Source code for langchain.retrievers.self_query.dashvector

"""Logic for converting internal query language to a valid DashVector query."""
from typing import Tuple, Union

from langchain_core.structured_query import (
    Comparator,
    Comparison,
    Operation,
    Operator,
    StructuredQuery,
    Visitor,
)


[docs]class DashvectorTranslator(Visitor): """Logic for converting internal query language elements to valid filters.""" allowed_operators = [Operator.AND, Operator.OR] allowed_comparators = [ Comparator.EQ, Comparator.GT, Comparator.GTE, Comparator.LT, Comparator.LTE, Comparator.LIKE, ] map_dict = { Operator.AND: " AND ", Operator.OR: " OR ", Comparator.EQ: " = ", Comparator.GT: " > ", Comparator.GTE: " >= ", Comparator.LT: " < ", Comparator.LTE: " <= ", Comparator.LIKE: " LIKE ", } def _format_func(self, func: Union[Operator, Comparator]) -> str: self._validate_func(func) return self.map_dict[func]
[docs] def visit_operation(self, operation: Operation) -> str: args = [arg.accept(self) for arg in operation.arguments] return self._format_func(operation.operator).join(args)
[docs] def visit_comparison(self, comparison: Comparison) -> str: value = comparison.value if isinstance(value, str): if comparison.comparator == Comparator.LIKE: value = f"'%{value}%'" else: value = f"'{value}'" return ( f"{comparison.attribute}{self._format_func(comparison.comparator)}{value}" )
[docs] def visit_structured_query( self, structured_query: StructuredQuery ) -> Tuple[str, dict]: if structured_query.filter is None: kwargs = {} else: kwargs = {"filter": structured_query.filter.accept(self)} return structured_query.query, kwargs