forked from phoenix/litellm-mirror
Litellm router trace (#6742)
* feat(router.py): add trace_id to parent functions - allows tracking retry/fallbacks * feat(router.py): log trace id across retry/fallback logic allows grouping llm logs for the same request * test: fix tests * fix: fix test * fix(transformation.py): only set non-none stop_sequences
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8 changed files with 197 additions and 32 deletions
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@ -14,6 +14,7 @@ from litellm.router import Deployment, LiteLLM_Params, ModelInfo
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from concurrent.futures import ThreadPoolExecutor
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from collections import defaultdict
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from dotenv import load_dotenv
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from unittest.mock import patch, MagicMock, AsyncMock
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load_dotenv()
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@ -83,3 +84,93 @@ def test_returned_settings():
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except Exception:
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print(traceback.format_exc())
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pytest.fail("An error occurred - " + traceback.format_exc())
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from litellm.types.utils import CallTypes
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def test_update_kwargs_before_fallbacks_unit_test():
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router = 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": "azure/chatgpt-v-2",
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"api_key": "bad-key",
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"api_version": os.getenv("AZURE_API_VERSION"),
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"api_base": os.getenv("AZURE_API_BASE"),
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},
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}
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],
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)
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kwargs = {"messages": [{"role": "user", "content": "write 1 sentence poem"}]}
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router._update_kwargs_before_fallbacks(
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model="gpt-3.5-turbo",
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kwargs=kwargs,
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)
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assert kwargs["litellm_trace_id"] is not None
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@pytest.mark.parametrize(
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"call_type",
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[
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CallTypes.acompletion,
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CallTypes.atext_completion,
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CallTypes.aembedding,
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CallTypes.arerank,
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CallTypes.atranscription,
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],
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)
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@pytest.mark.asyncio
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async def test_update_kwargs_before_fallbacks(call_type):
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router = 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": "azure/chatgpt-v-2",
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"api_key": "bad-key",
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"api_version": os.getenv("AZURE_API_VERSION"),
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"api_base": os.getenv("AZURE_API_BASE"),
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},
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}
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],
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)
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if call_type.value.startswith("a"):
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with patch.object(router, "async_function_with_fallbacks") as mock_client:
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if call_type.value == "acompletion":
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input_kwarg = {
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"messages": [{"role": "user", "content": "Hello, how are you?"}],
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}
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elif (
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call_type.value == "atext_completion"
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or call_type.value == "aimage_generation"
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):
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input_kwarg = {
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"prompt": "Hello, how are you?",
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}
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elif call_type.value == "aembedding" or call_type.value == "arerank":
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input_kwarg = {
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"input": "Hello, how are you?",
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}
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elif call_type.value == "atranscription":
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input_kwarg = {
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"file": "path/to/file",
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}
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else:
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input_kwarg = {}
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await getattr(router, call_type.value)(
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model="gpt-3.5-turbo",
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**input_kwarg,
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)
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mock_client.assert_called_once()
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print(mock_client.call_args.kwargs)
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assert mock_client.call_args.kwargs["litellm_trace_id"] is not None
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