Files
sglang/test/srt/openai/test_serving_completions.py
Xinyuan Tong 70c471a868 [Refactor] OAI Server components (#7167)
Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>
2025-06-16 20:45:20 -07:00

177 lines
6.0 KiB
Python

"""
Tests for the refactored completions serving handler
"""
from unittest.mock import AsyncMock, Mock, patch
import pytest
from sglang.srt.entrypoints.openai.protocol import (
CompletionRequest,
CompletionResponse,
CompletionResponseChoice,
CompletionStreamResponse,
ErrorResponse,
)
from sglang.srt.entrypoints.openai.serving_completions import OpenAIServingCompletion
from sglang.srt.managers.io_struct import GenerateReqInput
from sglang.srt.managers.tokenizer_manager import TokenizerManager
@pytest.fixture
def mock_tokenizer_manager():
"""Create a mock tokenizer manager"""
manager = Mock(spec=TokenizerManager)
# Mock tokenizer
manager.tokenizer = Mock()
manager.tokenizer.encode = Mock(return_value=[1, 2, 3, 4])
manager.tokenizer.decode = Mock(return_value="decoded text")
manager.tokenizer.bos_token_id = 1
# Mock model config
manager.model_config = Mock()
manager.model_config.is_multimodal = False
# Mock server args
manager.server_args = Mock()
manager.server_args.enable_cache_report = False
# Mock generation
manager.generate_request = AsyncMock()
manager.create_abort_task = Mock(return_value=None)
return manager
@pytest.fixture
def serving_completion(mock_tokenizer_manager):
"""Create a OpenAIServingCompletion instance"""
return OpenAIServingCompletion(mock_tokenizer_manager)
class TestPromptHandling:
"""Test different prompt types and formats from adapter.py"""
def test_single_string_prompt(self, serving_completion):
"""Test handling single string prompt"""
request = CompletionRequest(
model="test-model", prompt="Hello world", max_tokens=100
)
adapted_request, _ = serving_completion._convert_to_internal_request(
[request], ["test-id"]
)
assert adapted_request.text == "Hello world"
def test_single_token_ids_prompt(self, serving_completion):
"""Test handling single token IDs prompt"""
request = CompletionRequest(
model="test-model", prompt=[1, 2, 3, 4], max_tokens=100
)
adapted_request, _ = serving_completion._convert_to_internal_request(
[request], ["test-id"]
)
assert adapted_request.input_ids == [1, 2, 3, 4]
def test_completion_template_handling(self, serving_completion):
"""Test completion template processing"""
request = CompletionRequest(
model="test-model",
prompt="def hello():",
suffix="return 'world'",
max_tokens=100,
)
with patch(
"sglang.srt.entrypoints.openai.serving_completions.is_completion_template_defined",
return_value=True,
):
with patch(
"sglang.srt.entrypoints.openai.serving_completions.generate_completion_prompt_from_request",
return_value="processed_prompt",
):
adapted_request, _ = serving_completion._convert_to_internal_request(
[request], ["test-id"]
)
assert adapted_request.text == "processed_prompt"
class TestEchoHandling:
"""Test echo functionality from adapter.py"""
def test_echo_with_string_prompt_streaming(self, serving_completion):
"""Test echo handling with string prompt in streaming"""
request = CompletionRequest(
model="test-model", prompt="Hello", max_tokens=100, echo=True
)
# Test _get_echo_text method
echo_text = serving_completion._get_echo_text(request, 0)
assert echo_text == "Hello"
def test_echo_with_list_of_strings_streaming(self, serving_completion):
"""Test echo handling with list of strings in streaming"""
request = CompletionRequest(
model="test-model",
prompt=["Hello", "World"],
max_tokens=100,
echo=True,
n=1,
)
echo_text = serving_completion._get_echo_text(request, 0)
assert echo_text == "Hello"
echo_text = serving_completion._get_echo_text(request, 1)
assert echo_text == "World"
def test_echo_with_token_ids_streaming(self, serving_completion):
"""Test echo handling with token IDs in streaming"""
request = CompletionRequest(
model="test-model", prompt=[1, 2, 3], max_tokens=100, echo=True
)
serving_completion.tokenizer_manager.tokenizer.decode.return_value = (
"decoded_prompt"
)
echo_text = serving_completion._get_echo_text(request, 0)
assert echo_text == "decoded_prompt"
def test_echo_with_multiple_token_ids_streaming(self, serving_completion):
"""Test echo handling with multiple token ID prompts in streaming"""
request = CompletionRequest(
model="test-model", prompt=[[1, 2], [3, 4]], max_tokens=100, echo=True, n=1
)
serving_completion.tokenizer_manager.tokenizer.decode.return_value = "decoded"
echo_text = serving_completion._get_echo_text(request, 0)
assert echo_text == "decoded"
def test_prepare_echo_prompts_non_streaming(self, serving_completion):
"""Test prepare echo prompts for non-streaming response"""
# Test with single string
request = CompletionRequest(model="test-model", prompt="Hello", echo=True)
echo_prompts = serving_completion._prepare_echo_prompts(request)
assert echo_prompts == ["Hello"]
# Test with list of strings
request = CompletionRequest(
model="test-model", prompt=["Hello", "World"], echo=True
)
echo_prompts = serving_completion._prepare_echo_prompts(request)
assert echo_prompts == ["Hello", "World"]
# Test with token IDs
request = CompletionRequest(model="test-model", prompt=[1, 2, 3], echo=True)
serving_completion.tokenizer_manager.tokenizer.decode.return_value = "decoded"
echo_prompts = serving_completion._prepare_echo_prompts(request)
assert echo_prompts == ["decoded"]