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Added tests + docs + CI for Elasticsearch

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This commit is contained in:
Enrico Zimuel 2025-10-31 18:18:27 +01:00
parent f1c8a200c8
commit 12f8d96f48
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GPG key ID: 6CB203F6934A69F1
9 changed files with 209 additions and 115 deletions
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13
tests/integration/conftest.py
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@ -371,18 +371,7 @@ def vector_provider_wrapper(func):
inference_mode = os.environ.get("LLAMA_STACK_TEST_INFERENCE_MODE")
if inference_mode == "live":
# For live tests, try all providers (they'll skip if not available)
all_providers = [
"faiss",
"sqlite-vec",
"milvus",
"chromadb",
"pgvector",
"weaviate",
"qdrant",
]
else:
# For CI tests (replay/record), only use providers that are available in ci-tests environment
all_providers = ["faiss", "sqlite-vec"]
all_providers = ["faiss", "sqlite-vec", "milvus", "chromadb", "pgvector", "weaviate", "qdrant", "elasticsearch"]
return pytest.mark.parametrize("vector_io_provider_id", all_providers)(wrapper)

4
tests/integration/vector_io/test_openai_vector_stores.py
View file

@ -34,6 +34,7 @@ def skip_if_provider_doesnt_support_openai_vector_stores(client_with_models):
"remote::pgvector",
"remote::qdrant",
"remote::weaviate",
"remote::elasticsearch",
]:
return
@ -54,6 +55,7 @@ def skip_if_provider_doesnt_support_openai_vector_stores_search(client_with_mode
"remote::pgvector",
"remote::qdrant",
"remote::weaviate",
"remote::elasticsearch",
],
"keyword": [
"inline::milvus",
@ -61,6 +63,7 @@ def skip_if_provider_doesnt_support_openai_vector_stores_search(client_with_mode
"remote::milvus",
"remote::pgvector",
"remote::weaviate",
"remote::elasticsearch",
],
"hybrid": [
"inline::milvus",
@ -68,6 +71,7 @@ def skip_if_provider_doesnt_support_openai_vector_stores_search(client_with_mode
"remote::milvus",
"remote::pgvector",
"remote::weaviate",
"remote::elasticsearch",
],
}
supported_providers = search_mode_support.get(search_mode, [])

2
tests/integration/vector_io/test_vector_io.py
View file

@ -164,6 +164,7 @@ def test_insert_chunks_with_precomputed_embeddings(
"inline::milvus": {"score_threshold": -1.0},
"inline::qdrant": {"score_threshold": -1.0},
"remote::qdrant": {"score_threshold": -1.0},
"remote::elasticsearch": {"score_threshold": -1.0},
}
vector_store_name = "test_precomputed_embeddings_db"
register_response = client_with_empty_registry.vector_stores.create(
@ -214,6 +215,7 @@ def test_query_returns_valid_object_when_identical_to_embedding_in_vdb(
"inline::milvus": {"score_threshold": 0.0},
"remote::qdrant": {"score_threshold": 0.0},
"inline::qdrant": {"score_threshold": 0.0},
"remote::elasticsearch": {"score_threshold": 0.0},
}
vector_store_name = "test_precomputed_embeddings_db"
register_response = client_with_empty_registry.vector_stores.create(