[FEATURE] Add OpenAI-Compatible LoRA Adapter Selection (#11570)
This commit is contained in:
Neelabh Sinha
278
test/srt/openai_server/features/test_lora_openai_compatible.py
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278
test/srt/openai_server/features/test_lora_openai_compatible.py
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"""
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End-to-end tests for OpenAI-compatible LoRA adapter usage.
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Tests the model:adapter syntax and backward compatibility with explicit lora_path.
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Usage:
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python3 -m unittest openai_server.features.test_lora_openai_compatible.TestLoRAOpenAICompatible.test_model_adapter_syntax
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python3 -m unittest openai_server.features.test_lora_openai_compatible.TestLoRAOpenAICompatible.test_explicit_lora_path
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python3 -m unittest openai_server.features.test_lora_openai_compatible.TestLoRAOpenAICompatible.test_priority_model_over_explicit
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python3 -m unittest openai_server.features.test_lora_openai_compatible.TestLoRAOpenAICompatible.test_base_model_no_adapter
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python3 -m unittest openai_server.features.test_lora_openai_compatible.TestLoRAOpenAICompatible.test_completions_api_with_adapter
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python3 -m unittest openai_server.features.test_lora_openai_compatible.TestLoRAOpenAICompatible.test_streaming_with_adapter
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python3 -m unittest openai_server.features.test_lora_openai_compatible.TestLoRADisabledError.test_lora_disabled_error
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"""
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import unittest
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import openai
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from sglang.srt.utils import kill_process_tree
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from sglang.test.test_utils import (
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DEFAULT_SMALL_MODEL_NAME_FOR_TEST,
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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DEFAULT_URL_FOR_TEST,
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CustomTestCase,
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popen_launch_server,
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)
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def get_real_lora_adapter() -> str:
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"""Use a real LoRA adapter from Hugging Face."""
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return "codelion/Llama-3.2-1B-Instruct-tool-calling-lora"
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def setup_class(cls, enable_lora=True):
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"""Setup test class with LoRA-enabled server."""
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cls.model = DEFAULT_SMALL_MODEL_NAME_FOR_TEST
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cls.base_url = DEFAULT_URL_FOR_TEST
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# Use real LoRA adapter
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cls.lora_adapter_path = get_real_lora_adapter()
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other_args = [
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"--max-running-requests",
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"10",
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"--disable-radix-cache", # Disable cache for cleaner tests
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]
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if enable_lora:
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other_args.extend(
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[
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"--enable-lora",
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"--lora-paths",
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f"tool_calling={cls.lora_adapter_path}",
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]
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)
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cls.process = popen_launch_server(
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cls.model,
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cls.base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=other_args,
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)
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cls.client = openai.Client(api_key="EMPTY", base_url=f"{cls.base_url}/v1")
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class TestLoRAOpenAICompatible(CustomTestCase):
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"""Test OpenAI-compatible LoRA adapter usage."""
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@classmethod
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def setUpClass(cls):
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setup_class(cls, enable_lora=True)
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@classmethod
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def tearDownClass(cls):
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kill_process_tree(cls.process.pid)
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def test_model_adapter_syntax(self):
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"""Test the new model:adapter syntax works correctly."""
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response = self.client.chat.completions.create(
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# ← New OpenAI-compatible syntax
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model=f"{self.model}:tool_calling",
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messages=[{"role": "user", "content": "What tools do you have available?"}],
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max_tokens=50,
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temperature=0,
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)
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self.assertIsNotNone(response.choices[0].message.content)
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self.assertGreater(len(response.choices[0].message.content), 0)
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print(f"Model adapter syntax response: {response.choices[0].message.content}")
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def test_explicit_lora_path(self):
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"""Test backward compatibility with explicit lora_path via extra_body."""
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response = self.client.chat.completions.create(
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model=self.model,
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messages=[{"role": "user", "content": "What tools do you have available?"}],
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# ← Legacy explicit method
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extra_body={"lora_path": "tool_calling"},
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max_tokens=50,
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temperature=0,
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)
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self.assertIsNotNone(response.choices[0].message.content)
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self.assertGreater(len(response.choices[0].message.content), 0)
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print(f"Explicit lora_path response: {response.choices[0].message.content}")
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def test_priority_model_over_explicit(self):
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"""Test that model:adapter syntax takes precedence over explicit lora_path."""
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# This test verifies the priority logic in _resolve_lora_path
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response = self.client.chat.completions.create(
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# ← Model specifies tool_calling adapter
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model=f"{self.model}:tool_calling",
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messages=[{"role": "user", "content": "What tools do you have available?"}],
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# ← Both specify same adapter
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extra_body={"lora_path": "tool_calling"},
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max_tokens=50,
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temperature=0,
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)
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# Should use tool_calling adapter (model parameter takes precedence)
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self.assertIsNotNone(response.choices[0].message.content)
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self.assertGreater(len(response.choices[0].message.content), 0)
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print(f"Priority test response: {response.choices[0].message.content}")
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def test_base_model_no_adapter(self):
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"""Test using base model without any adapter."""
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response = self.client.chat.completions.create(
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model=self.model, # ← No adapter specified
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messages=[{"role": "user", "content": "Hello, how are you?"}],
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max_tokens=30,
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temperature=0,
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)
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self.assertIsNotNone(response.choices[0].message.content)
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self.assertGreater(len(response.choices[0].message.content), 0)
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print(f"Base model response: {response.choices[0].message.content}")
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def test_completions_api_with_adapter(self):
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"""Test completions API with LoRA adapter."""
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response = self.client.completions.create(
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model=f"{self.model}:tool_calling", # ← Using model:adapter syntax
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prompt="What tools do you have available?",
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max_tokens=50,
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temperature=0,
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)
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self.assertIsNotNone(response.choices[0].text)
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self.assertGreater(len(response.choices[0].text), 0)
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print(f"Completions API response: {response.choices[0].text}")
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def test_streaming_with_adapter(self):
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"""Test streaming with LoRA adapter."""
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stream = self.client.chat.completions.create(
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model=f"{self.model}:tool_calling",
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messages=[{"role": "user", "content": "What tools do you have available?"}],
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max_tokens=50,
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temperature=0,
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stream=True,
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)
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collected_content = ""
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for chunk in stream:
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if chunk.choices[0].delta.content:
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collected_content += chunk.choices[0].delta.content
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self.assertGreater(len(collected_content), 0)
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print(f"Streaming response: {collected_content}")
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def test_multiple_adapters(self):
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"""Test using different adapters in sequence."""
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# Test tool_calling adapter
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tool_response = self.client.chat.completions.create(
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model=f"{self.model}:tool_calling",
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messages=[{"role": "user", "content": "What tools do you have available?"}],
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max_tokens=30,
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temperature=0,
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)
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# Test base model without adapter
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base_response = self.client.chat.completions.create(
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model=self.model,
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messages=[{"role": "user", "content": "Hello, how are you?"}],
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max_tokens=30,
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temperature=0,
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)
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self.assertIsNotNone(tool_response.choices[0].message.content)
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self.assertIsNotNone(base_response.choices[0].message.content)
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print(
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f"Tool calling adapter response: {tool_response.choices[0].message.content}"
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)
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print(f"Base model response: {base_response.choices[0].message.content}")
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class TestLoRADisabledError(CustomTestCase):
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"""Test error handling when LoRA is disabled."""
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@classmethod
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def setUpClass(cls):
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setup_class(cls, enable_lora=False) # ← LoRA disabled
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@classmethod
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def tearDownClass(cls):
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kill_process_tree(cls.process.pid)
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def test_lora_disabled_error(self):
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"""Test that using LoRA adapter when LoRA is disabled raises appropriate error."""
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with self.assertRaises(openai.APIError) as context:
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self.client.chat.completions.create(
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model=f"{self.model}:tool_calling", # ← Trying to use adapter
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messages=[
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{"role": "user", "content": "What tools do you have available?"}
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],
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max_tokens=50,
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)
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# Verify the error message contains helpful guidance
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error_message = str(context.exception)
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self.assertIn("LoRA", error_message)
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self.assertIn("not enabled", error_message)
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print(f"Expected error message: {error_message}")
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class TestLoRAEdgeCases(CustomTestCase):
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"""Test edge cases for LoRA adapter usage."""
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@classmethod
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def setUpClass(cls):
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setup_class(cls, enable_lora=True)
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@classmethod
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def tearDownClass(cls):
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kill_process_tree(cls.process.pid)
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def test_model_with_colon_no_adapter(self):
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"""Test model parameter ending with colon (empty adapter)."""
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response = self.client.chat.completions.create(
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model=f"{self.model}:", # ← Model ends with colon
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messages=[{"role": "user", "content": "Hello!"}],
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max_tokens=30,
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temperature=0,
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)
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# Should work as base model (no adapter)
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self.assertIsNotNone(response.choices[0].message.content)
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print(f"Model with colon response: {response.choices[0].message.content}")
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def test_explicit_lora_path_none(self):
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"""Test explicit lora_path set to None."""
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response = self.client.chat.completions.create(
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model=self.model,
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messages=[{"role": "user", "content": "Hello!"}],
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extra_body={"lora_path": None}, # ← Explicitly None
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max_tokens=30,
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temperature=0,
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)
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# Should work as base model
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self.assertIsNotNone(response.choices[0].message.content)
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print(
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f"Explicit None lora_path response: {response.choices[0].message.content}"
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)
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def test_invalid_adapter_name(self):
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"""Test using non-existent adapter name."""
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with self.assertRaises(openai.APIError) as context:
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self.client.chat.completions.create(
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model=f"{self.model}:nonexistent", # ← Non-existent adapter
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messages=[{"role": "user", "content": "Hello!"}],
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max_tokens=30,
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)
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error_message = str(context.exception)
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print(f"Invalid adapter error: {error_message}")
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if __name__ == "__main__":
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unittest.main()
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