mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
ed58eeb9c5
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
103 lines
3.1 KiB
Python
103 lines
3.1 KiB
Python
"""Abstract interface for document loader implementations."""
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from __future__ import annotations
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from abc import ABC, abstractmethod
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from typing import TYPE_CHECKING, Iterator, List, Optional
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from langchain_core.documents import Document
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from langchain_community.document_loaders.blob_loaders import Blob
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if TYPE_CHECKING:
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from langchain.text_splitter import TextSplitter
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class BaseLoader(ABC):
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"""Interface for Document Loader.
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Implementations should implement the lazy-loading method using generators
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to avoid loading all Documents into memory at once.
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The `load` method will remain as is for backwards compatibility, but its
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implementation should be just `list(self.lazy_load())`.
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"""
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# Sub-classes should implement this method
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# as return list(self.lazy_load()).
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# This method returns a List which is materialized in memory.
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@abstractmethod
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def load(self) -> List[Document]:
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"""Load data into Document objects."""
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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 Documents and split into chunks. Chunks are returned as Documents.
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Args:
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text_splitter: TextSplitter instance to use for splitting documents.
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Defaults to RecursiveCharacterTextSplitter.
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Returns:
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List of Documents.
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"""
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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if text_splitter is None:
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_text_splitter: TextSplitter = RecursiveCharacterTextSplitter()
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else:
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_text_splitter = text_splitter
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docs = self.load()
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return _text_splitter.split_documents(docs)
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# Attention: This method will be upgraded into an abstractmethod once it's
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# implemented in all the existing subclasses.
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def lazy_load(
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self,
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) -> Iterator[Document]:
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"""A lazy loader for Documents."""
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raise NotImplementedError(
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f"{self.__class__.__name__} does not implement lazy_load()"
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)
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class BaseBlobParser(ABC):
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"""Abstract interface for blob parsers.
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A blob parser provides a way to parse raw data stored in a blob into one
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or more documents.
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The parser can be composed with blob loaders, making it easy to reuse
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a parser independent of how the blob was originally loaded.
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"""
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@abstractmethod
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def lazy_parse(self, blob: Blob) -> Iterator[Document]:
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"""Lazy parsing interface.
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Subclasses are required to implement this method.
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Args:
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blob: Blob instance
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Returns:
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Generator of documents
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"""
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def parse(self, blob: Blob) -> List[Document]:
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"""Eagerly parse the blob into a document or documents.
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This is a convenience method for interactive development environment.
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Production applications should favor the lazy_parse method instead.
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Subclasses should generally not over-ride this parse method.
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Args:
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blob: Blob instance
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Returns:
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List of documents
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"""
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return list(self.lazy_parse(blob))
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