vllm/tests/entrypoints/llm/test_chat.py
2025-03-02 17:34:51 -08:00

93 lines
2.0 KiB
Python

# SPDX-License-Identifier: Apache-2.0
import pytest
from vllm import LLM
from ..openai.test_vision import TEST_IMAGE_URLS
def test_chat():
llm = LLM(model="meta-llama/Llama-3.2-1B-Instruct")
prompt1 = "Explain the concept of entropy."
messages = [
{
"role": "system",
"content": "You are a helpful assistant"
},
{
"role": "user",
"content": prompt1
},
]
outputs = llm.chat(messages)
assert len(outputs) == 1
def test_multi_chat():
llm = LLM(model="meta-llama/Llama-3.2-1B-Instruct")
prompt1 = "Explain the concept of entropy."
prompt2 = "Explain what among us is."
conversation1 = [
{
"role": "system",
"content": "You are a helpful assistant"
},
{
"role": "user",
"content": prompt1
},
]
conversation2 = [
{
"role": "system",
"content": "You are a helpful assistant"
},
{
"role": "user",
"content": prompt2
},
]
messages = [conversation1, conversation2]
outputs = llm.chat(messages)
assert len(outputs) == 2
@pytest.mark.parametrize("image_urls",
[[TEST_IMAGE_URLS[0], TEST_IMAGE_URLS[1]]])
def test_chat_multi_image(image_urls: list[str]):
llm = LLM(
model="microsoft/Phi-3.5-vision-instruct",
dtype="bfloat16",
max_model_len=4096,
max_num_seqs=5,
enforce_eager=True,
trust_remote_code=True,
limit_mm_per_prompt={"image": 2},
)
messages = [{
"role":
"user",
"content": [
*({
"type": "image_url",
"image_url": {
"url": image_url
}
} for image_url in image_urls),
{
"type": "text",
"text": "What's in this image?"
},
],
}]
outputs = llm.chat(messages)
assert len(outputs) >= 0