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https://github.com/hwchase17/langchain.git
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feat: Add UnstructuredRSTLoader
(#6594)
### Summary Adds an `UnstructuredRSTLoader` for loading [reStructuredText](https://en.wikipedia.org/wiki/ReStructuredText) file. ### Testing ```python from langchain.document_loaders import UnstructuredRSTLoader loader = UnstructuredRSTLoader( file_path="example_data/README.rst", mode="elements" ) docs = loader.load() print(docs[0]) ``` ### Reviewers - @hwchase17 - @rlancemartin - @eyurtsev
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Example Docs
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------------
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The sample docs directory contains the following files:
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- ``example-10k.html`` - A 10-K SEC filing in HTML format
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- ``layout-parser-paper.pdf`` - A PDF copy of the layout parser paper
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- ``factbook.xml``/``factbook.xsl`` - Example XML/XLS files that you
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can use to test stylesheets
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These documents can be used to test out the parsers in the library. In
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addition, here are instructions for pulling in some sample docs that are
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too big to store in the repo.
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XBRL 10-K
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^^^^^^^^^
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You can get an example 10-K in inline XBRL format using the following
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``curl``. Note, you need to have the user agent set in the header or the
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SEC site will reject your request.
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.. code:: bash
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curl -O \
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-A '${organization} ${email}'
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https://www.sec.gov/Archives/edgar/data/311094/000117184321001344/0001171843-21-001344.txt
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You can parse this document using the HTML parser.
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# RST\n",
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"\n",
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">A [reStructured Text (RST)](https://en.wikipedia.org/wiki/ReStructuredText) file is a file format for textual data used primarily in the Python programming language community for technical documentation."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## `UnstructuredRSTLoader`\n",
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"\n",
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"You can load data from RST files with `UnstructuredRSTLoader` using the following workflow."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.document_loaders import UnstructuredRSTLoader"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"loader = UnstructuredRSTLoader(\n",
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" file_path=\"example_data/README.rst\", mode=\"elements\"\n",
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")\n",
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"docs = loader.load()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"page_content='Example Docs' metadata={'source': 'example_data/README.rst', 'filename': 'README.rst', 'file_directory': 'example_data', 'filetype': 'text/x-rst', 'page_number': 1, 'category': 'Title'}\n"
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]
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}
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],
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"source": [
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"print(docs[0])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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@ -97,6 +97,7 @@ from langchain.document_loaders.readthedocs import ReadTheDocsLoader
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from langchain.document_loaders.recursive_url_loader import RecusiveUrlLoader
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from langchain.document_loaders.reddit import RedditPostsLoader
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from langchain.document_loaders.roam import RoamLoader
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from langchain.document_loaders.rst import UnstructuredRSTLoader
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from langchain.document_loaders.rtf import UnstructuredRTFLoader
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from langchain.document_loaders.s3_directory import S3DirectoryLoader
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from langchain.document_loaders.s3_file import S3FileLoader
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@ -261,6 +262,7 @@ __all__ = [
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"UnstructuredODTLoader",
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"UnstructuredPDFLoader",
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"UnstructuredPowerPointLoader",
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"UnstructuredRSTLoader",
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"UnstructuredRTFLoader",
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"UnstructuredURLLoader",
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"UnstructuredWordDocumentLoader",
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langchain/document_loaders/rst.py
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langchain/document_loaders/rst.py
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"""Loader that loads RST files."""
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from typing import Any, List
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from langchain.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 UnstructuredRSTLoader(UnstructuredFileLoader):
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"""Loader that uses unstructured to load RST files."""
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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="0.7.5")
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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.rst import partition_rst
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return partition_rst(filename=self.file_path, **self.unstructured_kwargs)
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tests/integration_tests/document_loaders/test_rst.py
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tests/integration_tests/document_loaders/test_rst.py
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import os
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from pathlib import Path
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from langchain.document_loaders import UnstructuredRSTLoader
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EXAMPLE_DIRECTORY = file_path = Path(__file__).parent.parent / "examples"
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def test_unstructured_rst_loader() -> None:
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"""Test unstructured loader."""
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file_path = os.path.join(EXAMPLE_DIRECTORY, "README.rst")
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loader = UnstructuredRSTLoader(str(file_path))
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docs = loader.load()
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assert len(docs) == 1
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tests/integration_tests/examples/README.rst
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tests/integration_tests/examples/README.rst
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Example Docs
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------------
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The sample docs directory contains the following files:
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- ``example-10k.html`` - A 10-K SEC filing in HTML format
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- ``layout-parser-paper.pdf`` - A PDF copy of the layout parser paper
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- ``factbook.xml``/``factbook.xsl`` - Example XML/XLS files that you
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can use to test stylesheets
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These documents can be used to test out the parsers in the library. In
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addition, here are instructions for pulling in some sample docs that are
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too big to store in the repo.
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|
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XBRL 10-K
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^^^^^^^^^
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|
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You can get an example 10-K in inline XBRL format using the following
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``curl``. Note, you need to have the user agent set in the header or the
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SEC site will reject your request.
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.. code:: bash
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curl -O \
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-A '${organization} ${email}'
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https://www.sec.gov/Archives/edgar/data/311094/000117184321001344/0001171843-21-001344.txt
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You can parse this document using the HTML parser.
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