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https://github.com/BerriAI/litellm.git
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* fix(openai.py): fix returning o1 non-streaming requests fixes issue where fake stream always true for o1 * build(model_prices_and_context_window.json): add 'supports_vision' for o1 models * fix: add internal server error exception mapping * fix(base_llm_unit_tests.py): drop temperature from test * test: mark prompt caching as a flaky test
172 lines
5.2 KiB
Python
172 lines
5.2 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, patch, MagicMock
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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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from base_llm_unit_tests import BaseLLMChatTest
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@pytest.mark.parametrize("model", ["o1-preview", "o1-mini", "o1"])
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@pytest.mark.asyncio
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async def test_o1_handle_system_role(model):
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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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from openai import AsyncOpenAI
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from litellm.utils import supports_system_messages
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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litellm.set_verbose = True
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client = AsyncOpenAI(api_key="fake-api-key")
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with patch.object(
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client.chat.completions.with_raw_response, "create"
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) as mock_client:
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try:
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await litellm.acompletion(
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model=model,
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max_tokens=10,
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messages=[{"role": "system", "content": "Be a good bot!"}],
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client=client,
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)
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except Exception as e:
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print(f"Error: {e}")
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mock_client.assert_called_once()
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request_body = mock_client.call_args.kwargs
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print("request_body: ", request_body)
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assert request_body["model"] == model
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assert request_body["max_completion_tokens"] == 10
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if supports_system_messages(model, "openai"):
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assert request_body["messages"] == [
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{"role": "system", "content": "Be a good bot!"}
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]
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else:
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assert request_body["messages"] == [
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{"role": "user", "content": "Be a good bot!"}
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]
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@pytest.mark.parametrize(
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"model, expected_tool_calling_support",
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[("o1-preview", False), ("o1-mini", False), ("o1", True)],
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)
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@pytest.mark.asyncio
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async def test_o1_handle_tool_calling_optional_params(
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model, expected_tool_calling_support
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):
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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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from openai import AsyncOpenAI
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from litellm.utils import ProviderConfigManager
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from litellm.types.utils import LlmProviders
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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config = ProviderConfigManager.get_provider_chat_config(
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model=model, provider=LlmProviders.OPENAI
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)
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supported_params = config.get_supported_openai_params(model=model)
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assert expected_tool_calling_support == ("tools" in supported_params)
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@pytest.mark.asyncio
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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(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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from openai import AsyncOpenAI
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litellm.set_verbose = True
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client = AsyncOpenAI(api_key="fake-api-key")
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with patch.object(
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client.chat.completions.with_raw_response, "create"
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) as mock_client:
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try:
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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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client=client,
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)
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except Exception as e:
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print(f"Error: {e}")
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mock_client.assert_called_once()
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request_body = mock_client.call_args.kwargs
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print("request_body: ", request_body)
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assert request_body["model"] == model
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assert request_body["max_completion_tokens"] == 10
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assert request_body["messages"] == [{"role": "user", "content": "Hello!"}]
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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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class TestOpenAIO1(BaseLLMChatTest):
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def get_base_completion_call_args(self):
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return {
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"model": "o1",
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}
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def test_tool_call_no_arguments(self, tool_call_no_arguments):
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"""Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833"""
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pass
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def test_o1_supports_vision():
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"""Test that o1 supports vision"""
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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for k, v in litellm.model_cost.items():
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if k.startswith("o1") and v.get("litellm_provider") == "openai":
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assert v.get("supports_vision") is True, f"{k} does not support vision"
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