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Code Issues Packages Projects Releases Wiki Activity

refactor: refactor FAISS tests (#3537)

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* fix write docs behaviour

* refactor FAISS tests

* do not remove the sqlite db

* try

* remove extra slash

* Apply suggestions from code review

Co-authored-by: Sara Zan <sara.zanzottera@deepset.ai>

* review comments

* Update test/document_stores/test_faiss.py

Co-authored-by: Sara Zan <sara.zanzottera@deepset.ai>

* review comments

Co-authored-by: Sara Zan <sara.zanzottera@deepset.ai>
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Massimiliano Pippi 2022-11-08 16:37:01 +01:00 committed by GitHub
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98
.github/workflows/tests.yml vendored
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@ -295,10 +295,41 @@ jobs:
status: ${{ job.status }}
channel: '#haystack'
if: failure() && github.repository_owner == 'deepset-ai' && github.ref == 'refs/heads/main'
integration-tests-faiss:
name: Integration / faiss / ${{ matrix.os }}
needs:
- unit-tests
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest,macos-latest,windows-latest]
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@v3
- name: Setup Python
uses: ./.github/actions/python_cache/
- name: Install Haystack
run: pip install -U .
- name: Run tests
run: |
pytest --maxfail=5 -m "document_store and integration" test/document_stores/test_faiss.py
- uses: act10ns/slack@v1
with:
status: ${{ job.status }}
channel: '#haystack'
if: failure() && github.repository_owner == 'deepset-ai' && github.ref == 'refs/heads/main'
#
# TODO: the following steps need to be revisited
#
unit-tests-linux:
needs: [mypy, pylint, black]
strategy:
@ -392,73 +423,6 @@ jobs:
channel: '#haystack'
if: failure() && github.repository_owner == 'deepset-ai' && github.ref == 'refs/heads/main'
faiss-tests-linux:
needs:
- mypy
- pylint
runs-on: ubuntu-latest
if: contains(github.event.pull_request.labels.*.name, 'topic:faiss') || !github.event.pull_request.draft
steps:
- uses: actions/checkout@v3
- name: Setup Python
uses: ./.github/actions/python_cache/
# TODO Let's try to remove this one from the unit tests
- name: Install pdftotext
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
- name: Install Haystack
run: pip install .[faiss]
- name: Run tests
env:
TOKENIZERS_PARALLELISM: 'false'
run: |
pytest ${{ env.PYTEST_PARAMS }} -m "faiss and not integration" test/document_stores/ --document_store_type=faiss
- uses: act10ns/slack@v1
with:
status: ${{ job.status }}
channel: '#haystack'
if: failure() && github.repository_owner == 'deepset-ai' && github.ref == 'refs/heads/main'
faiss-tests-windows:
needs:
- mypy
- pylint
runs-on: windows-latest
if: contains(github.event.pull_request.labels.*.name, 'topic:faiss') && contains(github.event.pull_request.labels.*.name, 'topic:windows') || !github.event.pull_request.draft || !github.event.pull_request.draft
steps:
- uses: actions/checkout@v3
- name: Setup Python
uses: ./.github/actions/python_cache/
with:
prefix: windows
- name: Install pdftotext
run: |
choco install xpdf-utils
choco install openjdk11
refreshenv
- name: Install Haystack
run: pip install .[faiss]
- name: Run tests
env:
TOKENIZERS_PARALLELISM: 'false'
run: |
pytest ${{ env.PYTEST_PARAMS }} -m "faiss and not integration" ${{ env.SUITES_EXCLUDED_FROM_WINDOWS }} test/document_stores/ --document_store_type=faiss
- uses: act10ns/slack@v1
with:
status: ${{ job.status }}
channel: '#haystack'
if: failure() && github.repository_owner == 'deepset-ai' && github.ref == 'refs/heads/main'
milvus-tests-linux:
needs: [mypy, pylint, black]
runs-on: ubuntu-latest

4
haystack/document_stores/faiss.py
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@ -258,7 +258,7 @@ class FAISSDocumentStore(SQLDocumentStore):
documents=document_objects, index=index, duplicate_documents=duplicate_documents
)
if len(document_objects) > 0:
add_vectors = False if document_objects[0].embedding is None else True
add_vectors = all(doc.embedding is not None for doc in document_objects)
if self.duplicate_documents == "overwrite" and add_vectors:
logger.warning(
@ -494,7 +494,7 @@ class FAISSDocumentStore(SQLDocumentStore):
raise NotImplementedError("FAISSDocumentStore does not support headers.")
logger.warning(
"""DEPRECATION WARNINGS:
"""DEPRECATION WARNINGS:
1. delete_all_documents() method is deprecated, please use delete_documents method
For more details, please refer to the issue: https://github.com/deepset-ai/haystack/issues/1045
"""

476
test/document_stores/test_faiss.py
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@ -1,4 +1,5 @@
import sys
import os
import yaml
import faiss
@ -8,311 +9,248 @@ import numpy as np
from haystack.schema import Document
from haystack.document_stores.faiss import FAISSDocumentStore
from .test_base import DocumentStoreBaseTestAbstract
from haystack.pipelines import Pipeline
from haystack.nodes.retriever.dense import EmbeddingRetriever
from ..conftest import MockDenseRetriever
DOCUMENTS = [
{
"meta": {"name": "name_1", "year": "2020", "month": "01"},
"content": "text_1",
"embedding": np.random.rand(768).astype(np.float32),
},
{
"meta": {"name": "name_2", "year": "2020", "month": "02"},
"content": "text_2",
"embedding": np.random.rand(768).astype(np.float32),
},
{
"meta": {"name": "name_3", "year": "2020", "month": "03"},
"content": "text_3",
"embedding": np.random.rand(768).astype(np.float64),
},
{
"meta": {"name": "name_4", "year": "2021", "month": "01"},
"content": "text_4",
"embedding": np.random.rand(768).astype(np.float32),
},
{
"meta": {"name": "name_5", "year": "2021", "month": "02"},
"content": "text_5",
"embedding": np.random.rand(768).astype(np.float32),
},
{
"meta": {"name": "name_6", "year": "2021", "month": "03"},
"content": "text_6",
"embedding": np.random.rand(768).astype(np.float64),
},
]
@pytest.mark.skipif(sys.platform in ["win32", "cygwin"], reason="Test with tmp_path not working on windows runner")
def test_faiss_index_save_and_load(tmp_path, sql_url):
document_store = FAISSDocumentStore(
sql_url=sql_url,
index="haystack_test",
progress_bar=False, # Just to check if the init parameters are kept
isolation_level="AUTOCOMMIT",
)
document_store.write_documents(DOCUMENTS)
# test saving the index
document_store.save(tmp_path / "haystack_test_faiss")
# clear existing faiss_index
document_store.faiss_indexes[document_store.index].reset()
# test faiss index is cleared
assert document_store.faiss_indexes[document_store.index].ntotal == 0
# test loading the index
new_document_store = FAISSDocumentStore.load(tmp_path / "haystack_test_faiss")
# check faiss index is restored
assert new_document_store.faiss_indexes[document_store.index].ntotal == len(DOCUMENTS)
# check if documents are restored
assert len(new_document_store.get_all_documents()) == len(DOCUMENTS)
# Check if the init parameters are kept
assert not new_document_store.progress_bar
# test saving and loading the loaded faiss index
new_document_store.save(tmp_path / "haystack_test_faiss")
reloaded_document_store = FAISSDocumentStore.load(tmp_path / "haystack_test_faiss")
# check faiss index is restored
assert reloaded_document_store.faiss_indexes[document_store.index].ntotal == len(DOCUMENTS)
# check if documents are restored
assert len(reloaded_document_store.get_all_documents()) == len(DOCUMENTS)
# Check if the init parameters are kept
assert not reloaded_document_store.progress_bar
# test loading the index via init
new_document_store = FAISSDocumentStore(faiss_index_path=tmp_path / "haystack_test_faiss")
# check faiss index is restored
assert new_document_store.faiss_indexes[document_store.index].ntotal == len(DOCUMENTS)
# check if documents are restored
assert len(new_document_store.get_all_documents()) == len(DOCUMENTS)
# Check if the init parameters are kept
assert not new_document_store.progress_bar
@pytest.mark.skipif(sys.platform in ["win32", "cygwin"], reason="Test with tmp_path not working on windows runner")
def test_faiss_index_save_and_load_custom_path(tmp_path, sql_url):
document_store = FAISSDocumentStore(
sql_url=sql_url,
index="haystack_test",
progress_bar=False, # Just to check if the init parameters are kept
isolation_level="AUTOCOMMIT",
)
document_store.write_documents(DOCUMENTS)
# test saving the index
document_store.save(index_path=tmp_path / "haystack_test_faiss", config_path=tmp_path / "custom_path.json")
# clear existing faiss_index
document_store.faiss_indexes[document_store.index].reset()
# test faiss index is cleared
assert document_store.faiss_indexes[document_store.index].ntotal == 0
# test loading the index
new_document_store = FAISSDocumentStore.load(
index_path=tmp_path / "haystack_test_faiss", config_path=tmp_path / "custom_path.json"
)
# check faiss index is restored
assert new_document_store.faiss_indexes[document_store.index].ntotal == len(DOCUMENTS)
# check if documents are restored
assert len(new_document_store.get_all_documents()) == len(DOCUMENTS)
# Check if the init parameters are kept
assert not new_document_store.progress_bar
# test saving and loading the loaded faiss index
new_document_store.save(tmp_path / "haystack_test_faiss", config_path=tmp_path / "custom_path.json")
reloaded_document_store = FAISSDocumentStore.load(
tmp_path / "haystack_test_faiss", config_path=tmp_path / "custom_path.json"
)
# check faiss index is restored
assert reloaded_document_store.faiss_indexes[document_store.index].ntotal == len(DOCUMENTS)
# check if documents are restored
assert len(reloaded_document_store.get_all_documents()) == len(DOCUMENTS)
# Check if the init parameters are kept
assert not reloaded_document_store.progress_bar
# test loading the index via init
new_document_store = FAISSDocumentStore(
faiss_index_path=tmp_path / "haystack_test_faiss", faiss_config_path=tmp_path / "custom_path.json"
)
# check faiss index is restored
assert new_document_store.faiss_indexes[document_store.index].ntotal == len(DOCUMENTS)
# check if documents are restored
assert len(new_document_store.get_all_documents()) == len(DOCUMENTS)
# Check if the init parameters are kept
assert not new_document_store.progress_bar
@pytest.mark.skipif(sys.platform in ["win32", "cygwin"], reason="Test with tmp_path not working on windows runner")
def test_faiss_index_mutual_exclusive_args(tmp_path):
with pytest.raises(ValueError):
FAISSDocumentStore(
sql_url=f"sqlite:////{tmp_path/'haystack_test.db'}",
faiss_index_path=f"{tmp_path/'haystack_test'}",
class TestFAISSDocumentStore(DocumentStoreBaseTestAbstract):
@pytest.fixture
def ds(self, tmp_path):
return FAISSDocumentStore(
sql_url=f"sqlite:///{tmp_path}/haystack_test.db",
return_embedding=True,
isolation_level="AUTOCOMMIT",
progress_bar=False,
similarity="cosine",
)
with pytest.raises(ValueError):
FAISSDocumentStore(
f"sqlite:////{tmp_path/'haystack_test.db'}",
faiss_index_path=f"{tmp_path/'haystack_test'}",
isolation_level="AUTOCOMMIT",
@pytest.fixture
def documents_with_embeddings(self, documents):
# drop documents without embeddings from the original fixture
return [d for d in documents if d.embedding is not None]
@pytest.mark.unit
def test_index_mutual_exclusive_args(self, tmp_path):
with pytest.raises(ValueError, match="faiss_index_path"):
FAISSDocumentStore(
sql_url=f"sqlite:////{tmp_path/'haystack_test.db'}",
faiss_index_path=f"{tmp_path/'haystack_test'}",
isolation_level="AUTOCOMMIT",
)
with pytest.raises(ValueError, match="faiss_index_path"):
FAISSDocumentStore(
f"sqlite:////{tmp_path/'haystack_test.db'}",
faiss_index_path=f"{tmp_path/'haystack_test'}",
isolation_level="AUTOCOMMIT",
)
@pytest.mark.integration
def test_delete_index(self, ds, documents):
"""Contrary to other Document Stores, FAISSDocumentStore doesn't raise if the index is empty"""
ds.write_documents(documents)
assert ds.get_document_count() == len(documents)
ds.delete_index(ds.index)
assert ds.get_document_count() == 0
@pytest.mark.integration
@pytest.mark.parametrize("config_path", [None, "custom_path.json"])
def test_index_save_and_load(self, ds, documents_with_embeddings, tmp_path, config_path):
if config_path:
config_path = tmp_path / config_path
ds.write_documents(documents_with_embeddings)
# test saving the index
ds.save(index_path=tmp_path / "haystack_test_faiss", config_path=config_path)
# clear existing faiss_index
ds.faiss_indexes[ds.index].reset()
# test faiss index is cleared
assert ds.faiss_indexes[ds.index].ntotal == 0
# test loading the index
new_document_store = FAISSDocumentStore.load(
index_path=tmp_path / "haystack_test_faiss", config_path=config_path
)
# check faiss index is restored
assert new_document_store.faiss_indexes[ds.index].ntotal == len(documents_with_embeddings)
# check if documents are restored
assert len(new_document_store.get_all_documents()) == len(documents_with_embeddings)
# Check if the init parameters are kept
assert not new_document_store.progress_bar
@pytest.mark.parametrize("document_store", ["faiss"], indirect=True)
@pytest.mark.parametrize("index_buffer_size", [10_000, 2])
@pytest.mark.parametrize("batch_size", [2])
def test_faiss_write_docs(document_store, index_buffer_size, batch_size):
document_store.index_buffer_size = index_buffer_size
# test saving and loading the loaded faiss index
new_document_store.save(tmp_path / "haystack_test_faiss", config_path=config_path)
reloaded_document_store = FAISSDocumentStore.load(tmp_path / "haystack_test_faiss", config_path=config_path)
# Write in small batches
for i in range(0, len(DOCUMENTS), batch_size):
document_store.write_documents(DOCUMENTS[i : i + batch_size])
# check faiss index is restored
assert reloaded_document_store.faiss_indexes[ds.index].ntotal == len(documents_with_embeddings)
# check if documents are restored
assert len(reloaded_document_store.get_all_documents()) == len(documents_with_embeddings)
# Check if the init parameters are kept
assert not reloaded_document_store.progress_bar
documents_indexed = document_store.get_all_documents()
assert len(documents_indexed) == len(DOCUMENTS)
# test loading the index via init
new_document_store = FAISSDocumentStore(
faiss_index_path=tmp_path / "haystack_test_faiss", faiss_config_path=config_path
)
# test if correct vectors are associated with docs
for i, doc in enumerate(documents_indexed):
# we currently don't get the embeddings back when we call document_store.get_all_documents()
original_doc = [d for d in DOCUMENTS if d["content"] == doc.content][0]
stored_emb = document_store.faiss_indexes[document_store.index].reconstruct(int(doc.meta["vector_id"]))
# compare original input vec with stored one (ignore extra dim added by hnsw)
# original input vec is normalized as faiss only stores normalized vectors
assert np.allclose(original_doc["embedding"] / np.linalg.norm(original_doc["embedding"]), stored_emb, rtol=0.01)
# check faiss index is restored
assert new_document_store.faiss_indexes[ds.index].ntotal == len(documents_with_embeddings)
# check if documents are restored
assert len(new_document_store.get_all_documents()) == len(documents_with_embeddings)
# Check if the init parameters are kept
assert not new_document_store.progress_bar
@pytest.mark.integration
@pytest.mark.parametrize("index_buffer_size", [10_000, 2])
@pytest.mark.parametrize("index_factory", ["Flat", "HNSW", "IVF1,Flat"])
def test_write_index_docs(self, documents_with_embeddings, tmp_path, index_buffer_size, index_factory):
document_store = FAISSDocumentStore(
sql_url=f"sqlite:///{tmp_path}/test_faiss_retrieving_{index_factory}.db",
faiss_index_factory_str=index_factory,
isolation_level="AUTOCOMMIT",
return_embedding=True,
)
batch_size = 2
document_store.index_buffer_size = index_buffer_size
document_store.delete_all_documents(index=document_store.index)
if "ivf" in index_factory.lower():
document_store.train_index(documents_with_embeddings)
document_store.faiss_indexes[document_store.index].make_direct_map()
@pytest.mark.parametrize("document_store", ["faiss"], indirect=True)
def test_faiss_write_docs_different_indexes(document_store):
document_store.write_documents(DOCUMENTS, index="index1")
document_store.write_documents(DOCUMENTS, index="index2")
# Write in batches
for i in range(0, len(documents_with_embeddings), batch_size):
document_store.write_documents(documents_with_embeddings[i : i + batch_size])
docs_from_index1 = document_store.get_all_documents(index="index1", return_embedding=False)
assert len(docs_from_index1) == len(DOCUMENTS)
assert {int(doc.meta["vector_id"]) for doc in docs_from_index1} == set(range(0, 6))
documents_indexed = document_store.get_all_documents()
assert len(documents_indexed) == len(documents_with_embeddings)
assert all(doc.embedding is not None for doc in documents_indexed)
docs_from_index2 = document_store.get_all_documents(index="index2", return_embedding=False)
assert len(docs_from_index2) == len(DOCUMENTS)
assert {int(doc.meta["vector_id"]) for doc in docs_from_index2} == set(range(0, 6))
@pytest.mark.integration
def test_write_docs_different_indexes(self, ds, documents_with_embeddings):
docs_a = documents_with_embeddings[:2]
docs_b = documents_with_embeddings[2:]
ds.write_documents(docs_a, index="index_a")
ds.write_documents(docs_b, index="index_b")
docs_from_index_a = ds.get_all_documents(index="index_a", return_embedding=False)
assert len(docs_from_index_a) == len(docs_a)
assert {int(doc.meta["vector_id"]) for doc in docs_from_index_a} == {0, 1}
@pytest.mark.parametrize("document_store", ["faiss"], indirect=True)
def test_faiss_update_docs_different_indexes(document_store):
retriever = MockDenseRetriever(document_store=document_store)
docs_from_index_b = ds.get_all_documents(index="index_b", return_embedding=False)
assert len(docs_from_index_b) == len(docs_b)
assert {int(doc.meta["vector_id"]) for doc in docs_from_index_b} == {0, 1, 2, 3}
document_store.write_documents(DOCUMENTS, index="index1")
document_store.write_documents(DOCUMENTS, index="index2")
@pytest.mark.integration
def test_update_docs_different_indexes(self, ds, documents_with_embeddings):
retriever = MockDenseRetriever(document_store=ds)
document_store.update_embeddings(retriever=retriever, update_existing_embeddings=True, index="index1")
document_store.update_embeddings(retriever=retriever, update_existing_embeddings=True, index="index2")
docs_a = documents_with_embeddings[:2]
docs_b = documents_with_embeddings[2:]
ds.write_documents(docs_a, index="index_a")
ds.write_documents(docs_b, index="index_b")
docs_from_index1 = document_store.get_all_documents(index="index1", return_embedding=False)
assert len(docs_from_index1) == len(DOCUMENTS)
assert {int(doc.meta["vector_id"]) for doc in docs_from_index1} == set(range(0, 6))
ds.update_embeddings(retriever=retriever, update_existing_embeddings=True, index="index_a")
ds.update_embeddings(retriever=retriever, update_existing_embeddings=True, index="index_b")
docs_from_index2 = document_store.get_all_documents(index="index2", return_embedding=False)
assert len(docs_from_index2) == len(DOCUMENTS)
assert {int(doc.meta["vector_id"]) for doc in docs_from_index2} == set(range(0, 6))
docs_from_index_a = ds.get_all_documents(index="index_a", return_embedding=False)
assert len(docs_from_index_a) == len(docs_a)
assert {int(doc.meta["vector_id"]) for doc in docs_from_index_a} == {0, 1}
docs_from_index_b = ds.get_all_documents(index="index_b", return_embedding=False)
assert len(docs_from_index_b) == len(docs_b)
assert {int(doc.meta["vector_id"]) for doc in docs_from_index_b} == {0, 1, 2, 3}
@pytest.mark.skipif(sys.platform in ["win32", "cygwin"], reason="Test with tmp_path not working on windows runner")
@pytest.mark.parametrize("index_factory", ["Flat", "HNSW", "IVF1,Flat"])
def test_faiss_retrieving(index_factory, tmp_path):
document_store = FAISSDocumentStore(
sql_url=f"sqlite:////{tmp_path/'test_faiss_retrieving.db'}",
faiss_index_factory_str=index_factory,
isolation_level="AUTOCOMMIT",
)
@pytest.mark.integration
def test_passing_index_from_outside(self, documents_with_embeddings, tmp_path):
d = 768
nlist = 2
quantizer = faiss.IndexFlatIP(d)
index = "haystack_test_1"
faiss_index = faiss.IndexIVFFlat(quantizer, d, nlist, faiss.METRIC_INNER_PRODUCT)
faiss_index.set_direct_map_type(faiss.DirectMap.Hashtable)
faiss_index.nprobe = 2
document_store = FAISSDocumentStore(
sql_url=f"sqlite:///", faiss_index=faiss_index, index=index, isolation_level="AUTOCOMMIT"
)
document_store.delete_all_documents(index="document")
if "ivf" in index_factory.lower():
document_store.train_index(DOCUMENTS)
document_store.write_documents(DOCUMENTS)
document_store.delete_documents()
# as it is a IVF index we need to train it before adding docs
document_store.train_index(documents_with_embeddings)
retriever = EmbeddingRetriever(
document_store=document_store, embedding_model="deepset/sentence_bert", use_gpu=False
)
result = retriever.retrieve(query="How to test this?")
document_store.write_documents(documents=documents_with_embeddings)
documents_indexed = document_store.get_all_documents()
assert len(result) == len(DOCUMENTS)
assert type(result[0]) == Document
# test if vectors ids are associated with docs
for doc in documents_indexed:
assert 0 <= int(doc.meta["vector_id"]) <= 7
# Cleanup
document_store.faiss_indexes[document_store.index].reset()
@pytest.mark.integration
def test_pipeline_with_existing_faiss_docstore(self, ds, documents_with_embeddings, tmp_path):
ds.write_documents(documents_with_embeddings)
ds.save(tmp_path / "existing_faiss_document_store")
pipeline_config = {
"version": "ignore",
"components": [
{
"name": "DPRRetriever",
"type": "MockDenseRetriever",
"params": {"document_store": "ExistingFAISSDocumentStore"},
},
{
"name": "ExistingFAISSDocumentStore",
"type": "FAISSDocumentStore",
"params": {"faiss_index_path": f"{tmp_path / 'existing_faiss_document_store'}"},
},
],
"pipelines": [{"name": "query_pipeline", "nodes": [{"name": "DPRRetriever", "inputs": ["Query"]}]}],
}
pipeline = Pipeline.load_from_config(pipeline_config)
existing_document_store = pipeline.get_document_store()
faiss_index = existing_document_store.faiss_indexes[ds.index]
assert faiss_index.ntotal == len(documents_with_embeddings)
# See TestSQLDocumentStore about why we have to skip these tests
@pytest.mark.skipif(sys.platform in ["win32", "cygwin"], reason="Test with tmp_path not working on windows runner")
def test_faiss_passing_index_from_outside(tmp_path):
d = 768
nlist = 2
quantizer = faiss.IndexFlatIP(d)
index = "haystack_test_1"
faiss_index = faiss.IndexIVFFlat(quantizer, d, nlist, faiss.METRIC_INNER_PRODUCT)
faiss_index.set_direct_map_type(faiss.DirectMap.Hashtable)
faiss_index.nprobe = 2
document_store = FAISSDocumentStore(
sql_url=f"sqlite:////{tmp_path/'haystack_test_faiss.db'}",
faiss_index=faiss_index,
index=index,
isolation_level="AUTOCOMMIT",
)
@pytest.mark.skip
@pytest.mark.integration
def test_ne_filters(self, ds, documents):
pass
document_store.delete_documents()
# as it is a IVF index we need to train it before adding docs
document_store.train_index(DOCUMENTS)
@pytest.mark.skip
@pytest.mark.integration
def test_nin_filters(self, ds, documents):
pass
document_store.write_documents(documents=DOCUMENTS)
documents_indexed = document_store.get_all_documents()
@pytest.mark.skip
@pytest.mark.integration
def test_comparison_filters(self, ds, documents):
pass
# test if vectors ids are associated with docs
for doc in documents_indexed:
assert 0 <= int(doc.meta["vector_id"]) <= 7
@pytest.mark.skip
@pytest.mark.integration
def test_nested_condition_filters(self, ds, documents):
pass
@pytest.mark.skip
@pytest.mark.integration
def test_nested_condition_not_filters(self, ds, documents):
pass
@pytest.mark.integration
def test_pipeline_with_existing_faiss_docstore(tmp_path):
@pytest.mark.skip
@pytest.mark.integration
def test_delete_labels_by_filter(self, ds, labels):
pass
document_store: FAISSDocumentStore = FAISSDocumentStore(
sql_url=f'sqlite:///{(tmp_path / "faiss_document_store.db").absolute()}'
)
retriever = MockDenseRetriever(document_store=document_store)
document_store.write_documents(DOCUMENTS)
document_store.update_embeddings(retriever=retriever, update_existing_embeddings=True)
document_store.save(tmp_path / "existing_faiss_document_store")
query_config = f"""
version: ignore
components:
- name: DPRRetriever
type: MockDenseRetriever
params:
document_store: ExistingFAISSDocumentStore
- name: ExistingFAISSDocumentStore
type: FAISSDocumentStore
params:
faiss_index_path: '{tmp_path / "existing_faiss_document_store"}'
pipelines:
- name: query_pipeline
nodes:
- name: DPRRetriever
inputs: [Query]
"""
pipeline = Pipeline.load_from_config(yaml.safe_load(query_config))
existing_document_store = pipeline.get_document_store()
faiss_index = existing_document_store.faiss_indexes["document"]
assert faiss_index.ntotal == len(DOCUMENTS)
@pytest.mark.skip
@pytest.mark.integration
def test_delete_labels_by_filter_id(self, ds, labels):
pass