mirror of
https://github.com/hwchase17/langchain
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f92006de3c
0.2rc migrations - [x] Move memory - [x] Move remaining retrievers - [x] graph_qa chains - [x] some dependency from evaluation code potentially on math utils - [x] Move openapi chain from `langchain.chains.api.openapi` to `langchain_community.chains.openapi` - [x] Migrate `langchain.chains.ernie_functions` to `langchain_community.chains.ernie_functions` - [x] migrate `langchain/chains/llm_requests.py` to `langchain_community.chains.llm_requests` - [x] Moving `langchain_community.cross_enoders.base:BaseCrossEncoder` -> `langchain_community.retrievers.document_compressors.cross_encoder:BaseCrossEncoder` (namespace not ideal, but it needs to be moved to `langchain` to avoid circular deps) - [x] unit tests langchain -- add pytest.mark.community to some unit tests that will stay in langchain - [x] unit tests community -- move unit tests that depend on community to community - [x] mv integration tests that depend on community to community - [x] mypy checks Other todo - [x] Make deprecation warnings not noisy (need to use warn deprecated and check that things are implemented properly) - [x] Update deprecation messages with timeline for code removal (likely we actually won't be removing things until 0.4 release) -- will give people more time to transition their code. - [ ] Add information to deprecation warning to show users how to migrate their code base using langchain-cli - [ ] Remove any unnecessary requirements in langchain (e.g., is SQLALchemy required?) --------- Co-authored-by: Erick Friis <erick@langchain.dev>
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
"""Logic for converting internal query language to a valid DashVector query."""
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from typing import Tuple, Union
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from langchain_core.structured_query import (
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Comparator,
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Comparison,
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Operation,
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Operator,
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StructuredQuery,
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Visitor,
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)
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class DashvectorTranslator(Visitor):
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"""Logic for converting internal query language elements to valid filters."""
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allowed_operators = [Operator.AND, Operator.OR]
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allowed_comparators = [
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Comparator.EQ,
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Comparator.GT,
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Comparator.GTE,
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Comparator.LT,
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Comparator.LTE,
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Comparator.LIKE,
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]
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map_dict = {
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Operator.AND: " AND ",
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Operator.OR: " OR ",
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Comparator.EQ: " = ",
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Comparator.GT: " > ",
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Comparator.GTE: " >= ",
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Comparator.LT: " < ",
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Comparator.LTE: " <= ",
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Comparator.LIKE: " LIKE ",
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}
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def _format_func(self, func: Union[Operator, Comparator]) -> str:
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self._validate_func(func)
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return self.map_dict[func]
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def visit_operation(self, operation: Operation) -> str:
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args = [arg.accept(self) for arg in operation.arguments]
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return self._format_func(operation.operator).join(args)
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def visit_comparison(self, comparison: Comparison) -> str:
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value = comparison.value
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if isinstance(value, str):
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if comparison.comparator == Comparator.LIKE:
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value = f"'%{value}%'"
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else:
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value = f"'{value}'"
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return (
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f"{comparison.attribute}{self._format_func(comparison.comparator)}{value}"
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)
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def visit_structured_query(
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self, structured_query: StructuredQuery
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) -> Tuple[str, dict]:
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if structured_query.filter is None:
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kwargs = {}
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else:
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kwargs = {"filter": structured_query.filter.accept(self)}
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return structured_query.query, kwargs
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