mirror of
https://github.com/hwchase17/langchain
synced 2024-11-08 07:10:35 +00:00
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>
126 lines
3.5 KiB
Python
126 lines
3.5 KiB
Python
import re
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from typing import Any, Callable, Dict, Tuple
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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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def _DEFAULT_COMPOSER(op_name: str) -> Callable:
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"""
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Default composer for logical operators.
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Args:
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op_name: Name of the operator.
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Returns:
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Callable that takes a list of arguments and returns a string.
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"""
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def f(*args: Any) -> str:
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args_: map[str] = map(str, args)
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return f" {op_name} ".join(args_)
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return f
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def _FUNCTION_COMPOSER(op_name: str) -> Callable:
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"""
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Composer for functions.
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Args:
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op_name: Name of the function.
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Returns:
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Callable that takes a list of arguments and returns a string.
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"""
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def f(*args: Any) -> str:
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args_: map[str] = map(str, args)
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return f"{op_name}({','.join(args_)})"
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return f
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class MyScaleTranslator(Visitor):
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"""Translate `MyScale` internal query language elements to valid filters."""
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allowed_operators = [Operator.AND, Operator.OR, Operator.NOT]
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"""Subset of allowed logical operators."""
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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.CONTAIN,
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Comparator.LIKE,
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]
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map_dict = {
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Operator.AND: _DEFAULT_COMPOSER("AND"),
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Operator.OR: _DEFAULT_COMPOSER("OR"),
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Operator.NOT: _DEFAULT_COMPOSER("NOT"),
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Comparator.EQ: _DEFAULT_COMPOSER("="),
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Comparator.GT: _DEFAULT_COMPOSER(">"),
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Comparator.GTE: _DEFAULT_COMPOSER(">="),
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Comparator.LT: _DEFAULT_COMPOSER("<"),
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Comparator.LTE: _DEFAULT_COMPOSER("<="),
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Comparator.CONTAIN: _FUNCTION_COMPOSER("has"),
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Comparator.LIKE: _DEFAULT_COMPOSER("ILIKE"),
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}
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def __init__(self, metadata_key: str = "metadata") -> None:
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super().__init__()
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self.metadata_key = metadata_key
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def visit_operation(self, operation: Operation) -> Dict:
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args = [arg.accept(self) for arg in operation.arguments]
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func = operation.operator
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self._validate_func(func)
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return self.map_dict[func](*args)
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def visit_comparison(self, comparison: Comparison) -> Dict:
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regex = r"\((.*?)\)"
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matched = re.search(r"\(\w+\)", comparison.attribute)
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# If arbitrary function is applied to an attribute
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if matched:
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attr = re.sub(
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regex,
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f"({self.metadata_key}.{matched.group(0)[1:-1]})",
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comparison.attribute,
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)
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else:
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attr = f"{self.metadata_key}.{comparison.attribute}"
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value = comparison.value
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comp = comparison.comparator
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value = f"'{value}'" if isinstance(value, str) else value
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# convert timestamp for datetime objects
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if isinstance(value, dict) and value.get("type") == "date":
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attr = f"parseDateTime32BestEffort({attr})"
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value = f"parseDateTime32BestEffort('{value['date']}')"
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# string pattern match
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if comp is Comparator.LIKE:
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value = f"'%{value[1:-1]}%'"
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return self.map_dict[comp](attr, value)
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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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print(structured_query) # noqa: T201
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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 = {"where_str": structured_query.filter.accept(self)}
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return structured_query.query, kwargs
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