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fix: allow running vector tests with embedding dimension
Do not force 384 for the embedding dimension, use the one provided by the test run. ``` pytest -s -vvv tests/integration/vector_io/test_vector_io.py --stack-config=http://localhost:8321 \ -k "not(builtin_tool or safety_with_image or code_interpreter or test_rag)" \ --text-model="meta-llama/Llama-3.2-3B-Instruct" \ --embedding-model=granite-embedding-125m --embedding-dimension=768 Uninstalled 1 package in 16ms Installed 1 package in 11ms INFO 2025-06-18 10:52:03,314 tests.integration.conftest:59 tests: Setting DISABLE_CODE_SANDBOX=1 for macOS /Users/leseb/Documents/AI/llama-stack/.venv/lib/python3.10/site-packages/pytest_asyncio/plugin.py:207: PytestDeprecationWarning: The configuration option "asyncio_default_fixture_loop_scope" is unset. The event loop scope for asynchronous fixtures will default to the fixture caching scope. Future versions of pytest-asyncio will default the loop scope for asynchronous fixtures to function scope. Set the default fixture loop scope explicitly in order to avoid unexpected behavior in the future. Valid fixture loop scopes are: "function", "class", "module", "package", "session" warnings.warn(PytestDeprecationWarning(_DEFAULT_FIXTURE_LOOP_SCOPE_UNSET)) ================================================= test session starts ================================================= platform darwin -- Python 3.10.16, pytest-8.3.4, pluggy-1.5.0 -- /Users/leseb/Documents/AI/llama-stack/.venv/bin/python cachedir: .pytest_cache metadata: {'Python': '3.10.16', 'Platform': 'macOS-15.5-arm64-arm-64bit', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'cov': '6.0.0', 'html': '4.1.1', 'json-report': '1.5.0', 'timeout': '2.4.0', 'metadata': '3.1.1', 'asyncio': '0.25.3', 'anyio': '4.8.0', 'nbval': '0.11.0'}} rootdir: /Users/leseb/Documents/AI/llama-stack configfile: pyproject.toml plugins: cov-6.0.0, html-4.1.1, json-report-1.5.0, timeout-2.4.0, metadata-3.1.1, asyncio-0.25.3, anyio-4.8.0, nbval-0.11.0 asyncio: mode=strict, asyncio_default_fixture_loop_scope=None collected 8 items tests/integration/vector_io/test_vector_io.py::test_vector_db_retrieve[emb=granite-embedding-125m:dim=768] PASSED tests/integration/vector_io/test_vector_io.py::test_vector_db_register[emb=granite-embedding-125m:dim=768] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case0] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case1] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case2] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case3] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=granite-embedding-125m:dim=768-test_case4] PASSED tests/integration/vector_io/test_vector_io.py::test_insert_chunks_with_precomputed_embeddings[emb=granite-embedding-125m:dim=768] PASSED ================================================== 8 passed in 5.50s ================================================== ``` Signed-off-by: Sébastien Han <seb@redhat.com>
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3 changed files with 25 additions and 18 deletions
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@ -63,12 +63,14 @@ def assert_valid_text_response(response):
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assert all(isinstance(chunk.text, str) for chunk in response.content)
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def test_vector_db_insert_inline_and_query(client_with_empty_registry, sample_documents, embedding_model_id):
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def test_vector_db_insert_inline_and_query(
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client_with_empty_registry, sample_documents, embedding_model_id, embedding_dimension
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):
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vector_db_id = "test_vector_db"
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client_with_empty_registry.vector_dbs.register(
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vector_db_id=vector_db_id,
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embedding_model=embedding_model_id,
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embedding_dimension=384,
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embedding_dimension=embedding_dimension,
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)
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client_with_empty_registry.tool_runtime.rag_tool.insert(
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@ -116,7 +118,9 @@ def test_vector_db_insert_inline_and_query(client_with_empty_registry, sample_do
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assert all(score >= 0.01 for score in response4.scores)
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def test_vector_db_insert_from_url_and_query(client_with_empty_registry, sample_documents, embedding_model_id):
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def test_vector_db_insert_from_url_and_query(
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client_with_empty_registry, sample_documents, embedding_model_id, embedding_dimension
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):
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providers = [p for p in client_with_empty_registry.providers.list() if p.api == "vector_io"]
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assert len(providers) > 0
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@ -125,7 +129,7 @@ def test_vector_db_insert_from_url_and_query(client_with_empty_registry, sample_
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client_with_empty_registry.vector_dbs.register(
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vector_db_id=vector_db_id,
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embedding_model=embedding_model_id,
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embedding_dimension=384,
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embedding_dimension=embedding_dimension,
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)
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# list to check memory bank is successfully registered
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@ -170,7 +174,7 @@ def test_vector_db_insert_from_url_and_query(client_with_empty_registry, sample_
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assert any("llama2" in chunk.content.lower() for chunk in response2.chunks)
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def test_rag_tool_insert_and_query(client_with_empty_registry, embedding_model_id):
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def test_rag_tool_insert_and_query(client_with_empty_registry, embedding_model_id, embedding_dimension):
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providers = [p for p in client_with_empty_registry.providers.list() if p.api == "vector_io"]
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assert len(providers) > 0
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@ -179,7 +183,7 @@ def test_rag_tool_insert_and_query(client_with_empty_registry, embedding_model_i
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client_with_empty_registry.vector_dbs.register(
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vector_db_id=vector_db_id,
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embedding_model=embedding_model_id,
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embedding_dimension=384,
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embedding_dimension=embedding_dimension,
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)
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available_vector_dbs = [vector_db.identifier for vector_db in client_with_empty_registry.vector_dbs.list()]
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