class NLSQLTableQueryEngine(BaseSQLTableQueryEngine):
"""
Natural language SQL Table query engine.
Read NLStructStoreQueryEngine's docstring for more info on NL SQL.
NOTE: Any Text-to-SQL application should be aware that executing
arbitrary SQL queries can be a security risk. It is recommended to
take precautions as needed, such as using restricted roles, read-only
databases, sandboxing, etc.
"""
def __init__(
self,
sql_database: SQLDatabase,
llm: Optional[LLM] = None,
text_to_sql_prompt: Optional[BasePromptTemplate] = None,
context_query_kwargs: Optional[dict] = None,
synthesize_response: bool = True,
markdown_response: bool = False,
response_synthesis_prompt: Optional[BasePromptTemplate] = None,
refine_synthesis_prompt: Optional[BasePromptTemplate] = None,
tables: Optional[Union[List[str], List[Table]]] = None,
context_str_prefix: Optional[str] = None,
embed_model: Optional[BaseEmbedding] = None,
sql_only: bool = False,
callback_manager: Optional[CallbackManager] = None,
verbose: bool = False,
**kwargs: Any,
) -> None:
"""Initialize params."""
# self._tables = tables
self._sql_retriever = NLSQLRetriever(
sql_database,
llm=llm,
text_to_sql_prompt=text_to_sql_prompt,
context_query_kwargs=context_query_kwargs,
tables=tables,
context_str_prefix=context_str_prefix,
embed_model=embed_model,
sql_only=sql_only,
callback_manager=callback_manager,
verbose=verbose,
)
super().__init__(
synthesize_response=synthesize_response,
markdown_response=markdown_response,
response_synthesis_prompt=response_synthesis_prompt,
refine_synthesis_prompt=refine_synthesis_prompt,
llm=llm,
callback_manager=callback_manager,
verbose=verbose,
**kwargs,
)
@property
def sql_retriever(self) -> NLSQLRetriever:
"""Get SQL retriever."""
return self._sql_retriever
