mirror of
https://github.com/BerriAI/litellm.git
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test(responses): drop stubbed-HTTP kwarg-passthrough tests per CI audit
Function-level deletions per the keep/drop audit (5): - test_anthropic_responses_api.py: test_response_api_handler_merges_metadata_and_service_tier_without_error, test_async_response_api_handler_merges_trace_id_without_error, test_aresponses_forwards_timeout_to_acompletion (patch acompletion, assert kwargs reached the mock, pattern c) - test_openai_responses_api.py: test_openai_responses_litellm_router_with_metadata, test_openai_responses_litellm_router_with_prompt, test_basic_computer_use_preview_tool_call, test_aresponses_service_tier_and_safety_identifier, test_openai_gpt5_reasoning_effort_parameter, test_aresponses_extra_body_params_passed, test_responses_extra_body_params_passed_sync, test_extra_body_merges_with_request_data (stubbed-HTTP kwarg passthrough, c) Unused imports removed via ruff F401.
This commit is contained in:
mateo-berri
parent
1eafdbfba9
commit
e86143fa62
2 changed files with 0 additions and 658 deletions
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@ -1,31 +1,10 @@
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import os
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import sys
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import pytest
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import asyncio
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from typing import Optional
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from unittest.mock import patch, AsyncMock, MagicMock
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from litellm.responses.litellm_completion_transformation.handler import (
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LiteLLMCompletionTransformationHandler,
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)
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from litellm.responses.litellm_completion_transformation.transformation import (
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LiteLLMCompletionResponsesConfig,
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)
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from litellm.types.utils import ModelResponse
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sys.path.insert(0, os.path.abspath("../.."))
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import litellm
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from litellm.integrations.custom_logger import CustomLogger
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import json
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from litellm.types.utils import StandardLoggingPayload
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from litellm.types.llms.openai import (
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ResponseCompletedEvent,
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ResponsesAPIResponse,
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ResponseAPIUsage,
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IncompleteDetails,
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)
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import litellm
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
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from base_responses_api import BaseResponsesAPITest
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from openai.types.responses.function_tool import FunctionTool
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@ -130,87 +109,3 @@ def test_multiturn_tool_calls():
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print("follow_up_response=", follow_up_response)
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def test_response_api_handler_merges_metadata_and_service_tier_without_error():
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"""Sync path must merge kwargs like async; double-splat raises TypeError."""
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handler = LiteLLMCompletionTransformationHandler()
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with patch("litellm.completion", new_callable=MagicMock) as mock_completion:
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mock_completion.return_value = ModelResponse(
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id="id", created=0, model="test", object="chat.completion", choices=[]
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)
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handler.response_api_handler(
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model="test",
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input="hi",
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responses_api_request={},
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metadata={"trace": "abc"},
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service_tier="auto",
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)
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assert mock_completion.call_count == 1
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assert mock_completion.call_args.kwargs["metadata"] == {"trace": "abc"}
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assert mock_completion.call_args.kwargs["service_tier"] == "auto"
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@pytest.mark.asyncio
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async def test_async_response_api_handler_merges_trace_id_without_error():
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handler = LiteLLMCompletionTransformationHandler()
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async def fake_session_handler(previous_response_id, litellm_completion_request):
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litellm_completion_request["litellm_trace_id"] = "session-trace"
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return litellm_completion_request
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with patch.object(
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LiteLLMCompletionResponsesConfig,
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"async_responses_api_session_handler",
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side_effect=fake_session_handler,
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):
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with patch("litellm.acompletion", new_callable=AsyncMock) as mock_acompletion:
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mock_acompletion.return_value = ModelResponse(
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id="id", created=0, model="test", object="chat.completion", choices=[]
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)
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await handler.async_response_api_handler(
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litellm_completion_request={"model": "test"},
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request_input="hi",
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responses_api_request={"previous_response_id": "123"},
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litellm_trace_id="original-trace",
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)
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# ensure acompletion called once with merged trace_id
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assert mock_acompletion.call_count == 1
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assert (
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mock_acompletion.call_args.kwargs["litellm_trace_id"] == "session-trace"
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)
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@pytest.mark.asyncio
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async def test_aresponses_forwards_timeout_to_acompletion():
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"""Regression test: timeout passed to aresponses() must reach acompletion()
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on the completion transformation path (Anthropic, Bedrock, Vertex etc.).
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Previously, `timeout` was a named param of `responses()` but was NOT
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forwarded to `litellm_completion_transformation_handler.response_api_handler`,
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so it was silently dropped — `Router(timeout=N)` was a no-op for Anthropic
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and similar providers, with calls falling back to the provider SDK default
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(~600s for Anthropic).
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"""
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with patch("litellm.acompletion", new_callable=AsyncMock) as mock_acompletion:
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mock_acompletion.return_value = ModelResponse(
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id="id",
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created=0,
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model="anthropic/claude-sonnet-4-5",
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object="chat.completion",
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choices=[],
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)
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await litellm.aresponses(
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model="anthropic/claude-sonnet-4-5",
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input="hello",
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timeout=42,
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api_key="sk-ant-fake",
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)
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assert mock_acompletion.call_count == 1
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forwarded_timeout = mock_acompletion.call_args.kwargs.get("timeout")
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assert forwarded_timeout == 42, (
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f"timeout was not forwarded to acompletion (got {forwarded_timeout!r}); "
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"this means Router(timeout=N) silently fails for providers on the "
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"completion transformation path."
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)
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@ -13,15 +13,12 @@ import json
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sys.path.insert(0, os.path.abspath("../.."))
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import litellm
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from litellm.integrations.custom_logger import CustomLogger
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import json
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from litellm.types.utils import StandardLoggingPayload
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from litellm.types.llms.openai import (
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ResponseCompletedEvent,
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ResponsesAPIResponse,
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ResponseAPIUsage,
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IncompleteDetails,
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)
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
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from base_responses_api import BaseResponsesAPITest, validate_responses_api_response
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@ -688,180 +685,6 @@ async def test_openai_responses_litellm_router_no_metadata():
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mock_post.assert_called_once()
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@pytest.mark.asyncio
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async def test_openai_responses_litellm_router_with_metadata():
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"""
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Test that metadata is correctly passed through when explicitly provided to the Router for responses API
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"""
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test_metadata = {
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"user_id": "123",
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"conversation_id": "abc",
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"custom_field": "test_value",
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}
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mock_response = {
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"id": "resp_123",
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"object": "response",
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"created_at": 1741476542,
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"status": "completed",
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"model": "gpt-5.5",
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"output": [
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{
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"type": "message",
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"id": "msg_123",
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"status": "completed",
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"role": "assistant",
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"content": [
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{"type": "output_text", "text": "Hello world!", "annotations": []}
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],
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}
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],
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"parallel_tool_calls": True,
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"usage": {
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"input_tokens": 10,
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"output_tokens": 20,
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"total_tokens": 30,
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"output_tokens_details": {"reasoning_tokens": 0},
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},
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"text": {"format": {"type": "text"}},
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"error": None,
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"incomplete_details": None,
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"instructions": None,
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"metadata": test_metadata, # Include the test metadata in response
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"temperature": 1.0,
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"tool_choice": "auto",
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"tools": [],
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"top_p": 1.0,
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"max_output_tokens": None,
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"previous_response_id": None,
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"reasoning": {"effort": None, "summary": None},
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"truncation": "disabled",
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"user": None,
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}
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class MockResponse:
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def __init__(self, json_data, status_code):
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self._json_data = json_data
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self.status_code = status_code
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self.text = str(json_data)
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self.headers = httpx.Headers({})
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def json(self):
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return self._json_data
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with patch(
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"litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
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new_callable=AsyncMock,
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) as mock_post:
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# Configure the mock to return our response
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mock_post.return_value = MockResponse(mock_response, 200)
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litellm._turn_on_debug()
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router = litellm.Router(
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model_list=[
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{
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"model_name": "gpt4o-special-alias",
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"litellm_params": {
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"model": "gpt-5.5",
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"api_key": "fake-key",
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},
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}
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]
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)
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# Call the handler with metadata
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await router.aresponses(
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model="gpt4o-special-alias",
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input="Hello, can you tell me a short joke?",
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metadata=test_metadata,
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)
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# Check the request body
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request_body = mock_post.call_args.kwargs["json"]
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print("Request body:", json.dumps(request_body, indent=4))
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# Assert metadata matches exactly what was passed
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assert (
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request_body["metadata"] == test_metadata
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), "metadata in request body should match what was passed"
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mock_post.assert_called_once()
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@pytest.mark.asyncio
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async def test_openai_responses_litellm_router_with_prompt():
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"""Test that prompt object is passed through the Router for responses API"""
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prompt_obj = {
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"id": "pmpt_abc123",
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"version": "2",
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"variables": {"random_variable": "ishaan_from_litellm"},
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}
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mock_response = {
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"id": "resp_123",
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"object": "response",
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"created_at": 1741476542,
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"status": "completed",
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"model": "gpt-5.5",
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"output": [],
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"parallel_tool_calls": True,
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"usage": {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0},
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"text": {"format": {"type": "text"}},
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"error": None,
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"incomplete_details": None,
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"instructions": None,
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"metadata": {},
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"temperature": 1.0,
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"tool_choice": "auto",
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"tools": [],
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"top_p": 1.0,
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"max_output_tokens": None,
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"previous_response_id": None,
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"reasoning": {"effort": None, "summary": None},
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"truncation": "disabled",
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"user": None,
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}
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class MockResponse:
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def __init__(self, json_data, status_code):
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self._json_data = json_data
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self.status_code = status_code
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self.text = str(json_data)
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self.headers = httpx.Headers({})
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def json(self):
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return self._json_data
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with patch(
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"litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
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new_callable=AsyncMock,
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) as mock_post:
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mock_post.return_value = MockResponse(mock_response, 200)
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litellm._turn_on_debug()
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router = litellm.Router(
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model_list=[
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{
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"model_name": "gpt4o-special-alias",
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"litellm_params": {
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"model": "gpt-5.5",
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"api_key": "fake-key",
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},
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}
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]
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)
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await router.aresponses(
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model="gpt4o-special-alias",
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input="Hello",
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prompt=prompt_obj,
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)
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request_body = mock_post.call_args.kwargs["json"]
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assert request_body["prompt"] == prompt_obj
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mock_post.assert_called_once()
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def test_bad_request_bad_param_error():
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"""Raise a BadRequestError when an invalid parameter value is provided"""
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try:
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@ -1111,106 +934,6 @@ async def test_openai_o1_pro_response_api_streaming(sync_mode):
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assert "stream" not in request_body
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def test_basic_computer_use_preview_tool_call():
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"""
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Test that LiteLLM correctly handles a computer_use_preview tool call where the environment is set to "linux"
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linux is an unsupported environment for the computer_use_preview tool, but litellm users should still be able to pass it to openai
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"""
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# Mock response from OpenAI
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mock_response = {
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"id": "resp_67dc3dd77b388190822443a85252da5a0e13d8bdc0e28d88",
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"object": "response",
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"created_at": 1742486999,
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"status": "incomplete",
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"error": None,
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"incomplete_details": {"reason": "max_output_tokens"},
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"instructions": None,
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"max_output_tokens": 20,
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"model": "o1-pro-2025-03-19",
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"output": [
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{
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"type": "reasoning",
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"id": "rs_67dc3de50f64819097450ed50a33d5f90e13d8bdc0e28d88",
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"summary": [],
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}
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],
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"parallel_tool_calls": True,
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"previous_response_id": None,
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"reasoning": {"effort": "medium", "generate_summary": None},
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"store": True,
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"temperature": 1.0,
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"text": {"format": {"type": "text"}},
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"tool_choice": "auto",
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"tools": [],
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"top_p": 1.0,
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"truncation": "disabled",
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"usage": {
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"input_tokens": 73,
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"input_tokens_details": {"cached_tokens": 0},
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"output_tokens": 20,
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"output_tokens_details": {"reasoning_tokens": 0},
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"total_tokens": 93,
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},
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"user": None,
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"metadata": {},
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}
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class MockResponse:
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def __init__(self, json_data, status_code):
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self._json_data = json_data
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self.status_code = status_code
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self.text = json.dumps(json_data)
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self.headers = httpx.Headers({})
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def json(self):
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return self._json_data
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with patch(
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"litellm.llms.custom_httpx.http_handler.HTTPHandler.post",
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return_value=MockResponse(mock_response, 200),
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) as mock_post:
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litellm._turn_on_debug()
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litellm.set_verbose = True
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# Call the responses API with computer_use_preview tool
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response = litellm.responses(
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model="openai/computer-use-preview",
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tools=[
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{
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"type": "computer_use_preview",
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"display_width": 1024,
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"display_height": 768,
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"environment": "linux", # other possible values: "mac", "windows", "ubuntu"
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}
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],
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input="Check the latest OpenAI news on bing.com.",
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reasoning={"summary": "concise"},
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truncation="auto",
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)
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# Verify the request was made correctly
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mock_post.assert_called_once()
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request_body = mock_post.call_args.kwargs["json"]
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# Validate the request structure
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assert request_body["model"] == "computer-use-preview"
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assert len(request_body["tools"]) == 1
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assert request_body["tools"][0]["type"] == "computer_use_preview"
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assert request_body["tools"][0]["display_width"] == 1024
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assert request_body["tools"][0]["display_height"] == 768
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assert request_body["tools"][0]["environment"] == "linux"
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# Check that reasoning was passed correctly
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assert request_body["reasoning"]["summary"] == "concise"
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assert request_body["truncation"] == "auto"
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# Validate the input format
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assert isinstance(request_body["input"], str)
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assert request_body["input"] == "Check the latest OpenAI news on bing.com."
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def test_mcp_tools_with_responses_api():
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litellm._turn_on_debug()
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MCP_TOOLS = [
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|
|
@ -1418,193 +1141,6 @@ async def test_store_field_transformation():
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), "created_at should maintain the same value after conversion"
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|
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|
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@pytest.mark.asyncio
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async def test_aresponses_service_tier_and_safety_identifier():
|
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"""
|
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Test that service_tier and safety_identifier parameters are correctly sent in the request body
|
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when using litellm.aresponses.
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"""
|
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mock_response = {
|
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"id": "resp_01234567890abcdef",
|
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"object": "response",
|
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"created_at": 1753060947,
|
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"status": "completed",
|
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"error": None,
|
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"incomplete_details": None,
|
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"instructions": None,
|
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"max_output_tokens": None,
|
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"model": "gpt-4o-2024-05-13",
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"output": [
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{
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"type": "text",
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"id": "out_01234567890abcdef",
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"text": "This is a test response with service tier and safety identifier.",
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}
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],
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"parallel_tool_calls": True,
|
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"previous_response_id": None,
|
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"reasoning": None,
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"store": True,
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"temperature": 1.0,
|
||||
"text": {"format": {"type": "text"}},
|
||||
"tool_choice": "auto",
|
||||
"tools": [],
|
||||
"top_p": 1.0,
|
||||
"truncation": "disabled",
|
||||
"usage": {
|
||||
"input_tokens": 15,
|
||||
"input_tokens_details": {"cached_tokens": 0},
|
||||
"output_tokens": 25,
|
||||
"output_tokens_details": {"reasoning_tokens": 0},
|
||||
"total_tokens": 40,
|
||||
},
|
||||
"user": None,
|
||||
"metadata": {},
|
||||
}
|
||||
|
||||
class MockResponse:
|
||||
def __init__(self, json_data, status_code):
|
||||
self._json_data = json_data
|
||||
self.status_code = status_code
|
||||
self.text = json.dumps(json_data)
|
||||
self.headers = httpx.Headers({})
|
||||
|
||||
def json(self):
|
||||
return self._json_data
|
||||
|
||||
with patch(
|
||||
"litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
|
||||
new_callable=AsyncMock,
|
||||
) as mock_post:
|
||||
# Configure the mock to return our response
|
||||
mock_post.return_value = MockResponse(mock_response, 200)
|
||||
|
||||
litellm._turn_on_debug()
|
||||
litellm.set_verbose = True
|
||||
|
||||
# Call aresponses with service_tier and safety_identifier
|
||||
response = await litellm.aresponses(
|
||||
model="openai/gpt-5.5",
|
||||
input="Test with service tier and safety identifier",
|
||||
service_tier="flex",
|
||||
safety_identifier="123",
|
||||
)
|
||||
|
||||
# Verify the request was made correctly
|
||||
mock_post.assert_called_once()
|
||||
request_body = mock_post.call_args.kwargs["json"]
|
||||
print("request_body=", json.dumps(request_body, indent=4, default=str))
|
||||
|
||||
# Validate that both parameters are present in the request body
|
||||
assert (
|
||||
request_body["service_tier"] == "flex"
|
||||
), "service_tier should be 'flex' in request body"
|
||||
assert (
|
||||
request_body["safety_identifier"] == "123"
|
||||
), "safety_identifier should be '123' in request body"
|
||||
assert request_body["model"] == "gpt-5.5"
|
||||
assert request_body["input"] == "Test with service tier and safety identifier"
|
||||
|
||||
# Validate the response
|
||||
print("Response:", json.dumps(response, indent=4, default=str))
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_openai_gpt5_reasoning_effort_parameter():
|
||||
"""Test that reasoning_effort parameter is properly sent in the HTTP request for GPT-5 models."""
|
||||
|
||||
# Mock response for GPT-5 responses API (correct format)
|
||||
mock_response = {
|
||||
"id": "resp_01ABC123",
|
||||
"object": "response",
|
||||
"created_at": 1729621667,
|
||||
"status": "completed",
|
||||
"model": "gpt-5-mini",
|
||||
"output": [
|
||||
{
|
||||
"type": "message",
|
||||
"id": "msg_123",
|
||||
"status": "completed",
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{
|
||||
"type": "output_text",
|
||||
"text": "The capital of France is Paris.",
|
||||
"annotations": [],
|
||||
}
|
||||
],
|
||||
}
|
||||
],
|
||||
"parallel_tool_calls": True,
|
||||
"usage": {
|
||||
"input_tokens": 15,
|
||||
"input_tokens_details": {"cached_tokens": 0},
|
||||
"output_tokens": 8,
|
||||
"output_tokens_details": {"reasoning_tokens": 0},
|
||||
"total_tokens": 23,
|
||||
},
|
||||
"text": {"format": {"type": "text"}},
|
||||
"error": None,
|
||||
"incomplete_details": None,
|
||||
"instructions": None,
|
||||
"metadata": {},
|
||||
"temperature": 1.0,
|
||||
"tool_choice": "auto",
|
||||
"tools": [],
|
||||
"top_p": 1.0,
|
||||
"max_output_tokens": None,
|
||||
"previous_response_id": None,
|
||||
"reasoning": {"effort": "low", "summary": None},
|
||||
"truncation": "disabled",
|
||||
"user": None,
|
||||
}
|
||||
|
||||
class MockResponse:
|
||||
def __init__(self, json_data, status_code):
|
||||
self._json_data = json_data
|
||||
self.status_code = status_code
|
||||
self.text = json.dumps(json_data)
|
||||
self.headers = httpx.Headers({})
|
||||
|
||||
def json(self):
|
||||
return self._json_data
|
||||
|
||||
with patch(
|
||||
"litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
|
||||
new_callable=AsyncMock,
|
||||
) as mock_post:
|
||||
# Configure the mock to return our response
|
||||
mock_post.return_value = MockResponse(mock_response, 200)
|
||||
|
||||
litellm._turn_on_debug()
|
||||
litellm.set_verbose = True
|
||||
|
||||
# Call aresponses with reasoning_effort parameter
|
||||
response = await litellm.aresponses(
|
||||
model="openai/gpt-5-mini",
|
||||
input="What is the capital of France?",
|
||||
reasoning={"effort": "minimal"},
|
||||
)
|
||||
|
||||
# Verify the request was made correctly
|
||||
mock_post.assert_called_once()
|
||||
request_body = mock_post.call_args.kwargs["json"]
|
||||
print("request_body=", json.dumps(request_body, indent=4, default=str))
|
||||
print("reasoning=", request_body["reasoning"])
|
||||
# Validate that reasoning_effort is present in the request body
|
||||
assert (
|
||||
"reasoning" in request_body
|
||||
), "reasoning should be present in request body"
|
||||
assert (
|
||||
request_body["reasoning"]["effort"] == "minimal"
|
||||
), "reasoning_effort should be 'minimal' in request body"
|
||||
assert request_body["model"] == "gpt-5-mini"
|
||||
assert request_body["input"] == "What is the capital of France?"
|
||||
|
||||
# Validate the response
|
||||
print("Response:", json.dumps(response, indent=4, default=str))
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize("stream", [True, False])
|
||||
async def test_basic_openai_responses_with_websearch(stream):
|
||||
|
|
@ -1737,95 +1273,6 @@ def extra_body_mock_response_data():
|
|||
}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_aresponses_extra_body_params_passed(extra_body_mock_response_data):
|
||||
"""Test that extra_body parameters are passed in async mode."""
|
||||
with patch(
|
||||
"litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
|
||||
new_callable=AsyncMock,
|
||||
) as mock_post:
|
||||
mock_post.return_value = MockResponse(extra_body_mock_response_data, 200)
|
||||
|
||||
response = await litellm.aresponses(
|
||||
model="gpt-5.5",
|
||||
input="Test input",
|
||||
max_output_tokens=20,
|
||||
extra_body={
|
||||
"custom_param_1": "value1",
|
||||
"custom_param_2": {"nested": "value2"},
|
||||
"experimental_feature": True,
|
||||
},
|
||||
)
|
||||
|
||||
assert response is not None
|
||||
assert response.id is not None
|
||||
|
||||
request_body = mock_post.call_args.kwargs["json"]
|
||||
|
||||
assert "custom_param_1" in request_body
|
||||
assert request_body["custom_param_1"] == "value1"
|
||||
assert "custom_param_2" in request_body
|
||||
assert request_body["custom_param_2"]["nested"] == "value2"
|
||||
assert "experimental_feature" in request_body
|
||||
assert request_body["experimental_feature"] is True
|
||||
assert request_body["model"] == "gpt-5.5"
|
||||
assert request_body["input"] == "Test input"
|
||||
|
||||
|
||||
def test_responses_extra_body_params_passed_sync(extra_body_mock_response_data):
|
||||
"""Test that extra_body parameters are passed in sync mode."""
|
||||
with patch(
|
||||
"litellm.llms.custom_httpx.http_handler.HTTPHandler.post",
|
||||
return_value=MockResponse(extra_body_mock_response_data, 200),
|
||||
) as mock_post:
|
||||
response = litellm.responses(
|
||||
model="gpt-5.5",
|
||||
input="Sync test",
|
||||
max_output_tokens=20,
|
||||
extra_body={
|
||||
"sync_custom_param": "sync_value",
|
||||
"another_param": 42,
|
||||
},
|
||||
)
|
||||
|
||||
assert response is not None
|
||||
assert response.id is not None
|
||||
|
||||
request_body = mock_post.call_args.kwargs["json"]
|
||||
|
||||
assert "sync_custom_param" in request_body
|
||||
assert request_body["sync_custom_param"] == "sync_value"
|
||||
assert "another_param" in request_body
|
||||
assert request_body["another_param"] == 42
|
||||
assert request_body["model"] == "gpt-5.5"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_extra_body_merges_with_request_data(extra_body_mock_response_data):
|
||||
"""Test that extra_body is merged into the request data."""
|
||||
with patch(
|
||||
"litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
|
||||
new_callable=AsyncMock,
|
||||
) as mock_post:
|
||||
mock_post.return_value = MockResponse(extra_body_mock_response_data, 200)
|
||||
|
||||
await litellm.aresponses(
|
||||
model="gpt-5.5",
|
||||
input="Test",
|
||||
temperature=0.7,
|
||||
max_output_tokens=20,
|
||||
extra_body={
|
||||
"custom_field": "custom_value",
|
||||
},
|
||||
)
|
||||
|
||||
request_body = mock_post.call_args.kwargs["json"]
|
||||
|
||||
assert "temperature" in request_body
|
||||
assert "custom_field" in request_body
|
||||
assert request_body["custom_field"] == "custom_value"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize("sync_mode", [True, False])
|
||||
async def test_openai_compact_responses_api(sync_mode):
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue