khoj/tests/conftest.py
Debanjum Singh Solanky 02d944030f Use Base TextToJsonl class to standardize <text>_to_jsonl processors
- Start standardizing implementation of the `text_to_jsonl' processors
  - `text_to_jsonl; scripts already had a shared structure
  - This change starts to codify that implicit structure

- Benefits
  - Ease adding more `text_to_jsonl; processors
  - Allow merging shared functionality
  - Help with type hinting

- Drawbacks
  - Lower agility to change. But this was already an implicit issue as
    the text_to_jsonl processors got more deeply wired into the app
2022-09-16 00:53:11 +03:00

65 lines
2.4 KiB
Python

# External Packages
import pytest
# Internal Packages
from src.search_type import image_search, text_search
from src.utils.config import SearchType
from src.utils.helpers import resolve_absolute_path
from src.utils.rawconfig import ContentConfig, TextContentConfig, ImageContentConfig, SearchConfig, TextSearchConfig, ImageSearchConfig
from src.processor.org_mode.org_to_jsonl import OrgToJsonl
from src.search_filter.date_filter import DateFilter
from src.search_filter.word_filter import WordFilter
from src.search_filter.file_filter import FileFilter
@pytest.fixture(scope='session')
def search_config() -> SearchConfig:
model_dir = resolve_absolute_path('~/.khoj/search')
model_dir.mkdir(parents=True, exist_ok=True)
search_config = SearchConfig()
search_config.symmetric = TextSearchConfig(
encoder = "sentence-transformers/all-MiniLM-L6-v2",
cross_encoder = "cross-encoder/ms-marco-MiniLM-L-6-v2",
model_directory = model_dir / 'symmetric/'
)
search_config.asymmetric = TextSearchConfig(
encoder = "sentence-transformers/multi-qa-MiniLM-L6-cos-v1",
cross_encoder = "cross-encoder/ms-marco-MiniLM-L-6-v2",
model_directory = model_dir / 'asymmetric/'
)
search_config.image = ImageSearchConfig(
encoder = "sentence-transformers/clip-ViT-B-32",
model_directory = model_dir / 'image/'
)
return search_config
@pytest.fixture(scope='session')
def content_config(tmp_path_factory, search_config: SearchConfig):
content_dir = tmp_path_factory.mktemp('content')
# Generate Image Embeddings from Test Images
content_config = ContentConfig()
content_config.image = ImageContentConfig(
input_directories = ['tests/data/images'],
embeddings_file = content_dir.joinpath('image_embeddings.pt'),
batch_size = 1,
use_xmp_metadata = False)
image_search.setup(content_config.image, search_config.image, regenerate=False)
# Generate Notes Embeddings from Test Notes
content_config.org = TextContentConfig(
input_files = None,
input_filter = ['tests/data/org/*.org'],
compressed_jsonl = content_dir.joinpath('notes.jsonl.gz'),
embeddings_file = content_dir.joinpath('note_embeddings.pt'))
filters = [DateFilter(), WordFilter(), FileFilter()]
text_search.setup(OrgToJsonl, content_config.org, search_config.asymmetric, regenerate=False, filters=filters)
return content_config