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https://github.com/hwchase17/langchain.git
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community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463)
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
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GitHub
190
libs/community/langchain_community/document_loaders/generic.py
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190
libs/community/langchain_community/document_loaders/generic.py
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from __future__ import annotations
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from pathlib import Path
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from typing import (
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TYPE_CHECKING,
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Any,
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Iterator,
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List,
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Literal,
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Optional,
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Sequence,
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Union,
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)
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from langchain_core.documents import Document
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from langchain_community.document_loaders.base import BaseBlobParser, BaseLoader
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from langchain_community.document_loaders.blob_loaders import (
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BlobLoader,
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FileSystemBlobLoader,
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)
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from langchain_community.document_loaders.parsers.registry import get_parser
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if TYPE_CHECKING:
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from langchain.text_splitter import TextSplitter
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_PathLike = Union[str, Path]
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DEFAULT = Literal["default"]
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class GenericLoader(BaseLoader):
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"""Generic Document Loader.
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A generic document loader that allows combining an arbitrary blob loader with
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a blob parser.
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Examples:
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Parse a specific PDF file:
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.. code-block:: python
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from langchain_community.document_loaders import GenericLoader
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from langchain_community.document_loaders.parsers.pdf import PyPDFParser
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# Recursively load all text files in a directory.
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loader = GenericLoader.from_filesystem(
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"my_lovely_pdf.pdf",
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parser=PyPDFParser()
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)
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.. code-block:: python
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from langchain_community.document_loaders import GenericLoader
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from langchain_community.document_loaders.blob_loaders import FileSystemBlobLoader
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loader = GenericLoader.from_filesystem(
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path="path/to/directory",
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glob="**/[!.]*",
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suffixes=[".pdf"],
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show_progress=True,
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)
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docs = loader.lazy_load()
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next(docs)
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Example instantiations to change which files are loaded:
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.. code-block:: python
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# Recursively load all text files in a directory.
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loader = GenericLoader.from_filesystem("/path/to/dir", glob="**/*.txt")
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# Recursively load all non-hidden files in a directory.
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loader = GenericLoader.from_filesystem("/path/to/dir", glob="**/[!.]*")
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# Load all files in a directory without recursion.
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loader = GenericLoader.from_filesystem("/path/to/dir", glob="*")
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Example instantiations to change which parser is used:
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.. code-block:: python
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from langchain_community.document_loaders.parsers.pdf import PyPDFParser
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# Recursively load all text files in a directory.
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loader = GenericLoader.from_filesystem(
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"/path/to/dir",
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glob="**/*.pdf",
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parser=PyPDFParser()
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)
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""" # noqa: E501
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def __init__(
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self,
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blob_loader: BlobLoader,
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blob_parser: BaseBlobParser,
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) -> None:
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"""A generic document loader.
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Args:
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blob_loader: A blob loader which knows how to yield blobs
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blob_parser: A blob parser which knows how to parse blobs into documents
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"""
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self.blob_loader = blob_loader
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self.blob_parser = blob_parser
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def lazy_load(
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self,
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) -> Iterator[Document]:
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"""Load documents lazily. Use this when working at a large scale."""
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for blob in self.blob_loader.yield_blobs():
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yield from self.blob_parser.lazy_parse(blob)
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def load(self) -> List[Document]:
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"""Load all documents."""
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return list(self.lazy_load())
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def load_and_split(
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self, text_splitter: Optional[TextSplitter] = None
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) -> List[Document]:
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"""Load all documents and split them into sentences."""
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raise NotImplementedError(
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"Loading and splitting is not yet implemented for generic loaders. "
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"When they will be implemented they will be added via the initializer. "
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"This method should not be used going forward."
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)
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@classmethod
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def from_filesystem(
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cls,
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path: _PathLike,
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*,
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glob: str = "**/[!.]*",
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exclude: Sequence[str] = (),
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suffixes: Optional[Sequence[str]] = None,
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show_progress: bool = False,
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parser: Union[DEFAULT, BaseBlobParser] = "default",
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parser_kwargs: Optional[dict] = None,
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) -> GenericLoader:
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"""Create a generic document loader using a filesystem blob loader.
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Args:
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path: The path to the directory to load documents from OR the path to a
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single file to load. If this is a file, glob, exclude, suffixes
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will be ignored.
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glob: The glob pattern to use to find documents.
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suffixes: The suffixes to use to filter documents. If None, all files
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matching the glob will be loaded.
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exclude: A list of patterns to exclude from the loader.
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show_progress: Whether to show a progress bar or not (requires tqdm).
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Proxies to the file system loader.
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parser: A blob parser which knows how to parse blobs into documents,
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will instantiate a default parser if not provided.
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The default can be overridden by either passing a parser or
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setting the class attribute `blob_parser` (the latter
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should be used with inheritance).
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parser_kwargs: Keyword arguments to pass to the parser.
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Returns:
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A generic document loader.
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"""
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blob_loader = FileSystemBlobLoader(
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path,
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glob=glob,
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exclude=exclude,
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suffixes=suffixes,
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show_progress=show_progress,
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)
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if isinstance(parser, str):
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if parser == "default":
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try:
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# If there is an implementation of get_parser on the class, use it.
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blob_parser = cls.get_parser(**(parser_kwargs or {}))
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except NotImplementedError:
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# if not then use the global registry.
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blob_parser = get_parser(parser)
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else:
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blob_parser = get_parser(parser)
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else:
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blob_parser = parser
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return cls(blob_loader, blob_parser)
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@staticmethod
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def get_parser(**kwargs: Any) -> BaseBlobParser:
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"""Override this method to associate a default parser with the class."""
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raise NotImplementedError()
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