mirror of
https://github.com/hwchase17/langchain.git
synced 2025-08-13 22:59:05 +00:00
feat(text-splitters): ruff fixes and rules (#32502)
This commit is contained in:
Mason Daugherty
GitHub
parent
27b6b53f20
commit
457ce9c4b0
@ -3,11 +3,10 @@ from __future__ import annotations
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import copy
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import logging
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from abc import ABC, abstractmethod
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from collections.abc import Collection, Iterable, Sequence
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from collections.abc import Set as AbstractSet
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from dataclasses import dataclass
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from enum import Enum
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from typing import (
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TYPE_CHECKING,
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Any,
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Callable,
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Literal,
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@ -17,6 +16,11 @@ from typing import (
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)
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from langchain_core.documents import BaseDocumentTransformer, Document
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from typing_extensions import Self
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if TYPE_CHECKING:
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from collections.abc import Collection, Iterable, Sequence
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from collections.abc import Set as AbstractSet
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logger = logging.getLogger(__name__)
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@ -163,33 +167,33 @@ class TextSplitter(BaseDocumentTransformer, ABC):
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def _huggingface_tokenizer_length(text: str) -> int:
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return len(tokenizer.tokenize(text))
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except ImportError:
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except ImportError as err:
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msg = (
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"Could not import transformers python package. "
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"Please install it with `pip install transformers`."
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)
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raise ValueError(msg)
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raise ValueError(msg) from err
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return cls(length_function=_huggingface_tokenizer_length, **kwargs)
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@classmethod
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def from_tiktoken_encoder(
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cls: type[TS],
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cls,
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encoding_name: str = "gpt2",
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model_name: Optional[str] = None,
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allowed_special: Union[Literal["all"], AbstractSet[str]] = set(),
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disallowed_special: Union[Literal["all"], Collection[str]] = "all",
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**kwargs: Any,
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) -> TS:
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) -> Self:
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"""Text splitter that uses tiktoken encoder to count length."""
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try:
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import tiktoken
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except ImportError:
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except ImportError as err:
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msg = (
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"Could not import tiktoken python package. "
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"This is needed in order to calculate max_tokens_for_prompt. "
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"Please install it with `pip install tiktoken`."
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)
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raise ImportError(msg)
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raise ImportError(msg) from err
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if model_name is not None:
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enc = tiktoken.encoding_for_model(model_name)
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@ -238,13 +242,13 @@ class TokenTextSplitter(TextSplitter):
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super().__init__(**kwargs)
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try:
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import tiktoken
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except ImportError:
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except ImportError as err:
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msg = (
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"Could not import tiktoken python package. "
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"This is needed in order to for TokenTextSplitter. "
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"Please install it with `pip install tiktoken`."
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)
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raise ImportError(msg)
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raise ImportError(msg) from err
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if model_name is not None:
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enc = tiktoken.encoding_for_model(model_name)
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@ -39,8 +39,8 @@ class CharacterTextSplitter(TextSplitter):
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)
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# 4. Decide merge separator:
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# - if keep_separator or lookaround → don’t re-insert
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# - else → re-insert literal separator
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# - if keep_separator or lookaround -> don't re-insert
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# - else -> re-insert literal separator
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merge_sep = ""
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if not (self._keep_separator or is_lookaround):
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merge_sep = self._separator
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@ -3,9 +3,9 @@ from __future__ import annotations
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import copy
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import pathlib
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import re
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from collections.abc import Iterable, Sequence
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from io import StringIO
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from typing import (
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TYPE_CHECKING,
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Any,
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Callable,
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Literal,
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@ -21,6 +21,11 @@ from langchain_core.documents import BaseDocumentTransformer, Document
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from langchain_text_splitters.character import RecursiveCharacterTextSplitter
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if TYPE_CHECKING:
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from collections.abc import Iterable, Sequence
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from bs4.element import PageElement
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class ElementType(TypedDict):
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"""Element type as typed dict."""
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@ -159,7 +164,11 @@ class HTMLHeaderTextSplitter:
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requests.RequestException: If the HTTP request fails.
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"""
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kwargs.setdefault("timeout", timeout)
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response = requests.get(url, **kwargs)
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response = requests.get(
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url,
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timeout=kwargs.get("timeout", timeout),
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**{k: v for k, v in kwargs.items() if k != "timeout"},
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)
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response.raise_for_status()
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return self.split_text(response.text)
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@ -229,9 +238,9 @@ class HTMLHeaderTextSplitter:
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children = list(node.children)
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from bs4.element import Tag
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for child in reversed(children):
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if isinstance(child, Tag):
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stack.append(child)
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stack.extend(
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child for child in reversed(children) if isinstance(child, Tag)
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)
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tag = getattr(node, "name", None)
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if not tag:
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@ -382,7 +391,6 @@ class HTMLSectionSplitter:
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"""
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try:
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from bs4 import BeautifulSoup
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from bs4.element import PageElement
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except ImportError as e:
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msg = "Unable to import BeautifulSoup/PageElement, \
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please install with `pip install \
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@ -396,7 +404,7 @@ class HTMLSectionSplitter:
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headers = soup.find_all(["body", *headers]) # type: ignore[assignment]
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for i, header in enumerate(headers):
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header_element = cast(PageElement, header)
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header_element = cast("PageElement", header)
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if i == 0:
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current_header = "#TITLE#"
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current_header_tag = "h1"
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@ -477,7 +485,7 @@ class HTMLSectionSplitter:
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return [
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Document(
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cast(str, section["content"]),
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cast("str", section["content"]),
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metadata={
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self.headers_to_split_on[str(section["tag_name"])]: section[
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"header"
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@ -587,19 +595,19 @@ class HTMLSemanticPreservingSplitter(BaseDocumentTransformer):
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denylist_tags: Optional[list[str]] = None,
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preserve_parent_metadata: bool = False,
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keep_separator: Union[bool, Literal["start", "end"]] = True,
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):
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) -> None:
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"""Initialize splitter."""
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try:
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from bs4 import BeautifulSoup, Tag
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self._BeautifulSoup = BeautifulSoup
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self._Tag = Tag
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except ImportError:
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except ImportError as err:
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msg = (
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"Could not import BeautifulSoup. "
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"Please install it with 'pip install bs4'."
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)
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raise ImportError(msg)
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raise ImportError(msg) from err
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self._headers_to_split_on = sorted(headers_to_split_on)
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self._max_chunk_size = max_chunk_size
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@ -647,11 +655,11 @@ class HTMLSemanticPreservingSplitter(BaseDocumentTransformer):
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nltk.download("stopwords")
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self._stopwords = set(nltk.corpus.stopwords.words(self._stopword_lang))
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except ImportError:
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except ImportError as err:
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msg = (
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"Could not import nltk. Please install it with 'pip install nltk'."
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)
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raise ImportError(msg)
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raise ImportError(msg) from err
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def split_text(self, text: str) -> list[Document]:
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"""Splits the provided HTML text into smaller chunks based on the configuration.
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@ -23,7 +23,7 @@ class RecursiveJsonSplitter:
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def __init__(
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self, max_chunk_size: int = 2000, min_chunk_size: Optional[int] = None
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):
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) -> None:
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"""Initialize the chunk size configuration for text processing.
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This constructor sets up the maximum and minimum chunk sizes, ensuring that
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@ -21,12 +21,12 @@ class KonlpyTextSplitter(TextSplitter):
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self._separator = separator
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try:
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import konlpy
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except ImportError:
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except ImportError as err:
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msg = """
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Konlpy is not installed, please install it with
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`pip install konlpy`
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"""
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raise ImportError(msg)
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raise ImportError(msg) from err
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self.kkma = konlpy.tag.Kkma()
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def split_text(self, text: str) -> list[str]:
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@ -26,7 +26,7 @@ class MarkdownHeaderTextSplitter:
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headers_to_split_on: list[tuple[str, str]],
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return_each_line: bool = False, # noqa: FBT001,FBT002
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strip_headers: bool = True, # noqa: FBT001,FBT002
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):
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) -> None:
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"""Create a new MarkdownHeaderTextSplitter.
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Args:
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@ -281,7 +281,7 @@ class ExperimentalMarkdownSyntaxTextSplitter:
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headers_to_split_on: Union[list[tuple[str, str]], None] = None,
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return_each_line: bool = False, # noqa: FBT001,FBT002
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strip_headers: bool = True, # noqa: FBT001,FBT002
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):
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) -> None:
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"""Initialize the text splitter with header splitting and formatting options.
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This constructor sets up the required configuration for splitting text into
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@ -31,9 +31,9 @@ class NLTKTextSplitter(TextSplitter):
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self._tokenizer = nltk.tokenize._get_punkt_tokenizer(self._language)
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else:
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self._tokenizer = nltk.tokenize.sent_tokenize
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except ImportError:
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except ImportError as err:
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msg = "NLTK is not installed, please install it with `pip install nltk`."
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raise ImportError(msg)
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raise ImportError(msg) from err
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def split_text(self, text: str) -> list[str]:
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"""Split incoming text and return chunks."""
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@ -20,13 +20,13 @@ class SentenceTransformersTokenTextSplitter(TextSplitter):
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try:
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from sentence_transformers import SentenceTransformer
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except ImportError:
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except ImportError as err:
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msg = (
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"Could not import sentence_transformers python package. "
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"This is needed in order to for SentenceTransformersTokenTextSplitter. "
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"Please install it with `pip install sentence-transformers`."
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)
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raise ImportError(msg)
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raise ImportError(msg) from err
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self.model_name = model_name
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self._model = SentenceTransformer(self.model_name)
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@ -45,11 +45,13 @@ def _make_spacy_pipeline_for_splitting(
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) -> Any: # avoid importing spacy
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try:
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import spacy
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except ImportError:
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except ImportError as err:
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msg = "Spacy is not installed, please install it with `pip install spacy`."
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raise ImportError(msg)
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raise ImportError(msg) from err
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if pipeline == "sentencizer":
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sentencizer: Any = spacy.lang.en.English()
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from spacy.lang.en import English
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sentencizer: Any = English()
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sentencizer.add_pipe("sentencizer")
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else:
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sentencizer = spacy.load(pipeline, exclude=["ner", "tagger"])
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@ -6,7 +6,10 @@ build-backend = "pdm.backend"
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authors = []
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license = { text = "MIT" }
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requires-python = ">=3.9"
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dependencies = ["langchain-core<1.0.0,>=0.3.72"]
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dependencies = [
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"langchain-core<1.0.0,>=0.3.72",
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"pip>=25.2",
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]
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name = "langchain-text-splitters"
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version = "0.3.9"
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description = "LangChain text splitting utilities"
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@ -18,7 +21,7 @@ readme = "README.md"
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repository = "https://github.com/langchain-ai/langchain"
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[dependency-groups]
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lint = ["ruff<0.13,>=0.12.2", "langchain-core"]
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lint = ["ruff<0.13,>=0.12.8", "langchain-core"]
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typing = [
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"mypy<2.0,>=1.15",
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"lxml-stubs<1.0.0,>=0.5.1",
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@ -42,6 +45,7 @@ test_integration = [
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"nltk<4.0.0,>=3.9.1",
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"transformers<5.0.0,>=4.51.3",
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"sentence-transformers>=3.0.1",
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"tiktoken<1.0.0,>=0.8.0",
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]
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[tool.uv.sources]
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@ -61,10 +65,72 @@ ignore_missing_imports = "True"
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target-version = "py39"
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[tool.ruff.lint]
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select = ["E", "F", "FBT", "I", "UP", "PGH003", "T201", "D"]
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ignore = ["D100",]
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select = [
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"A", # flake8-builtins
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"B", # flake8-bugbear
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"ASYNC", # flake8-async
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"C4", # flake8-comprehensions
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"COM", # flake8-commas
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"D", # pydocstyle
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"E", # pycodestyle error
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"EM", # flake8-errmsg
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"F", # pyflakes
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"FA", # flake8-future-annotations
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"FBT", # flake8-boolean-trap
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"FLY", # flake8-flynt
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"I", # isort
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"ICN", # flake8-import-conventions
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"INT", # flake8-gettext
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"ISC", # isort-comprehensions
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"PGH", # pygrep-hooks
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"PIE", # flake8-pie
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"PERF", # flake8-perf
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"PYI", # flake8-pyi
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"Q", # flake8-quotes
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"RET", # flake8-return
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"RSE", # flake8-rst-docstrings
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"RUF", # ruff
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"S", # flake8-bandit
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"SLF", # flake8-self
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"SLOT", # flake8-slots
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"SIM", # flake8-simplify
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"T10", # flake8-debugger
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"T20", # flake8-print
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"TID", # flake8-tidy-imports
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"UP", # pyupgrade
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"W", # pycodestyle warning
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"YTT", # flake8-2020
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]
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ignore = [
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"D100", # pydocstyle: Missing docstring in public module
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"D101", # pydocstyle: Missing docstring in public class
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"D102", # pydocstyle: Missing docstring in public method
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"D103", # pydocstyle: Missing docstring in public function
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"D104", # pydocstyle: Missing docstring in public package
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"D105", # pydocstyle: Missing docstring in magic method
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"D107", # pydocstyle: Missing docstring in __init__
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"D203", # Messes with the formatter
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"D213", # pydocstyle: Multi-line docstring summary should start at the second line (incompatible with D212)
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"D407", # pydocstyle: Missing-dashed-underline-after-section
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"COM812", # Messes with the formatter
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"ISC001", # Messes with the formatter
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"PERF203", # Rarely useful
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"S112", # Rarely useful
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"RUF012", # Doesn't play well with Pydantic
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"SLF001", # Private member access
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"UP007", # pyupgrade: non-pep604-annotation-union
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"UP045", # pyupgrade: non-pep604-annotation-optional
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]
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unfixable = ["B028"] # People should intentionally tune the stacklevel
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pyupgrade.keep-runtime-typing = true
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[tool.ruff.lint.extend-per-file-ignores]
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"tests/**/*.py" = [
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"S101", # Tests need assertions
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"S311", # Standard pseudo-random generators are not suitable for cryptographic purposes
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]
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[tool.coverage.run]
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omit = ["tests/*"]
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@ -1,7 +1,6 @@
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import random
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import string
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import sys
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import traceback
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import uuid
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from importlib.machinery import SourceFileLoader
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if __name__ == "__main__":
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@ -9,9 +8,7 @@ if __name__ == "__main__":
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has_failure = False
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for file in files:
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try:
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module_name = "".join(
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random.choice(string.ascii_letters) for _ in range(20)
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)
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module_name = f"test_module_{uuid.uuid4().hex[:20]}"
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SourceFileLoader(module_name, file).load_module()
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except Exception:
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has_failure = True
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@ -1,5 +1,5 @@
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version = 1
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revision = 2
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revision = 3
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requires-python = ">=3.9"
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resolution-markers = [
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"python_full_version >= '3.13'",
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@ -1090,7 +1090,7 @@ wheels = [
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[[package]]
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name = "langchain-core"
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version = "0.3.72"
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version = "0.3.74"
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source = { editable = "../core" }
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dependencies = [
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{ name = "jsonpatch" },
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@ -1152,6 +1152,7 @@ version = "0.3.9"
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source = { editable = "." }
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dependencies = [
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{ name = "langchain-core" },
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{ name = "pip" },
|
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]
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|
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[package.dev-dependencies]
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@ -1178,6 +1179,7 @@ test-integration = [
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{ name = "sentence-transformers" },
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{ name = "spacy" },
|
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{ name = "thinc" },
|
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{ name = "tiktoken" },
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{ name = "transformers" },
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]
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typing = [
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@ -1188,7 +1190,10 @@ typing = [
|
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]
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[package.metadata]
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requires-dist = [{ name = "langchain-core", editable = "../core" }]
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requires-dist = [
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{ name = "langchain-core", editable = "../core" },
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{ name = "pip", specifier = ">=25.2" },
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]
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[package.metadata.requires-dev]
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dev = [
|
||||
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Loading…
Reference in New Issue
Block a user