forked from Archives/langchain
feat: add pytest-vcr for recording HTTP interactions in integration tests (#2445)
Using `pytest-vcr` in integration tests has several benefits. Firstly, it removes the need to mock external services, as VCR records and replays HTTP interactions on the fly. Secondly, it simplifies the integration test setup by eliminating the need to set up and tear down external services in some cases. Finally, it allows for more reliable and deterministic integration tests by ensuring that HTTP interactions are always replayed with the same response. Overall, `pytest-vcr` is a valuable tool for simplifying integration test setup and improving their reliability This commit adds the `pytest-vcr` package as a dependency for integration tests in the `pyproject.toml` file. It also introduces two new fixtures in `tests/integration_tests/conftest.py` files for managing cassette directories and VCR configurations. In addition, the `tests/integration_tests/vectorstores/test_elasticsearch.py` file has been updated to use the `@pytest.mark.vcr` decorator for recording and replaying HTTP interactions. Finally, this commit removes the `documents` fixture from the `test_elasticsearch.py` file and replaces it with a new fixture defined in `tests/integration_tests/vectorstores/conftest.py` that yields a list of documents to use in any other tests. This also includes my second attempt to fix issue : https://github.com/hwchase17/langchain/issues/2386 Maybe related https://github.com/hwchase17/langchain/issues/2484
This commit is contained in:
sergerdn
GitHub
parent
c9f93f5f74
commit
6dc86ad48f
@ -27,7 +27,7 @@ FROM builder AS dependencies
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COPY pyproject.toml poetry.lock poetry.toml ./
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COPY pyproject.toml poetry.lock poetry.toml ./
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# Install the Poetry dependencies (this layer will be cached as long as the dependencies don't change)
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# Install the Poetry dependencies (this layer will be cached as long as the dependencies don't change)
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RUN $POETRY_HOME/bin/poetry install --no-interaction --no-ansi
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RUN $POETRY_HOME/bin/poetry install --no-interaction --no-ansi --with test
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# Use a multi-stage build to run tests
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# Use a multi-stage build to run tests
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FROM dependencies AS tests
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FROM dependencies AS tests
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@ -35,7 +35,7 @@ FROM dependencies AS tests
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# Copy the rest of the app source code (this layer will be invalidated and rebuilt whenever the source code changes)
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# Copy the rest of the app source code (this layer will be invalidated and rebuilt whenever the source code changes)
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COPY . .
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COPY . .
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RUN /opt/poetry/bin/poetry install --no-interaction --no-ansi
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RUN /opt/poetry/bin/poetry install --no-interaction --no-ansi --with test
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# Set the entrypoint to run tests using Poetry
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# Set the entrypoint to run tests using Poetry
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ENTRYPOINT ["/opt/poetry/bin/poetry", "run", "pytest"]
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ENTRYPOINT ["/opt/poetry/bin/poetry", "run", "pytest"]
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@ -146,6 +146,7 @@ class ElasticVectorSearch(VectorStore, ABC):
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List of ids from adding the texts into the vectorstore.
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List of ids from adding the texts into the vectorstore.
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"""
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"""
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try:
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try:
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from elasticsearch.exceptions import NotFoundError
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from elasticsearch.helpers import bulk
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from elasticsearch.helpers import bulk
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except ImportError:
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except ImportError:
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raise ValueError(
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raise ValueError(
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@ -155,6 +156,17 @@ class ElasticVectorSearch(VectorStore, ABC):
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requests = []
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requests = []
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ids = []
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ids = []
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embeddings = self.embedding.embed_documents(list(texts))
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embeddings = self.embedding.embed_documents(list(texts))
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dim = len(embeddings[0])
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mapping = _default_text_mapping(dim)
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# check to see if the index already exists
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try:
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self.client.indices.get(index=self.index_name)
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except NotFoundError:
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# TODO would be nice to create index before embedding,
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# just to save expensive steps for last
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self.client.indices.create(index=self.index_name, mappings=mapping)
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for i, text in enumerate(texts):
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for i, text in enumerate(texts):
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metadata = metadatas[i] if metadatas else {}
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metadata = metadatas[i] if metadatas else {}
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_id = str(uuid.uuid4())
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_id = str(uuid.uuid4())
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@ -229,6 +241,7 @@ class ElasticVectorSearch(VectorStore, ABC):
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)
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)
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try:
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try:
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import elasticsearch
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import elasticsearch
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from elasticsearch.exceptions import NotFoundError
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from elasticsearch.helpers import bulk
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from elasticsearch.helpers import bulk
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except ImportError:
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except ImportError:
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raise ValueError(
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raise ValueError(
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@ -245,9 +258,15 @@ class ElasticVectorSearch(VectorStore, ABC):
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embeddings = embedding.embed_documents(texts)
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embeddings = embedding.embed_documents(texts)
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dim = len(embeddings[0])
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dim = len(embeddings[0])
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mapping = _default_text_mapping(dim)
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mapping = _default_text_mapping(dim)
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# TODO would be nice to create index before embedding,
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# just to save expensive steps for last
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# check to see if the index already exists
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client.indices.create(index=index_name, mappings=mapping)
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try:
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client.indices.get(index=index_name)
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except NotFoundError:
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# TODO would be nice to create index before embedding,
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# just to save expensive steps for last
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client.indices.create(index=index_name, mappings=mapping)
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requests = []
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requests = []
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for i, text in enumerate(texts):
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for i, text in enumerate(texts):
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metadata = metadatas[i] if metadatas else {}
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metadata = metadatas[i] if metadatas else {}
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46
poetry.lock
generated
46
poetry.lock
generated
@ -1,4 +1,4 @@
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# This file is automatically @generated by Poetry and should not be changed by hand.
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# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
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[[package]]
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[[package]]
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name = "absl-py"
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name = "absl-py"
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@ -5516,6 +5516,22 @@ files = [
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pytest = ">=5.0.0"
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pytest = ">=5.0.0"
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python-dotenv = ">=0.9.1"
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python-dotenv = ">=0.9.1"
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[[package]]
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name = "pytest-vcr"
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version = "1.0.2"
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description = "Plugin for managing VCR.py cassettes"
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category = "dev"
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optional = false
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python-versions = "*"
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files = [
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{file = "pytest-vcr-1.0.2.tar.gz", hash = "sha256:23ee51b75abbcc43d926272773aae4f39f93aceb75ed56852d0bf618f92e1896"},
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{file = "pytest_vcr-1.0.2-py2.py3-none-any.whl", hash = "sha256:2f316e0539399bea0296e8b8401145c62b6f85e9066af7e57b6151481b0d6d9c"},
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]
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[package.dependencies]
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pytest = ">=3.6.0"
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vcrpy = "*"
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[[package]]
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[[package]]
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name = "pytest-watcher"
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name = "pytest-watcher"
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version = "0.2.6"
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version = "0.2.6"
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@ -6828,7 +6844,7 @@ files = [
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]
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]
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[package.dependencies]
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[package.dependencies]
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greenlet = {version = "!=0.4.17", markers = "python_version >= \"3\" and (platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\")"}
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greenlet = {version = "!=0.4.17", markers = "python_version >= \"3\" and platform_machine == \"aarch64\" or python_version >= \"3\" and platform_machine == \"ppc64le\" or python_version >= \"3\" and platform_machine == \"x86_64\" or python_version >= \"3\" and platform_machine == \"amd64\" or python_version >= \"3\" and platform_machine == \"AMD64\" or python_version >= \"3\" and platform_machine == \"win32\" or python_version >= \"3\" and platform_machine == \"WIN32\""}
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[package.extras]
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[package.extras]
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aiomysql = ["aiomysql", "greenlet (!=0.4.17)"]
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aiomysql = ["aiomysql", "greenlet (!=0.4.17)"]
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@ -7930,6 +7946,24 @@ decorator = ">=3.4.0"
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[package.extras]
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[package.extras]
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test = ["flake8 (>=2.4.0)", "isort (>=4.2.2)", "pytest (>=2.2.3)"]
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test = ["flake8 (>=2.4.0)", "isort (>=4.2.2)", "pytest (>=2.2.3)"]
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[[package]]
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name = "vcrpy"
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version = "4.2.1"
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description = "Automatically mock your HTTP interactions to simplify and speed up testing"
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category = "dev"
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optional = false
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python-versions = ">=3.7"
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files = [
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{file = "vcrpy-4.2.1-py2.py3-none-any.whl", hash = "sha256:efac3e2e0b2af7686f83a266518180af7a048619b2f696e7bad9520f5e2eac09"},
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{file = "vcrpy-4.2.1.tar.gz", hash = "sha256:7cd3e81a2c492e01c281f180bcc2a86b520b173d2b656cb5d89d99475423e013"},
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]
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[package.dependencies]
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PyYAML = "*"
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six = ">=1.5"
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wrapt = "*"
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yarl = "*"
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[[package]]
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[[package]]
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name = "wasabi"
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name = "wasabi"
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version = "1.1.1"
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version = "1.1.1"
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@ -8291,7 +8325,7 @@ name = "wrapt"
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version = "1.15.0"
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version = "1.15.0"
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description = "Module for decorators, wrappers and monkey patching."
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description = "Module for decorators, wrappers and monkey patching."
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category = "main"
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category = "main"
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optional = true
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optional = false
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python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
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python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
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files = [
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files = [
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{file = "wrapt-1.15.0-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:ca1cccf838cd28d5a0883b342474c630ac48cac5df0ee6eacc9c7290f76b11c1"},
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{file = "wrapt-1.15.0-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:ca1cccf838cd28d5a0883b342474c630ac48cac5df0ee6eacc9c7290f76b11c1"},
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@ -8488,13 +8522,13 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker
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testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
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testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
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[extras]
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[extras]
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all = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "jina", "manifest-ml", "elasticsearch", "opensearch-py", "google-search-results", "faiss-cpu", "sentence-transformers", "transformers", "spacy", "nltk", "wikipedia", "beautifulsoup4", "tiktoken", "torch", "jinja2", "pinecone-client", "weaviate-client", "redis", "google-api-python-client", "wolframalpha", "qdrant-client", "tensorflow-text", "pypdf", "networkx", "nomic", "aleph-alpha-client", "deeplake", "pgvector", "psycopg2-binary", "boto3", "pyowm"]
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all = ["aleph-alpha-client", "anthropic", "beautifulsoup4", "boto3", "cohere", "deeplake", "elasticsearch", "faiss-cpu", "google-api-python-client", "google-search-results", "huggingface_hub", "jina", "jinja2", "manifest-ml", "networkx", "nlpcloud", "nltk", "nomic", "openai", "opensearch-py", "pgvector", "pinecone-client", "psycopg2-binary", "pyowm", "pypdf", "qdrant-client", "redis", "sentence-transformers", "spacy", "tensorflow-text", "tiktoken", "torch", "transformers", "weaviate-client", "wikipedia", "wolframalpha"]
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cohere = ["cohere"]
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cohere = ["cohere"]
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llms = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "manifest-ml", "torch", "transformers"]
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llms = ["anthropic", "cohere", "huggingface_hub", "manifest-ml", "nlpcloud", "openai", "torch", "transformers"]
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openai = ["openai"]
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openai = ["openai"]
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qdrant = ["qdrant-client"]
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qdrant = ["qdrant-client"]
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[metadata]
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[metadata]
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lock-version = "2.0"
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lock-version = "2.0"
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python-versions = ">=3.8.1,<4.0"
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python-versions = ">=3.8.1,<4.0"
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content-hash = "6dc5842fe2ea7b5e284a1593ee69fdc3bf5589b698153df196d50dad6fd5d5f4"
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content-hash = "5327202e7caf3f6be668049d15cbe117b7d23bfcb4877fa40e24f795a0354ed3"
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@ -90,6 +90,8 @@ optional = true
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[tool.poetry.group.test_integration.dependencies]
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[tool.poetry.group.test_integration.dependencies]
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openai = "^0.27.4"
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openai = "^0.27.4"
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elasticsearch = {extras = ["async"], version = "^8.6.2"}
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elasticsearch = {extras = ["async"], version = "^8.6.2"}
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pytest-vcr = "^1.0.2"
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wrapt = "^1.15.0"
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[tool.poetry.group.lint.dependencies]
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[tool.poetry.group.lint.dependencies]
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ruff = "^0.0.249"
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ruff = "^0.0.249"
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57
tests/README.md
Normal file
57
tests/README.md
Normal file
@ -0,0 +1,57 @@
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# Readme tests(draft)
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## Integrations Tests
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### Prepare
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This repository contains functional tests for several search engines and databases. The
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tests aim to verify the correct behavior of the engines and databases according to their
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specifications and requirements.
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To run some integration tests, such as tests located in
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`tests/integration_tests/vectorstores/`, you will need to install the following
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software:
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- Docker
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- Python 3.8.1 or later
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We have optional group `test_integration` in the `pyproject.toml` file. This group
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should contain dependencies for the integration tests and can be installed using the
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command:
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```bash
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poetry install --with test_integration
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```
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Any new dependencies should be added by running:
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```bash
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poetry add some_new_deps --group "test_integration"
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```
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Before running any tests, you should start a specific Docker container that has all the
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necessary dependencies installed. For instance, we use the `elasticsearch.yml` container
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for `test_elasticsearch.py`:
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```bash
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cd tests/integration_tests/vectorstores/docker-compose
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docker-compose -f elasticsearch.yml up
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```
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Additionally, it's important to note that some integration tests may require certain
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environment variables to be set, such as `OPENAI_API_KEY`. Be sure to set any required
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environment variables before running the tests to ensure they run correctly.
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### Recording HTTP interactions with pytest-vcr
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Some of the integration tests in this repository involve making HTTP requests to
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external services. To prevent these requests from being made every time the tests are
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run, we use pytest-vcr to record and replay HTTP interactions.
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When running tests in a CI/CD pipeline, you may not want to modify the existing
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cassettes. You can use the --vcr-record=none command-line option to disable recording
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new cassettes. Here's an example:
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```bash
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pytest tests/integration_tests/vectorstores/test_elasticsearch.py --vcr-record=none
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```
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32
tests/integration_tests/conftest.py
Normal file
32
tests/integration_tests/conftest.py
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@ -0,0 +1,32 @@
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import os
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import pytest
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# Getting the absolute path of the current file's directory
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ABS_PATH = os.path.dirname(os.path.abspath(__file__))
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# This fixture returns a string containing the path to the cassette directory for the
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# current module
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@pytest.fixture(scope="module")
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def vcr_cassette_dir(request: pytest.FixtureRequest) -> str:
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return os.path.join(
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os.path.dirname(request.module.__file__),
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||||||
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"cassettes",
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||||||
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os.path.basename(request.module.__file__).replace(".py", ""),
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)
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# This fixture returns a dictionary containing filter_headers options
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# for replacing certain headers with dummy values during cassette playback
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# Specifically, it replaces the authorization header with a dummy value to
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# prevent sensitive data from being recorded in the cassette.
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@pytest.fixture(scope="module")
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def vcr_config() -> dict:
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return {
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"filter_headers": [
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("authorization", "authorization-DUMMY"),
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("X-OpenAI-Client-User-Agent", "X-OpenAI-Client-User-Agent-DUMMY"),
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("User-Agent", "User-Agent-DUMMY"),
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],
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}
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@ -0,0 +1,582 @@
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interactions:
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- request:
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body: '{"input": ["Sharks are a group of elasmobranch fish characterized by a
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cartilaginous skeleton, five to seven gill slits on the sides of the head, and
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pectoral fins that are not fused to the head. Modern sharks are classified within
|
||||||
|
the clade Selachimorpha (or Selachii) and are the sister group to the Batoidea
|
||||||
|
(rays and kin). Some sources extend the term \"shark\" as an informal category
|
||||||
|
including extinct members of Chondrichthyes (cartilaginous fish) with a shark-like
|
||||||
|
morphology, such as hybodonts and xenacanths. Shark-like chondrichthyans such
|
||||||
|
as Cladoselache and Doliodus first appeared in the Devonian Period (419-359
|
||||||
|
Ma), though some fossilized chondrichthyan-like scales are as old as the Late
|
||||||
|
Ordovician (458-444 Ma). The oldest modern sharks (selachians) are known from
|
||||||
|
the Early Jurassic, about 200 Ma.", "Sharks range in size from the small dwarf
|
||||||
|
lanternshark (Etmopterus perryi), a deep sea species that is only 17 centimetres
|
||||||
|
(6.7 in) in length, to the whale shark (Rhincodon typus), the largest fish in
|
||||||
|
the world, which reaches approximately 12 metres (40 ft) in length. They are
|
||||||
|
found in all seas and are common to depths up to 2,000 metres (6,600 ft). They
|
||||||
|
generally do not live in freshwater, although there are a few known exceptions,
|
||||||
|
such as the bull shark and the river shark, which can be found in both seawater
|
||||||
|
and freshwater.[3] Sharks have a covering of dermal denticles that protects
|
||||||
|
their skin from damage and parasites in addition to improving their fluid dynamics.
|
||||||
|
They have numerous sets of replaceable teeth.\n\nSeveral species are apex predators,
|
||||||
|
which are organisms that are at the top of their food chain. Select examples
|
||||||
|
include the tiger shark, blue shark, great white shark, mako shark, thresher
|
||||||
|
shark, and hammerhead shark.", "Sharks are caught by humans for shark meat or
|
||||||
|
shark fin soup. Many shark populations are threatened by human activities. Since
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1970, shark populations have been reduced by 71%, mostly from overfishing."],
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openai-processing-ms:
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code: 200
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message: OK
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version: 1
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25
tests/integration_tests/vectorstores/conftest.py
Normal file
25
tests/integration_tests/vectorstores/conftest.py
Normal file
@ -0,0 +1,25 @@
|
|||||||
|
import os
|
||||||
|
from typing import Generator, List
|
||||||
|
|
||||||
|
import pytest
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|
|
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|
from langchain.document_loaders import TextLoader
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from langchain.schema import Document
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from langchain.text_splitter import CharacterTextSplitter
|
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|
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||||||
|
# Define a fixture that yields a generator object returning a list of documents
|
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|
@pytest.fixture(scope="module")
|
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|
def documents() -> Generator[List[Document], None, None]:
|
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|
"""Return a generator that yields a list of documents."""
|
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|
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||||||
|
# Create a CharacterTextSplitter object for splitting the documents into chunks
|
||||||
|
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
|
||||||
|
|
||||||
|
# Load the documents from a file located in the fixtures directory
|
||||||
|
documents = TextLoader(
|
||||||
|
os.path.join(os.path.dirname(__file__), "fixtures", "sharks.txt")
|
||||||
|
).load()
|
||||||
|
|
||||||
|
# Yield the documents split into chunks
|
||||||
|
yield text_splitter.split_documents(documents)
|
||||||
@ -1,6 +1,7 @@
|
|||||||
"""Test ElasticSearch functionality."""
|
"""Test ElasticSearch functionality."""
|
||||||
import logging
|
import logging
|
||||||
import os
|
import os
|
||||||
|
import uuid
|
||||||
from typing import Generator, List, Union
|
from typing import Generator, List, Union
|
||||||
|
|
||||||
import pytest
|
import pytest
|
||||||
@ -76,6 +77,7 @@ class TestElasticsearch:
|
|||||||
output = docsearch.similarity_search("foo", k=1)
|
output = docsearch.similarity_search("foo", k=1)
|
||||||
assert output == [Document(page_content="foo", metadata={"page": 0})]
|
assert output == [Document(page_content="foo", metadata={"page": 0})]
|
||||||
|
|
||||||
|
@pytest.mark.vcr(ignore_localhost=True)
|
||||||
def test_default_index_from_documents(
|
def test_default_index_from_documents(
|
||||||
self, documents: List[Document], openai_api_key: str, elasticsearch_url: str
|
self, documents: List[Document], openai_api_key: str, elasticsearch_url: str
|
||||||
) -> None:
|
) -> None:
|
||||||
@ -94,44 +96,55 @@ class TestElasticsearch:
|
|||||||
print(search_result)
|
print(search_result)
|
||||||
assert len(search_result) != 0
|
assert len(search_result) != 0
|
||||||
|
|
||||||
|
@pytest.mark.vcr(ignore_localhost=True)
|
||||||
def test_custom_index_from_documents(
|
def test_custom_index_from_documents(
|
||||||
self, documents: List[Document], openai_api_key: str, elasticsearch_url: str
|
self, documents: List[Document], openai_api_key: str, elasticsearch_url: str
|
||||||
) -> None:
|
) -> None:
|
||||||
"""This test checks the construction of a custom
|
"""This test checks the construction of a custom
|
||||||
ElasticSearch index using the 'from_documents'."""
|
ElasticSearch index using the 'from_documents'."""
|
||||||
|
|
||||||
|
index_name = f"custom_index_{uuid.uuid4().hex}"
|
||||||
embedding = OpenAIEmbeddings(openai_api_key=openai_api_key)
|
embedding = OpenAIEmbeddings(openai_api_key=openai_api_key)
|
||||||
elastic_vector_search = ElasticVectorSearch.from_documents(
|
elastic_vector_search = ElasticVectorSearch.from_documents(
|
||||||
documents=documents,
|
documents=documents,
|
||||||
embedding=embedding,
|
embedding=embedding,
|
||||||
elasticsearch_url=elasticsearch_url,
|
elasticsearch_url=elasticsearch_url,
|
||||||
index_name="custom_index",
|
index_name=index_name,
|
||||||
)
|
)
|
||||||
es = Elasticsearch(hosts=elasticsearch_url)
|
es = Elasticsearch(hosts=elasticsearch_url)
|
||||||
index_names = es.indices.get(index="_all").keys()
|
index_names = es.indices.get(index="_all").keys()
|
||||||
assert "custom_index" in index_names
|
assert index_name in index_names
|
||||||
|
|
||||||
search_result = elastic_vector_search.similarity_search("sharks")
|
search_result = elastic_vector_search.similarity_search("sharks")
|
||||||
print(search_result)
|
print(search_result)
|
||||||
|
|
||||||
assert len(search_result) != 0
|
assert len(search_result) != 0
|
||||||
|
|
||||||
|
@pytest.mark.vcr(ignore_localhost=True)
|
||||||
def test_custom_index_add_documents(
|
def test_custom_index_add_documents(
|
||||||
self, documents: List[Document], openai_api_key: str, elasticsearch_url: str
|
self, documents: List[Document], openai_api_key: str, elasticsearch_url: str
|
||||||
) -> None:
|
) -> None:
|
||||||
"""This test checks the construction of a custom
|
"""This test checks the construction of a custom
|
||||||
ElasticSearch index using the 'add_documents'."""
|
ElasticSearch index using the 'add_documents'."""
|
||||||
|
|
||||||
|
index_name = f"custom_index_{uuid.uuid4().hex}"
|
||||||
embedding = OpenAIEmbeddings(openai_api_key=openai_api_key)
|
embedding = OpenAIEmbeddings(openai_api_key=openai_api_key)
|
||||||
elastic_vector_search = ElasticVectorSearch(
|
elastic_vector_search = ElasticVectorSearch(
|
||||||
embedding=embedding,
|
embedding=embedding,
|
||||||
elasticsearch_url=elasticsearch_url,
|
elasticsearch_url=elasticsearch_url,
|
||||||
index_name="custom_index",
|
index_name=index_name,
|
||||||
)
|
)
|
||||||
es = Elasticsearch(hosts=elasticsearch_url)
|
es = Elasticsearch(hosts=elasticsearch_url)
|
||||||
index_names = es.indices.get(index="_all").keys()
|
|
||||||
assert "custom_index" in index_names
|
|
||||||
|
|
||||||
elastic_vector_search.add_documents(documents)
|
elastic_vector_search.add_documents(documents)
|
||||||
|
|
||||||
|
index_names = es.indices.get(index="_all").keys()
|
||||||
|
assert index_name in index_names
|
||||||
|
|
||||||
search_result = elastic_vector_search.similarity_search("sharks")
|
search_result = elastic_vector_search.similarity_search("sharks")
|
||||||
print(search_result)
|
print(search_result)
|
||||||
|
|
||||||
assert len(search_result) != 0
|
assert len(search_result) != 0
|
||||||
|
|
||||||
|
def test_custom_index_add_documents_to_exists_store(self) -> None:
|
||||||
|
# TODO: implement it
|
||||||
|
pass
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user