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[feat] Implement OpenAI APIs in qdrant

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Signed-off-by: Varsha Prasad Narsing <varshaprasad96@gmail.com>
This commit is contained in:
Varsha Prasad Narsing 2025-07-30 17:09:01 -07:00
parent f3d5459647
commit b0e435808a
13 changed files with 205 additions and 119 deletions
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9
tests/unit/providers/vector_io/test_qdrant.py
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@ -23,6 +23,7 @@ from llama_stack.providers.inline.vector_io.qdrant.config import (
from llama_stack.providers.remote.vector_io.qdrant.qdrant import (
QdrantVectorIOAdapter,
)
from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
# This test is a unit test for the QdrantVectorIOAdapter class. This should only contain
# tests which are specific to this class. More general (API-level) tests should be placed in
@ -36,7 +37,8 @@ from llama_stack.providers.remote.vector_io.qdrant.qdrant import (
@pytest.fixture
def qdrant_config(tmp_path) -> InlineQdrantVectorIOConfig:
return InlineQdrantVectorIOConfig(path=os.path.join(tmp_path, "qdrant.db"))
kvstore_config = SqliteKVStoreConfig(db_name=os.path.join(tmp_path, "test_kvstore.db"))
return InlineQdrantVectorIOConfig(path=os.path.join(tmp_path, "qdrant.db"), kvstore=kvstore_config)
@pytest.fixture(scope="session")
@ -50,6 +52,9 @@ def mock_vector_db(vector_db_id) -> MagicMock:
mock_vector_db.embedding_model = "embedding_model"
mock_vector_db.identifier = vector_db_id
mock_vector_db.embedding_dimension = 384
mock_vector_db.model_dump_json.return_value = (
'{"identifier": "' + vector_db_id + '", "embedding_model": "embedding_model", "embedding_dimension": 384}'
)
return mock_vector_db
@ -69,7 +74,7 @@ def mock_api_service(sample_embeddings):
@pytest.fixture
async def qdrant_adapter(qdrant_config, mock_vector_db_store, mock_api_service, loop) -> QdrantVectorIOAdapter:
adapter = QdrantVectorIOAdapter(config=qdrant_config, inference_api=mock_api_service)
adapter = QdrantVectorIOAdapter(config=qdrant_config, inference_api=mock_api_service, files_api=None)
adapter.vector_db_store = mock_vector_db_store
await adapter.initialize()
yield adapter