mirror of
https://github.com/deepset-ai/haystack.git
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refactor: Refactor Weaviate tests (#3541)
* refactor tests * fix job * revert * revert * revert * use latest weaviate * fix abstract methods signatures * pass class_name to all the CRUD methods * finish moving all the tests * bump weaviate version * raise, don't pass
This commit is contained in:
Massimiliano Pippi
GitHub
parent
da6b0dc66f
commit
4dfddf0d10
110
.github/workflows/tests.yml
vendored
110
.github/workflows/tests.yml
vendored
@ -325,6 +325,44 @@ jobs:
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if: failure() && github.repository_owner == 'deepset-ai' && github.ref == 'refs/heads/main'
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integration-tests-weaviate:
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name: Integration / Weaviate / ${{ matrix.os }}
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needs:
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- unit-tests
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strategy:
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fail-fast: false
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matrix:
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os: [ubuntu-latest]
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runs-on: ${{ matrix.os }}
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services:
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weaviate:
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image: semitechnologies/weaviate:1.16.0
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env:
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AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED: "true"
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PERSISTENCE_DATA_PATH: "/var/lib/weaviate"
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ENABLE_EXPERIMENTAL_BM25: "true"
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DISK_USE_READONLY_PERCENTAGE: 95
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ports:
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- 8080:8080
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steps:
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- uses: actions/checkout@v3
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- name: Setup Python
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uses: ./.github/actions/python_cache/
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- name: Install Haystack
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run: pip install -U .[docstores]
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- name: Run tests
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run: |
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pytest --maxfail=5 -m "document_store and integration" test/document_stores/test_weaviate.py
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- uses: act10ns/slack@v1
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with:
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status: ${{ job.status }}
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channel: '#haystack'
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if: failure() && github.repository_owner == 'deepset-ai' && github.ref == 'refs/heads/main'
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#
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# TODO: the following steps need to be revisited
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#
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@ -502,78 +540,6 @@ jobs:
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# pytest ${{ env.PYTEST_PARAMS }} -m "milvus and not integration" ${{ env.SUITES_EXCLUDED_FROM_WINDOWS }} test/document_stores/ --document_store_type=milvus
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weaviate-tests-linux:
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needs: [mypy, pylint, black]
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runs-on: ubuntu-latest
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if: contains(github.event.pull_request.labels.*.name, 'topic:weaviate') || !github.event.pull_request.draft
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steps:
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- uses: actions/checkout@v3
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- name: Setup Python
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uses: ./.github/actions/python_cache/
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- name: Setup Weaviate
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run: docker run -d -p 8080:8080 --name haystack_test_weaviate --env AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED='true' --env PERSISTENCE_DATA_PATH='/var/lib/weaviate' --env ENABLE_EXPERIMENTAL_BM25='true' --env DISK_USE_READONLY_PERCENTAGE='95' semitechnologies/weaviate:1.14.1
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# TODO Let's try to remove this one from the unit tests
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- name: Install pdftotext
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run: wget --no-check-certificate https://dl.xpdfreader.com/xpdf-tools-linux-4.04.tar.gz && tar -xvf xpdf-tools-linux-4.04.tar.gz && sudo cp xpdf-tools-linux-4.04/bin64/pdftotext /usr/local/bin
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- name: Install Haystack
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run: pip install .[weaviate]
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- name: Run tests
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env:
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TOKENIZERS_PARALLELISM: 'false'
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run: |
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pytest ${{ env.PYTEST_PARAMS }} -m "weaviate and not integration" test/document_stores/ --document_store_type=weaviate
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- name: Dump docker logs on failure
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if: failure()
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uses: jwalton/gh-docker-logs@v1
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- uses: act10ns/slack@v1
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with:
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status: ${{ job.status }}
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channel: '#haystack'
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if: failure() && github.repository_owner == 'deepset-ai' && github.ref == 'refs/heads/main'
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# FIXME: seems like we can't run containers on Windows
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# weaviate-tests-windows:
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# needs:
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# - mypy
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# - pylint
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# runs-on: windows-latest
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# if: contains(github.event.pull_request.labels.*.name, 'topic:weaviate') && contains(github.event.pull_request.labels.*.name, 'topic:windows') || !github.event.pull_request.draft
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# steps:
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# - uses: actions/checkout@v3
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# - name: Setup Python
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# uses: ./.github/actions/python_cache/
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# with:
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# prefix: windows
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# - name: Setup Weaviate
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# run: docker run -d -p 8080:8080 --name haystack_test_weaviate --env AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED='true' --env PERSISTENCE_DATA_PATH='/var/lib/weaviate' --env ENABLE_EXPERIMENTAL_BM25='true' --env DISK_USE_READONLY_PERCENTAGE='95' semitechnologies/weaviate:1.14.1
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# - name: Install pdftotext
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# run: |
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# choco install xpdf-utils
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# choco install openjdk11
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# refreshenv
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# - name: Install Haystack
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# run: pip install .[weaviate]
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# - name: Run tests
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# env:
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# TOKENIZERS_PARALLELISM: 'false'
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# run: |
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# pytest ${{ env.PYTEST_PARAMS }} -m "weaviate and not integration" ${{ env.SUITES_EXCLUDED_FROM_WINDOWS }} test/document_stores/ --document_store_type=weaviate
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pinecone-tests-linux:
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needs: [mypy, pylint, black]
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runs-on: ubuntu-latest
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@ -17,7 +17,7 @@ except (ImportError, ModuleNotFoundError) as ie:
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_optional_component_not_installed(__name__, "weaviate", ie)
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from haystack.schema import Document
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from haystack.schema import Document, Label
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from haystack.document_stores import BaseDocumentStore
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from haystack.document_stores.base import get_batches_from_generator
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from haystack.document_stores.filter_utils import LogicalFilterClause
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@ -312,7 +312,7 @@ class WeaviateDocumentStore(BaseDocumentStore):
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id = self._sanitize_id(id=id, index=index)
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result = None
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try:
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result = self.weaviate_client.data_object.get_by_id(id, with_vector=True)
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result = self.weaviate_client.data_object.get_by_id(id, class_name=index, with_vector=True)
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except weaviate.exceptions.UnexpectedStatusCodeException as usce:
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logging.debug("Weaviate could not get the document requested: %s", usce)
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if result:
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@ -339,7 +339,7 @@ class WeaviateDocumentStore(BaseDocumentStore):
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id = self._sanitize_id(id=id, index=index)
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result = None
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try:
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result = self.weaviate_client.data_object.get_by_id(id, with_vector=True)
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result = self.weaviate_client.data_object.get_by_id(id, class_name=index, with_vector=True)
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except weaviate.exceptions.UnexpectedStatusCodeException as usce:
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logging.debug("Weaviate could not get the document requested: %s", usce)
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if result:
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@ -1352,7 +1352,7 @@ class WeaviateDocumentStore(BaseDocumentStore):
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if ids and not filters:
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for id in ids:
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self.weaviate_client.data_object.delete(id)
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self.weaviate_client.data_object.delete(id, class_name=index)
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else:
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# Use filters to restrict list of retrieved documents, before checking these against provided ids
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@ -1360,7 +1360,7 @@ class WeaviateDocumentStore(BaseDocumentStore):
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if ids:
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docs_to_delete = [doc for doc in docs_to_delete if doc.id in ids]
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for doc in docs_to_delete:
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self.weaviate_client.data_object.delete(doc.id)
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self.weaviate_client.data_object.delete(doc.id, class_name=index)
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def delete_index(self, index: str):
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"""
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@ -1382,7 +1382,13 @@ class WeaviateDocumentStore(BaseDocumentStore):
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self.weaviate_client.schema.delete_class(index)
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logger.info("Index '%s' deleted.", index)
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def delete_labels(self):
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def delete_labels(
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self,
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index: Optional[str] = None,
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ids: Optional[List[str]] = None,
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filters: Optional[Dict[str, Union[Dict, List, str, int, float, bool]]] = None,
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headers: Optional[Dict[str, str]] = None,
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):
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"""
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Implemented to respect BaseDocumentStore's contract.
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@ -1390,7 +1396,12 @@ class WeaviateDocumentStore(BaseDocumentStore):
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"""
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raise NotImplementedError("Weaviate does not support labels (yet).")
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def get_all_labels(self):
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def get_all_labels(
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self,
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index: Optional[str] = None,
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filters: Optional[Dict[str, Union[Dict, List, str, int, float, bool]]] = None,
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headers: Optional[Dict[str, str]] = None,
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) -> List[Label]:
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"""
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Implemented to respect BaseDocumentStore's contract.
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@ -1398,7 +1409,7 @@ class WeaviateDocumentStore(BaseDocumentStore):
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"""
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raise NotImplementedError("Weaviate does not support labels (yet).")
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def get_label_count(self):
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def get_label_count(self, index: Optional[str] = None, headers: Optional[Dict[str, str]] = None) -> int:
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"""
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Implemented to respect BaseDocumentStore's contract.
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@ -1406,10 +1417,15 @@ class WeaviateDocumentStore(BaseDocumentStore):
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"""
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raise NotImplementedError("Weaviate does not support labels (yet).")
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def write_labels(self):
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def write_labels(
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self,
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labels: Union[List[Label], List[dict]],
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index: Optional[str] = None,
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headers: Optional[Dict[str, str]] = None,
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):
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"""
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Implemented to respect BaseDocumentStore's contract.
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Weaviate does not support labels (yet).
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"""
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pass
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raise NotImplementedError("Weaviate does not support labels (yet).")
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@ -70,7 +70,7 @@ def launch_weaviate(sleep=15):
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logger.debug("Starting Weaviate ...")
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status = subprocess.run(
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[
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f"docker start {WEAVIATE_CONTAINER_NAME} > /dev/null 2>&1 || docker run -d -p 8080:8080 --env AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED='true' --env PERSISTENCE_DATA_PATH='/var/lib/weaviate' --name {WEAVIATE_CONTAINER_NAME} semitechnologies/weaviate:1.14.0"
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f"docker start {WEAVIATE_CONTAINER_NAME} > /dev/null 2>&1 || docker run -d -p 8080:8080 --env AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED='true' --env PERSISTENCE_DATA_PATH='/var/lib/weaviate' --name {WEAVIATE_CONTAINER_NAME} semitechnologies/weaviate:latest"
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],
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shell=True,
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)
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@ -124,7 +124,7 @@ milvus = [
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"farm-haystack[sql,only-milvus]",
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]
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weaviate = [
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"weaviate-client==3.6.0",
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"weaviate-client==3.9.0",
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]
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only-pinecone = [
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"pinecone-client>=2.0.11,<3",
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@ -314,9 +314,6 @@ disable = [
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"simplifiable-if-expression",
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"use-list-literal",
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# To review later
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"cyclic-import",
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"import-outside-toplevel",
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@ -334,7 +331,7 @@ addopts = "--strict-markers"
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markers = [
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"unit: unit tests",
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"integration: integration tests",
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"generator: generator tests",
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"summarizer: summarizer tests",
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"embedding_dim: uses a document store with non-default embedding dimension (e.g @pytest.mark.embedding_dim(128))",
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@ -493,7 +493,7 @@ def weaviate_fixture():
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print("Starting Weaviate servers ...")
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status = subprocess.run(["docker rm haystack_test_weaviate"], shell=True)
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status = subprocess.run(
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["docker run -d --name haystack_test_weaviate -p 8080:8080 semitechnologies/weaviate:1.14.1"], shell=True
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["docker run -d --name haystack_test_weaviate -p 8080:8080 semitechnologies/weaviate:latest"], shell=True
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)
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if status.returncode:
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raise Exception("Failed to launch Weaviate. Please check docker container logs.")
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@ -177,13 +177,13 @@ class DocumentStoreBaseTestAbstract:
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def test_comparison_filters(self, ds, documents):
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ds.write_documents(documents)
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result = ds.get_all_documents(filters={"numbers": {"$gt": 0}})
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result = ds.get_all_documents(filters={"numbers": {"$gt": 0.0}})
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assert len(result) == 3
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result = ds.get_all_documents(filters={"numbers": {"$gte": -2}})
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result = ds.get_all_documents(filters={"numbers": {"$gte": -2.0}})
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assert len(result) == 6
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result = ds.get_all_documents(filters={"numbers": {"$lt": 0}})
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result = ds.get_all_documents(filters={"numbers": {"$lt": 0.0}})
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assert len(result) == 3
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result = ds.get_all_documents(filters={"numbers": {"$lte": 2.0}})
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@ -297,7 +297,7 @@ class DocumentStoreBaseTestAbstract:
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@pytest.mark.integration
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def test_get_document_count(self, ds, documents):
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ds.write_documents(documents)
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assert ds.get_document_count() == 9
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assert ds.get_document_count() == len(documents)
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assert ds.get_document_count(filters={"year": ["2020"]}) == 3
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assert ds.get_document_count(filters={"month": ["02"]}) == 3
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@ -1,3 +1,11 @@
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import pytest
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from haystack.document_stores.weaviate import WeaviateDocumentStore
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from haystack.schema import Document
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from .test_base import DocumentStoreBaseTestAbstract
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import uuid
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from unittest.mock import MagicMock
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@ -5,7 +13,6 @@ import numpy as np
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import pytest
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from haystack.schema import Document
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from ..conftest import get_document_store
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embedding_dim = 768
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@ -14,162 +21,207 @@ def get_uuid():
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return str(uuid.uuid4())
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DOCUMENTS = [
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{"content": "text1", "id": "not a correct uuid", "key": "a"},
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{"content": "text2", "id": get_uuid(), "key": "b", "embedding": np.random.rand(embedding_dim).astype(np.float32)},
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{"content": "text3", "id": get_uuid(), "key": "b", "embedding": np.random.rand(embedding_dim).astype(np.float32)},
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{"content": "text4", "id": get_uuid(), "key": "b", "embedding": np.random.rand(embedding_dim).astype(np.float32)},
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{"content": "text5", "id": get_uuid(), "key": "b", "embedding": np.random.rand(embedding_dim).astype(np.float32)},
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]
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class TestWeaviateDocumentStore(DocumentStoreBaseTestAbstract):
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# Constants
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DOCUMENTS_XS = [
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# current "dict" format for a document
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{
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"content": "My name is Carla and I live in Berlin",
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"id": get_uuid(),
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"meta": {"metafield": "test1", "name": "filename1"},
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"embedding": np.random.rand(embedding_dim).astype(np.float32),
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},
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# meta_field at the top level for backward compatibility
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{
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"content": "My name is Paul and I live in New York",
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"id": get_uuid(),
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"metafield": "test2",
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"name": "filename2",
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"embedding": np.random.rand(embedding_dim).astype(np.float32),
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},
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# Document object for a doc
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Document(
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content="My name is Christelle and I live in Paris",
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id=get_uuid(),
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meta={"metafield": "test3", "name": "filename3"},
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embedding=np.random.rand(embedding_dim).astype(np.float32),
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),
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]
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index_name = "DocumentsTest"
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@pytest.fixture
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def ds(self):
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return WeaviateDocumentStore(index=self.index_name, recreate_index=True)
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@pytest.fixture(params=["weaviate"])
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def document_store_with_docs(request, tmp_path):
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document_store = get_document_store(request.param, tmp_path=tmp_path)
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document_store.write_documents(DOCUMENTS_XS)
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yield document_store
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document_store.delete_index(document_store.index)
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@pytest.fixture(scope="class")
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def documents(self):
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documents = []
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for i in range(3):
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documents.append(
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Document(
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id=get_uuid(),
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content=f"A Foo Document {i}",
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meta={"name": f"name_{i}", "year": "2020", "month": "01", "numbers": [2.0, 4.0]},
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embedding=np.random.rand(768).astype(np.float32),
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)
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)
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documents.append(
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Document(
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id=get_uuid(),
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content=f"A Bar Document {i}",
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meta={"name": f"name_{i}", "year": "2021", "month": "02", "numbers": [-2.0, -4.0]},
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embedding=np.random.rand(768).astype(np.float32),
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)
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)
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@pytest.fixture(params=["weaviate"])
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def document_store(request, tmp_path):
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document_store = get_document_store(request.param, tmp_path=tmp_path)
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yield document_store
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document_store.delete_index(document_store.index)
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documents.append(
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Document(
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id=get_uuid(),
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content=f"A Baz Document {i}",
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meta={"name": f"name_{i}", "month": "03"},
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embedding=np.random.rand(768).astype(np.float32),
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)
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)
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return documents
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@pytest.mark.weaviate
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@pytest.mark.parametrize("document_store", ["weaviate"], indirect=True)
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@pytest.mark.parametrize("batch_size", [2])
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||||
def test_weaviate_write_docs(document_store, batch_size):
|
||||
# Write in small batches
|
||||
for i in range(0, len(DOCUMENTS), batch_size):
|
||||
document_store.write_documents(DOCUMENTS[i : i + batch_size])
|
||||
@pytest.mark.skip(reason="Weaviate does not support labels")
|
||||
@pytest.mark.integration
|
||||
def test_write_labels(self):
|
||||
pass
|
||||
|
||||
documents_indexed = document_store.get_all_documents()
|
||||
assert len(documents_indexed) == len(DOCUMENTS)
|
||||
@pytest.mark.skip(reason="Weaviate does not support labels")
|
||||
@pytest.mark.integration
|
||||
def test_delete_labels(self):
|
||||
pass
|
||||
|
||||
documents_indexed = document_store.get_all_documents(batch_size=batch_size)
|
||||
assert len(documents_indexed) == len(DOCUMENTS)
|
||||
@pytest.mark.skip(reason="Weaviate does not support labels")
|
||||
@pytest.mark.integration
|
||||
def test_delete_labels_by_id(self):
|
||||
pass
|
||||
|
||||
@pytest.mark.skip(reason="Weaviate does not support labels")
|
||||
@pytest.mark.integration
|
||||
def test_delete_labels_by_filter(self):
|
||||
pass
|
||||
|
||||
@pytest.mark.weaviate
|
||||
@pytest.mark.parametrize("document_store_with_docs", ["weaviate"], indirect=True)
|
||||
def test_query_by_embedding(document_store_with_docs):
|
||||
docs = document_store_with_docs.query_by_embedding(np.random.rand(embedding_dim).astype(np.float32))
|
||||
assert len(docs) == 3
|
||||
@pytest.mark.skip(reason="Weaviate does not support labels")
|
||||
@pytest.mark.integration
|
||||
def test_delete_labels_by_filter_id(self):
|
||||
pass
|
||||
|
||||
docs = document_store_with_docs.query_by_embedding(np.random.rand(embedding_dim).astype(np.float32), top_k=1)
|
||||
assert len(docs) == 1
|
||||
@pytest.mark.skip(reason="Weaviate does not support labels")
|
||||
@pytest.mark.integration
|
||||
def test_get_label_count(self):
|
||||
pass
|
||||
|
||||
docs = document_store_with_docs.query_by_embedding(
|
||||
np.random.rand(embedding_dim).astype(np.float32), filters={"name": ["filename2"]}
|
||||
)
|
||||
assert len(docs) == 1
|
||||
@pytest.mark.skip(reason="Weaviate does not support labels")
|
||||
@pytest.mark.integration
|
||||
def test_write_labels_duplicate(self):
|
||||
pass
|
||||
|
||||
@pytest.mark.skip(reason="Weaviate does not support labels")
|
||||
@pytest.mark.integration
|
||||
def test_write_get_all_labels(self):
|
||||
pass
|
||||
|
||||
@pytest.mark.weaviate
|
||||
@pytest.mark.parametrize("document_store_with_docs", ["weaviate"], indirect=True)
|
||||
def test_query(document_store_with_docs):
|
||||
query_text = "My name is Carla and I live in Berlin"
|
||||
docs = document_store_with_docs.query(query_text)
|
||||
assert len(docs) == 3
|
||||
@pytest.mark.integration
|
||||
def test_ne_filters(self, ds, documents):
|
||||
"""
|
||||
Weaviate doesn't include documents if the field is missing,
|
||||
so we customize this test
|
||||
"""
|
||||
ds.write_documents(documents)
|
||||
|
||||
# BM25 retrieval WITH filters is not yet supported as of Weaviate v1.14.1
|
||||
with pytest.raises(Exception):
|
||||
docs = document_store_with_docs.query(query_text, filters={"name": ["filename2"]})
|
||||
result = ds.get_all_documents(filters={"year": {"$ne": "2020"}})
|
||||
assert len(result) == 3
|
||||
|
||||
docs = document_store_with_docs.query(filters={"name": ["filename2"]})
|
||||
assert len(docs) == 1
|
||||
@pytest.mark.integration
|
||||
def test_nin_filters(self, ds, documents):
|
||||
"""
|
||||
Weaviate doesn't include documents if the field is missing,
|
||||
so we customize this test
|
||||
"""
|
||||
ds.write_documents(documents)
|
||||
|
||||
docs = document_store_with_docs.query(filters={"content": [query_text.lower()]})
|
||||
assert len(docs) == 1
|
||||
result = ds.get_all_documents(filters={"year": {"$nin": ["2020", "2021", "n.a."]}})
|
||||
assert len(result) == 0
|
||||
|
||||
docs = document_store_with_docs.query(filters={"content": ["live"]})
|
||||
assert len(docs) == 3
|
||||
@pytest.mark.integration
|
||||
def test_delete_index(self, ds, documents):
|
||||
"""Contrary to other Document Stores, this doesn't raise if the index is empty"""
|
||||
ds.write_documents(documents, index="custom_index")
|
||||
assert ds.get_document_count(index="custom_index") == len(documents)
|
||||
ds.delete_index(index="custom_index")
|
||||
assert ds.get_document_count(index="custom_index") == 0
|
||||
|
||||
@pytest.mark.integration
|
||||
def test_query_by_embedding(self, ds, documents):
|
||||
ds.write_documents(documents)
|
||||
|
||||
@pytest.mark.weaviate
|
||||
def test_get_all_documents_unaffected_by_QUERY_MAXIMUM_RESULTS(document_store_with_docs, monkeypatch):
|
||||
"""
|
||||
Ensure `get_all_documents` works no matter the value of QUERY_MAXIMUM_RESULTS
|
||||
see https://github.com/deepset-ai/haystack/issues/2517
|
||||
"""
|
||||
monkeypatch.setattr(document_store_with_docs, "get_document_count", lambda **kwargs: 13_000)
|
||||
docs = document_store_with_docs.get_all_documents()
|
||||
assert len(docs) == 3
|
||||
docs = ds.query_by_embedding(np.random.rand(embedding_dim).astype(np.float32))
|
||||
assert len(docs) == 9
|
||||
|
||||
docs = ds.query_by_embedding(np.random.rand(embedding_dim).astype(np.float32), top_k=1)
|
||||
assert len(docs) == 1
|
||||
|
||||
@pytest.mark.weaviate
|
||||
@pytest.mark.parametrize("document_store_with_docs", ["weaviate"], indirect=True)
|
||||
def test_deleting_by_id_or_by_filters(document_store_with_docs):
|
||||
# This test verifies that deleting an object by its ID does not first require fetching all documents. This fixes
|
||||
# a bug, as described in https://github.com/deepset-ai/haystack/issues/2898
|
||||
document_store_with_docs.get_all_documents = MagicMock(wraps=document_store_with_docs.get_all_documents)
|
||||
docs = ds.query_by_embedding(np.random.rand(embedding_dim).astype(np.float32), filters={"name": ["name_1"]})
|
||||
assert len(docs) == 3
|
||||
|
||||
assert document_store_with_docs.get_document_count() == 3
|
||||
@pytest.mark.integration
|
||||
def test_query(self, ds, documents):
|
||||
ds.write_documents(documents)
|
||||
|
||||
# Delete a document by its ID. This should bypass the get_all_documents() call
|
||||
document_store_with_docs.delete_documents(ids=[DOCUMENTS_XS[0]["id"]])
|
||||
document_store_with_docs.get_all_documents.assert_not_called()
|
||||
assert document_store_with_docs.get_document_count() == 2
|
||||
query_text = "Foo"
|
||||
docs = ds.query(query_text)
|
||||
assert len(docs) == 3
|
||||
|
||||
document_store_with_docs.get_all_documents.reset_mock()
|
||||
# Delete a document with filters. Prove that using the filters will go through get_all_documents()
|
||||
document_store_with_docs.delete_documents(filters={"name": ["filename2"]})
|
||||
document_store_with_docs.get_all_documents.assert_called()
|
||||
assert document_store_with_docs.get_document_count() == 1
|
||||
# BM25 retrieval WITH filters is not yet supported as of Weaviate v1.14.1
|
||||
with pytest.raises(Exception):
|
||||
docs = ds.query(query_text, filters={"name": ["filename2"]})
|
||||
|
||||
docs = ds.query(filters={"name": ["name_0"]})
|
||||
assert len(docs) == 3
|
||||
|
||||
@pytest.mark.weaviate
|
||||
@pytest.mark.parametrize("similarity", ["cosine", "l2", "dot_product"])
|
||||
def test_similarity_existing_index(tmp_path, similarity):
|
||||
"""Testing non-matching similarity"""
|
||||
# create the document_store
|
||||
document_store = get_document_store("weaviate", tmp_path, similarity=similarity, recreate_index=True)
|
||||
docs = ds.query(filters={"content": [query_text.lower()]})
|
||||
assert len(docs) == 3
|
||||
|
||||
# try to connect to the same document store but using the wrong similarity
|
||||
non_matching_similarity = "l2" if similarity == "cosine" else "cosine"
|
||||
with pytest.raises(ValueError, match=r"This index already exists in Weaviate with similarity .*"):
|
||||
document_store2 = get_document_store(
|
||||
"weaviate", tmp_path, similarity=non_matching_similarity, recreate_index=False
|
||||
docs = ds.query(filters={"content": ["baz"]})
|
||||
assert len(docs) == 3
|
||||
|
||||
@pytest.mark.integration
|
||||
def test_get_all_documents_unaffected_by_QUERY_MAXIMUM_RESULTS(self, ds, documents, monkeypatch):
|
||||
"""
|
||||
Ensure `get_all_documents` works no matter the value of QUERY_MAXIMUM_RESULTS
|
||||
see https://github.com/deepset-ai/haystack/issues/2517
|
||||
"""
|
||||
ds.write_documents(documents)
|
||||
monkeypatch.setattr(ds, "get_document_count", lambda **kwargs: 13_000)
|
||||
docs = ds.get_all_documents()
|
||||
assert len(docs) == 9
|
||||
|
||||
@pytest.mark.integration
|
||||
def test_deleting_by_id_or_by_filters(self, ds, documents):
|
||||
ds.write_documents(documents)
|
||||
# This test verifies that deleting an object by its ID does not first require fetching all documents. This fixes
|
||||
# a bug, as described in https://github.com/deepset-ai/haystack/issues/2898
|
||||
ds.get_all_documents = MagicMock(wraps=ds.get_all_documents)
|
||||
|
||||
assert ds.get_document_count() == 9
|
||||
|
||||
# Delete a document by its ID. This should bypass the get_all_documents() call
|
||||
ds.delete_documents(ids=[documents[0].id])
|
||||
ds.get_all_documents.assert_not_called()
|
||||
assert ds.get_document_count() == 8
|
||||
|
||||
ds.get_all_documents.reset_mock()
|
||||
# Delete a document with filters. Prove that using the filters will go through get_all_documents()
|
||||
ds.delete_documents(filters={"name": ["name_0"]})
|
||||
ds.get_all_documents.assert_called()
|
||||
assert ds.get_document_count() == 6
|
||||
|
||||
@pytest.mark.integration
|
||||
@pytest.mark.parametrize("similarity", ["cosine", "l2", "dot_product"])
|
||||
def test_similarity_existing_index(self, similarity):
|
||||
"""Testing non-matching similarity"""
|
||||
# create the document_store
|
||||
document_store = WeaviateDocumentStore(
|
||||
similarity=similarity, index=f"test_similarity_existing_index_{similarity}", recreate_index=True
|
||||
)
|
||||
|
||||
# try to connect to the same document store but using the wrong similarity
|
||||
non_matching_similarity = "l2" if similarity == "cosine" else "cosine"
|
||||
with pytest.raises(ValueError, match=r"This index already exists in Weaviate with similarity .*"):
|
||||
document_store2 = WeaviateDocumentStore(
|
||||
similarity=non_matching_similarity,
|
||||
index=f"test_similarity_existing_index_{similarity}",
|
||||
recreate_index=False,
|
||||
)
|
||||
|
||||
@pytest.mark.weaviate
|
||||
@pytest.mark.parametrize("document_store", ["weaviate"], indirect=True)
|
||||
def test_cant_write_id_in_meta(document_store):
|
||||
with pytest.raises(ValueError, match='"meta" info contains duplicate key "id"'):
|
||||
document_store.write_documents([Document(content="test", meta={"id": "test-id"})])
|
||||
@pytest.mark.integration
|
||||
def test_cant_write_id_in_meta(self, ds):
|
||||
with pytest.raises(ValueError, match='"meta" info contains duplicate key "id"'):
|
||||
ds.write_documents([Document(content="test", meta={"id": "test-id"})])
|
||||
|
||||
|
||||
@pytest.mark.weaviate
|
||||
@pytest.mark.parametrize("document_store", ["weaviate"], indirect=True)
|
||||
def test_cant_write_top_level_fields_in_meta(document_store):
|
||||
with pytest.raises(ValueError, match='"meta" info contains duplicate key "content"'):
|
||||
document_store.write_documents([Document(content="test", meta={"content": "test-id"})])
|
||||
@pytest.mark.integration
|
||||
def test_cant_write_top_level_fields_in_meta(self, ds):
|
||||
with pytest.raises(ValueError, match='"meta" info contains duplicate key "content"'):
|
||||
ds.write_documents([Document(content="test", meta={"content": "test-id"})])
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user