mirror of
https://github.com/hwchase17/langchain
synced 2024-11-16 06:13:16 +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
38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
from typing import Any, List
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from langchain_community.document_loaders.unstructured import (
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UnstructuredFileLoader,
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validate_unstructured_version,
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)
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class UnstructuredTSVLoader(UnstructuredFileLoader):
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"""Load `TSV` files using `Unstructured`.
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Like other
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Unstructured loaders, UnstructuredTSVLoader can be used in both
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"single" and "elements" mode. If you use the loader in "elements"
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mode, the TSV file will be a single Unstructured Table element.
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If you use the loader in "elements" mode, an HTML representation
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of the table will be available in the "text_as_html" key in the
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document metadata.
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Examples
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--------
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from langchain_community.document_loaders.tsv import UnstructuredTSVLoader
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loader = UnstructuredTSVLoader("stanley-cups.tsv", mode="elements")
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docs = loader.load()
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"""
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def __init__(
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self, file_path: str, mode: str = "single", **unstructured_kwargs: Any
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):
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validate_unstructured_version(min_unstructured_version="0.7.6")
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super().__init__(file_path=file_path, mode=mode, **unstructured_kwargs)
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def _get_elements(self) -> List:
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from unstructured.partition.tsv import partition_tsv
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return partition_tsv(filename=self.file_path, **self.unstructured_kwargs)
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