import json import os import sys from datetime import datetime from unittest.mock import AsyncMock sys.path.insert( 0, os.path.abspath("../..") ) # Adds the parent directory to the system path import httpx import pytest from respx import MockRouter import litellm from litellm import Choices, Message, ModelResponse, EmbeddingResponse, Usage from litellm import completion from unittest.mock import patch from litellm.llms.xai.chat.transformation import XAIChatConfig, XAI_API_BASE from base_llm_unit_tests import BaseReasoningLLMTests def test_xai_chat_config_get_openai_compatible_provider_info(): config = XAIChatConfig() # Test with default values api_base, api_key = config._get_openai_compatible_provider_info( api_base=None, api_key=None ) assert api_base == XAI_API_BASE assert api_key == os.environ.get("XAI_API_KEY") # Test with custom API key custom_api_key = "test_api_key" api_base, api_key = config._get_openai_compatible_provider_info( api_base=None, api_key=custom_api_key ) assert api_base == XAI_API_BASE assert api_key == custom_api_key # Test with custom environment variables for api_base and api_key with patch.dict( "os.environ", {"XAI_API_BASE": "https://env.x.ai/v1", "XAI_API_KEY": "env_api_key"}, ): api_base, api_key = config._get_openai_compatible_provider_info(None, None) assert api_base == "https://env.x.ai/v1" assert api_key == "env_api_key" def test_xai_chat_config_map_openai_params(): """ XAI is OpenAI compatible* Does not support all OpenAI parameters: - max_completion_tokens -> max_tokens """ config = XAIChatConfig() # Test mapping of parameters non_default_params = { "max_completion_tokens": 100, "frequency_penalty": 0.5, "logit_bias": {"50256": -100}, "logprobs": 5, "messages": [{"role": "user", "content": "Hello"}], "model": "xai/grok-beta", "n": 2, "presence_penalty": 0.2, "response_format": {"type": "json_object"}, "seed": 42, "stop": ["END"], "stream": True, "stream_options": {}, "temperature": 0.7, "tool_choice": "auto", "tools": [{"type": "function", "function": {"name": "get_weather"}}], "top_logprobs": 3, "top_p": 0.9, "user": "test_user", "unsupported_param": "value", } optional_params = {} model = "xai/grok-beta" result = config.map_openai_params(non_default_params, optional_params, model) # Assert all supported parameters are present in the result assert result["max_tokens"] == 100 # max_completion_tokens -> max_tokens assert result["frequency_penalty"] == 0.5 assert result["logit_bias"] == {"50256": -100} assert result["logprobs"] == 5 assert result["n"] == 2 assert result["presence_penalty"] == 0.2 assert result["response_format"] == {"type": "json_object"} assert result["seed"] == 42 assert result["stop"] == ["END"] assert result["stream"] is True assert result["stream_options"] == {} assert result["temperature"] == 0.7 assert result["tool_choice"] == "auto" assert result["tools"] == [ {"type": "function", "function": {"name": "get_weather"}} ] assert result["top_logprobs"] == 3 assert result["top_p"] == 0.9 assert result["user"] == "test_user" # Assert unsupported parameter is not in the result assert "unsupported_param" not in result @pytest.mark.parametrize("stream", [False, True]) def test_completion_xai(stream): try: litellm.set_verbose = True messages = [ {"role": "system", "content": "You're a good bot"}, { "role": "user", "content": "Hey", }, ] response = completion( model="xai/grok-beta", messages=messages, stream=stream, ) print(response) if stream is True: for chunk in response: print(chunk) assert chunk is not None assert isinstance(chunk, litellm.ModelResponseStream) assert isinstance(chunk.choices[0], litellm.utils.StreamingChoices) else: assert response is not None assert isinstance(response, litellm.ModelResponse) assert response.choices[0].message.content is not None except Exception as e: pytest.fail(f"Error occurred: {e}") def test_xai_message_name_filtering(): messages = [ { "role": "system", "content": "*I press the green button*", "name": "example_user" }, {"role": "user", "content": "Hello", "name": "John"}, {"role": "assistant", "content": "Hello", "name": "Jane"}, ] response = completion( model="xai/grok-beta", messages=messages, ) assert response is not None assert response.choices[0].message.content is not None class TestXAIReasoningEffort(BaseReasoningLLMTests): def get_base_completion_call_args(self): return { "model": "xai/grok-3-mini-beta", "messages": [{"role": "user", "content": "Hello"}], }