mirror of
https://github.com/deepset-ai/haystack.git
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131 lines
6.0 KiB
Python
131 lines
6.0 KiB
Python
import logging
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from html.parser import HTMLParser
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from pathlib import Path
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from typing import List, Optional, Dict, Any
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import requests
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from tika import parser as tikaparser
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from haystack.file_converter.base import BaseConverter
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logger = logging.getLogger(__name__)
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# Use the built-in HTML parser with minimum dependencies
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class TikaXHTMLParser(HTMLParser):
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def __init__(self):
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self.ingest = True
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self.page = ""
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self.pages: List[str] = []
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super(TikaXHTMLParser, self).__init__()
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def handle_starttag(self, tag, attrs):
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# find page div
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pagediv = [value for attr, value in attrs if attr == "class" and value == "page"]
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if tag == "div" and pagediv:
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self.ingest = True
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def handle_endtag(self, tag):
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# close page div, or a single page without page div, save page and open a new page
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if (tag == "div" or tag == "body") and self.ingest:
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self.ingest = False
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# restore words hyphened to the next line
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self.pages.append(self.page.replace("-\n", ""))
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self.page = ""
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def handle_data(self, data):
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if self.ingest:
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self.page += data
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class TikaConverter(BaseConverter):
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def __init__(
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self,
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tika_url: str = "http://localhost:9998/tika",
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remove_numeric_tables: bool = False,
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valid_languages: Optional[List[str]] = None
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):
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"""
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:param tika_url: URL of the Tika server
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:param remove_numeric_tables: This option uses heuristics to remove numeric rows from the tables.
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The tabular structures in documents might be noise for the reader model if it
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does not have table parsing capability for finding answers. However, tables
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may also have long strings that could possible candidate for searching answers.
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The rows containing strings are thus retained in this option.
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:param valid_languages: validate languages from a list of languages specified in the ISO 639-1
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(https://en.wikipedia.org/wiki/ISO_639-1) format.
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This option can be used to add test for encoding errors. If the extracted text is
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not one of the valid languages, then it might likely be encoding error resulting
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in garbled text.
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"""
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ping = requests.get(tika_url)
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if ping.status_code != 200:
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raise Exception(f"Apache Tika server is not reachable at the URL '{tika_url}'. To run it locally"
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f"with Docker, execute: 'docker run -p 9998:9998 apache/tika:1.24.1'")
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self.tika_url = tika_url
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super().__init__(remove_numeric_tables=remove_numeric_tables, valid_languages=valid_languages)
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def convert(
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self,
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file_path: Path,
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meta: Optional[Dict[str, str]] = None,
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remove_numeric_tables: Optional[bool] = None,
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valid_languages: Optional[List[str]] = None,
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) -> Dict[str, Any]:
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"""
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:param file_path: path of the file to convert
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:param meta: dictionary of meta data key-value pairs to append in the returned document.
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:param remove_numeric_tables: This option uses heuristics to remove numeric rows from the tables.
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The tabular structures in documents might be noise for the reader model if it
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does not have table parsing capability for finding answers. However, tables
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may also have long strings that could possible candidate for searching answers.
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The rows containing strings are thus retained in this option.
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:param valid_languages: validate languages from a list of languages specified in the ISO 639-1
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(https://en.wikipedia.org/wiki/ISO_639-1) format.
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This option can be used to add test for encoding errors. If the extracted text is
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not one of the valid languages, then it might likely be encoding error resulting
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in garbled text.
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:return: a list of pages and the extracted meta data of the file.
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"""
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if remove_numeric_tables is None:
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remove_numeric_tables = self.remove_numeric_tables
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if valid_languages is None:
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valid_languages = self.valid_languages
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parsed = tikaparser.from_file(file_path.as_posix(), self.tika_url, xmlContent=True)
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parser = TikaXHTMLParser()
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parser.feed(parsed["content"])
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cleaned_pages = []
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# TODO investigate title of document appearing in the first extracted page
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for page in parser.pages:
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lines = page.splitlines()
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cleaned_lines = []
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for line in lines:
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words = line.split()
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digits = [word for word in words if any(i.isdigit() for i in word)]
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# remove lines having > 40% of words as digits AND not ending with a period(.)
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if remove_numeric_tables:
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if words and len(digits) / len(words) > 0.4 and not line.strip().endswith("."):
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logger.debug(f"Removing line '{line}' from {file_path}")
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continue
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cleaned_lines.append(line)
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page = "\n".join(cleaned_lines)
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cleaned_pages.append(page)
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if valid_languages:
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document_text = "".join(cleaned_pages)
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if not self.validate_language(document_text):
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logger.warning(
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f"The language for {file_path} is not one of {valid_languages}. The file may not have "
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f"been decoded in the correct text format."
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)
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text = "\f".join(cleaned_pages)
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document = {"text": text, "meta": {**parsed["metadata"], **(meta or {})}}
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return document
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