test_similarity_relevance_search_no_threshold() — langchain Function Reference
Architecture documentation for the test_similarity_relevance_search_no_threshold() function in test_search.py from the langchain codebase.
Entity Profile
Dependency Diagram
graph TD 6e0e97e2_bd51_e4a8_7289_ceb30180d33a["test_similarity_relevance_search_no_threshold()"] 7105a1c4_0f67_8c01_efc7_d00363a3ed66["test_search.py"] 6e0e97e2_bd51_e4a8_7289_ceb30180d33a -->|defined in| 7105a1c4_0f67_8c01_efc7_d00363a3ed66 style 6e0e97e2_bd51_e4a8_7289_ceb30180d33a fill:#6366f1,stroke:#818cf8,color:#fff
Relationship Graph
Source Code
libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_search.py lines 150–173
def test_similarity_relevance_search_no_threshold(
location: str,
vector_name: str,
) -> None:
"""Test end to end construction and search."""
texts = ["foo", "bar", "baz"]
metadatas = [
{"page": i, "metadata": {"page": i + 1, "pages": [i + 2, -1]}}
for i in range(len(texts))
]
docsearch = QdrantVectorStore.from_texts(
texts,
ConsistentFakeEmbeddings(),
metadatas=metadatas,
location=location,
vector_name=vector_name,
)
output = docsearch.similarity_search_with_relevance_scores(
"foo", k=3, score_threshold=None
)
assert len(output) == 3
for i in range(len(output)):
assert round(output[i][1], 2) >= 0
assert round(output[i][1], 2) <= 1
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Subdomains
Source
Frequently Asked Questions
What does test_similarity_relevance_search_no_threshold() do?
test_similarity_relevance_search_no_threshold() is a function in the langchain codebase, defined in libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_search.py.
Where is test_similarity_relevance_search_no_threshold() defined?
test_similarity_relevance_search_no_threshold() is defined in libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_search.py at line 150.
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