fix vector db sql injection (#16096)

api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py

 
     def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 4)
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         score_threshold = float(kwargs.get("score_threshold") or 0.0)
         with self._get_cursor() as cur:
             query_vector_str = json.dumps(query_vector)
 
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 4)
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         with self._get_cursor() as cur:
             cur.execute(
                 f"""SELECT id, vector, page_content, metadata_, 

api/core/rag/datasource/vdb/myscale/myscale_vector.py

 
     def _search(self, dist: str, order: SortOrder, **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 4)
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         score_threshold = float(kwargs.get("score_threshold") or 0.0)
         where_str = (
             f"WHERE dist < {1 - score_threshold}"

api/core/rag/datasource/vdb/opengauss/opengauss.py

         :return: List of Documents that are nearest to the query vector.
         """
         top_k = kwargs.get("top_k", 4)
-
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         with self._get_cursor() as cur:
             cur.execute(
                 f"SELECT meta, text, embedding <=> %s AS distance FROM {self.table_name}"
 
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 5)
-
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         with self._get_cursor() as cur:
             cur.execute(
                 f"""SELECT meta, text, ts_rank(to_tsvector(coalesce(text, '')), plainto_tsquery(%s)) AS score

api/core/rag/datasource/vdb/pgvector/pgvector.py

         :return: List of Documents that are nearest to the query vector.
         """
         top_k = kwargs.get("top_k", 4)
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
 
         with self._get_cursor() as cur:
             cur.execute(
 
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 5)
-
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         with self._get_cursor() as cur:
             if self.pg_bigm:
                 cur.execute("SET pg_bigm.similarity_limit TO 0.000001")