forked from phoenix/litellm-mirror
7f4dfe434a
* add requester_metadata in standard logging payload * log requester_metadata in metadata * use StandardLoggingPayload for logging * docs StandardLoggingPayload * fix import * include standard logging object in failure * add test for requester metadata * handle completion_tokens_details * add test for completion_tokens_details
122 lines
3.3 KiB
Python
122 lines
3.3 KiB
Python
import json
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import os
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import sys
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from datetime import datetime
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from unittest.mock import AsyncMock
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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 httpx
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import pytest
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from respx import MockRouter
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import litellm
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from litellm import Choices, Message, ModelResponse
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@pytest.mark.asyncio
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@pytest.mark.respx
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async def test_o1_handle_system_role(respx_mock: MockRouter):
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"""
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Tests that:
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- max_tokens is translated to 'max_completion_tokens'
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- role 'system' is translated to 'user'
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"""
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litellm.set_verbose = True
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mock_response = ModelResponse(
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id="cmpl-mock",
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choices=[Choices(message=Message(content="Mocked response", role="assistant"))],
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created=int(datetime.now().timestamp()),
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model="o1-preview",
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)
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mock_request = respx_mock.post("https://api.openai.com/v1/chat/completions").mock(
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return_value=httpx.Response(200, json=mock_response.dict())
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)
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response = await litellm.acompletion(
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model="o1-preview",
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max_tokens=10,
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messages=[{"role": "system", "content": "Hello!"}],
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)
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assert mock_request.called
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request_body = json.loads(mock_request.calls[0].request.content)
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print("request_body: ", request_body)
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assert request_body == {
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"model": "o1-preview",
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"max_completion_tokens": 10,
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"messages": [{"role": "user", "content": "Hello!"}],
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}
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print(f"response: {response}")
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assert isinstance(response, ModelResponse)
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@pytest.mark.asyncio
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@pytest.mark.respx
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@pytest.mark.parametrize("model", ["gpt-4", "gpt-4-0314", "gpt-4-32k", "o1-preview"])
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async def test_o1_max_completion_tokens(respx_mock: MockRouter, model: str):
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"""
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Tests that:
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- max_completion_tokens is passed directly to OpenAI chat completion models
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"""
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litellm.set_verbose = True
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mock_response = ModelResponse(
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id="cmpl-mock",
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choices=[Choices(message=Message(content="Mocked response", role="assistant"))],
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created=int(datetime.now().timestamp()),
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model=model,
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)
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mock_request = respx_mock.post("https://api.openai.com/v1/chat/completions").mock(
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return_value=httpx.Response(200, json=mock_response.dict())
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)
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response = await litellm.acompletion(
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model=model,
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max_completion_tokens=10,
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messages=[{"role": "user", "content": "Hello!"}],
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)
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assert mock_request.called
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request_body = json.loads(mock_request.calls[0].request.content)
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print("request_body: ", request_body)
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assert request_body == {
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"model": model,
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"max_completion_tokens": 10,
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"messages": [{"role": "user", "content": "Hello!"}],
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}
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print(f"response: {response}")
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assert isinstance(response, ModelResponse)
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def test_litellm_responses():
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"""
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ensures that type of completion_tokens_details is correctly handled / returned
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"""
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from litellm import ModelResponse
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from litellm.types.utils import CompletionTokensDetails
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response = ModelResponse(
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usage={
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"completion_tokens": 436,
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"prompt_tokens": 14,
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"total_tokens": 450,
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"completion_tokens_details": {"reasoning_tokens": 0},
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}
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)
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print("response: ", response)
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assert isinstance(response.usage.completion_tokens_details, CompletionTokensDetails)
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