries = [query]
-        if not self._vector_store_connector:
+        if not self._index_store:
             raise ValueError("Vector store connector is not provided.")
         candidates = [
-            self._vector_store_connector.similar_search(query, self._top_k)
-            for query in queries
+            self._index_store.similar_search(query, self._top_k) for query in queries
         ]
         return cast(List[Chunk], reduce(lambda x, y: x + y, candidates))