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https://github.com/BerriAI/litellm.git
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fix(tests): use class-level AsyncHTTPHandler mock in vertex GPT-OSS tests
Replace instance-level patch.object(client, "post", side_effect=...) with class-level patch of AsyncHTTPHandler and AsyncMock to reliably intercept HTTP calls in CI where real Google credentials are available. The old approach patched a specific instance's post method and passed client=client to acompletion(). In CI, the mock wasn't intercepting actual HTTP calls, causing 401 ACCESS_TOKEN_TYPE_UNSUPPORTED errors. The new approach patches AsyncHTTPHandler at the class level so any instance created internally by get_async_httpx_client() is also mocked. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Julio Quinteros Pro
parent
f2480f4f37
commit
f0fc44c244
1 changed files with 28 additions and 50 deletions
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@ -1,9 +1,8 @@
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import json
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import os
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import sys
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from unittest.mock import MagicMock, patch
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from unittest.mock import AsyncMock, MagicMock, patch
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import httpx
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import pytest
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sys.path.insert(
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@ -76,11 +75,6 @@ async def test_vertex_ai_gpt_oss_simple_request():
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Test that a simple request to vertex_ai/openai/gpt-oss-20b-maas lands at the correct URL
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with the correct request body.
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"""
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
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from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
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VertexLLM,
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)
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# Mock response
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mock_response = MagicMock()
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mock_response.status_code = 200
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@ -107,21 +101,17 @@ async def test_vertex_ai_gpt_oss_simple_request():
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}
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}
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client = AsyncHTTPHandler()
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async def mock_post_func(*args, **kwargs):
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return mock_response
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# Mock vertexai module to prevent import from triggering authentication
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mock_vertexai = MagicMock()
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mock_vertexai.preview = MagicMock()
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mock_vertexai.preview.language_models = MagicMock()
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with patch.object(client, "post", side_effect=mock_post_func) as mock_post, \
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patch.object(VertexLLM, "_ensure_access_token", return_value=("fake-token", "pathrise-convert-1606954137718")), \
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patch('litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexAIError', Exception), \
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patch.dict('sys.modules', {'vertexai': mock_vertexai, 'vertexai.preview': mock_vertexai.preview}), \
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with patch("litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler") as mock_http_handler, \
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patch("litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexLLM._ensure_access_token",
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return_value=("fake-token", "pathrise-convert-1606954137718")), \
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patch.dict("sys.modules", {"vertexai": mock_vertexai, "vertexai.preview": mock_vertexai.preview}), \
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patch.dict(os.environ, {"VERTEXAI_PROJECT": "pathrise-convert-1606954137718"}):
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mock_http_handler.return_value.post = AsyncMock(return_value=mock_response)
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response = await litellm.acompletion(
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model="vertex_ai/openai/gpt-oss-20b-maas",
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messages=[
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@ -136,22 +126,20 @@ async def test_vertex_ai_gpt_oss_simple_request():
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],
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vertex_ai_location="us-central1",
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vertex_ai_project="pathrise-convert-1606954137718",
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client=client
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)
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# Verify the mock was called
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mock_post.assert_called_once()
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mock_http_handler.return_value.post.assert_called_once()
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# Get the call arguments
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call_args = mock_post.call_args
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# For side_effect, the URL is passed as kwargs['url']
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call_args = mock_http_handler.return_value.post.call_args
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called_url = call_args.kwargs["url"]
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request_body = json.loads(call_args.kwargs["data"])
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# Verify the URL
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expected_url = "https://us-central1-aiplatform.googleapis.com/v1/projects/pathrise-convert-1606954137718/locations/us-central1/endpoints/openapi/chat/completions"
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assert called_url == expected_url
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# Verify the request body
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expected_request_body = {
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'model': 'openai/gpt-oss-20b-maas',
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@ -168,7 +156,7 @@ async def test_vertex_ai_gpt_oss_simple_request():
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'stream': False
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}
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assert request_body == expected_request_body
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# Verify response structure
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assert response.model == "openai/gpt-oss-20b-maas"
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assert len(response.choices) == 1
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@ -181,11 +169,6 @@ async def test_vertex_ai_gpt_oss_reasoning_effort():
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Test that reasoning_effort parameter is correctly passed in the request body
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for GPT-OSS models.
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"""
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
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from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
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VertexLLM,
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)
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# Mock response
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mock_response = MagicMock()
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mock_response.status_code = 200
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@ -212,21 +195,17 @@ async def test_vertex_ai_gpt_oss_reasoning_effort():
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}
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}
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client = AsyncHTTPHandler()
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async def mock_post_func(*args, **kwargs):
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return mock_response
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# Mock vertexai module to prevent import from triggering authentication
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mock_vertexai = MagicMock()
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mock_vertexai.preview = MagicMock()
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mock_vertexai.preview.language_models = MagicMock()
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with patch.object(client, "post", side_effect=mock_post_func) as mock_post, \
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patch.object(VertexLLM, "_ensure_access_token", return_value=("fake-token", "pathrise-convert-1606954137718")), \
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patch('litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexAIError', Exception), \
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patch.dict('sys.modules', {'vertexai': mock_vertexai, 'vertexai.preview': mock_vertexai.preview}), \
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with patch("litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler") as mock_http_handler, \
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patch("litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexLLM._ensure_access_token",
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return_value=("fake-token", "pathrise-convert-1606954137718")), \
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patch.dict("sys.modules", {"vertexai": mock_vertexai, "vertexai.preview": mock_vertexai.preview}), \
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patch.dict(os.environ, {"VERTEXAI_PROJECT": "pathrise-convert-1606954137718"}):
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mock_http_handler.return_value.post = AsyncMock(return_value=mock_response)
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response = await litellm.acompletion(
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model="vertex_ai/openai/gpt-oss-20b-maas",
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messages=[
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@ -242,20 +221,19 @@ async def test_vertex_ai_gpt_oss_reasoning_effort():
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reasoning_effort="low",
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vertex_ai_location="us-central1",
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vertex_ai_project="pathrise-convert-1606954137718",
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client=client
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)
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# Verify the mock was called
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mock_post.assert_called_once()
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# Get the call arguments
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call_args = mock_post.call_args
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mock_http_handler.return_value.post.assert_called_once()
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# Get the call arguments
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call_args = mock_http_handler.return_value.post.call_args
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request_body = json.loads(call_args.kwargs["data"])
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# Verify reasoning_effort is in the request body
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assert "reasoning_effort" in request_body
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assert request_body["reasoning_effort"] == "low"
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# Verify other expected fields
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expected_request_body = {
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'model': 'openai/gpt-oss-20b-maas',
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@ -273,7 +251,7 @@ async def test_vertex_ai_gpt_oss_reasoning_effort():
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'stream': False
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}
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assert request_body == expected_request_body
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# Verify response structure
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assert response.model == "openai/gpt-oss-20b-maas"
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assert len(response.choices) == 1
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