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https://github.com/BerriAI/litellm.git
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6a0d03914c
* test: drop the cwd-relative sys.path.insert calls from the test suite
TQ003 stands at 1,077 across 1,058 files, and 1,015 of them are the same shape:
sys.path.insert(0, os.path.abspath("../..")) and its deeper siblings. The
argument resolves against the working directory rather than the file, so from
the repo root, where every job runs pytest, it inserts the directory two levels
above the checkout. It has never pointed at litellm. The package is installed
into the environment anyway, which is what actually makes the import work, and
what the rule's message has said all along.
Removing them leaves 1,634 imports of sys and os with no remaining reference,
and those go too, except where another test module imports the name back out of
the file. The rest of TQ003 is 62 call sites that resolve against __file__ or a
variable, which are a different question and are left alone.
Collection is identical either way: 45,871 tests and the same 51 pre-existing
collection errors before and after, and ruff reports no new undefined name.
* test: drop the duplicate imports the sys.path sweep exposed to F811
* test(pre-call-utils): restore the os import the new bedrock tests need
235 lines
7.5 KiB
Python
235 lines
7.5 KiB
Python
import json
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import os
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from datetime import datetime
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from unittest.mock import AsyncMock, patch, MagicMock
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import httpx
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import pytest
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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, BaseOSeriesModelsTest
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class TestAzureOpenAIO3Mini(BaseOSeriesModelsTest, BaseLLMChatTest):
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def get_base_completion_call_args(self):
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# Clear the LLM client cache to prevent test pollution from cached clients
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litellm.in_memory_llm_clients_cache.flush_cache()
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return {
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"model": "azure/o3-mini",
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"api_key": os.getenv("AZURE_AI_API_KEY"),
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"api_base": os.getenv("AZURE_AI_API_BASE"),
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"api_version": "2024-12-01-preview",
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}
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def get_client(self):
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from openai import AzureOpenAI
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return AzureOpenAI(
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api_key="my-fake-o1-key",
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base_url="https://openai-prod-test.openai.azure.com",
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api_version="2024-02-15-preview",
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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_basic_tool_calling(self):
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pass
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def test_prompt_caching(self):
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"""Temporary override. o1 prompt caching is not working."""
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pass
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def test_override_fake_stream(self):
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"""Test that native streaming is not supported for o1."""
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router = litellm.Router(
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model_list=[
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{
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"model_name": "azure/o1-preview",
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"litellm_params": {
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"model": "azure/o1-preview",
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"api_key": "my-fake-o1-key",
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"api_base": "https://openai-gpt-4-test-v-1.openai.azure.com",
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},
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"model_info": {
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"supports_native_streaming": True,
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},
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}
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]
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)
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## check model info
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model_info = litellm.get_model_info(
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model="azure/o1-preview", custom_llm_provider="azure"
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)
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assert model_info["supports_native_streaming"] is True
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fake_stream = litellm.AzureOpenAIO1Config().should_fake_stream(
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model="azure/o1-preview", stream=True
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)
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assert fake_stream is False
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class TestAzureOpenAIO3(BaseOSeriesModelsTest):
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def get_base_completion_call_args(self):
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return {
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"model": "azure/o3-mini",
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"api_key": "my-fake-o1-key",
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"api_base": "https://openai-gpt-4-test-v-1.openai.azure.com",
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}
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def get_client(self):
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from openai import AzureOpenAI
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return AzureOpenAI(
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api_key="my-fake-o1-key",
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base_url="https://openai-gpt-4-test-v-1.openai.azure.com",
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api_version="2024-02-15-preview",
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)
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def test_azure_o3_streaming():
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"""
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Test that o3 models handles fake streaming correctly.
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"""
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from openai import AzureOpenAI
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from litellm import completion
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client = AzureOpenAI(
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api_key="my-fake-o1-key",
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base_url="https://openai-gpt-4-test-v-1.openai.azure.com",
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api_version="2024-02-15-preview",
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)
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with patch.object(
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client.chat.completions.with_raw_response, "create"
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) as mock_create:
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try:
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completion(
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model="azure/o3-mini",
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messages=[{"role": "user", "content": "Hello, world!"}],
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stream=True,
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client=client,
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)
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except (
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Exception
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) as e: # expect output translation error as mock response doesn't return a json
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print(e)
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assert mock_create.call_count == 1
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assert "stream" in mock_create.call_args.kwargs
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def test_azure_o_series_routing():
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"""
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Allows user to pass model="azure/o_series/<any-deployment-name>" for explicit o_series model routing.
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"""
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from openai import AzureOpenAI
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from litellm import completion
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client = AzureOpenAI(
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api_key="my-fake-o1-key",
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base_url="https://openai-gpt-4-test-v-1.openai.azure.com",
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api_version="2024-02-15-preview",
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)
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with patch.object(
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client.chat.completions.with_raw_response, "create"
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) as mock_create:
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try:
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completion(
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model="azure/o_series/my-random-deployment-name",
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messages=[{"role": "user", "content": "Hello, world!"}],
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stream=True,
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client=client,
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)
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except (
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Exception
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) as e: # expect output translation error as mock response doesn't return a json
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print(e)
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assert mock_create.call_count == 1
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assert "stream" not in mock_create.call_args.kwargs
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@patch("litellm.main.azure_o1_chat_completions._get_openai_client")
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def test_openai_o_series_max_retries_0(mock_get_openai_client):
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import litellm
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litellm.set_verbose = True
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response = litellm.completion(
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model="azure/o1-preview",
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messages=[{"role": "user", "content": "hi"}],
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max_retries=0,
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)
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mock_get_openai_client.assert_called_once()
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assert mock_get_openai_client.call_args.kwargs["max_retries"] == 0
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@pytest.mark.asyncio
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async def test_azure_o1_series_response_format_extra_params():
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"""
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Tool calling should work for all azure o_series models.
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"""
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litellm._turn_on_debug()
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from openai import AsyncAzureOpenAI
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litellm.set_verbose = True
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client = AsyncAzureOpenAI(
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api_key="fake-api-key",
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base_url="https://openai-prod-test.openai.azure.com/openai/deployments/o1/chat/completions?api-version=2025-01-01-preview",
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api_version="2025-01-01-preview",
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)
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tools = [
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{
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"type": "function",
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"function": {
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"name": "get_current_time",
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"description": "Get the current time in a given location.",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city name, e.g. San Francisco",
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}
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},
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"required": ["location"],
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},
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},
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}
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]
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response_format = {"type": "json_object"}
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tool_choice = "auto"
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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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client=client,
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model="azure/o_series/<my-deployment-name>",
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api_key="xxxxx",
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api_base="https://openai-prod-test.openai.azure.com/openai/deployments/o1/chat/completions?api-version=2025-01-01-preview",
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api_version="2024-12-01-preview",
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messages=[{"role": "user", "content": "Hello! return a json object"}],
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tools=tools,
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response_format=response_format,
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tool_choice=tool_choice,
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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: ", json.dumps(request_body, indent=4))
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assert request_body["tools"] == tools
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assert request_body["response_format"] == response_format
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assert request_body["tool_choice"] == tool_choice
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