Merge 376eb94def into d266c59c2a

tests/unit/providers/vector_io/conftest.py

@@ -29,7 +29,7 @@ from llama_stack.providers.remote.vector_io.qdrant.qdrant import QdrantVectorIOA
 from llama_stack.providers.remote.vector_io.weaviate.config import WeaviateVectorIOConfig
 from llama_stack.providers.remote.vector_io.weaviate.weaviate import WeaviateIndex, WeaviateVectorIOAdapter
 
-EMBEDDING_DIMENSION = 384
+EMBEDDING_DIMENSION = 768
 COLLECTION_PREFIX = "test_collection"
 MILVUS_ALIAS = "test_milvus"
 

tests/unit/providers/vector_io/remote/test_pgvector.py

@@ -23,7 +23,7 @@ def loop():
 @pytest.fixture
 def embedding_dimension():
     """Default embedding dimension for tests."""
-    return 384
+    return 768
 
 
 @pytest.fixture

tests/unit/providers/vector_io/test_faiss.py

@@ -39,7 +39,7 @@ def loop():
 
 @pytest.fixture
 def embedding_dimension():
-    return 384
+    return 768
 
 
 @pytest.fixture

tests/unit/providers/vector_io/test_qdrant.py

@@ -52,11 +52,9 @@ def mock_vector_db(vector_db_id) -> MagicMock:
     mock_vector_db = MagicMock(spec=VectorDB)
     mock_vector_db.embedding_model = "embedding_model"
     mock_vector_db.identifier = vector_db_id
-    mock_vector_db.embedding_dimension = 384
+    mock_vector_db.embedding_dimension = 768
     mock_vector_db.model_dump_json.return_value = (
-        '{"identifier": "'
-        + vector_db_id
-        + '", "provider_id": "qdrant", "embedding_model": "embedding_model", "embedding_dimension": 384}'
+        '{"identifier": "' + vector_db_id + '", "embedding_model": "embedding_model", "embedding_dimension": 768}'
     )
     return mock_vector_db