512c24fc9c
In the current solution, AgentType and AGENT_TO_CLASS are placed in two separate files and both manually maintained. This might cause inconsistency when we update either of them. — latest — based on the discussion with hwchase17, we don’t know how to further use the newly introduced AgentTypeConfig type, so it doesn’t make sense yet to add it. Instead, it’s better to move the dictionary to another file to keep the loading.py file clear. The consistency is a good point. Instead of asserting the consistency during linting, we added a unittest for consistency check. I think it works as auto unittest is triggered every time with clear failure notice. (well, force push is possible, but we all know what we are doing, so let’s show trust. :>) ~~This PR includes~~ - ~~Introduced AgentTypeConfig as the source of truth of all AgentType related meta data.~~ - ~~Each AgentTypeConfig is a annotated class type which can be used for annotation in other places.~~ - ~~Each AgentTypeConfig can be easily extended when we have more meta data needs.~~ - ~~Strong assertion to ensure AgentType and AGENT_TO_CLASS are always consistent.~~ - ~~Made AGENT_TO_CLASS automatically generated.~~ ~~Test Plan:~~ - ~~since this change is focusing on annotation, lint is the major test focus.~~ - ~~lint, format and test passed on local.~~ |
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| 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.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