llama_cpp/tools/server/tests/unit/test_vision_api.py

60 lines
2.2 KiB
Python

import pytest
from utils import *
import base64
import requests
server: ServerProcess
IMG_URL_0 = "https://huggingface.co/ggml-org/tinygemma3-GGUF/resolve/main/test/11_truck.png"
IMG_URL_1 = "https://huggingface.co/ggml-org/tinygemma3-GGUF/resolve/main/test/91_cat.png"
response = requests.get(IMG_URL_0)
response.raise_for_status() # Raise an exception for bad status codes
IMG_BASE64_0 = "data:image/png;base64," + base64.b64encode(response.content).decode("utf-8")
@pytest.fixture(autouse=True)
def create_server():
global server
server = ServerPreset.tinygemma3()
@pytest.mark.parametrize(
"prompt, image_url, success, re_content",
[
# test model is trained on CIFAR-10, but it's quite dumb due to small size
("What is this:\n", IMG_URL_0, True, "(cat)+"),
("What is this:\n", "IMG_BASE64_0", True, "(cat)+"), # exceptional, so that we don't cog up the log
("What is this:\n", IMG_URL_1, True, "(frog)+"),
("Test test\n", IMG_URL_1, True, "(frog)+"), # test invalidate cache
("What is this:\n", "malformed", False, None),
("What is this:\n", "https://google.com/404", False, None), # non-existent image
("What is this:\n", "https://ggml.ai", False, None), # non-image data
]
)
def test_vision_chat_completion(prompt, image_url, success, re_content):
global server
server.start(timeout_seconds=60) # vision model may take longer to load due to download size
if image_url == "IMG_BASE64_0":
image_url = IMG_BASE64_0
res = server.make_request("POST", "/chat/completions", data={
"temperature": 0.0,
"top_k": 1,
"messages": [
{"role": "user", "content": [
{"type": "text", "text": prompt},
{"type": "image_url", "image_url": {
"url": image_url,
}},
]},
],
})
if success:
assert res.status_code == 200
choice = res.body["choices"][0]
assert "assistant" == choice["message"]["role"]
assert match_regex(re_content, choice["message"]["content"])
else:
assert res.status_code != 200