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Standardize structure of text to entries to match other entry processors
Add process_single_plaintext_file func etc with similar signatures as org_to_entries and markdown_to_entries processors The standardization makes modifications, abstractions easier to create
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3 changed files with 84 additions and 28 deletions
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@ -1,7 +1,9 @@
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import logging
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import re
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from pathlib import Path
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from typing import List, Tuple
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from typing import Dict, List, Tuple
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import urllib3
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from bs4 import BeautifulSoup
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from khoj.database.models import Entry as DbEntry
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@ -28,21 +30,8 @@ class PlaintextToEntries(TextToEntries):
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else:
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deletion_file_names = None
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with timer("Scrub plaintext files and extract text", logger):
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for file in files:
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try:
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plaintext_content = files[file]
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if file.endswith(("html", "htm", "xml")):
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plaintext_content = PlaintextToEntries.extract_html_content(
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plaintext_content, file.split(".")[-1]
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)
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files[file] = plaintext_content
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except Exception as e:
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logger.warning(f"Unable to read file: {file} as plaintext. Skipping file.")
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logger.warning(e, exc_info=True)
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# Extract Entries from specified plaintext files
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with timer("Parse entries from specified Plaintext files", logger):
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with timer("Extract entries from specified Plaintext files", logger):
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current_entries = PlaintextToEntries.extract_plaintext_entries(files)
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# Split entries by max tokens supported by model
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@ -74,16 +63,57 @@ class PlaintextToEntries(TextToEntries):
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return soup.get_text(strip=True, separator="\n")
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@staticmethod
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def extract_plaintext_entries(entry_to_file_map: dict[str, str]) -> List[Entry]:
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"Convert each plaintext entries into a dictionary"
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entries = []
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for file, entry in entry_to_file_map.items():
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def extract_plaintext_entries(text_files: Dict[str, str]) -> List[Entry]:
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entries: List[str] = []
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entry_to_file_map: List[Tuple[str, str]] = []
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for text_file in text_files:
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try:
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text_content = text_files[text_file]
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entries, entry_to_file_map = PlaintextToEntries.process_single_plaintext_file(
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text_content, text_file, entries, entry_to_file_map
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)
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except Exception as e:
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logger.warning(f"Unable to read file: {text_file} as plaintext. Skipping file.")
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logger.warning(e, exc_info=True)
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# Extract Entries from specified plaintext files
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return PlaintextToEntries.convert_text_files_to_entries(entries, dict(entry_to_file_map))
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@staticmethod
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def process_single_plaintext_file(
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text_content: str,
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text_file: str,
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entries: List[str],
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entry_to_file_map: List[Tuple[str, str]],
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) -> Tuple[List[str], List[Tuple[str, str]]]:
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if text_file.endswith(("html", "htm", "xml")):
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text_content = PlaintextToEntries.extract_html_content(text_content, text_file.split(".")[-1])
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entry_to_file_map += [(text_content, text_file)]
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entries.extend([text_content])
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return entries, entry_to_file_map
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@staticmethod
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def convert_text_files_to_entries(parsed_entries: List[str], entry_to_file_map: dict[str, str]) -> List[Entry]:
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"Convert each plaintext file into an entry"
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entries: List[Entry] = []
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for parsed_entry in parsed_entries:
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raw_filename = entry_to_file_map[parsed_entry]
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# Check if raw_filename is a URL. If so, save it as is. If not, convert it to a Path.
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if type(raw_filename) == str and re.search(r"^https?://", raw_filename):
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# Escape the URL to avoid issues with special characters
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entry_filename = urllib3.util.parse_url(raw_filename).url
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else:
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entry_filename = raw_filename
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# Append base filename to compiled entry for context to model
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entries.append(
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Entry(
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raw=entry,
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file=file,
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compiled=f"{Path(file).stem}\n{entry}",
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heading=Path(file).stem,
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raw=parsed_entry,
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file=f"{entry_filename}",
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compiled=f"{entry_filename}\n{parsed_entry}",
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heading=entry_filename,
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)
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)
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logger.debug(f"Converted {len(parsed_entries)} plaintext files to entries")
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return entries
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@ -1,6 +1,5 @@
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# Standard Modules
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import os
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from io import BytesIO
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from urllib.parse import quote
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import pytest
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@ -15,8 +15,6 @@ def test_plaintext_file(tmp_path):
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"""
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plaintextfile = create_file(tmp_path, raw_entry)
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filename = plaintextfile.stem
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# Act
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# Extract Entries from specified plaintext files
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@ -24,7 +22,7 @@ def test_plaintext_file(tmp_path):
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f"{plaintextfile}": raw_entry,
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}
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entries = PlaintextToEntries.extract_plaintext_entries(entry_to_file_map=data)
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entries = PlaintextToEntries.extract_plaintext_entries(data)
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# Convert each entry.file to absolute path to make them JSON serializable
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for entry in entries:
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@ -35,7 +33,7 @@ def test_plaintext_file(tmp_path):
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# Ensure raw entry with no headings do not get heading prefix prepended
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assert not entries[0].raw.startswith("#")
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# Ensure compiled entry has filename prepended as top level heading
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assert entries[0].compiled == f"{filename}\n{raw_entry}"
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assert entries[0].compiled == f"{plaintextfile}\n{raw_entry}"
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def test_get_plaintext_files(tmp_path):
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@ -100,6 +98,35 @@ def test_parse_html_plaintext_file(content_config, default_user: KhojUser):
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assert "<div>" not in entries[0].raw
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def test_large_plaintext_file_split_into_multiple_entries(tmp_path):
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"Convert files with no heading to jsonl."
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# Arrange
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max_tokens = 256
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normal_entry = " ".join([f"{number}" for number in range(max_tokens - 1)])
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large_entry = " ".join([f"{number}" for number in range(max_tokens)])
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normal_plaintextfile = create_file(tmp_path, normal_entry)
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large_plaintextfile = create_file(tmp_path, large_entry)
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normal_data = {f"{normal_plaintextfile}": normal_entry}
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large_data = {f"{large_plaintextfile}": large_entry}
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# Act
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# Extract Entries from specified plaintext files
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normal_entries = PlaintextToEntries.split_entries_by_max_tokens(
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PlaintextToEntries.extract_plaintext_entries(normal_data),
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max_tokens=max_tokens,
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raw_is_compiled=True,
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)
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large_entries = PlaintextToEntries.split_entries_by_max_tokens(
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PlaintextToEntries.extract_plaintext_entries(large_data), max_tokens=max_tokens, raw_is_compiled=True
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)
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# Assert
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assert len(normal_entries) == 1
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assert len(large_entries) == 2
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# Helper Functions
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def create_file(tmp_path: Path, entry=None, filename="test.md"):
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file_ = tmp_path / filename
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