88 lines
2.7 KiB
Python
88 lines
2.7 KiB
Python
import unittest
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import openai
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from sglang.srt.hf_transformers_utils import get_tokenizer
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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_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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class TestOpenAIServer(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = "intfloat/e5-mistral-7b-instruct"
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cls.base_url = DEFAULT_URL_FOR_TEST
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cls.api_key = "sk-123456"
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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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api_key=cls.api_key,
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)
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cls.base_url += "/v1"
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cls.tokenizer = get_tokenizer(cls.model)
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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 run_embedding(self, use_list_input, token_input):
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client = openai.Client(api_key=self.api_key, base_url=self.base_url)
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prompt = "The capital of France is"
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if token_input:
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prompt_input = self.tokenizer.encode(prompt)
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num_prompt_tokens = len(prompt_input)
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else:
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prompt_input = prompt
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num_prompt_tokens = len(self.tokenizer.encode(prompt))
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if use_list_input:
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prompt_arg = [prompt_input] * 2
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num_prompts = len(prompt_arg)
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num_prompt_tokens *= num_prompts
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else:
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prompt_arg = prompt_input
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num_prompts = 1
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response = client.embeddings.create(
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input=prompt_arg,
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model=self.model,
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)
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assert len(response.data) == num_prompts
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assert isinstance(response.data, list)
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assert response.data[0].embedding
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assert response.data[0].index is not None
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assert response.data[0].object == "embedding"
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assert response.model == self.model
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assert response.object == "list"
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assert (
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response.usage.prompt_tokens == num_prompt_tokens
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), f"{response.usage.prompt_tokens} vs {num_prompt_tokens}"
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assert (
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response.usage.total_tokens == num_prompt_tokens
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), f"{response.usage.total_tokens} vs {num_prompt_tokens}"
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def run_batch(self):
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# FIXME: not implemented
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pass
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def test_embedding(self):
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# TODO: the fields of encoding_format, dimensions, user are skipped
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# TODO: support use_list_input
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for use_list_input in [False, True]:
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for token_input in [False, True]:
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self.run_embedding(use_list_input, token_input)
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def test_batch(self):
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self.run_batch()
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if __name__ == "__main__":
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unittest.main()
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