litellm/tests/llm_translation/test_xai.py
Cursor Agent 93300019bd
test(vcr): drop dead 'from respx import MockRouter' imports
These seven test files were on _RESPX_CONFLICTING_FILES, which made the
auto-marker skip them entirely. Inspecting the source shows the only
respx artifact is a top-level 'from respx import MockRouter' that no
test ever uses - no @pytest.mark.respx, no respx_mock fixture, no
respx.mock context manager. The import is dead code left over from a
previous mocking pattern.

Now that apply_vcr_auto_marker_to_items detects respx per-item via the
marker / fixture chain (b637d9f64a), the file-level skip is no longer
needed for these files - they were the reason the OpenAI tests
(test_o3_reasoning_effort, test_streaming_response[o1/o3-mini],
TestOpenAIO1::test_streaming, TestOpenAIChatCompletion::test_web_search,
TestOpenAIO3::test_web_search, etc.) ran live every CI build despite
the cassette cache being healthy.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
2026-05-13 00:32:03 +00:00

271 lines
8.5 KiB
Python

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
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, BaseLLMChatTest
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
def test_xai_check_for_stop_in_supported_params():
supported_params = XAIChatConfig().get_supported_openai_params(
model="xai/grok-3-mini"
)
assert "stop" not in supported_params
@pytest.mark.parametrize("model", ["xai/grok-4", "xai/grok-4-0709"])
def test_xai_grok_4_stop_not_supported(model):
"""
Test that grok-4 models do not support the stop parameter
Issue: https://github.com/BerriAI/litellm/issues/12635
"""
supported_params = XAIChatConfig().get_supported_openai_params(model=model)
assert "stop" not in supported_params
@pytest.mark.parametrize(
"model",
[
"xai/grok-4",
"xai/grok-4-0709",
"xai/grok-4-latest",
"xai/grok-code-fast",
"xai/grok-code-fast-1",
],
)
def test_xai_grok_4_frequency_penalty_not_supported(model):
"""
Test that grok-4 models do not support the frequency_penalty parameter
"""
supported_params = XAIChatConfig().get_supported_openai_params(model=model)
assert "frequency_penalty" not in supported_params
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-3-mini-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"}],
}
class TestXAIChat(BaseLLMChatTest):
def get_base_completion_call_args(self):
return {
"model": "xai/grok-3-mini-beta",
}
def test_tool_call_no_arguments(self, tool_call_no_arguments):
"""Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833"""
pass
def test_web_search(self):
"""Web search is only supported for Grok 4 family models"""
from litellm.utils import supports_web_search
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
litellm.model_cost = litellm.get_model_cost_map(url="")
litellm._turn_on_debug()
# Use grok-4-1-fast which supports web search
model = "xai/grok-4-1-fast"
if not supports_web_search(model, None):
pytest.skip("Model does not support web search")
response = completion(
model=model,
messages=[
{"role": "user", "content": "What's the weather like in Boston today?"}
],
web_search_options={},
max_tokens=100,
)
assert response is not None
def test_xai_streaming_with_include_usage():
"""
Test that xAI streaming correctly handles usage in the last chunk
when stream_options={"include_usage": True} is set.
xAI sends usage in a chunk with empty choices array, which should be
handled by XAIChatCompletionStreamingHandler.
"""
try:
response = completion(
model="xai/grok-4-1-fast-non-reasoning",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Say hello in one word"},
],
stream=True,
stream_options={"include_usage": True},
max_tokens=10,
)
chunks = []
usage_chunk = None
for chunk in response:
chunks.append(chunk)
if hasattr(chunk, "usage") and chunk.usage is not None:
usage_chunk = chunk
# Verify we got chunks
assert len(chunks) > 0, "Should receive streaming chunks"
# Verify usage was included in one of the chunks
assert usage_chunk is not None, "Should receive usage in streaming chunks"
# Verify usage has expected fields
assert hasattr(
usage_chunk.usage, "prompt_tokens"
), "Usage should have prompt_tokens"
assert hasattr(
usage_chunk.usage, "completion_tokens"
), "Usage should have completion_tokens"
assert hasattr(
usage_chunk.usage, "total_tokens"
), "Usage should have total_tokens"
# Verify usage values are positive
assert usage_chunk.usage.prompt_tokens > 0, "prompt_tokens should be positive"
assert (
usage_chunk.usage.completion_tokens > 0
), "completion_tokens should be positive"
assert usage_chunk.usage.total_tokens > 0, "total_tokens should be positive"
print(f"✓ Successfully received usage in streaming chunk: {usage_chunk.usage}")
except Exception as e:
if "API key" in str(e) or "authentication" in str(e).lower():
pytest.skip(f"Skipping test due to API key issue: {str(e)}")
raise