mirror of
https://github.com/tiennm99/litellm.git
synced 2026-07-17 04:17:43 +00:00
Sameer Kankute
2506ccb2bc
- Only use_chat_completions_api and openai/chat_completions/ opt into the bridge - Extract MCP gateway and file_search emulation dispatch to cut responses() size - Update docs and tests Made-with: Cursor
283 lines
11 KiB
Python
283 lines
11 KiB
Python
"""
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Tests for forcing the /responses → /chat/completions bridge for `openai/` models
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(via `use_chat_completions_api` or the `openai/chat_completions/<model>` model id).
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Includes file_search emulation: the flag must be forwarded on inner aresponses
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calls so routed requests do not hit a custom api_base /v1/responses endpoint.
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"""
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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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sys.path.insert(
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0, os.path.abspath("../../..")
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) # Adds the parent directory to the system path
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import litellm
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from litellm.types.llms.openai import ResponseAPIUsage, ResponsesAPIResponse
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class TestUseResponsesApiBridgeFlag:
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"""Test that bridge opt-in forces the chat completions path."""
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@patch(
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"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler"
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)
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@patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config"
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)
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def test_bridge_used_when_use_chat_completions_api_true(
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self, mock_get_config, mock_bridge_handler
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):
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"""When use_chat_completions_api=True, the bridge handler should be called."""
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mock_get_config.return_value = litellm.OpenAIResponsesAPIConfig()
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mock_bridge_handler.return_value = MagicMock()
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litellm.responses(
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model="openai/my-custom-model",
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input="Hello",
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use_chat_completions_api=True,
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litellm_logging_obj=MagicMock(),
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)
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mock_bridge_handler.assert_called_once()
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@patch(
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"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler"
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)
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@patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config"
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)
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def test_bridge_used_when_model_uses_chat_completions_prefix(
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self, mock_get_config, mock_bridge_handler
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):
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"""`openai/chat_completions/<name>` normalizes to `openai/<name>` and uses the bridge."""
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mock_get_config.return_value = litellm.OpenAIResponsesAPIConfig()
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mock_bridge_handler.return_value = MagicMock()
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litellm.responses(
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model="openai/chat_completions/my-custom-model",
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input="Hello",
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litellm_logging_obj=MagicMock(),
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)
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mock_bridge_handler.assert_called_once()
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# Model string is provider-normalized after resolution; prefix only forces the bridge.
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assert mock_bridge_handler.call_args.kwargs["model"].endswith("my-custom-model")
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@patch("litellm.responses.main.base_llm_http_handler.response_api_handler")
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@patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config"
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)
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def test_native_forwarding_when_flag_absent(
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self, mock_get_config, mock_native_handler
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):
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"""When use_chat_completions_api is not set, openai/ models should use
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native responses API forwarding (existing behavior)."""
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mock_get_config.return_value = litellm.OpenAIResponsesAPIConfig()
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mock_native_handler.return_value = MagicMock()
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litellm.responses(
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model="openai/gpt-4o",
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input="Hello",
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litellm_logging_obj=MagicMock(),
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)
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mock_native_handler.assert_called_once()
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@patch(
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"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler"
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)
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@patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config"
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)
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def test_flag_does_not_leak_into_kwargs(self, mock_get_config, mock_bridge_handler):
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"""use_chat_completions_api should be popped and not passed to the bridge handler."""
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mock_get_config.return_value = litellm.OpenAIResponsesAPIConfig()
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mock_bridge_handler.return_value = MagicMock()
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litellm.responses(
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model="openai/my-custom-model",
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input="Hello",
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use_chat_completions_api=True,
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litellm_logging_obj=MagicMock(),
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)
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call_kwargs = mock_bridge_handler.call_args
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all_kwargs = call_kwargs.kwargs if call_kwargs.kwargs else {}
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assert "use_chat_completions_api" not in all_kwargs
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@patch(
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"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler"
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)
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@patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config"
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)
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def test_bridge_used_when_provider_config_none(
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self, mock_get_config, mock_bridge_handler
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):
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"""When the provider has no native responses API config (returns None),
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the bridge should be used regardless of the flag (existing behavior)."""
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mock_get_config.return_value = None
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mock_bridge_handler.return_value = MagicMock()
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litellm.responses(
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model="anthropic/claude-3-haiku",
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input="Hello",
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litellm_logging_obj=MagicMock(),
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)
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mock_bridge_handler.assert_called_once()
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@patch("litellm.responses.file_search.emulated_handler._call_aresponses")
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@patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config"
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)
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async def test_bridge_flag_forwarded_to_file_search_emulation(
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self, mock_get_config, mock_call_aresponses
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):
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"""When use_chat_completions_api=True and file_search tool is present,
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the flag should be forwarded to the inner aresponses call in the
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file_search emulation path."""
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# Setup: provider has native responses API support
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mock_get_config.return_value = litellm.OpenAIResponsesAPIConfig()
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# Mock the inner aresponses call to return a valid response
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mock_response = ResponsesAPIResponse(
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id="resp_123",
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model="openai/my-custom-model",
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created_at=1234567890,
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output=[
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{"type": "message", "content": [{"type": "text", "text": "Answer"}]}
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],
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usage=ResponseAPIUsage(
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input_tokens=10, output_tokens=5, total_tokens=15
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),
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)
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mock_call_aresponses.return_value = mock_response
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await litellm.aresponses(
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model="openai/my-custom-model",
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input="Search for information",
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tools=[{"type": "file_search"}],
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use_chat_completions_api=True,
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litellm_logging_obj=MagicMock(),
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)
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# Verify _call_aresponses was called with use_chat_completions_api=True
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mock_call_aresponses.assert_called_once()
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call_kwargs = mock_call_aresponses.call_args.kwargs
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assert (
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call_kwargs.get("use_chat_completions_api") is True
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), "use_chat_completions_api should be forwarded to inner aresponses call"
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@patch(
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"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler"
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)
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@patch("litellm.vector_stores.main.asearch")
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@patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config"
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)
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async def test_bridge_flag_prevents_native_responses_endpoint_call(
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self, mock_get_config, mock_asearch, mock_bridge_handler
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):
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"""
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Concrete failing scenario: native OpenAI responses config + bridge flag +
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file_search → emulation must still route inner calls through the bridge
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(chat completions), not POST to api_base /v1/responses.
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"""
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mock_get_config.return_value = litellm.OpenAIResponsesAPIConfig()
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mock_asearch.return_value = []
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first_response = ResponsesAPIResponse(
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id="resp_first",
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model="openai/my-local-model",
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created_at=1234567890,
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output=[
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{
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"type": "function_call",
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"name": "litellm_file_search",
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"call_id": "call_123",
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"arguments": '{"queries": ["test query"]}',
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}
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],
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usage=ResponseAPIUsage(
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input_tokens=10, output_tokens=5, total_tokens=15
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),
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)
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second_response = ResponsesAPIResponse(
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id="resp_second",
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model="openai/my-local-model",
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created_at=1234567891,
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output=[
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{
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"type": "message",
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"content": [{"type": "text", "text": "Final answer"}],
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}
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],
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usage=ResponseAPIUsage(
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input_tokens=20, output_tokens=10, total_tokens=30
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),
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)
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mock_bridge_handler.side_effect = [first_response, second_response]
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result = await litellm.aresponses(
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model="openai/my-local-model",
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input="Search for information",
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tools=[
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{
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"type": "file_search",
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"file_search": {"vector_store_ids": ["vs_123"]},
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}
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],
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use_chat_completions_api=True,
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api_base="http://localhost:8080/v1",
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litellm_logging_obj=MagicMock(),
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)
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assert mock_bridge_handler.call_count == 2, (
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"Bridge handler should be called twice: initial function-tool call "
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"and follow-up with tool results"
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)
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for call in mock_bridge_handler.call_args_list:
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all_kwargs = call.kwargs if call.kwargs else {}
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assert "use_chat_completions_api" not in all_kwargs
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assert result is not None
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assert result.id is not None
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@patch("litellm.responses.main.base_llm_http_handler.response_api_handler")
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@patch("litellm.vector_stores.main.asearch")
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@patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config"
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)
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async def test_without_bridge_flag_uses_native_endpoint(
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self, mock_get_config, mock_asearch, mock_native_handler
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):
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"""Without the bridge flag, openai/ with native config uses the native handler."""
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mock_get_config.return_value = litellm.OpenAIResponsesAPIConfig()
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mock_asearch.return_value = []
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mock_native_handler.return_value = ResponsesAPIResponse(
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id="resp_native",
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model="openai/gpt-4o",
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created_at=1234567890,
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output=[
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{
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"type": "message",
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"content": [{"type": "text", "text": "Native response"}],
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}
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],
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usage=ResponseAPIUsage(
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input_tokens=10, output_tokens=5, total_tokens=15
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),
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)
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result = await litellm.aresponses(
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model="openai/gpt-4o",
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input="Hello",
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litellm_logging_obj=MagicMock(),
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)
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mock_native_handler.assert_called_once()
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assert result is not None
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