Mike Nitsenko
d983046f90
**PR Description:** This pull request introduces several enhancements and new features to the `CubeSemanticLoader`. The changes include the following: 1. Added imports for the `json` and `time` modules. 2. Added new constructor parameters: `load_dimension_values`, `dimension_values_limit`, `dimension_values_max_retries`, and `dimension_values_retry_delay`. 3. Updated the class documentation with descriptions for the new constructor parameters. 4. Added a new private method `_get_dimension_values()` to retrieve dimension values from Cube's REST API. 5. Modified the `load()` method to load dimension values for string dimensions if `load_dimension_values` is set to `True`. 6. Updated the API endpoint in the `load()` method from the base URL to the metadata endpoint. 7. Refactored the code to retrieve metadata from the response JSON. 8. Added the `column_member_type` field to the metadata dictionary to indicate if a column is a measure or a dimension. 9. Added the `column_values` field to the metadata dictionary to store the dimension values retrieved from Cube's API. 10. Modified the `page_content` construction to include the column title and description instead of the table name, column name, data type, title, and description. These changes improve the functionality and flexibility of the `CubeSemanticLoader` class by allowing the loading of dimension values and providing more detailed metadata for each document. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
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.exampletotests/.env - set variables in
tests/.envfile, e.gOPENAI_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