| @@ -1,38 +1,29 @@ | |||
| import uuid | |||
| from core.rag.datasource.vdb.milvus.milvus_vector import MilvusConfig, MilvusVector | |||
| from models.dataset import Dataset | |||
| from tests.integration_tests.vdb.test_vector_store import ( | |||
| get_sample_document, | |||
| get_sample_embedding, | |||
| get_sample_query_vector, | |||
| AbstractTestVector, | |||
| get_sample_text, | |||
| setup_mock_redis, | |||
| ) | |||
| def test_milvus_vector(setup_mock_redis) -> None: | |||
| dataset_id = str(uuid.uuid4()) | |||
| vector = MilvusVector( | |||
| collection_name=Dataset.gen_collection_name_by_id(dataset_id), | |||
| config=MilvusConfig( | |||
| host='localhost', | |||
| port=19530, | |||
| user='root', | |||
| password='Milvus', | |||
| class TestMilvusVector(AbstractTestVector): | |||
| def __init__(self): | |||
| super().__init__() | |||
| self.vector = MilvusVector( | |||
| collection_name=self.collection_name, | |||
| config=MilvusConfig( | |||
| host='localhost', | |||
| port=19530, | |||
| user='root', | |||
| password='Milvus', | |||
| ) | |||
| ) | |||
| ) | |||
| # create vector | |||
| vector.create( | |||
| texts=[get_sample_document(dataset_id)], | |||
| embeddings=[get_sample_embedding()], | |||
| ) | |||
| # search by vector | |||
| hits_by_vector = vector.search_by_vector(query_vector=get_sample_query_vector()) | |||
| assert len(hits_by_vector) >= 1 | |||
| def search_by_full_text(self): | |||
| # milvus dos not support full text searching yet in < 2.3.x | |||
| hits_by_full_text = self.vector.search_by_full_text(query=get_sample_text()) | |||
| assert len(hits_by_full_text) == 0 | |||
| # milvus dos not support full text searching yet in < 2.3.x | |||
| # delete vector | |||
| vector.delete() | |||
| def test_milvus_vector(setup_mock_redis): | |||
| TestMilvusVector().run_all_test() | |||
| @@ -1,40 +1,23 @@ | |||
| import uuid | |||
| from core.rag.datasource.vdb.qdrant.qdrant_vector import QdrantConfig, QdrantVector | |||
| from models.dataset import Dataset | |||
| from tests.integration_tests.vdb.test_vector_store import ( | |||
| get_sample_document, | |||
| get_sample_embedding, | |||
| get_sample_query_vector, | |||
| get_sample_text, | |||
| AbstractTestVector, | |||
| setup_mock_redis, | |||
| ) | |||
| def test_qdrant_vector(setup_mock_redis)-> None: | |||
| dataset_id = str(uuid.uuid4()) | |||
| vector = QdrantVector( | |||
| collection_name=Dataset.gen_collection_name_by_id(dataset_id), | |||
| group_id=dataset_id, | |||
| config=QdrantConfig( | |||
| endpoint='http://localhost:6333', | |||
| api_key='difyai123456', | |||
| class TestQdrantVector(AbstractTestVector): | |||
| def __init__(self): | |||
| super().__init__() | |||
| self.attributes = ['doc_id', 'dataset_id', 'document_id', 'doc_hash'] | |||
| self.vector = QdrantVector( | |||
| collection_name=self.collection_name, | |||
| group_id=self.dataset_id, | |||
| config=QdrantConfig( | |||
| endpoint='http://localhost:6333', | |||
| api_key='difyai123456', | |||
| ) | |||
| ) | |||
| ) | |||
| # create vector | |||
| vector.create( | |||
| texts=[get_sample_document(dataset_id)], | |||
| embeddings=[get_sample_embedding()], | |||
| ) | |||
| # search by vector | |||
| hits_by_vector = vector.search_by_vector(query_vector=get_sample_query_vector()) | |||
| assert len(hits_by_vector) >= 1 | |||
| # search by full text | |||
| hits_by_full_text = vector.search_by_full_text(query=get_sample_text()) | |||
| assert len(hits_by_full_text) >= 1 | |||
| # delete vector | |||
| vector.delete() | |||
| def test_qdrant_vector(setup_mock_redis): | |||
| TestQdrantVector().run_all_test() | |||
| @@ -1,9 +1,11 @@ | |||
| import uuid | |||
| from unittest.mock import MagicMock | |||
| import pytest | |||
| from core.rag.models.document import Document | |||
| from extensions import ext_redis | |||
| from models.dataset import Dataset | |||
| def get_sample_text() -> str: | |||
| @@ -44,3 +46,33 @@ def setup_mock_redis() -> None: | |||
| mock_redis_lock.__enter__ = MagicMock() | |||
| mock_redis_lock.__exit__ = MagicMock() | |||
| ext_redis.redis_client.lock = mock_redis_lock | |||
| class AbstractTestVector: | |||
| def __init__(self): | |||
| self.vector = None | |||
| self.dataset_id = str(uuid.uuid4()) | |||
| self.collection_name = Dataset.gen_collection_name_by_id(self.dataset_id) | |||
| def create_vector(self) -> None: | |||
| self.vector.create( | |||
| texts=[get_sample_document(self.dataset_id)], | |||
| embeddings=[get_sample_embedding()], | |||
| ) | |||
| def search_by_vector(self): | |||
| hits_by_vector = self.vector.search_by_vector(query_vector=get_sample_query_vector()) | |||
| assert len(hits_by_vector) >= 1 | |||
| def search_by_full_text(self): | |||
| hits_by_full_text = self.vector.search_by_full_text(query=get_sample_text()) | |||
| assert len(hits_by_full_text) >= 1 | |||
| def delete_vector(self): | |||
| self.vector.delete() | |||
| def run_all_test(self): | |||
| self.create_vector() | |||
| self.search_by_vector() | |||
| self.search_by_full_text() | |||
| self.delete_vector() | |||
| @@ -1,41 +1,24 @@ | |||
| import uuid | |||
| from core.rag.datasource.vdb.weaviate.weaviate_vector import WeaviateConfig, WeaviateVector | |||
| from models.dataset import Dataset | |||
| from tests.integration_tests.vdb.test_vector_store import ( | |||
| get_sample_document, | |||
| get_sample_embedding, | |||
| get_sample_query_vector, | |||
| get_sample_text, | |||
| AbstractTestVector, | |||
| setup_mock_redis, | |||
| ) | |||
| def test_weaviate_vector(setup_mock_redis) -> None: | |||
| attributes = ['doc_id', 'dataset_id', 'document_id', 'doc_hash'] | |||
| dataset_id = str(uuid.uuid4()) | |||
| vector = WeaviateVector( | |||
| collection_name=Dataset.gen_collection_name_by_id(dataset_id), | |||
| config=WeaviateConfig( | |||
| endpoint='http://localhost:8080', | |||
| api_key='WVF5YThaHlkYwhGUSmCRgsX3tD5ngdN8pkih', | |||
| ), | |||
| attributes=attributes | |||
| ) | |||
| # create vector | |||
| vector.create( | |||
| texts=[get_sample_document(dataset_id)], | |||
| embeddings=[get_sample_embedding()], | |||
| ) | |||
| # search by vector | |||
| hits_by_vector = vector.search_by_vector(query_vector=get_sample_query_vector()) | |||
| assert len(hits_by_vector) >= 1 | |||
| class TestWeaviateVector(AbstractTestVector): | |||
| def __init__(self): | |||
| super().__init__() | |||
| self.attributes = ['doc_id', 'dataset_id', 'document_id', 'doc_hash'] | |||
| self.vector = WeaviateVector( | |||
| collection_name=self.collection_name, | |||
| config=WeaviateConfig( | |||
| endpoint='http://localhost:8080', | |||
| api_key='WVF5YThaHlkYwhGUSmCRgsX3tD5ngdN8pkih', | |||
| ), | |||
| attributes=self.attributes | |||
| ) | |||
| # search by full text | |||
| hits_by_full_text = vector.search_by_full_text(query=get_sample_text()) | |||
| assert len(hits_by_full_text) >= 1 | |||
| # delete vector | |||
| vector.delete() | |||
| def test_weaviate_vector(setup_mock_redis): | |||
| TestWeaviateVector().run_all_test() | |||