Add UnstructuredReader with support for various legacy files (.doc, .xls) (#99)
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@ -2,6 +2,7 @@ from .base import AutoReader, DirectoryReader
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from .excel_loader import PandasExcelReader
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from .mathpix_loader import MathpixPDFReader
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from .ocr_loader import OCRReader
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from .unstructured_loader import UnstructuredReader
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__all__ = [
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"AutoReader",
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@ -9,4 +10,5 @@ __all__ = [
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"MathpixPDFReader",
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"OCRReader",
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"DirectoryReader",
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"UnstructuredReader",
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]
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110
knowledgehub/loaders/unstructured_loader.py
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110
knowledgehub/loaders/unstructured_loader.py
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"""Unstructured file reader.
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A parser for unstructured text files using Unstructured.io.
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Supports .txt, .docx, .pptx, .jpg, .png, .eml, .html, and .pdf documents.
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To use .doc and .xls parser, install
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sudo apt-get install -y libmagic-dev poppler-utils libreoffice
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pip install xlrd
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"""
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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from llama_index.readers.base import BaseReader
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from kotaemon.base import Document
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class UnstructuredReader(BaseReader):
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"""General unstructured text reader for a variety of files."""
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def __init__(self, *args: Any, **kwargs: Any) -> None:
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"""Init params."""
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super().__init__(*args) # not passing kwargs to parent bc it cannot accept it
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self.api = False # we default to local
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if "url" in kwargs:
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self.server_url = str(kwargs["url"])
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self.api = True # is url was set, switch to api
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else:
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self.server_url = "http://localhost:8000"
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if "api" in kwargs:
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self.api = kwargs["api"]
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self.api_key = ""
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if "api_key" in kwargs:
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self.api_key = kwargs["api_key"]
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""" Loads data using Unstructured.io
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Depending on the construction if url is set or api = True
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it'll parse file using API call, else parse it locally
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additional_metadata is extended by the returned metadata if
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split_documents is True
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Returns list of documents
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"""
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def load_data(
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self,
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file: Path,
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additional_metadata: Optional[Dict] = None,
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split_documents: Optional[bool] = False,
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**kwargs,
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) -> List[Document]:
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"""If api is set, parse through api"""
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file_path_str = str(file)
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if self.api:
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from unstructured.partition.api import partition_via_api
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elements = partition_via_api(
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filename=file_path_str,
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api_key=self.api_key,
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api_url=self.server_url + "/general/v0/general",
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)
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else:
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"""Parse file locally"""
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from unstructured.partition.auto import partition
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elements = partition(filename=file_path_str)
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""" Process elements """
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docs = []
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file_name = Path(file).name
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if split_documents:
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for node in elements:
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metadata = {"file_name": file_name}
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if hasattr(node, "metadata"):
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"""Load metadata fields"""
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for field, val in vars(node.metadata).items():
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if field == "_known_field_names":
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continue
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# removing coordinates because it does not serialize
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# and dont want to bother with it
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if field == "coordinates":
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continue
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# removing bc it might cause interference
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if field == "parent_id":
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continue
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metadata[field] = val
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if additional_metadata is not None:
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metadata.update(additional_metadata)
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metadata["file_name"] = file_name
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docs.append(Document(text=node.text, metadata=metadata))
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else:
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text_chunks = [" ".join(str(el).split()) for el in elements]
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metadata = {"file_name": file_name}
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if additional_metadata is not None:
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metadata.update(additional_metadata)
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# Create a single document by joining all the texts
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docs.append(Document(text="\n\n".join(text_chunks), metadata=metadata))
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return docs
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@ -4,7 +4,7 @@ from langchain.schema import Document as LangchainDocument
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from llama_index.node_parser import SimpleNodeParser
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from kotaemon.base import Document
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from kotaemon.loaders import AutoReader
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from kotaemon.loaders import AutoReader, UnstructuredReader
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def test_pdf_reader():
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@ -26,3 +26,22 @@ def test_pdf_reader():
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node_parser = SimpleNodeParser.from_defaults(chunk_size=100, chunk_overlap=20)
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nodes = node_parser.get_nodes_from_documents(documents)
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assert len(nodes) > 0
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def test_unstructured_pdf_reader():
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reader = UnstructuredReader()
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dirpath = Path(__file__).parent
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input_path = dirpath / "resources/dummy.pdf"
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documents = reader.load_data(input_path)
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# check document reader output
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assert len(documents) == 1
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first_doc = documents[0]
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assert isinstance(first_doc, Document)
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assert first_doc.text.lower().replace(" ", "") == "dummypdffile"
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# split documents mode
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documents = reader.load_data(input_path, split_documents=True)
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# check document reader output
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assert len(documents) == 1
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