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chore!: BREAKING CHANGE: vector_db_id -> vector_store_id

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# What does this PR do?


## Test Plan
This commit is contained in:
Eric Huang 2025-10-27 13:22:39 -07:00
parent a9b00db421
commit 960f5e4cd4
29 changed files with 175 additions and 175 deletions
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12
tests/integration/vector_io/test_openai_vector_stores.py
View file

@ -367,7 +367,7 @@ def test_openai_vector_store_with_chunks(
# Insert chunks using the native LlamaStack API (since OpenAI API doesn't have direct chunk insertion)
llama_client.vector_io.insert(
vector_db_id=vector_store.id,
vector_store_id=vector_store.id,
chunks=sample_chunks,
)
@ -434,7 +434,7 @@ def test_openai_vector_store_search_relevance(
# Insert chunks using native API
llama_client.vector_io.insert(
vector_db_id=vector_store.id,
vector_store_id=vector_store.id,
chunks=sample_chunks,
)
@ -484,7 +484,7 @@ def test_openai_vector_store_search_with_ranking_options(
# Insert chunks
llama_client.vector_io.insert(
vector_db_id=vector_store.id,
vector_store_id=vector_store.id,
chunks=sample_chunks,
)
@ -544,7 +544,7 @@ def test_openai_vector_store_search_with_high_score_filter(
# Insert chunks
llama_client.vector_io.insert(
vector_db_id=vector_store.id,
vector_store_id=vector_store.id,
chunks=sample_chunks,
)
@ -610,7 +610,7 @@ def test_openai_vector_store_search_with_max_num_results(
# Insert chunks
llama_client.vector_io.insert(
vector_db_id=vector_store.id,
vector_store_id=vector_store.id,
chunks=sample_chunks,
)
@ -1175,7 +1175,7 @@ def test_openai_vector_store_search_modes(
)
client_with_models.vector_io.insert(
vector_db_id=vector_store.id,
vector_store_id=vector_store.id,
chunks=sample_chunks,
)
query = "Python programming language"

14
tests/integration/vector_io/test_vector_io.py
View file

@ -123,12 +123,12 @@ def test_insert_chunks(
actual_vector_store_id = create_response.id
client_with_empty_registry.vector_io.insert(
vector_db_id=actual_vector_store_id,
vector_store_id=actual_vector_store_id,
chunks=sample_chunks,
)
response = client_with_empty_registry.vector_io.query(
vector_db_id=actual_vector_store_id,
vector_store_id=actual_vector_store_id,
query="What is the capital of France?",
)
assert response is not None
@ -137,7 +137,7 @@ def test_insert_chunks(
query, expected_doc_id = test_case
response = client_with_empty_registry.vector_io.query(
vector_db_id=actual_vector_store_id,
vector_store_id=actual_vector_store_id,
query=query,
)
assert response is not None
@ -174,13 +174,13 @@ def test_insert_chunks_with_precomputed_embeddings(
]
client_with_empty_registry.vector_io.insert(
vector_db_id=actual_vector_store_id,
vector_store_id=actual_vector_store_id,
chunks=chunks_with_embeddings,
)
provider = [p.provider_id for p in client_with_empty_registry.providers.list() if p.api == "vector_io"][0]
response = client_with_empty_registry.vector_io.query(
vector_db_id=actual_vector_store_id,
vector_store_id=actual_vector_store_id,
query="precomputed embedding test",
params=vector_io_provider_params_dict.get(provider, None),
)
@ -224,13 +224,13 @@ def test_query_returns_valid_object_when_identical_to_embedding_in_vdb(
]
client_with_empty_registry.vector_io.insert(
vector_db_id=actual_vector_store_id,
vector_store_id=actual_vector_store_id,
chunks=chunks_with_embeddings,
)
provider = [p.provider_id for p in client_with_empty_registry.providers.list() if p.api == "vector_io"][0]
response = client_with_empty_registry.vector_io.query(
vector_db_id=actual_vector_store_id,
vector_store_id=actual_vector_store_id,
query="duplicate",
params=vector_io_provider_params_dict.get(provider, None),
)