feat: add SDXL Turbo image generator wrapper

This commit is contained in:
Mortdecai
2026-04-10 01:24:50 -04:00
parent 6725231775
commit 5e12527e23
2 changed files with 109 additions and 0 deletions
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"""SDXL Turbo wrapper for horror image generation."""
import io
import torch
try:
from diffusers import AutoPipelineForText2Image
except ImportError: # pragma: no cover - exercised only in test environments
AutoPipelineForText2Image = None # Tests patch this attribute directly.
from server.config import config
from server.prompts import NEGATIVE_PROMPT
class AssetGenerator:
"""Generates horror images via SDXL Turbo."""
def __init__(self, device: str | None = None, model_id: str | None = None):
self.device = device or config.device
self.model_id = model_id or config.models.sdxl_model_id
if AutoPipelineForText2Image is None:
raise RuntimeError(
"diffusers is not installed; install diffusers to use AssetGenerator"
)
use_fp16 = self.device == "cuda"
self._pipe = AutoPipelineForText2Image.from_pretrained(
self.model_id,
torch_dtype=torch.float16 if use_fp16 else torch.float32,
variant="fp16" if use_fp16 else None,
)
if self.device == "cuda":
self._pipe = self._pipe.to("cuda")
def generate(self, prompt: str, seed: int | None = None) -> bytes:
"""Generate a 512x512 PNG image from a horror prompt. Returns PNG bytes."""
if seed is None:
seed = torch.randint(0, 2**32, (1,)).item()
generator = torch.Generator(device=self.device).manual_seed(seed)
result = self._pipe(
prompt=prompt,
negative_prompt=NEGATIVE_PROMPT,
num_inference_steps=config.models.sdxl_steps,
guidance_scale=config.models.sdxl_guidance_scale,
width=config.models.sdxl_width,
height=config.models.sdxl_height,
generator=generator,
)
image = result.images[0]
buf = io.BytesIO()
image.save(buf, format="PNG")
return buf.getvalue()
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from unittest.mock import MagicMock, patch
from PIL import Image
from server.asset_generator import AssetGenerator
class TestAssetGenerator:
@patch("server.asset_generator.AutoPipelineForText2Image")
def test_init_loads_model(self, mock_pipeline_cls):
"""Generator loads the SDXL Turbo pipeline on init."""
mock_pipe = MagicMock()
mock_pipeline_cls.from_pretrained.return_value = mock_pipe
mock_pipe.to.return_value = mock_pipe
gen = AssetGenerator(device="cpu")
mock_pipeline_cls.from_pretrained.assert_called_once()
@patch("server.asset_generator.AutoPipelineForText2Image")
def test_generate_returns_bytes(self, mock_pipeline_cls):
"""Generate returns PNG bytes."""
mock_pipe = MagicMock()
mock_pipeline_cls.from_pretrained.return_value = mock_pipe
mock_pipe.to.return_value = mock_pipe
# Mock pipeline output
fake_image = Image.new("RGB", (512, 512), color="black")
mock_result = MagicMock()
mock_result.images = [fake_image]
mock_pipe.return_value = mock_result
gen = AssetGenerator(device="cpu")
data = gen.generate("dark void, horror")
assert isinstance(data, bytes)
assert len(data) > 0
@patch("server.asset_generator.AutoPipelineForText2Image")
def test_generate_uses_negative_prompt(self, mock_pipeline_cls):
"""Generate passes the negative prompt to the pipeline."""
mock_pipe = MagicMock()
mock_pipeline_cls.from_pretrained.return_value = mock_pipe
mock_pipe.to.return_value = mock_pipe
fake_image = Image.new("RGB", (512, 512), color="black")
mock_result = MagicMock()
mock_result.images = [fake_image]
mock_pipe.return_value = mock_result
gen = AssetGenerator(device="cpu")
gen.generate("test prompt")
call_kwargs = mock_pipe.call_args
assert "negative_prompt" in call_kwargs.kwargs