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Merge pull request #21425 from BerriAI/fix/test-module-reload-class-staleness

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fix: remove importlib.reload calls causing cross-test class-reference staleness
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jquinter 2026-02-17 20:35:47 -03:00 • committed by GitHub
commit b221b4595c
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2 changed files with 3 additions and 27 deletions
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20
tests/test_litellm/llms/huggingface/embedding/test_huggingface_embedding_handler.py
View file

@ -1,4 +1,3 @@
import importlib
import json
import os
import sys
@ -16,22 +15,7 @@ MOCK_EMBEDDING_RESPONSE = [[0.1, 0.2, 0.3, 0.4, 0.5]]
@pytest.fixture
def reload_huggingface_modules():
"""
Reload modules to ensure fresh references after conftest reloads litellm.
This ensures the HTTPHandler class being patched is the same one used by
the embedding handler during parallel test execution.
"""
import litellm.llms.custom_httpx.http_handler as http_handler_module
import litellm.llms.huggingface.embedding.handler as hf_embedding_handler_module
importlib.reload(http_handler_module)
importlib.reload(hf_embedding_handler_module)
yield
@pytest.fixture
def mock_embedding_http_handler(reload_huggingface_modules):
def mock_embedding_http_handler():
"""Fixture to mock the HTTP handler for embedding tests"""
with patch("litellm.llms.custom_httpx.http_handler.HTTPHandler.post") as mock_post:
mock_response = MagicMock()
@ -43,7 +27,7 @@ def mock_embedding_http_handler(reload_huggingface_modules):
@pytest.fixture
def mock_embedding_async_http_handler(reload_huggingface_modules):
def mock_embedding_async_http_handler():
"""Fixture to mock the async HTTP handler for embedding tests"""
with patch("litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post", new_callable=AsyncMock) as mock_post:
mock_response = MagicMock()

10
tests/test_litellm/llms/vertex_ai/rerank/test_vertex_ai_rerank_integration.py
View file

@ -2,7 +2,6 @@
Integration tests for Vertex AI rerank functionality.
These tests demonstrate end-to-end usage of the Vertex AI rerank feature.
"""
import importlib
import os
from unittest.mock import MagicMock, patch
@ -14,14 +13,7 @@ from litellm.llms.vertex_ai.rerank.transformation import VertexAIRerankConfig
class TestVertexAIRerankIntegration:
def setup_method(self):
# Reload modules to ensure fresh references after conftest reloads litellm.
# This ensures the class being patched is the same one used by the tests.
import litellm.llms.vertex_ai.rerank.transformation as rerank_transformation_module
importlib.reload(rerank_transformation_module)
# Re-import after reload to get the fresh class
from litellm.llms.vertex_ai.rerank.transformation import VertexAIRerankConfig as FreshConfig
self.config = FreshConfig()
self.config = VertexAIRerankConfig()
self.model = "semantic-ranker-default@latest"
@patch('litellm.llms.vertex_ai.rerank.transformation.VertexAIRerankConfig._ensure_access_token')