langchain/tests
Raymond Yuan 5171c3bcca
Refactor vector storage to correctly handle relevancy scores (#6570)
Description: This pull request aims to support generating the correct
generic relevancy scores for different vector stores by refactoring the
relevance score functions and their selection in the base class and
subclasses of VectorStore. This is especially relevant with VectorStores
that require a distance metric upon initialization. Note many of the
current implenetations of `_similarity_search_with_relevance_scores` are
not technically correct, as they just return
`self.similarity_search_with_score(query, k, **kwargs)` without applying
the relevant score function

Also includes changes associated with:
https://github.com/hwchase17/langchain/pull/6564 and
https://github.com/hwchase17/langchain/pull/6494

See more indepth discussion in thread in #6494 

Issue: 
https://github.com/hwchase17/langchain/issues/6526
https://github.com/hwchase17/langchain/issues/6481
https://github.com/hwchase17/langchain/issues/6346

Dependencies: None

The changes include:
- Properly handling score thresholding in FAISS
`similarity_search_with_score_by_vector` for the corresponding distance
metric.
- Refactoring the `_similarity_search_with_relevance_scores` method in
the base class and removing it from the subclasses for incorrectly
implemented subclasses.
- Adding a `_select_relevance_score_fn` method in the base class and
implementing it in the subclasses to select the appropriate relevance
score function based on the distance strategy.
- Updating the `__init__` methods of the subclasses to set the
`relevance_score_fn` attribute.
- Removing the `_default_relevance_score_fn` function from the FAISS
class and using the base class's `_euclidean_relevance_score_fn`
instead.
- Adding the `DistanceStrategy` enum to the `utils.py` file and updating
the imports in the vector store classes.
- Updating the tests to import the `DistanceStrategy` enum from the
`utils.py` file.

---------

Co-authored-by: Hanit <37485638+hanit-com@users.noreply.github.com>
2023-07-10 20:37:03 -07:00
..
integration_tests Refactor vector storage to correctly handle relevancy scores (#6570) 2023-07-10 20:37:03 -07:00
mock_servers
unit_tests Add ZepMemory; improve ZepChatMessageHistory handling of metadata; Fix bugs (#7444) 2023-07-10 01:53:49 -04:00
__init__.py
data.py Add workflow for testing with all deps (#4410) 2023-05-10 09:35:07 -04:00
README.md

Readme tests(draft)

Integrations Tests

Prepare

This repository contains functional tests for several search engines and databases. The tests aim to verify the correct behavior of the engines and databases according to their specifications and requirements.

To run some integration tests, such as tests located in tests/integration_tests/vectorstores/, you will need to install the following software:

  • Docker
  • Python 3.8.1 or later

We have optional group test_integration in the pyproject.toml file. This group should contain dependencies for the integration tests and can be installed using the command:

poetry install --with test_integration

Any new dependencies should be added by running:

# add package and install it after adding:
poetry add tiktoken@latest --group "test_integration" && poetry install --with test_integration

Before running any tests, you should start a specific Docker container that has all the necessary dependencies installed. For instance, we use the elasticsearch.yml container for test_elasticsearch.py:

cd tests/integration_tests/vectorstores/docker-compose
docker-compose -f elasticsearch.yml up

Prepare environment variables for local testing:

  • copy tests/.env.example to tests/.env
  • set variables in tests/.env file, e.g OPENAI_API_KEY

Additionally, it's important to note that some integration tests may require certain environment variables to be set, such as OPENAI_API_KEY. Be sure to set any required environment variables before running the tests to ensure they run correctly.

Recording HTTP interactions with pytest-vcr

Some of the integration tests in this repository involve making HTTP requests to external services. To prevent these requests from being made every time the tests are run, we use pytest-vcr to record and replay HTTP interactions.

When running tests in a CI/CD pipeline, you may not want to modify the existing cassettes. You can use the --vcr-record=none command-line option to disable recording new cassettes. Here's an example:

pytest --log-cli-level=10 tests/integration_tests/vectorstores/test_pinecone.py --vcr-record=none
pytest tests/integration_tests/vectorstores/test_elasticsearch.py --vcr-record=none

Run some tests with coverage:

pytest tests/integration_tests/vectorstores/test_elasticsearch.py --cov=langchain --cov-report=html
start "" htmlcov/index.html || open htmlcov/index.html