mirror of
https://github.com/hwchase17/langchain
synced 2024-11-20 03:25:56 +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
46 lines
1.6 KiB
Python
46 lines
1.6 KiB
Python
from typing import Iterator
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from langchain_core.documents import Document
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from langchain_community.document_loaders.base import BaseBlobParser
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from langchain_community.document_loaders.blob_loaders import Blob
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class MsWordParser(BaseBlobParser):
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"""Parse the Microsoft Word documents from a blob."""
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def lazy_parse(self, blob: Blob) -> Iterator[Document]:
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"""Parse a Microsoft Word document into the Document iterator.
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Args:
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blob: The blob to parse.
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Returns: An iterator of Documents.
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"""
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try:
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from unstructured.partition.doc import partition_doc
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from unstructured.partition.docx import partition_docx
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except ImportError as e:
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raise ImportError(
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"Could not import unstructured, please install with `pip install "
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"unstructured`."
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) from e
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mime_type_parser = {
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"application/msword": partition_doc,
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"application/vnd.openxmlformats-officedocument.wordprocessingml.document": (
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partition_docx
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),
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}
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if blob.mimetype not in (
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"application/msword",
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"application/vnd.openxmlformats-officedocument.wordprocessingml.document",
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):
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raise ValueError("This blob type is not supported for this parser.")
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with blob.as_bytes_io() as word_document:
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elements = mime_type_parser[blob.mimetype](file=word_document)
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text = "\n\n".join([str(el) for el in elements])
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metadata = {"source": blob.source}
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yield Document(page_content=text, metadata=metadata)
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