Extract logic to mark entries for embeddings update into helper function

- This could be re-used by other text_to_jsonl converters like
  markdown, beancount
This commit is contained in:
Debanjum Singh Solanky 2022-09-07 03:31:48 +03:00
parent 899bfc5c3e
commit b01b4d7daa
2 changed files with 40 additions and 33 deletions

View file

@ -7,12 +7,11 @@ import argparse
import pathlib
import glob
import logging
import hashlib
import time
# Internal Packages
from src.processor.org_mode import orgnode
from src.utils.helpers import get_absolute_path, is_none_or_empty
from src.utils.helpers import get_absolute_path, is_none_or_empty, mark_entries_for_update
from src.utils.jsonl import dump_jsonl, compress_jsonl_data
from src.utils import state
@ -46,37 +45,7 @@ def org_to_jsonl(org_files, org_file_filter, output_file, previous_entries=None)
if not previous_entries:
entries_with_ids = list(enumerate(current_entries))
else:
# Hash all current and previous entries to identify new entries
start = time.time()
current_entry_hashes = list(map(lambda e: hashlib.md5(bytes(e['compiled'], encoding='utf-8')).hexdigest(), current_entries))
previous_entry_hashes = list(map(lambda e: hashlib.md5(bytes(e['compiled'], encoding='utf-8')).hexdigest(), previous_entries))
end = time.time()
logger.debug(f"Hash previous, current entries: {end - start} seconds")
start = time.time()
hash_to_current_entries = dict(zip(current_entry_hashes, current_entries))
hash_to_previous_entries = dict(zip(previous_entry_hashes, previous_entries))
# All entries that did not exist in the previous set are to be added
new_entry_hashes = set(current_entry_hashes) - set(previous_entry_hashes)
# All entries that exist in both current and previous sets are kept
existing_entry_hashes = set(current_entry_hashes) & set(previous_entry_hashes)
# Mark new entries with no ids for later embeddings generation
new_entries = [
(None, hash_to_current_entries[entry_hash])
for entry_hash in new_entry_hashes
]
# Set id of existing entries to their previous ids to reuse their existing encoded embeddings
existing_entries = [
(previous_entry_hashes.index(entry_hash), hash_to_previous_entries[entry_hash])
for entry_hash in existing_entry_hashes
]
existing_entries_sorted = sorted(existing_entries, key=lambda e: e[0])
entries_with_ids = existing_entries_sorted + new_entries
end = time.time()
logger.debug(f"Identify, Mark, Combine new, existing entries: {end - start} seconds")
entries_with_ids = mark_entries_for_update(current_entries, previous_entries, key='compiled', logger=logger)
# Process Each Entry from All Notes Files
start = time.time()

View file

@ -1,6 +1,8 @@
# Standard Packages
import pathlib
import sys
import time
import hashlib
from os.path import join
from collections import OrderedDict
@ -79,3 +81,39 @@ class LRU(OrderedDict):
if len(self) > self.capacity:
oldest = next(iter(self))
del self[oldest]
def mark_entries_for_update(current_entries, previous_entries, key='compiled', logger=None):
# Hash all current and previous entries to identify new entries
start = time.time()
current_entry_hashes = list(map(lambda e: hashlib.md5(bytes(e[key], encoding='utf-8')).hexdigest(), current_entries))
previous_entry_hashes = list(map(lambda e: hashlib.md5(bytes(e[key], encoding='utf-8')).hexdigest(), previous_entries))
end = time.time()
logger.debug(f"Hash previous, current entries: {end - start} seconds")
start = time.time()
hash_to_current_entries = dict(zip(current_entry_hashes, current_entries))
hash_to_previous_entries = dict(zip(previous_entry_hashes, previous_entries))
# All entries that did not exist in the previous set are to be added
new_entry_hashes = set(current_entry_hashes) - set(previous_entry_hashes)
# All entries that exist in both current and previous sets are kept
existing_entry_hashes = set(current_entry_hashes) & set(previous_entry_hashes)
# Mark new entries with no ids for later embeddings generation
new_entries = [
(None, hash_to_current_entries[entry_hash])
for entry_hash in new_entry_hashes
]
# Set id of existing entries to their previous ids to reuse their existing encoded embeddings
existing_entries = [
(previous_entry_hashes.index(entry_hash), hash_to_previous_entries[entry_hash])
for entry_hash in existing_entry_hashes
]
existing_entries_sorted = sorted(existing_entries, key=lambda e: e[0])
entries_with_ids = existing_entries_sorted + new_entries
end = time.time()
logger.debug(f"Identify, Mark, Combine new, existing entries: {end - start} seconds")
return entries_with_ids