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khoj/tests/conftest.py

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Create test directory with model data to reuse for pytest session - Use pytest fixture with session scope - Instantiate test directory with model data to reuse for tests
2021-10-02 19:46:29 -07:00
# Standard Packages
import pytest
Improve Query Speed. Normalize Embeddings, Moving them to Cuda GPU - Move embeddings to CUDA GPU for compute, when available - Normalize embeddings and Use Dot Product instead of Cosine
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import torch
Create test directory with model data to reuse for pytest session - Use pytest fixture with session scope - Instantiate test directory with model data to reuse for tests
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# Internal Packages
Merge Symmetric, Asymmetric Search Types into a single Text Search Type - The code for both the text search types were mostly the same It was earlier done this way for expedience while experimenting - The minor differences were reconciled and merged into a single text_search type - This simplifies the app and making it easier to process other text types
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from src.search_type import image_search, text_search
from src.utils.rawconfig import ContentConfig, TextContentConfig, ImageContentConfig, SearchConfig, TextSearchConfig, ImageSearchConfig
from src.processor.org_mode.org_to_jsonl import org_to_jsonl
Create test directory with model data to reuse for pytest session - Use pytest fixture with session scope - Instantiate test directory with model data to reuse for tests
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@pytest.fixture(scope='session')
Setup Search with Search_Config to Fix Tests - Rename pytest fixture search_config to more appropriate content_config - Create search_config pytest fixture - Use search_config where search being setup, used in tests
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def search_config(tmp_path_factory):
Create test directory with model data to reuse for pytest session - Use pytest fixture with session scope - Instantiate test directory with model data to reuse for tests
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model_dir = tmp_path_factory.mktemp('data')
Rename RawConfig Types for Consistency - Naming convention - [ContentType][ConfigType]Config - Where [ConfigType] ~ Content, Search, Processor - Where [ContentType] ~ Text, Image, Asymmetric, Symmetric, Conversation - Current Configs: - Content: - Org Notes - Org Music - Image - Ledger/Beancount - Search: - Asymmetric - Symmetric - Image - Processor: - Conversation
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search_config = SearchConfig()
Setup Search with Search_Config to Fix Tests - Rename pytest fixture search_config to more appropriate content_config - Create search_config pytest fixture - Use search_config where search being setup, used in tests
2022-01-14 20:13:14 -05:00
Merge Symmetric, Asymmetric Search Types into a single Text Search Type - The code for both the text search types were mostly the same It was earlier done this way for expedience while experimenting - The minor differences were reconciled and merged into a single text_search type - This simplifies the app and making it easier to process other text types
2022-07-21 18:05:43 +04:00
search_config.symmetric = TextSearchConfig(
Use a more accurate model for symmetric semantic search - The all-MiniLM-L6-v2 is more accurate - The exact previous model isn't benchmarked but based on the performance of the closest model to it. Seems like the new model maybe similar in speed and size - On very preliminary evaluation of the model, the new model seems faster, with pretty decent results
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encoder = "sentence-transformers/all-MiniLM-L6-v2",
Setup Search with Search_Config to Fix Tests - Rename pytest fixture search_config to more appropriate content_config - Create search_config pytest fixture - Use search_config where search being setup, used in tests
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cross_encoder = "cross-encoder/ms-marco-MiniLM-L-6-v2",
model_directory = model_dir
)
Merge Symmetric, Asymmetric Search Types into a single Text Search Type - The code for both the text search types were mostly the same It was earlier done this way for expedience while experimenting - The minor differences were reconciled and merged into a single text_search type - This simplifies the app and making it easier to process other text types
2022-07-21 18:05:43 +04:00
search_config.asymmetric = TextSearchConfig(
Use a better model for asymmetric semantic search - The multi-qa-MiniLM-L6-cos-v1 is more extensively benchmarked[1] - It has the right mix of model query speed, size and performance on benchmarks - On hugging face it has way more downloads and likes than the msmarco model[2] - On very preliminary evaluation of the model - It doubles the encoding speed of all entries (down from ~8min to 4mins) - It gave more entries that stay relevant to the query (3/5 vs 1/5 earlier) [1]: https://www.sbert.net/docs/pretrained_models.html [2]: https://huggingface.co/sentence-transformers
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encoder = "sentence-transformers/multi-qa-MiniLM-L6-cos-v1",
Setup Search with Search_Config to Fix Tests - Rename pytest fixture search_config to more appropriate content_config - Create search_config pytest fixture - Use search_config where search being setup, used in tests
2022-01-14 20:13:14 -05:00
cross_encoder = "cross-encoder/ms-marco-MiniLM-L-6-v2",
model_directory = model_dir
)
Rename RawConfig Types for Consistency - Naming convention - [ContentType][ConfigType]Config - Where [ConfigType] ~ Content, Search, Processor - Where [ContentType] ~ Text, Image, Asymmetric, Symmetric, Conversation - Current Configs: - Content: - Org Notes - Org Music - Image - Ledger/Beancount - Search: - Asymmetric - Symmetric - Image - Processor: - Conversation
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search_config.image = ImageSearchConfig(
Setup Search with Search_Config to Fix Tests - Rename pytest fixture search_config to more appropriate content_config - Create search_config pytest fixture - Use search_config where search being setup, used in tests
2022-01-14 20:13:14 -05:00
encoder = "clip-ViT-B-32",
model_directory = model_dir
)
return search_config
@pytest.fixture(scope='session')
def model_dir(search_config):
model_dir = search_config.asymmetric.model_directory
Improve Query Speed. Normalize Embeddings, Moving them to Cuda GPU - Move embeddings to CUDA GPU for compute, when available - Normalize embeddings and Use Dot Product instead of Cosine
2022-06-30 00:59:57 +04:00
device = torch.device("cuda:0") if torch.cuda.is_available() else torch.device("cpu")
Setup Search with Search_Config to Fix Tests - Rename pytest fixture search_config to more appropriate content_config - Create search_config pytest fixture - Use search_config where search being setup, used in tests
2022-01-14 20:13:14 -05:00
Create test directory with model data to reuse for pytest session - Use pytest fixture with session scope - Instantiate test directory with model data to reuse for tests
2021-10-02 19:46:29 -07:00
# Generate Image Embeddings from Test Images
Rename RawConfig Types for Consistency - Naming convention - [ContentType][ConfigType]Config - Where [ConfigType] ~ Content, Search, Processor - Where [ContentType] ~ Text, Image, Asymmetric, Symmetric, Conversation - Current Configs: - Content: - Org Notes - Org Music - Image - Ledger/Beancount - Search: - Asymmetric - Symmetric - Image - Processor: - Conversation
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content_config = ContentConfig()
content_config.image = ImageContentConfig(
Allow indexing multiple image directories for image search
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input_directories = ['tests/data/images'],
Improve test data organization and update correspoding conftests - Put test data for each content type into separate directories - Makes config.yml for docker and local host consistent - Prepending tests to /data in sample_config.yml makes application run on local host using test data - Allows mounting separate volume for each content type in docker-compose - Ignore gitignore to only add tests content, not generated models or embeddings
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embeddings_file = model_dir.joinpath('image_embeddings.pt'),
Create test directory with model data to reuse for pytest session - Use pytest fixture with session scope - Instantiate test directory with model data to reuse for tests
2021-10-02 19:46:29 -07:00
batch_size = 10,
Update types used in conftest.py
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use_xmp_metadata = False)
Create test directory with model data to reuse for pytest session - Use pytest fixture with session scope - Instantiate test directory with model data to reuse for tests
2021-10-02 19:46:29 -07:00
Setup Search with Search_Config to Fix Tests - Rename pytest fixture search_config to more appropriate content_config - Create search_config pytest fixture - Use search_config where search being setup, used in tests
2022-01-14 20:13:14 -05:00
image_search.setup(content_config.image, search_config.image, regenerate=False, verbose=True)
Create test directory with model data to reuse for pytest session - Use pytest fixture with session scope - Instantiate test directory with model data to reuse for tests
2021-10-02 19:46:29 -07:00
# Generate Notes Embeddings from Test Notes
Rename RawConfig Types for Consistency - Naming convention - [ContentType][ConfigType]Config - Where [ConfigType] ~ Content, Search, Processor - Where [ContentType] ~ Text, Image, Asymmetric, Symmetric, Conversation - Current Configs: - Content: - Org Notes - Org Music - Image - Ledger/Beancount - Search: - Asymmetric - Symmetric - Image - Processor: - Conversation
2022-01-14 20:54:38 -05:00
content_config.org = TextContentConfig(
Improve test data organization and update correspoding conftests - Put test data for each content type into separate directories - Makes config.yml for docker and local host consistent - Prepending tests to /data in sample_config.yml makes application run on local host using test data - Allows mounting separate volume for each content type in docker-compose - Ignore gitignore to only add tests content, not generated models or embeddings
2022-01-29 01:57:08 -05:00
input_files = None,
input_filter = 'tests/data/notes/*.org',
compressed_jsonl = model_dir.joinpath('notes.jsonl.gz'),
embeddings_file = model_dir.joinpath('note_embeddings.pt'))
Create test directory with model data to reuse for pytest session - Use pytest fixture with session scope - Instantiate test directory with model data to reuse for tests
2021-10-02 19:46:29 -07:00
Merge Symmetric, Asymmetric Search Types into a single Text Search Type - The code for both the text search types were mostly the same It was earlier done this way for expedience while experimenting - The minor differences were reconciled and merged into a single text_search type - This simplifies the app and making it easier to process other text types
2022-07-21 18:05:43 +04:00
text_search.setup(org_to_jsonl, content_config.org, search_config.asymmetric, regenerate=False, device=device, verbose=True)
Create test directory with model data to reuse for pytest session - Use pytest fixture with session scope - Instantiate test directory with model data to reuse for tests
2021-10-02 19:46:29 -07:00
return model_dir
Split test_main into client and search type specific test files - Move search config fixture to conftests.py to be shared across tests - Move image search type specific tests to test_image_search.py file - Move, create asymmetric search type specific tests in new file
2021-10-02 20:28:33 -07:00
@pytest.fixture(scope='session')
Setup Search with Search_Config to Fix Tests - Rename pytest fixture search_config to more appropriate content_config - Create search_config pytest fixture - Use search_config where search being setup, used in tests
2022-01-14 20:13:14 -05:00
def content_config(model_dir):
Rename RawConfig Types for Consistency - Naming convention - [ContentType][ConfigType]Config - Where [ConfigType] ~ Content, Search, Processor - Where [ContentType] ~ Text, Image, Asymmetric, Symmetric, Conversation - Current Configs: - Content: - Org Notes - Org Music - Image - Ledger/Beancount - Search: - Asymmetric - Symmetric - Image - Processor: - Conversation
2022-01-14 20:54:38 -05:00
content_config = ContentConfig()
content_config.org = TextContentConfig(
Improve test data organization and update correspoding conftests - Put test data for each content type into separate directories - Makes config.yml for docker and local host consistent - Prepending tests to /data in sample_config.yml makes application run on local host using test data - Allows mounting separate volume for each content type in docker-compose - Ignore gitignore to only add tests content, not generated models or embeddings
2022-01-29 01:57:08 -05:00
input_files = None,
input_filter = 'tests/data/notes/*.org',
compressed_jsonl = model_dir.joinpath('notes.jsonl.gz'),
embeddings_file = model_dir.joinpath('note_embeddings.pt'))
Split test_main into client and search type specific test files - Move search config fixture to conftests.py to be shared across tests - Move image search type specific tests to test_image_search.py file - Move, create asymmetric search type specific tests in new file
2021-10-02 20:28:33 -07:00
Rename RawConfig Types for Consistency - Naming convention - [ContentType][ConfigType]Config - Where [ConfigType] ~ Content, Search, Processor - Where [ContentType] ~ Text, Image, Asymmetric, Symmetric, Conversation - Current Configs: - Content: - Org Notes - Org Music - Image - Ledger/Beancount - Search: - Asymmetric - Symmetric - Image - Processor: - Conversation
2022-01-14 20:54:38 -05:00
content_config.image = ImageContentConfig(
Allow indexing multiple image directories for image search
2022-07-20 02:54:03 +04:00
input_directories = ['tests/data/images'],
Improve test data organization and update correspoding conftests - Put test data for each content type into separate directories - Makes config.yml for docker and local host consistent - Prepending tests to /data in sample_config.yml makes application run on local host using test data - Allows mounting separate volume for each content type in docker-compose - Ignore gitignore to only add tests content, not generated models or embeddings
2022-01-29 01:57:08 -05:00
embeddings_file = model_dir.joinpath('image_embeddings.pt'),
Split test_main into client and search type specific test files - Move search config fixture to conftests.py to be shared across tests - Move image search type specific tests to test_image_search.py file - Move, create asymmetric search type specific tests in new file
2021-10-02 20:28:33 -07:00
batch_size = 10,
Update types used in conftest.py
2021-12-04 12:02:19 -05:00
use_xmp_metadata = False)
Split test_main into client and search type specific test files - Move search config fixture to conftests.py to be shared across tests - Move image search type specific tests to test_image_search.py file - Move, create asymmetric search type specific tests in new file
2021-10-02 20:28:33 -07:00
Improve test data organization and update correspoding conftests - Put test data for each content type into separate directories - Makes config.yml for docker and local host consistent - Prepending tests to /data in sample_config.yml makes application run on local host using test data - Allows mounting separate volume for each content type in docker-compose - Ignore gitignore to only add tests content, not generated models or embeddings
2022-01-29 01:57:08 -05:00
return content_config
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