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42 lines
1.1 KiB
Python
42 lines
1.1 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import random
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import numpy as np
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import pytest
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from llama_stack.apis.vector_io import Chunk
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EMBEDDING_DIMENSION = 384
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@pytest.fixture
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def vector_db_id() -> str:
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return f"test-vector-db-{random.randint(1, 100)}"
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@pytest.fixture(scope="session")
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def embedding_dimension() -> int:
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return EMBEDDING_DIMENSION
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@pytest.fixture(scope="session")
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def sample_chunks():
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"""Generates chunks that force multiple batches for a single document to expose ID conflicts."""
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n, k = 10, 3
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sample = [
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Chunk(content=f"Sentence {i} from document {j}", metadata={"document_id": f"document-{j}"})
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for j in range(k)
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for i in range(n)
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]
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return sample
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@pytest.fixture(scope="session")
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def sample_embeddings(sample_chunks):
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np.random.seed(42)
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return np.array([np.random.rand(EMBEDDING_DIMENSION).astype(np.float32) for _ in sample_chunks])
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