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-rw-r--r--pyproject.toml2
-rw-r--r--script/smoke_matrix.py304
-rw-r--r--src/mcp_sd15/pipeline_factory.py21
-rw-r--r--tests/test_pipeline_factory.py4
-rw-r--r--uv.lock130
5 files changed, 361 insertions, 100 deletions
diff --git a/pyproject.toml b/pyproject.toml
index ce5350f..bb5b190 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -20,7 +20,7 @@ dependencies = [
"safetensors>=0.4",
"torch==2.14.0+cu132",
"torchvision==0.29.0+cu132",
- "transformers>=4.45",
+ "transformers>=4.45,<5",
]
[project.scripts]
diff --git a/script/smoke_matrix.py b/script/smoke_matrix.py
new file mode 100644
index 0000000..7fc3ec2
--- /dev/null
+++ b/script/smoke_matrix.py
@@ -0,0 +1,304 @@
+"""Run generate_image across all checkpoint/VAE/LoRA/scheduler combinations.
+
+For each pattern, this script writes a temporary TOML config, starts the
+``mcp-sd15`` server with ``streamable-http`` transport, calls ``generate_image``
+through the HTTP endpoint, saves the PNG, and records the result.
+
+Usage::
+
+ uv run python script/smoke_matrix.py --output-dir data/outputs/matrix
+"""
+
+from __future__ import annotations
+
+import argparse
+import asyncio
+import base64
+import json
+import subprocess
+import sys
+import time
+from pathlib import Path
+
+from mcp import Client
+from mcp.types import ImageContent
+
+DEFAULT_PROMPT = "a small red cube on a white table, studio photograph, detailed"
+DEFAULT_NEGATIVE = "blurry, low quality"
+
+PATTERNS: list[dict[str, object]] = [
+ {
+ "name": "01_v15_base",
+ "checkpoint": "v1-5-pruned-emaonly.safetensors",
+ "vae": None,
+ "loras": [],
+ "scheduler": "dpmpp_2m_karras",
+ "steps": 20,
+ "cfg_scale": 7.0,
+ "prompt": DEFAULT_PROMPT,
+ "negative": DEFAULT_NEGATIVE,
+ },
+ {
+ "name": "02_animekawa_base",
+ "checkpoint": "animekawa_v10.safetensors",
+ "vae": None,
+ "loras": [],
+ "scheduler": "dpmpp_2m_karras",
+ "steps": 20,
+ "cfg_scale": 7.0,
+ "prompt": DEFAULT_PROMPT,
+ "negative": DEFAULT_NEGATIVE,
+ },
+ {
+ "name": "03_amore_base",
+ "checkpoint": "animeModel_amore.safetensors",
+ "vae": None,
+ "loras": [],
+ "scheduler": "dpmpp_2m_karras",
+ "steps": 20,
+ "cfg_scale": 7.0,
+ "prompt": DEFAULT_PROMPT,
+ "negative": DEFAULT_NEGATIVE,
+ },
+ {
+ "name": "04_animepastel_base",
+ "checkpoint": "animePastelDream_softBakedVae_full_fp16.safetensors",
+ "vae": None,
+ "loras": [],
+ "scheduler": "dpmpp_2m_karras",
+ "steps": 20,
+ "cfg_scale": 7.0,
+ "prompt": DEFAULT_PROMPT,
+ "negative": DEFAULT_NEGATIVE,
+ },
+ {
+ "name": "05_v15_external_vae",
+ "checkpoint": "v1-5-pruned-emaonly.safetensors",
+ "vae": "vaeKlF8Anime2_klF8Anime2VAE.safetensors",
+ "loras": [],
+ "scheduler": "dpmpp_2m_karras",
+ "steps": 20,
+ "cfg_scale": 7.0,
+ "prompt": DEFAULT_PROMPT,
+ "negative": DEFAULT_NEGATIVE,
+ },
+ {
+ "name": "06_v15_lora_pixel_sprites",
+ "checkpoint": "v1-5-pruned-emaonly.safetensors",
+ "vae": None,
+ "loras": [{"file": "pixel sprites.safetensors", "weight": 0.8}],
+ "scheduler": "dpmpp_2m_karras",
+ "steps": 20,
+ "cfg_scale": 7.0,
+ "prompt": "pixel art, a small red cube on a white table, detailed",
+ "negative": DEFAULT_NEGATIVE,
+ },
+ {
+ "name": "07_v15_lora_pixelartV3",
+ "checkpoint": "v1-5-pruned-emaonly.safetensors",
+ "vae": None,
+ "loras": [{"file": "pixelartV3.safetensors", "weight": 0.8}],
+ "scheduler": "dpmpp_2m_karras",
+ "steps": 20,
+ "cfg_scale": 7.0,
+ "prompt": "pixelart, a small red cube on a white table, detailed",
+ "negative": DEFAULT_NEGATIVE,
+ },
+ {
+ "name": "08_v15_lora_pixel_f2",
+ "checkpoint": "v1-5-pruned-emaonly.safetensors",
+ "vae": None,
+ "loras": [{"file": "pixel_f2.safetensors", "weight": 0.8}],
+ "scheduler": "dpmpp_2m_karras",
+ "steps": 20,
+ "cfg_scale": 7.0,
+ "prompt": "pixel, a small red cube on a white table, detailed",
+ "negative": DEFAULT_NEGATIVE,
+ },
+ {
+ "name": "09_v15_lcm_lora",
+ "checkpoint": "v1-5-pruned-emaonly.safetensors",
+ "vae": None,
+ "loras": [{"file": "LCM_LoRA_Weights_SD15.safetensors", "weight": 1.0}],
+ "scheduler": "lcm",
+ "steps": 4,
+ "cfg_scale": 1.0,
+ "prompt": DEFAULT_PROMPT,
+ "negative": DEFAULT_NEGATIVE,
+ },
+ {
+ "name": "10_animekawa_vae_lora",
+ "checkpoint": "animekawa_v10.safetensors",
+ "vae": "vaeKlF8Anime2_klF8Anime2VAE.safetensors",
+ "loras": [{"file": "pixelartV3.safetensors", "weight": 0.7}],
+ "scheduler": "euler_a",
+ "steps": 20,
+ "cfg_scale": 7.0,
+ "prompt": "pixelart, a small red cube on a white table, detailed",
+ "negative": DEFAULT_NEGATIVE,
+ },
+]
+
+
+def make_toml(pattern: dict[str, object], port: int) -> str:
+ lines: list[str] = []
+ lines.append("[model]")
+ lines.append('root = "."')
+ lines.append(f'checkpoint = "{pattern["checkpoint"]}"')
+ if pattern["vae"]:
+ lines.append(f'vae = "{pattern["vae"]}"')
+ for lora in pattern["loras"]: # type: ignore[union-attr]
+ lines.append("[[model.lora]]")
+ lines.append(f'file = "{lora["file"]}"') # type: ignore[index]
+ lines.append(f"weight = {lora['weight']}") # type: ignore[index]
+ lines.append("[generation]")
+ lines.append(f"steps = {pattern['steps']}")
+ lines.append(f"cfg_scale = {pattern['cfg_scale']}")
+ lines.append(f'scheduler = "{pattern["scheduler"]}"')
+ lines.append('default_size = "square_512"')
+ lines.append("[output]")
+ lines.append("enabled = false")
+ lines.append("[server]")
+ lines.append('transport = "streamable-http"')
+ lines.append('host = "127.0.0.1"')
+ lines.append(f"port = {port}")
+ return "\n".join(lines) + "\n"
+
+
+async def run_one(
+ pattern: dict[str, object],
+ config_path: Path,
+ output_path: Path,
+ port: int,
+) -> dict[str, object]:
+ toml = make_toml(pattern, port)
+ config_path.write_text(toml, encoding="utf-8")
+
+ proc = subprocess.Popen(
+ [sys.executable, "-m", "mcp_sd15", "--config", str(config_path)],
+ stdout=subprocess.PIPE,
+ stderr=subprocess.STDOUT,
+ text=True,
+ bufsize=1,
+ )
+
+ result: dict[str, object] = {"name": pattern["name"], "status": "unknown"}
+ started = time.monotonic()
+
+ try:
+ # Wait for server to be ready (up to 120s for model loading)
+ url = f"http://127.0.0.1:{port}/mcp"
+ for _wait in range(120):
+ if proc.poll() is not None:
+ # Process died; drain stdout
+ dead_output = ""
+ if proc.stdout:
+ dead_output = proc.stdout.read()
+ result["status"] = "server_died"
+ result["output"] = dead_output[-3000:]
+ return result
+ try:
+ import httpx
+
+ resp = httpx.get(url, timeout=2.0)
+ if resp.status_code == 400:
+ break
+ except Exception:
+ pass
+ await asyncio.sleep(1)
+ else:
+ result["status"] = "server_timeout"
+ return result
+
+ async with Client(url, raise_exceptions=True) as client:
+ tools = (await client.list_tools()).tools
+ tool_names = {tool.name for tool in tools}
+ if tool_names != {"generate_image", "generate_guided_image", "inpaint_image"}:
+ result["status"] = "wrong_tools"
+ result["tools"] = list(tool_names)
+ return result
+
+ call_result = await client.call_tool(
+ "generate_image",
+ {
+ "positive_prompt": pattern["prompt"], # type: ignore[index]
+ "negative_prompt": pattern["negative"], # type: ignore[index]
+ "size": "square_512",
+ },
+ )
+
+ if call_result.is_error or len(call_result.content) != 1:
+ result["status"] = "tool_error"
+ result["detail"] = str(call_result)
+ return result
+
+ content = call_result.content[0]
+ if not isinstance(content, ImageContent) or content.mime_type != "image/png":
+ result["status"] = "wrong_content"
+ result["detail"] = str(content)
+ return result
+
+ output_path.parent.mkdir(parents=True, exist_ok=True)
+ output_path.write_bytes(base64.b64decode(content.data, validate=True))
+ elapsed = round(time.monotonic() - started, 1)
+ result["status"] = "ok"
+ result["elapsed"] = elapsed
+ result["output_file"] = str(output_path)
+ return result
+ except Exception as exc:
+ result["status"] = "exception"
+ result["detail"] = str(exc)
+ return result
+ finally:
+ proc.terminate()
+ try:
+ proc.wait(timeout=10)
+ except subprocess.TimeoutExpired:
+ proc.kill()
+
+
+async def main(args: argparse.Namespace) -> None:
+ config_path = args.data_dir / "config.matrix.toml"
+ results: list[dict[str, object]] = []
+
+ for i, pattern in enumerate(PATTERNS):
+ name = pattern["name"]
+ print(f"[{i + 1}/{len(PATTERNS)}] {name} ...", flush=True)
+ output_path = args.output_dir / f"{name}.png"
+ result = await run_one(pattern, config_path, output_path, args.port + i)
+ status = result["status"]
+ if status == "ok":
+ print(
+ f" -> OK elapsed={result.get('elapsed')}s file={result.get('output_file')}",
+ flush=True,
+ )
+ else:
+ print(f" -> FAIL status={status} detail={result.get('detail', '')}", flush=True)
+ results.append(result)
+
+ config_path.unlink(missing_ok=True)
+
+ summary_path = args.output_dir / "matrix_results.json"
+ summary_path.parent.mkdir(parents=True, exist_ok=True)
+ summary_path.write_text(json.dumps(results, indent=2, ensure_ascii=False), encoding="utf-8")
+
+ ok = sum(1 for r in results if r["status"] == "ok")
+ fail = len(results) - ok
+ print(f"\n=== Summary: {ok} ok / {fail} fail / {len(results)} total ===", flush=True)
+ if fail:
+ print("Failures:", flush=True)
+ for r in results:
+ if r["status"] != "ok":
+ print(f" {r['name']}: {r['status']} {r.get('detail', '')}", flush=True)
+
+
+def parse_args() -> argparse.Namespace:
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--output-dir", type=Path, default=Path("data/outputs/matrix"))
+ parser.add_argument("--data-dir", type=Path, default=Path("data"))
+ parser.add_argument("--port", type=int, default=8130)
+ return parser.parse_args()
+
+
+if __name__ == "__main__":
+ asyncio.run(main(parse_args()))
diff --git a/src/mcp_sd15/pipeline_factory.py b/src/mcp_sd15/pipeline_factory.py
index b0525ea..02fe882 100644
--- a/src/mcp_sd15/pipeline_factory.py
+++ b/src/mcp_sd15/pipeline_factory.py
@@ -38,11 +38,16 @@ class PipelineFactory:
)
vae_path = self.config.model.vae_path()
if vae_path is not None:
+ # from_single_file needs a Diffusers config directory to avoid
+ # network access. Reuse the VAE config that the base pipeline
+ # already resolved from the local huggingface cache.
+ vae_config_dir = self._vae_config_dir(cache_dir)
pipeline.vae = diffusers.AutoencoderKL.from_single_file(
str(vae_path),
torch_dtype=torch.float16,
local_files_only=True,
cache_dir=cache_dir,
+ config=vae_config_dir,
)
if getattr(pipeline, "vae", None) is None:
raise ConfigError(
@@ -156,3 +161,19 @@ class PipelineFactory:
except KeyError as exc:
raise ConfigError(f"unsupported scheduler: {name}") from exc
return scheduler_class.from_config(current.config)
+
+ @staticmethod
+ def _vae_config_dir(cache_dir: str) -> str:
+ """Find the VAE config.json inside the local huggingface cache."""
+ snapshots = (
+ Path(cache_dir) / "models--stable-diffusion-v1-5--stable-diffusion-v1-5" / "snapshots"
+ )
+ if not snapshots.is_dir():
+ raise ConfigError(
+ "cannot locate VAE config: huggingface cache snapshots directory not found"
+ )
+ for snapshot in snapshots.iterdir():
+ vae_dir = snapshot / "vae"
+ if (vae_dir / "config.json").is_file():
+ return str(vae_dir)
+ raise ConfigError("cannot locate VAE config.json in the local huggingface cache")
diff --git a/tests/test_pipeline_factory.py b/tests/test_pipeline_factory.py
index 408133b..14b771b 100644
--- a/tests/test_pipeline_factory.py
+++ b/tests/test_pipeline_factory.py
@@ -91,11 +91,15 @@ def test_base_pipeline_requires_vae_and_applies_all_loras(app_config, monkeypatc
external_vae = object()
runtime = (SimpleNamespace(float16="float16"), fake_diffusers(pipeline, external_vae))
monkeypatch.setattr(factory, "_runtime", lambda: runtime)
+ monkeypatch.setattr(
+ PipelineFactory, "_vae_config_dir", staticmethod(lambda cache_dir: "fake_vae_config")
+ )
result = factory.create_base()
assert result is pipeline
assert pipeline.vae is external_vae
+ assert pipeline.vae_load["config"] == "fake_vae_config" # type: ignore[attr-defined]
assert pipeline.adapters == (["configured_lora_0", "configured_lora_1"], [0.8, 0.5])
assert [item["weight_name"] for item in pipeline.lora_loads] == [
"detail.safetensors",
diff --git a/uv.lock b/uv.lock
index c41195a..c84563a 100644
--- a/uv.lock
+++ b/uv.lock
@@ -21,15 +21,6 @@ wheels = [
]
[[package]]
-name = "annotated-doc"
-version = "0.0.5"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/5a/8e/38aa427ed5402449e226975b649c5dc73ccadfefeb95e6aecb8f8ea4b6b6/annotated_doc-0.0.5.tar.gz", hash = "sha256:c7e58ce09192557605d8bbd92836d7e1d520ac9580096042c0bfd197efacf1bb", size = 10758, upload-time = "2026-07-28T13:50:58.129Z" }
-wheels = [
- { url = "https://files.pythonhosted.org/packages/3e/30/e900b21425a860e195f32e37657aa1f7c7f2b1bfb26f03ca209b90933c06/annotated_doc-0.0.5-py3-none-any.whl", hash = "sha256:117bac03a25ede5df5440e855b32d556049ca169ead221505badf432fed4b101", size = 5302, upload-time = "2026-07-28T13:50:57.239Z" },
-]
-
-[[package]]
name = "annotated-types"
version = "0.8.0"
source = { registry = "https://pypi.org/simple" }
@@ -289,7 +280,7 @@ nvtx = [
[[package]]
name = "diffusers"
-version = "0.40.0"
+version = "0.39.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "filelock" },
@@ -302,9 +293,9 @@ dependencies = [
{ name = "requests" },
{ name = "safetensors" },
]
-sdist = { url = "https://files.pythonhosted.org/packages/59/32/b9c6a198812e2a7d2c2828a850dba384306f9af285eac23e35e89d5b008a/diffusers-0.40.0.tar.gz", hash = "sha256:49f112ce52ff6d332ab68afec01f79a53e6489b42cb69104444c98b4a2f64af8", size = 4886420, upload-time = "2026-08-20T14:30:40.923Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/1a/81/6095237b86a3116c4789f28c4435d5296c00c0fc74ffde99008fd6b3a36c/diffusers-0.39.0.tar.gz", hash = "sha256:14bb1d98c85a0e463d734c99aaa73b480a7bc9bad22af30fbf730ef8f09c1d67", size = 4651240, upload-time = "2026-07-03T08:48:47.904Z" }
wheels = [
- { url = "https://files.pythonhosted.org/packages/db/df/ffb593ebed2a068d2d6be44261283f39a6b809c0fcdfdcafbd448cbeec77/diffusers-0.40.0-py3-none-any.whl", hash = "sha256:5b5da7c3ddb62152fa4afc577f02e050af688c797375c34fb2d01006da3f3541", size = 5911654, upload-time = "2026-08-20T14:30:38.422Z" },
+ { url = "https://files.pythonhosted.org/packages/3f/3f/7469c46e9d22307ea686bab687d70e6bf328722952f9d10339f5e913e608/diffusers-0.39.0-py3-none-any.whl", hash = "sha256:912aca51b5787365110806e984d5555735bf8a461073bb8459029d0bca7870ef", size = 5631176, upload-time = "2026-07-03T08:48:45.337Z" },
]
[[package]]
@@ -418,22 +409,21 @@ wheels = [
[[package]]
name = "huggingface-hub"
-version = "1.31.0"
+version = "0.36.2"
source = { registry = "https://pypi.org/simple" }
dependencies = [
- { name = "click" },
{ name = "filelock" },
{ name = "fsspec" },
- { name = "hf-xet", marker = "platform_machine == 'AMD64' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'arm64' or platform_machine == 'x86_64'" },
- { name = "httpx" },
+ { name = "hf-xet", marker = "platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'arm64' or platform_machine == 'x86_64'" },
{ name = "packaging" },
{ name = "pyyaml" },
+ { name = "requests" },
{ name = "tqdm" },
{ name = "typing-extensions" },
]
-sdist = { url = "https://files.pythonhosted.org/packages/9b/f0/61159db90b5cd275d55516fe27920828e7d3be4053fdbdb27c3f70e5f1ef/huggingface_hub-1.31.0.tar.gz", hash = "sha256:f8e9e710a210613fa5d0f26bba6da05ef4aef9fba5a0f23f508f5ac4d08b6f90", size = 968039, upload-time = "2026-09-10T10:27:22.724Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/7c/b7/8cb61d2eece5fb05a83271da168186721c450eb74e3c31f7ef3169fa475b/huggingface_hub-0.36.2.tar.gz", hash = "sha256:1934304d2fb224f8afa3b87007d58501acfda9215b334eed53072dd5e815ff7a", size = 649782, upload-time = "2026-02-06T09:24:13.098Z" }
wheels = [
- { url = "https://files.pythonhosted.org/packages/c3/7f/3f886a625043b77312b80da2f2bf00b5ecbf5a73061af1aa0259cd258c9d/huggingface_hub-1.31.0-py3-none-any.whl", hash = "sha256:9dbb6a503cbe2494ea666695207e7262d410659e09134059deb83e5480864667", size = 798313, upload-time = "2026-09-10T10:27:20.798Z" },
+ { url = "https://files.pythonhosted.org/packages/a8/af/48ac8483240de756d2438c380746e7130d1c6f75802ef22f3c6d49982787/huggingface_hub-0.36.2-py3-none-any.whl", hash = "sha256:48f0c8eac16145dfce371e9d2d7772854a4f591bcb56c9cf548accf531d54270", size = 566395, upload-time = "2026-02-06T09:24:11.133Z" },
]
[[package]]
@@ -531,18 +521,6 @@ wheels = [
]
[[package]]
-name = "markdown-it-py"
-version = "4.2.0"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
- { name = "mdurl" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/06/ff/7841249c247aa650a76b9ee4bbaeae59370dc8bfd2f6c01f3630c35eb134/markdown_it_py-4.2.0.tar.gz", hash = "sha256:04a21681d6fbb623de53f6f364d352309d4094dd4194040a10fd51833e418d49", size = 82454, upload-time = "2026-05-07T12:08:28.36Z" }
-wheels = [
- { url = "https://files.pythonhosted.org/packages/b3/81/4da04ced5a082363ecfa159c010d200ecbd959ae410c10c0264a38cac0f5/markdown_it_py-4.2.0-py3-none-any.whl", hash = "sha256:9f7ebbcd14fe59494226453aed97c1070d83f8d24b6fc3a3bcf9a38092641c4a", size = 91687, upload-time = "2026-05-07T12:08:27.182Z" },
-]
-
-[[package]]
name = "markupsafe"
version = "3.0.3"
source = { registry = "https://pypi.org/simple" }
@@ -626,7 +604,7 @@ requires-dist = [
{ name = "safetensors", specifier = ">=0.4" },
{ name = "torch", specifier = "==2.14.0+cu132", index = "https://download.pytorch.org/whl/cu132" },
{ name = "torchvision", specifier = "==0.29.0+cu132", index = "https://download.pytorch.org/whl/cu132" },
- { name = "transformers", specifier = ">=4.45" },
+ { name = "transformers", specifier = ">=4.45,<5" },
]
[package.metadata.requires-dev]
@@ -651,15 +629,6 @@ wheels = [
]
[[package]]
-name = "mdurl"
-version = "0.1.2"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/d6/54/cfe61301667036ec958cb99bd3efefba235e65cdeb9c84d24a8293ba1d90/mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba", size = 8729, upload-time = "2022-08-14T12:40:10.846Z" }
-wheels = [
- { url = "https://files.pythonhosted.org/packages/b3/38/89ba8ad64ae25be8de66a6d463314cf1eb366222074cfda9ee839c56a4b4/mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8", size = 9979, upload-time = "2022-08-14T12:40:09.779Z" },
-]
-
-[[package]]
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