369 lines
13 KiB
Python
369 lines
13 KiB
Python
# Copyright 2023-2024 SGLang Team
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Tests for OpenAI API protocol models"""
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import json
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import time
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import unittest
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from typing import Dict, List, Optional
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from pydantic import BaseModel, Field, ValidationError
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from sglang.srt.entrypoints.openai.protocol import (
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BatchRequest,
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BatchResponse,
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ChatCompletionMessageContentImagePart,
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ChatCompletionMessageContentTextPart,
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ChatCompletionRequest,
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ChatCompletionResponse,
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ChatCompletionResponseChoice,
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ChatCompletionResponseStreamChoice,
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ChatCompletionStreamResponse,
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ChatCompletionTokenLogprob,
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ChatMessage,
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ChoiceLogprobs,
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CompletionRequest,
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CompletionResponse,
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CompletionResponseChoice,
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DeltaMessage,
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EmbeddingObject,
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EmbeddingRequest,
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EmbeddingResponse,
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ErrorResponse,
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FileDeleteResponse,
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FileRequest,
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FileResponse,
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Function,
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FunctionResponse,
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JsonSchemaResponseFormat,
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LogProbs,
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ModelCard,
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ModelList,
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MultimodalEmbeddingInput,
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ResponseFormat,
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ScoringRequest,
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ScoringResponse,
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StreamOptions,
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StructuralTagResponseFormat,
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Tool,
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ToolCall,
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ToolChoice,
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TopLogprob,
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UsageInfo,
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)
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class TestModelCard(unittest.TestCase):
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"""Test ModelCard protocol model"""
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def test_model_card_serialization(self):
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"""Test model card JSON serialization"""
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card = ModelCard(id="test-model", max_model_len=4096)
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data = card.model_dump()
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self.assertEqual(data["id"], "test-model")
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self.assertEqual(data["object"], "model")
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self.assertEqual(data["max_model_len"], 4096)
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class TestModelList(unittest.TestCase):
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"""Test ModelList protocol model"""
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def test_empty_model_list(self):
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"""Test empty model list creation"""
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model_list = ModelList()
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self.assertEqual(model_list.object, "list")
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self.assertEqual(len(model_list.data), 0)
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def test_model_list_with_cards(self):
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"""Test model list with model cards"""
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cards = [
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ModelCard(id="model-1"),
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ModelCard(id="model-2", max_model_len=2048),
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]
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model_list = ModelList(data=cards)
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self.assertEqual(len(model_list.data), 2)
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self.assertEqual(model_list.data[0].id, "model-1")
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self.assertEqual(model_list.data[1].id, "model-2")
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class TestCompletionRequest(unittest.TestCase):
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"""Test CompletionRequest protocol model"""
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def test_basic_completion_request(self):
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"""Test basic completion request"""
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request = CompletionRequest(model="test-model", prompt="Hello world")
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self.assertEqual(request.model, "test-model")
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self.assertEqual(request.prompt, "Hello world")
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self.assertEqual(request.max_tokens, 16) # default
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self.assertEqual(request.temperature, 1.0) # default
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self.assertEqual(request.n, 1) # default
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self.assertFalse(request.stream) # default
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self.assertFalse(request.echo) # default
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def test_completion_request_sglang_extensions(self):
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"""Test completion request with SGLang-specific extensions"""
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request = CompletionRequest(
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model="test-model",
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prompt="Hello",
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top_k=50,
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min_p=0.1,
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repetition_penalty=1.1,
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regex=r"\d+",
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json_schema='{"type": "object"}',
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lora_path="/path/to/lora",
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)
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self.assertEqual(request.top_k, 50)
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self.assertEqual(request.min_p, 0.1)
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self.assertEqual(request.repetition_penalty, 1.1)
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self.assertEqual(request.regex, r"\d+")
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self.assertEqual(request.json_schema, '{"type": "object"}')
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self.assertEqual(request.lora_path, "/path/to/lora")
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def test_completion_request_validation_errors(self):
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"""Test completion request validation errors"""
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with self.assertRaises(ValidationError):
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CompletionRequest() # missing required fields
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with self.assertRaises(ValidationError):
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CompletionRequest(model="test-model") # missing prompt
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class TestChatCompletionRequest(unittest.TestCase):
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"""Test ChatCompletionRequest protocol model"""
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def test_basic_chat_completion_request(self):
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"""Test basic chat completion request"""
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messages = [{"role": "user", "content": "Hello"}]
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request = ChatCompletionRequest(model="test-model", messages=messages)
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self.assertEqual(request.model, "test-model")
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self.assertEqual(len(request.messages), 1)
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self.assertEqual(request.messages[0].role, "user")
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self.assertEqual(request.messages[0].content, "Hello")
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self.assertEqual(request.temperature, 0.7) # default
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self.assertFalse(request.stream) # default
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self.assertEqual(request.tool_choice, "none") # default when no tools
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def test_chat_completion_tool_choice_validation(self):
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"""Test tool choice validation logic"""
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messages = [{"role": "user", "content": "Hello"}]
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# No tools, tool_choice should default to "none"
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request1 = ChatCompletionRequest(model="test-model", messages=messages)
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self.assertEqual(request1.tool_choice, "none")
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# With tools, tool_choice should default to "auto"
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tools = [
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{
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"type": "function",
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"function": {"name": "test_func", "description": "Test function"},
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}
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]
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request2 = ChatCompletionRequest(
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model="test-model", messages=messages, tools=tools
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)
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self.assertEqual(request2.tool_choice, "auto")
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def test_chat_completion_sglang_extensions(self):
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"""Test chat completion with SGLang extensions"""
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messages = [{"role": "user", "content": "Hello"}]
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request = ChatCompletionRequest(
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model="test-model",
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messages=messages,
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top_k=40,
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min_p=0.05,
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separate_reasoning=False,
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stream_reasoning=False,
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chat_template_kwargs={"custom_param": "value"},
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)
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self.assertEqual(request.top_k, 40)
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self.assertEqual(request.min_p, 0.05)
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self.assertFalse(request.separate_reasoning)
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self.assertFalse(request.stream_reasoning)
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self.assertEqual(request.chat_template_kwargs, {"custom_param": "value"})
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def test_chat_completion_reasoning_effort(self):
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"""Test chat completion with reasoning effort"""
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messages = [{"role": "user", "content": "Hello"}]
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request = ChatCompletionRequest(
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model="test-model",
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messages=messages,
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reasoning={
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"enabled": True,
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"reasoning_effort": "high",
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},
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)
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self.assertEqual(request.reasoning_effort, "high")
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self.assertEqual(request.chat_template_kwargs, {"thinking": True})
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def test_chat_completion_json_format(self):
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"""Test chat completion json format"""
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transcript = "Good morning! It's 7:00 AM, and I'm just waking up. Today is going to be a busy day, "
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"so let's get started. First, I need to make a quick breakfast. I think I'll have some "
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"scrambled eggs and toast with a cup of coffee. While I'm cooking, I'll also check my "
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"emails to see if there's anything urgent."
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messages = [
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{
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"role": "system",
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"content": "The following is a voice message transcript. Only answer in JSON.",
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},
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{
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"role": "user",
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"content": transcript,
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},
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]
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class VoiceNote(BaseModel):
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title: str = Field(description="A title for the voice note")
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summary: str = Field(
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description="A short one sentence summary of the voice note."
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)
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strict: Optional[bool] = True
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actionItems: List[str] = Field(
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description="A list of action items from the voice note"
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)
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request = ChatCompletionRequest(
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model="test-model",
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messages=messages,
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top_k=40,
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min_p=0.05,
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separate_reasoning=False,
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stream_reasoning=False,
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chat_template_kwargs={"custom_param": "value"},
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response_format={
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"type": "json_schema",
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"schema": VoiceNote.model_json_schema(),
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},
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)
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res_format = request.response_format
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json_format = res_format.json_schema
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name = json_format.name
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schema = json_format.schema_
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strict = json_format.strict
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self.assertEqual(name, "VoiceNote")
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self.assertEqual(strict, True)
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self.assertNotIn("strict", schema["properties"])
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request = ChatCompletionRequest(
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model="test-model",
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messages=messages,
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top_k=40,
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min_p=0.05,
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separate_reasoning=False,
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stream_reasoning=False,
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chat_template_kwargs={"custom_param": "value"},
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response_format={
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"type": "json_schema",
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"json_schema": {
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"name": "VoiceNote",
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"schema": VoiceNote.model_json_schema(),
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"strict": True,
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},
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},
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)
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res_format = request.response_format
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json_format = res_format.json_schema
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name = json_format.name
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schema = json_format.schema_
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strict = json_format.strict
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self.assertEqual(name, "VoiceNote")
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self.assertEqual(strict, True)
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class TestModelSerialization(unittest.TestCase):
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"""Test model serialization with hidden states"""
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def test_hidden_states_excluded_when_none(self):
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"""Test that None hidden_states are excluded with exclude_none=True"""
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choice = ChatCompletionResponseChoice(
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index=0,
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message=ChatMessage(role="assistant", content="Hello"),
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finish_reason="stop",
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hidden_states=None,
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)
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response = ChatCompletionResponse(
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id="test-id",
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model="test-model",
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choices=[choice],
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usage=UsageInfo(prompt_tokens=5, completion_tokens=1, total_tokens=6),
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)
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# Test exclude_none serialization (should exclude None hidden_states)
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data = response.model_dump(exclude_none=True)
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self.assertNotIn("hidden_states", data["choices"][0])
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def test_hidden_states_included_when_not_none(self):
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"""Test that non-None hidden_states are included"""
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choice = ChatCompletionResponseChoice(
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index=0,
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message=ChatMessage(role="assistant", content="Hello"),
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finish_reason="stop",
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hidden_states=[0.1, 0.2, 0.3],
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)
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response = ChatCompletionResponse(
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id="test-id",
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model="test-model",
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choices=[choice],
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usage=UsageInfo(prompt_tokens=5, completion_tokens=1, total_tokens=6),
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)
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# Test exclude_none serialization (should include non-None hidden_states)
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data = response.model_dump(exclude_none=True)
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self.assertIn("hidden_states", data["choices"][0])
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self.assertEqual(data["choices"][0]["hidden_states"], [0.1, 0.2, 0.3])
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class TestValidationEdgeCases(unittest.TestCase):
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"""Test edge cases and validation scenarios"""
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def test_invalid_tool_choice_type(self):
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"""Test invalid tool choice type"""
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messages = [{"role": "user", "content": "Hello"}]
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with self.assertRaises(ValidationError):
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ChatCompletionRequest(
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model="test-model", messages=messages, tool_choice=123
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)
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def test_negative_token_limits(self):
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"""Test negative token limits"""
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with self.assertRaises(ValidationError):
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CompletionRequest(model="test-model", prompt="Hello", max_tokens=-1)
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def test_model_serialization_roundtrip(self):
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"""Test that models can be serialized and deserialized"""
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original_request = ChatCompletionRequest(
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model="test-model",
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messages=[{"role": "user", "content": "Hello"}],
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temperature=0.7,
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max_tokens=100,
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)
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# Serialize to dict
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data = original_request.model_dump()
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# Deserialize back
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restored_request = ChatCompletionRequest(**data)
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self.assertEqual(restored_request.model, original_request.model)
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self.assertEqual(restored_request.temperature, original_request.temperature)
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self.assertEqual(restored_request.max_tokens, original_request.max_tokens)
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self.assertEqual(len(restored_request.messages), len(original_request.messages))
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if __name__ == "__main__":
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unittest.main(verbosity=2)
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