787010a637
V1 is enabled by default, no need to set it by hand now. This PR remove
the useless setting in example and tests
- vLLM version: v0.9.2
- vLLM main:
9ad0a4588b
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
61 lines
3.2 KiB
Python
61 lines
3.2 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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import vllm
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from modelscope import snapshot_download # type: ignore
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from vllm.lora.request import LoRARequest
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from tests.e2e.conftest import VllmRunner
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MODEL_PATH = "vllm-ascend/ilama-3.2-1B"
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PROMPT_TEMPLATE = """I want you to act as a SQL terminal in front of an example database, you need only to return the sql command to me.Below is an instruction that describes a task, Write a response that appropriately completes the request.\n"\n##Instruction:\nconcert_singer contains tables such as stadium, singer, concert, singer_in_concert. Table stadium has columns such as Stadium_ID, Location, Name, Capacity, Highest, Lowest, Average. Stadium_ID is the primary key.\nTable singer has columns such as Singer_ID, Name, Country, Song_Name, Song_release_year, Age, Is_male. Singer_ID is the primary key.\nTable concert has columns such as concert_ID, concert_Name, Theme, Stadium_ID, Year. concert_ID is the primary key.\nTable singer_in_concert has columns such as concert_ID, Singer_ID. concert_ID is the primary key.\nThe Stadium_ID of concert is the foreign key of Stadium_ID of stadium.\nThe Singer_ID of singer_in_concert is the foreign key of Singer_ID of singer.\nThe concert_ID of singer_in_concert is the foreign key of concert_ID of concert.\n\n###Input:\n{query}\n\n###Response:""" # noqa: E501
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EXPECTED_LORA_OUTPUT = [
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"SELECT count(*) FROM singer",
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"SELECT avg(age) , min(age) , max(age) FROM singer WHERE country = 'France'", # noqa: E501
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"SELECT DISTINCT Country FROM singer WHERE Age > 20",
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]
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def do_sample(llm: vllm.LLM, lora_path: str, lora_id: int) -> list[str]:
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prompts = [
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PROMPT_TEMPLATE.format(query="How many singers do we have?"),
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PROMPT_TEMPLATE.format(
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query=
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"What is the average, minimum, and maximum age of all singers from France?" # noqa: E501
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),
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PROMPT_TEMPLATE.format(
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query=
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"What are all distinct countries where singers above age 20 are from?" # noqa: E501
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),
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]
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sampling_params = vllm.SamplingParams(temperature=0, max_tokens=32)
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outputs = llm.generate(
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prompts,
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sampling_params,
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lora_request=LoRARequest(str(lora_id), lora_id, lora_path)
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if lora_id else None)
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# Print the outputs.
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generated_texts: list[str] = []
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for output in outputs:
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prompt = output.prompt
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generated_text = output.outputs[0].text.strip()
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generated_texts.append(generated_text)
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print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
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return generated_texts
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def test_ilama_lora(ilama_lora_files):
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with VllmRunner(snapshot_download(MODEL_PATH),
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enable_lora=True,
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max_loras=4,
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max_model_len=1024,
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max_num_seqs=16) as vllm_model:
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output1 = do_sample(vllm_model.model, ilama_lora_files, lora_id=1)
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for i in range(len(EXPECTED_LORA_OUTPUT)):
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assert output1[i] == EXPECTED_LORA_OUTPUT[i]
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output2 = do_sample(vllm_model.model, ilama_lora_files, lora_id=2)
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for i in range(len(EXPECTED_LORA_OUTPUT)):
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assert output2[i] == EXPECTED_LORA_OUTPUT[i]
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