95 lines
3.8 KiB
Python
95 lines
3.8 KiB
Python
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# Copyright (c) "Neo4j"
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# Neo4j Sweden AB [https://neo4j.com]
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# #
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# #
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# https://www.apache.org/licenses/LICENSE-2.0
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# #
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from unittest.mock import MagicMock, Mock, patch
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import pytest
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from tenacity import RetryError
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from neo4j_graphrag.embeddings.vertexai import VertexAIEmbeddings
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from neo4j_graphrag.exceptions import EmbeddingsGenerationError
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@patch("neo4j_graphrag.embeddings.vertexai.TextEmbeddingModel", None)
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def test_vertexai_embedder_missing_dependency() -> None:
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with pytest.raises(ImportError):
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VertexAIEmbeddings()
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@patch("neo4j_graphrag.embeddings.vertexai.TextEmbeddingModel")
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def test_vertexai_embedder_happy_path(mock_vertexai: Mock) -> None:
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mock_vertexai.from_pretrained.return_value.get_embeddings.return_value = [
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MagicMock(values=[1.0, 2.0])
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]
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embedder = VertexAIEmbeddings()
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res = embedder.embed_query("my text")
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assert isinstance(res, list)
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assert res == [1.0, 2.0]
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@patch("neo4j_graphrag.embeddings.vertexai.TextEmbeddingModel")
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def test_vertexai_embedder_non_retryable_error_handling(mock_vertexai: Mock) -> None:
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"""Test that non-retryable errors fail immediately without retries."""
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mock_embeddings = mock_vertexai.from_pretrained.return_value.get_embeddings
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mock_embeddings.side_effect = Exception("API Error")
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embedder = VertexAIEmbeddings()
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with pytest.raises(
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EmbeddingsGenerationError, match="Failed to generate embedding with VertexAI"
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):
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embedder.embed_query("my text")
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# Verify the API was called only once (no retries for non-rate-limit errors)
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assert mock_embeddings.call_count == 1
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@patch("neo4j_graphrag.embeddings.vertexai.TextEmbeddingModel")
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def test_vertexai_embedder_rate_limit_error_retries(mock_vertexai: Mock) -> None:
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"""Test that rate limit errors are retried the expected number of times."""
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# Rate limit error that should trigger retries (matches "resource exhausted" pattern)
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mock_embeddings = mock_vertexai.from_pretrained.return_value.get_embeddings
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mock_embeddings.side_effect = [
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Exception("resource exhausted - quota exceeded"),
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Exception("resource exhausted - quota exceeded"),
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Exception("resource exhausted - quota exceeded"),
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]
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embedder = VertexAIEmbeddings()
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# After exhausting retries, tenacity raises RetryError
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with pytest.raises(RetryError):
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embedder.embed_query("my text")
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# Verify the API was called 3 times (default max_attempts for RetryRateLimitHandler)
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assert mock_embeddings.call_count == 3
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@patch("neo4j_graphrag.embeddings.vertexai.TextEmbeddingModel")
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def test_vertexai_embedder_rate_limit_error_eventual_success(
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mock_vertexai: Mock,
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) -> None:
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"""Test that rate limit errors eventually succeed after retries."""
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# First two calls fail with rate limit, third succeeds
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mock_embeddings = mock_vertexai.from_pretrained.return_value.get_embeddings
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mock_embeddings.side_effect = [
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Exception("resource exhausted - quota exceeded"),
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Exception("resource exhausted - quota exceeded"),
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[MagicMock(values=[1.0, 2.0])],
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]
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embedder = VertexAIEmbeddings()
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result = embedder.embed_query("my text")
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# Verify successful result
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assert result == [1.0, 2.0]
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# Verify the API was called 3 times before succeeding
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assert mock_embeddings.call_count == 3
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