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