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* test: move the unit half of 126 mixed legacy files into tests/unit * test: restore litellm globals that moved tests set * test: finalize migration test cleanup * test: restore original bodies of moved legacy tests The move into tests/unit had rewritten 612 test bodies, and some of the rewrites dropped assertions. Each moved test now carries its original body from the legacy file, with only the imports, helpers, fake provider credentials and monkeypatched env it needs to run under tests/unit test_timeout_streaming goes back to tests/local_testing because it needs the fake OpenAI endpoint server. The image payload fixture moves with its only user, and two tests that leaked global state (a registered model cost entry and queued logging tasks) are now isolated * test: drop module imports shadowed by restored local imports * test: assert on LiteLLM output in no-assertion moved tests and isolate leaks Twenty no-assertion candidates get one assertion on the value LiteLLM returns, with the original lines unchanged. Four tests go back to their legacy files because they only check types or imports, write into the working directory, or cannot assert without a body change Two moved tests leaked globals into later tests in the same worker, so monkeypatch fixtures now restore the retry-after header parser and the end user cost tracking flags * test: drain queued logging tasks before the Phoenix span test The moved Phoenix test counted spans from logging tasks that earlier tests had queued, so the drain fixture moves to tests/unit/conftest.py and both it and the Datadog batch test use it. test_factory_function goes back to its legacy file because its returned wrapper calls the real Assistants API and cannot be asserted on without a body change --------- Co-authored-by: yuneng <yuneng@berri.ai>
87 lines
2.7 KiB
Python
87 lines
2.7 KiB
Python
import os
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from typing import Any
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import pytest
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from litellm import Router
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from litellm.router_utils.fallback_event_handlers import (
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run_async_fallback,
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)
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from tests.fake_openai_endpoint import FAKE_OPENAI_API_BASE
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# Helper function to create a Router instance
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def create_test_router_2():
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return Router(
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model_list=[
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{
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"model_name": "gpt-3.5-turbo",
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"litellm_params": {
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"model": "gpt-3.5-turbo",
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"api_key": os.getenv("OPENAI_API_KEY"),
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},
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},
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{
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"model_name": "gpt-4",
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"litellm_params": {
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"model": "gpt-4",
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"api_key": "very-fake-key",
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},
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},
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{
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"model_name": "fake-openai-endpoint-2",
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"litellm_params": {
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"model": "openai/fake-openai-endpoint-2",
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"api_key": "working-key-since-this-is-fake-endpoint",
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"api_base": FAKE_OPENAI_API_BASE,
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},
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},
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],
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)
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@pytest.mark.asyncio
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@pytest.mark.parametrize("function_name", ["_acompletion", "_atext_completion"])
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async def test_multiple_fallbacks(function_name):
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"""
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Tests that if multiple fallbacks passed:
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- fallback 1 = bad configured deployment / failing endpoint
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- fallback 2 = working deployment / working endpoint
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Assert that:
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- a success response is received from the working endpoint (fallback 2)
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"""
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router_2 = create_test_router_2()
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original_function = getattr(router_2, function_name)
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fallback_model_group = ["gpt-4", "fake-openai-endpoint-2"]
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original_model_group = "gpt-3.5-turbo"
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original_exception = Exception("Simulated error")
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request_kwargs: dict[str, Any] = {
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"metadata": {"previous_models": ["gpt-3.5-turbo"]}
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}
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if function_name == "_aembedding":
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request_kwargs["input"] = "hello this is a test for run_async_fallback"
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elif function_name == "_atext_completion":
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request_kwargs["prompt"] = "hello this is a test for run_async_fallback"
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elif function_name == "_acompletion":
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request_kwargs["messages"] = [{"role": "user", "content": "Hello, world!"}]
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result = await run_async_fallback(
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litellm_router=router_2,
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original_function=original_function,
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num_retries=1,
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fallback_model_group=fallback_model_group,
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original_model_group=original_model_group,
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original_exception=original_exception,
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max_fallbacks=5,
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fallback_depth=0,
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**request_kwargs,
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)
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print(result)
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print(result._hidden_params)
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assert result._hidden_params["api_base"] == FAKE_OPENAI_API_BASE
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