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refactor: switch to the new default nomic-embed-text-v1.5 embedding model in LS
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63 changed files with 16170 additions and 186 deletions
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@ -27,7 +27,7 @@ from llama_stack.providers.remote.vector_io.pgvector.config import PGVectorVecto
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from llama_stack.providers.remote.vector_io.pgvector.pgvector import PGVectorIndex, PGVectorVectorIOAdapter
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from llama_stack.providers.remote.vector_io.qdrant.qdrant import QdrantVectorIOAdapter
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EMBEDDING_DIMENSION = 384
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EMBEDDING_DIMENSION = 768
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COLLECTION_PREFIX = "test_collection"
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MILVUS_ALIAS = "test_milvus"
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@ -23,7 +23,7 @@ def loop():
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@pytest.fixture
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def embedding_dimension():
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"""Default embedding dimension for tests."""
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return 384
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return 768
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@pytest.fixture
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@ -39,7 +39,7 @@ def loop():
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@pytest.fixture
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def embedding_dimension():
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return 384
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return 768
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@pytest.fixture
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@ -52,11 +52,9 @@ def mock_vector_db(vector_db_id) -> MagicMock:
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mock_vector_db = MagicMock(spec=VectorDB)
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mock_vector_db.embedding_model = "embedding_model"
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mock_vector_db.identifier = vector_db_id
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mock_vector_db.embedding_dimension = 384
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mock_vector_db.embedding_dimension = 768
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mock_vector_db.model_dump_json.return_value = (
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'{"identifier": "'
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+ vector_db_id
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+ '", "provider_id": "qdrant", "embedding_model": "embedding_model", "embedding_dimension": 384}'
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'{"identifier": "' + vector_db_id + '", "embedding_model": "embedding_model", "embedding_dimension": 768}'
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)
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return mock_vector_db
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