Skip to content

PGVector SQL

PGVectorSQLQueryEngine #

Bases: BaseSQLTableQueryEngine

PGvector SQL query engine.

A modified version of the normal text-to-SQL query engine because we can infer embedding vectors in the sql query.

NOTE: this is a beta feature

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.

Source code in llama-index-core/llama_index/core/indices/struct_store/sql_query.py
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
class PGVectorSQLQueryEngine(BaseSQLTableQueryEngine):
    """PGvector SQL query engine.

    A modified version of the normal text-to-SQL query engine because
    we can infer embedding vectors in the sql query.

    NOTE: this is a beta feature

    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,
        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,
        sql_only: bool = False,
        callback_manager: Optional[CallbackManager] = None,
        **kwargs: Any,
    ) -> None:
        """Initialize params."""
        text_to_sql_prompt = text_to_sql_prompt or DEFAULT_TEXT_TO_SQL_PGVECTOR_PROMPT
        self._sql_retriever = NLSQLRetriever(
            sql_database,
            llm=llm,
            text_to_sql_prompt=text_to_sql_prompt,
            context_query_kwargs=context_query_kwargs,
            tables=tables,
            sql_parser_mode=SQLParserMode.PGVECTOR,
            context_str_prefix=context_str_prefix,
            sql_only=sql_only,
            callback_manager=callback_manager,
        )
        super().__init__(
            synthesize_response=synthesize_response,
            response_synthesis_prompt=response_synthesis_prompt,
            refine_synthesis_prompt=refine_synthesis_prompt,
            llm=llm,
            callback_manager=callback_manager,
            **kwargs,
        )

    @property
    def sql_retriever(self) -> NLSQLRetriever:
        """Get SQL retriever."""
        return self._sql_retriever

sql_retriever property #

sql_retriever: NLSQLRetriever

Get SQL retriever.