Merge remote-tracking branch 'origin/diffusion-controlnet' into diffusion-sdxl
# Conflicts: # studio/backend/core/inference/diffusion.py
This commit is contained in:
Daniel Han
commit
74c3aa8a6d
8 changed files with 379 additions and 87 deletions
|
|
@ -211,9 +211,18 @@ def _is_trusted_diffusion_repo(repo_id: str) -> bool:
|
|||
non-GGUF paths are gated to the ``unsloth/*`` org (the curated safetensors models),
|
||||
a short allowlist of official safetensors-only base repos (``_TRUSTED_NON_GGUF_REPOS``,
|
||||
e.g. the SDXL base), and local paths the user explicitly pointed at (already on their
|
||||
disk). The GGUF path is unchanged and stays open to any repo, as before."""
|
||||
if Path(repo_id).expanduser().exists():
|
||||
return True
|
||||
disk). The GGUF path is unchanged and stays open to any repo, as before.
|
||||
|
||||
A bare ``owner/name`` HF id is never a real filesystem path, and an id with invalid
|
||||
characters makes ``Path.exists()`` raise OSError; treat any such failure as "not a
|
||||
local path" so the trust decision falls through to the org/allowlist checks (the
|
||||
loader's validate_load_request raises the clear FileNotFoundError for a genuinely
|
||||
missing local pick)."""
|
||||
try:
|
||||
if Path(repo_id).expanduser().exists():
|
||||
return True
|
||||
except OSError:
|
||||
pass
|
||||
rid = repo_id.strip().lower()
|
||||
return rid.startswith("unsloth/") or rid in _TRUSTED_NON_GGUF_REPOS
|
||||
|
||||
|
|
@ -1284,11 +1293,30 @@ class DiffusionBackend:
|
|||
if cn_model is None:
|
||||
if cancel.is_set():
|
||||
raise RuntimeError(DIFFUSION_CANCELLED_MSG)
|
||||
cn_model = (
|
||||
getattr(diffusers, model_cls_name)
|
||||
.from_pretrained(resolved_cn.path, torch_dtype = state.dtype, token = state.hf_token)
|
||||
.to(state.device)
|
||||
import torch
|
||||
|
||||
# state.dtype is the display string saved at load ("bfloat16"), NOT a
|
||||
# torch.dtype; pass the real dtype so diffusers loads the ControlNet at the
|
||||
# base compute dtype instead of silently defaulting to float32 (extra VRAM).
|
||||
cn_dtype = getattr(torch, str(state.dtype).replace("torch.", ""), None)
|
||||
cn_model = getattr(diffusers, model_cls_name).from_pretrained(
|
||||
resolved_cn.path,
|
||||
torch_dtype = cn_dtype,
|
||||
# An empty / malformed token means anonymous access; the HF client can
|
||||
# raise on a blank credential instead of falling back, so coerce to None.
|
||||
token = state.hf_token or None,
|
||||
)
|
||||
# Placement must follow the base model's offload policy. A resident base moves
|
||||
# the ControlNet resident too; an offloaded (low-VRAM) base streams it through
|
||||
# the device with group offloading instead of forcing the whole module onto the
|
||||
# GPU, which would defeat the offload and risk an OOM. Best-effort: any failure
|
||||
# falls back to the resident placement (the prior behaviour).
|
||||
if getattr(state, "offload_policy", OFFLOAD_NONE) != OFFLOAD_NONE and (
|
||||
_offload_controlnet_module(cn_model, state.device, logger)
|
||||
):
|
||||
pass
|
||||
else:
|
||||
cn_model = cn_model.to(state.device)
|
||||
if cancel.is_set():
|
||||
# An unload raced the blocking download above and already cleared the
|
||||
# ControlNet caches; caching now would pin the module past the unload.
|
||||
|
|
@ -1366,6 +1394,15 @@ class DiffusionBackend:
|
|||
)
|
||||
|
||||
resolved = diffusion_lora.resolve_specs(specs, hf_token = state.hf_token, cancel_event = cancel)
|
||||
# The shared catalog scans both .safetensors and .gguf, but diffusers'
|
||||
# load_lora_weights only takes safetensors; a .gguf adapter would otherwise fail
|
||||
# deep in generation. Reject it here as a clean 400 before touching the pipe.
|
||||
bad = [r.id for r in resolved if r.fmt != "safetensors"]
|
||||
if bad:
|
||||
raise ValueError(
|
||||
"GGUF LoRA adapters are not supported on the diffusers engine "
|
||||
f"({', '.join(bad)}); use a .safetensors adapter, or the native engine."
|
||||
)
|
||||
# Unique adapter names (diffusers requires distinct names; sanitized stems can collide).
|
||||
uniq: list[tuple[str, str, float]] = []
|
||||
seen: set[str] = set()
|
||||
|
|
@ -1473,8 +1510,24 @@ class DiffusionBackend:
|
|||
pipe = state.pipe
|
||||
init_pil = mask_pil = None
|
||||
control_pil = None
|
||||
cn_scale = cn_gstart = cn_gend = None
|
||||
cn_scale = cn_gstart = cn_gend = cn_mode = None
|
||||
ref_extra: list = []
|
||||
# Validate parameter dependencies up front: mask / upscale / reference all
|
||||
# need an input image, and reference conditioning needs a family that
|
||||
# supports it. Without these guards an unsupported combination would be
|
||||
# silently ignored and quietly fall back to txt2img / img2img.
|
||||
if init_image is None:
|
||||
if mask_image is not None:
|
||||
raise ValueError("mask_image requires an input image (init_image).")
|
||||
if upscale is not None and upscale > 1.0:
|
||||
raise ValueError("upscale requires an input image (init_image).")
|
||||
if reference_images:
|
||||
raise ValueError("reference_images require an input image (init_image).")
|
||||
if reference_images and not getattr(state.family, "reference", False):
|
||||
raise ValueError(
|
||||
f"Reference images are not supported for the '{state.family.name}' "
|
||||
"model family."
|
||||
)
|
||||
if getattr(state.family, "edit", False):
|
||||
# Instruction editing: the loaded pipe is the edit pipeline. It always
|
||||
# needs an input image; the prompt is the edit instruction. No mask, no
|
||||
|
|
@ -1543,41 +1596,55 @@ class DiffusionBackend:
|
|||
# and passes a control map. v1 conditions txt2img only (not img2img/inpaint/edit).
|
||||
if controlnet is not None:
|
||||
from core.inference import diffusion_controlnet
|
||||
|
||||
if workflow != "txt2img":
|
||||
raise ValueError(
|
||||
"ControlNet currently combines with plain text-to-image only, not the "
|
||||
f"{workflow} workflow."
|
||||
)
|
||||
if not diffusion_controlnet.supports_controlnet(
|
||||
engine = "diffusers",
|
||||
family = state.family.name,
|
||||
has_controlnet_pipeline = bool(
|
||||
getattr(state.family, "controlnet_pipeline_class", None)
|
||||
),
|
||||
model_kind = state.kind,
|
||||
transformer_quant = state.transformer_quant,
|
||||
):
|
||||
raise ValueError(
|
||||
"ControlNet is not supported for this model/quantisation on the "
|
||||
"diffusers engine (needs a bf16 or bnb-4bit load of a family with a "
|
||||
"ControlNet pipeline; not GGUF-via-diffusers or torchao fp8/int8)."
|
||||
)
|
||||
cn_id, cn_image_b64, cn_type, cn_strength, cn_gs, cn_ge = controlnet
|
||||
resolved_cn = diffusion_controlnet.resolve_controlnet(
|
||||
cn_id,
|
||||
family = state.family.name,
|
||||
hf_token = state.hf_token,
|
||||
cancel_event = cancel,
|
||||
)
|
||||
pipe = self._controlnet_pipe(state, resolved_cn, cancel)
|
||||
workflow = "controlnet"
|
||||
src = _decode_b64_image(cn_image_b64, mode = "RGB")
|
||||
# Control map at the OUTPUT size so it aligns with the generated latents.
|
||||
control_pil = diffusion_controlnet.preprocess_control(src, cn_type).resize(
|
||||
(width, height), Image.LANCZOS
|
||||
)
|
||||
cn_scale, cn_gstart, cn_gend = cn_strength, cn_gs, cn_ge
|
||||
# strength 0 disables ControlNet (documented on the request model, and the
|
||||
# frontend slider allows it): skip the whole path so a no-op selection never
|
||||
# pays the multi-GB ControlNet download / VRAM cost.
|
||||
if cn_strength in (None, 0, 0.0):
|
||||
controlnet = None
|
||||
else:
|
||||
if workflow != "txt2img":
|
||||
raise ValueError(
|
||||
"ControlNet currently combines with plain text-to-image only, not "
|
||||
f"the {workflow} workflow."
|
||||
)
|
||||
if not diffusion_controlnet.supports_controlnet(
|
||||
engine = "diffusers",
|
||||
family = state.family.name,
|
||||
has_controlnet_pipeline = bool(
|
||||
getattr(state.family, "controlnet_pipeline_class", None)
|
||||
),
|
||||
model_kind = state.kind,
|
||||
transformer_quant = state.transformer_quant,
|
||||
):
|
||||
raise ValueError(
|
||||
"ControlNet is not supported for this model/quantisation on the "
|
||||
"diffusers engine (needs a bf16 or bnb-4bit load of a family with a "
|
||||
"ControlNet pipeline; not GGUF-via-diffusers or torchao fp8/int8)."
|
||||
)
|
||||
# Decode + preprocess the control image FIRST so a malformed / unsupported
|
||||
# image fails as a clean 400 BEFORE any ControlNet download or pipe build,
|
||||
# rather than after paying that cost. Control map at the OUTPUT size so it
|
||||
# aligns with the generated latents.
|
||||
src = _decode_b64_image(cn_image_b64, mode = "RGB")
|
||||
control_pil = diffusion_controlnet.preprocess_control(src, cn_type).resize(
|
||||
(width, height), Image.LANCZOS
|
||||
)
|
||||
try:
|
||||
resolved_cn = diffusion_controlnet.resolve_controlnet(
|
||||
cn_id, family = state.family.name
|
||||
)
|
||||
except FileNotFoundError as exc:
|
||||
# An unknown / missing ControlNet id is a bad selection -> 400, not a
|
||||
# generic 500 (the route maps ValueError, not FileNotFoundError).
|
||||
raise ValueError(str(exc)) from exc
|
||||
pipe = self._controlnet_pipe(state, resolved_cn, cancel)
|
||||
workflow = "controlnet"
|
||||
cn_scale, cn_gstart, cn_gend = cn_strength, cn_gs, cn_ge
|
||||
# Flux Union ControlNet selects the active mode by an integer
|
||||
# ``control_mode`` (canny/depth/pose/...); map the chosen control type so
|
||||
# the union model applies the right head instead of a default/wrong one.
|
||||
cn_mode = diffusion_controlnet.union_control_mode(cn_id, cn_type)
|
||||
# Auto-resize odd-sized inputs to a multiple of 16 for the workflows whose
|
||||
# OUTPUT size is taken from the input image (img2img / inpaint / extend / edit),
|
||||
# so an upload like 186px tall no longer fails the pipeline's divisibility check.
|
||||
|
|
@ -1653,6 +1720,10 @@ class DiffusionBackend:
|
|||
kwargs["control_guidance_start"] = cn_gstart
|
||||
if "control_guidance_end" in call_params and cn_gend is not None:
|
||||
kwargs["control_guidance_end"] = cn_gend
|
||||
# Union ControlNet mode index (Flux); only when the pipe accepts it and the
|
||||
# selected control type maps to a known mode.
|
||||
if "control_mode" in call_params and cn_mode is not None:
|
||||
kwargs["control_mode"] = cn_mode
|
||||
|
||||
gen = _GenState(total_steps = steps)
|
||||
|
||||
|
|
@ -1757,13 +1828,13 @@ class DiffusionBackend:
|
|||
if state.eager_patched:
|
||||
uninstall_patches()
|
||||
uninstall_arch_patches()
|
||||
# Drop any LoRA adapters applied to the pipe so a later reference-path load is
|
||||
# bit-identical and the freed transformer carries no adapter layers. Idempotent.
|
||||
try:
|
||||
if getattr(state.pipe, "_unsloth_loras", ()):
|
||||
state.pipe.unload_lora_weights()
|
||||
except Exception: # noqa: BLE001 -- best-effort cleanup on teardown
|
||||
pass
|
||||
# NOTE: we deliberately do NOT call state.pipe.unload_lora_weights() here. unload()
|
||||
# sets the cancel event but does not take _generate_lock, so a LoRA-backed denoise
|
||||
# can still be running on this same pipe for up to one more callback; mutating its
|
||||
# adapter layers now would race that in-flight generation. The whole pipe is dropped
|
||||
# just below (self._state = None; del state; clear_gpu_cache()), so the adapter
|
||||
# tensors are freed with it -- no explicit unload is needed for memory or for a
|
||||
# later load (which builds a fresh pipe).
|
||||
# Drop the workflow pipes built around this load's modules so they don't pin the
|
||||
# freed pipeline (they only re-wire its components, but holding the wrappers
|
||||
# would keep the modules alive past unload).
|
||||
|
|
@ -1894,6 +1965,34 @@ def _hf_base_model(repo_id: str, hf_token: Optional[str]) -> Optional[str]:
|
|||
return base if isinstance(base, str) and base.strip() else None
|
||||
|
||||
|
||||
def _offload_controlnet_module(cn_model: Any, device: str, logger: Any) -> bool:
|
||||
"""Stream a ControlNet module through ``device`` via diffusers group offloading.
|
||||
|
||||
Used when the base model was loaded with an offload policy: forcing the ControlNet
|
||||
fully resident with ``.to(device)`` would defeat that low-VRAM placement and can OOM.
|
||||
Group offloading is applied to this single module (it does not touch the base pipe's
|
||||
existing hooks), so it is isolated and reversible. Returns True on success; on any
|
||||
failure the caller falls back to a resident placement, so this never blocks a load."""
|
||||
try:
|
||||
import torch
|
||||
from diffusers.hooks import apply_group_offloading
|
||||
|
||||
onload = torch.device(device)
|
||||
apply_group_offloading(
|
||||
cn_model,
|
||||
onload_device = onload,
|
||||
offload_device = torch.device("cpu"),
|
||||
offload_type = "block_level",
|
||||
num_blocks_per_group = 1,
|
||||
use_stream = onload.type == "cuda",
|
||||
)
|
||||
return True
|
||||
except Exception as exc: # noqa: BLE001 — offload is best-effort; resident is the fallback
|
||||
if logger is not None:
|
||||
logger.warning("diffusion.controlnet: group offload failed (%s); loading resident", exc)
|
||||
return False
|
||||
|
||||
|
||||
def _base_file_downloaded(rfilename: str) -> bool:
|
||||
"""True for base-repo files ``from_pretrained`` actually fetches.
|
||||
|
||||
|
|
|
|||
|
|
@ -19,7 +19,6 @@ backend read an arbitrary location.
|
|||
from __future__ import annotations
|
||||
|
||||
import re
|
||||
import threading
|
||||
from dataclasses import dataclass
|
||||
from pathlib import Path
|
||||
from typing import Any, Optional
|
||||
|
|
@ -138,21 +137,28 @@ def _catalog_by_id() -> dict[str, ControlNetCatalogEntry]:
|
|||
return {e.id: e for e in (list(_CURATED) + _scan_local())}
|
||||
|
||||
|
||||
def resolve_controlnet(
|
||||
spec_id: str,
|
||||
*,
|
||||
family: Optional[str] = None,
|
||||
hf_token: Optional[str] = None,
|
||||
cancel_event: Optional[threading.Event] = None,
|
||||
) -> ResolvedControlNet:
|
||||
def resolve_controlnet(spec_id: str, *, family: Optional[str] = None) -> ResolvedControlNet:
|
||||
"""Resolve a ControlNet id to a loadable repo id / local dir.
|
||||
|
||||
Accepts a catalog/local id, or a bare public HF repo id (``owner/name``). The backend
|
||||
loads the result with ``ControlNetModelClass.from_pretrained(path)`` (download + cache
|
||||
handled there, like the base pipeline). Raises on an unknown id -> the caller maps to 400.
|
||||
|
||||
``family`` (the loaded base family) enforces catalog compatibility: a ControlNet is
|
||||
architecture-specific, so a catalog entry tagged for another family is rejected here
|
||||
with a clear error rather than being loaded through the wrong pipeline class later.
|
||||
"""
|
||||
entry = _catalog_by_id().get(spec_id)
|
||||
if entry is not None:
|
||||
# A curated/local entry may declare the families it is built for. A client that
|
||||
# bypasses the UI filter (direct API call) could send an entry for another family;
|
||||
# reject it before any download so it never reaches the wrong ControlNet pipeline.
|
||||
fam = (family or "").strip().lower()
|
||||
if entry.families and fam and fam not in {f.lower() for f in entry.families}:
|
||||
raise ValueError(
|
||||
f"ControlNet '{spec_id}' is for {', '.join(entry.families)}, not the loaded "
|
||||
f"'{family}' model; pick a ControlNet built for this family."
|
||||
)
|
||||
if entry.source == "local":
|
||||
path = entry.local_path or ""
|
||||
if not path or not Path(path).is_dir():
|
||||
|
|
@ -174,6 +180,33 @@ def resolve_controlnet(
|
|||
)
|
||||
|
||||
|
||||
# Union ControlNet mode indices. A single "union" model covers several control modes and
|
||||
# selects the active one via an integer ``control_mode`` argument; these are the standard
|
||||
# indices used by the FLUX.1 / Qwen-Image union ControlNets. "passthrough" (an already-made
|
||||
# map) carries no intrinsic mode, so it maps to nothing (the caller omits control_mode).
|
||||
_UNION_CONTROL_MODES: dict[str, int] = {
|
||||
"canny": 0,
|
||||
"tile": 1,
|
||||
"depth": 2,
|
||||
"blur": 3,
|
||||
"pose": 4,
|
||||
"gray": 5,
|
||||
"lq": 6,
|
||||
}
|
||||
|
||||
|
||||
def union_control_mode(spec_id: str, control_type: str) -> Optional[int]:
|
||||
"""The integer ``control_mode`` for a union ControlNet, or None.
|
||||
|
||||
Returns a mode only for a curated *union* catalog entry AND a control type that maps to a
|
||||
known index; otherwise None so the caller omits the kwarg (a non-union ControlNet has a
|
||||
single fixed mode, and 'passthrough' does not name one). Pure lookup, no network."""
|
||||
entry = _catalog_by_id().get(spec_id)
|
||||
if entry is None or not entry.is_union:
|
||||
return None
|
||||
return _UNION_CONTROL_MODES.get((control_type or "").strip().lower())
|
||||
|
||||
|
||||
def preprocess_control(image: Any, control_type: str) -> Any:
|
||||
"""Turn a source image into a control map.
|
||||
|
||||
|
|
|
|||
|
|
@ -95,26 +95,31 @@ def sanitize_alias(raw: str) -> str:
|
|||
|
||||
|
||||
def _scan_local() -> list[LoraCatalogEntry]:
|
||||
entries: list[LoraCatalogEntry] = []
|
||||
root = loras_dir()
|
||||
try:
|
||||
children = sorted(root.iterdir())
|
||||
except OSError:
|
||||
return entries
|
||||
for p in children:
|
||||
if not p.is_file():
|
||||
continue
|
||||
return []
|
||||
files = [p for p in children if p.is_file() and p.suffix.lower() in _ALL_EXTS]
|
||||
# Two files that share a stem but differ in extension (foo.safetensors + foo.gguf)
|
||||
# would collide on id (== stem), so the frontend select value and resolve_one's
|
||||
# id->entry lookup could only ever address one of them. Disambiguate a colliding
|
||||
# stem by keeping the full filename as the id; a unique stem stays the clean stem.
|
||||
stem_counts: dict[str, int] = {}
|
||||
for p in files:
|
||||
stem_counts[p.stem] = stem_counts.get(p.stem, 0) + 1
|
||||
entries: list[LoraCatalogEntry] = []
|
||||
for p in files:
|
||||
ext = p.suffix.lower()
|
||||
if ext not in _ALL_EXTS:
|
||||
continue
|
||||
try:
|
||||
size = p.stat().st_size
|
||||
except OSError:
|
||||
size = 0
|
||||
entry_id = p.name if stem_counts.get(p.stem, 0) > 1 else p.stem
|
||||
entries.append(
|
||||
LoraCatalogEntry(
|
||||
id = p.stem,
|
||||
display_name = p.stem,
|
||||
id = entry_id,
|
||||
display_name = entry_id,
|
||||
source = "local",
|
||||
fmt = "gguf" if ext == ".gguf" else "safetensors",
|
||||
local_path = str(p),
|
||||
|
|
@ -157,6 +162,9 @@ def resolve_one(
|
|||
shared xet-fallback helper. Raises FileNotFoundError/ValueError on an unresolvable or
|
||||
unsupported id -- the caller maps that to a clear 400.
|
||||
"""
|
||||
# An empty / whitespace token sent verbatim to HfApi triggers an auth error instead
|
||||
# of falling back to anonymous access; normalise it to None.
|
||||
hf_token = hf_token.strip() if hf_token and hf_token.strip() else None
|
||||
entry = _catalog_by_id().get(spec_id)
|
||||
if entry is not None:
|
||||
if entry.source == "local":
|
||||
|
|
@ -176,6 +184,17 @@ def resolve_one(
|
|||
if "/" in spec_id:
|
||||
repo_id, _, weight_name = spec_id.partition(":")
|
||||
weight_name = weight_name or None
|
||||
if weight_name is not None:
|
||||
# A client-supplied weight file must stay a plain filename inside the repo:
|
||||
# reject traversal / absolute paths so it can never resolve outside the HF
|
||||
# cache dir once handed to the downloader.
|
||||
if (
|
||||
".." in weight_name
|
||||
or weight_name.startswith(("/", "\\", "~"))
|
||||
or "\\" in weight_name
|
||||
or os.path.isabs(weight_name)
|
||||
):
|
||||
raise ValueError(f"invalid LoRA weight file path '{weight_name}'")
|
||||
if weight_name is None:
|
||||
weight_name = _pick_repo_weight_file(repo_id, hf_token)
|
||||
ext = os.path.splitext(weight_name)[1].lower()
|
||||
|
|
@ -218,12 +237,19 @@ def resolve_specs(
|
|||
hf_token: Optional[str] = None,
|
||||
cancel_event: Optional[threading.Event] = None,
|
||||
) -> list[ResolvedLora]:
|
||||
"""Resolve request (id, weight) pairs, dropping zero-weight entries."""
|
||||
"""Resolve request (id, weight) pairs, dropping zero-weight entries.
|
||||
|
||||
A stale / unknown id raises FileNotFoundError inside resolve_one; convert it to
|
||||
ValueError so the route (which maps only ValueError to a 400) reports bad client
|
||||
input instead of a generic 500."""
|
||||
out: list[ResolvedLora] = []
|
||||
for spec_id, weight in specs:
|
||||
if weight == 0:
|
||||
continue
|
||||
out.append(resolve_one(spec_id, weight, hf_token = hf_token, cancel_event = cancel_event))
|
||||
try:
|
||||
for spec_id, weight in specs:
|
||||
if weight == 0:
|
||||
continue
|
||||
out.append(resolve_one(spec_id, weight, hf_token = hf_token, cancel_event = cancel_event))
|
||||
except FileNotFoundError as exc:
|
||||
raise ValueError(str(exc)) from exc
|
||||
return out
|
||||
|
||||
|
||||
|
|
@ -265,20 +291,27 @@ _TAG_RE = re.compile(r"<lora:([^:>]+):([^>]+)>")
|
|||
|
||||
|
||||
def inject_prompt_tags(prompt: str, resolved: list[ResolvedLora]) -> str:
|
||||
"""Append `<lora:ALIAS:WEIGHT>` tags to the prompt, skipping any the user already typed.
|
||||
"""Append `<lora:ALIAS:WEIGHT>` tags for the selected adapters, using the backend-
|
||||
validated weights.
|
||||
|
||||
sd-cli strips these tags before they reach the model, so appending them is safe and
|
||||
deterministic. Duplicate protection: if the prompt already contains a tag for the same
|
||||
alias, we don't add a second one.
|
||||
deterministic. A selected adapter's weight is validated (0-2) and recorded in the
|
||||
request/gallery, so the injected tag must WIN over any `<lora:ALIAS:...>` the user
|
||||
typed for that same alias: strip a user tag whose alias matches a selected adapter,
|
||||
then append the validated one. Tags for aliases the user typed that are NOT selected
|
||||
are left untouched (free-form use).
|
||||
"""
|
||||
existing = {m.group(1) for m in _TAG_RE.finditer(prompt)}
|
||||
tags = [
|
||||
f"<lora:{r.alias}:{_fmt_weight(r.weight)}>" for r in resolved if r.alias not in existing
|
||||
]
|
||||
selected = {r.alias for r in resolved}
|
||||
# Drop any user-typed tag whose alias is one of the selected adapters, so the typed
|
||||
# weight can't override the validated weight (or slip outside the 0-2 bounds).
|
||||
cleaned = _TAG_RE.sub(lambda m: "" if m.group(1) in selected else m.group(0), prompt)
|
||||
# Collapse whitespace left by stripped tags without disturbing the user's text.
|
||||
cleaned = re.sub(r"[ \t]{2,}", " ", cleaned).strip()
|
||||
tags = [f"<lora:{r.alias}:{_fmt_weight(r.weight)}>" for r in resolved]
|
||||
if not tags:
|
||||
return prompt
|
||||
sep = "" if not prompt or prompt.endswith(" ") else " "
|
||||
return f"{prompt}{sep}{' '.join(tags)}"
|
||||
return cleaned
|
||||
sep = "" if not cleaned or cleaned.endswith(" ") else " "
|
||||
return f"{cleaned}{sep}{' '.join(tags)}"
|
||||
|
||||
|
||||
def _fmt_weight(w: float) -> str:
|
||||
|
|
|
|||
|
|
@ -1856,6 +1856,14 @@ class ControlNetSpec(BaseModel):
|
|||
1.0, ge = 0.0, le = 1.0, description = "Fraction of steps at which ControlNet ends"
|
||||
)
|
||||
|
||||
@model_validator(mode = "after")
|
||||
def _check_guidance_range(self) -> "ControlNetSpec":
|
||||
# An inverted range (start > end) means "act over no steps"; reject it as a clean
|
||||
# 422 instead of letting the diffusers pipeline raise a 500 deep in the denoise.
|
||||
if self.guidance_start > self.guidance_end:
|
||||
raise ValueError("guidance_start must be <= guidance_end")
|
||||
return self
|
||||
|
||||
|
||||
class DiffusionGenerateRequest(BaseModel):
|
||||
"""Request to generate one image from the loaded diffusion model."""
|
||||
|
|
|
|||
|
|
@ -483,6 +483,38 @@ def test_generate_img2img_unsupported_family_raises(fake_runtime, tmp_path, monk
|
|||
backend.generate(prompt = "x", steps = 4, init_image = _tiny_png_b64())
|
||||
|
||||
|
||||
def test_generate_rejects_conditioning_without_init_image(fake_runtime, tmp_path):
|
||||
"""mask / upscale / reference all need an input image; without one they must raise a
|
||||
clear ValueError rather than silently degrading to txt2img."""
|
||||
(tmp_path / "model.gguf").write_bytes(b"x")
|
||||
backend = DiffusionBackend()
|
||||
backend.load_pipeline(
|
||||
str(tmp_path), gguf_filename = "model.gguf", base_repo = "base/repo", family_override = "z-image"
|
||||
)
|
||||
with pytest.raises(ValueError, match = "mask_image requires"):
|
||||
backend.generate(prompt = "x", steps = 4, mask_image = _mask_b64(64))
|
||||
with pytest.raises(ValueError, match = "upscale requires"):
|
||||
backend.generate(prompt = "x", steps = 4, upscale = 2.0)
|
||||
with pytest.raises(ValueError, match = "reference_images require"):
|
||||
backend.generate(prompt = "x", steps = 4, reference_images = [_tiny_png_b64()])
|
||||
|
||||
|
||||
def test_generate_rejects_reference_on_unsupported_family(fake_runtime, tmp_path):
|
||||
"""A non-reference family rejects reference_images instead of silently dropping them."""
|
||||
(tmp_path / "model.gguf").write_bytes(b"x")
|
||||
backend = DiffusionBackend()
|
||||
backend.load_pipeline(
|
||||
str(tmp_path), gguf_filename = "model.gguf", base_repo = "base/repo", family_override = "z-image"
|
||||
)
|
||||
with pytest.raises(ValueError, match = "Reference images are not supported"):
|
||||
backend.generate(
|
||||
prompt = "x",
|
||||
steps = 4,
|
||||
init_image = _tiny_png_b64(),
|
||||
reference_images = [_tiny_png_b64()],
|
||||
)
|
||||
|
||||
|
||||
def test_generate_upscale_enlarges_and_low_strength(fake_runtime, tmp_path):
|
||||
"""An init_image + upscale factor routes generate() through the family's img2img
|
||||
pipeline (hires fix): the source is enlarged to size*factor (rounded to /16) before the
|
||||
|
|
|
|||
|
|
@ -45,6 +45,26 @@ def test_resolve_controlnet_rejects_filesystem_like_ids():
|
|||
dc.resolve_controlnet(bad)
|
||||
|
||||
|
||||
def test_resolve_controlnet_enforces_family_match():
|
||||
# A curated entry tagged for another family must be rejected before download so it
|
||||
# never reaches the wrong ControlNet pipeline class.
|
||||
with pytest.raises(ValueError, match = "not the"):
|
||||
dc.resolve_controlnet("qwen-union", family = "flux.1")
|
||||
# The matching family resolves fine, and no family (unfiltered) is permissive.
|
||||
assert dc.resolve_controlnet("qwen-union", family = "qwen-image").path
|
||||
assert dc.resolve_controlnet("qwen-union").path
|
||||
|
||||
|
||||
def test_union_control_mode_maps_only_union_entries():
|
||||
# Union entries map a known control type to its integer mode; passthrough / unknown
|
||||
# types and non-union ids return None so the caller omits control_mode.
|
||||
assert dc.union_control_mode("flux-union-pro", "canny") == 0
|
||||
assert dc.union_control_mode("flux-union-pro", "depth") == 2
|
||||
assert dc.union_control_mode("flux-union-pro", "pose") == 4
|
||||
assert dc.union_control_mode("flux-union-pro", "passthrough") is None
|
||||
assert dc.union_control_mode("some/bare-repo", "canny") is None
|
||||
|
||||
|
||||
def test_resolve_controlnet_local(tmp_path, monkeypatch):
|
||||
d = tmp_path / "controlnets"
|
||||
d.mkdir()
|
||||
|
|
|
|||
|
|
@ -37,10 +37,19 @@ def test_inject_prompt_tags_appends_with_spacing():
|
|||
assert dl.inject_prompt_tags("x", [r1]) == "x <lora:s:1>"
|
||||
|
||||
|
||||
def test_inject_prompt_tags_dedupes_user_typed_tag():
|
||||
def test_inject_prompt_tags_validated_weight_overrides_user_typed():
|
||||
r = dl.ResolvedLora("id", "style", "/p", "safetensors", 0.8)
|
||||
# user already wrote a tag for the same alias -> not duplicated
|
||||
assert dl.inject_prompt_tags("a cat <lora:style:1>", [r]) == "a cat <lora:style:1>"
|
||||
# A user-typed tag for a SELECTED adapter is replaced by the backend-validated weight
|
||||
# (so the recorded/validated 0-2 weight wins over whatever was typed), not duplicated.
|
||||
assert dl.inject_prompt_tags("a cat <lora:style:1>", [r]) == "a cat <lora:style:0.8>"
|
||||
|
||||
|
||||
def test_inject_prompt_tags_keeps_unselected_user_tags():
|
||||
r = dl.ResolvedLora("id", "style", "/p", "safetensors", 0.8)
|
||||
# A user tag for an alias that is NOT one of the selected adapters is left untouched.
|
||||
out = dl.inject_prompt_tags("a cat <lora:other:0.5>", [r])
|
||||
assert "<lora:other:0.5>" in out
|
||||
assert "<lora:style:0.8>" in out
|
||||
|
||||
|
||||
def test_inject_prompt_tags_empty_returns_prompt():
|
||||
|
|
@ -129,6 +138,41 @@ def test_resolve_specs_drops_zero_weight(tmp_path, monkeypatch):
|
|||
assert len(out) == 1 and out[0].weight == 1.0
|
||||
|
||||
|
||||
def test_resolve_specs_maps_unknown_id_to_valueerror(tmp_path, monkeypatch):
|
||||
# An unknown / stale id raises FileNotFoundError in resolve_one; resolve_specs must
|
||||
# surface it as ValueError so the route returns 400, not a generic 500.
|
||||
d = tmp_path / "loras"
|
||||
d.mkdir()
|
||||
monkeypatch.setattr(dl, "loras_dir", lambda: d)
|
||||
with pytest.raises(ValueError):
|
||||
dl.resolve_specs([("nope", 1.0)])
|
||||
|
||||
|
||||
def test_scan_local_disambiguates_identical_stems(tmp_path, monkeypatch):
|
||||
# foo.safetensors and foo.gguf must get distinct ids so each is addressable; a
|
||||
# unique stem keeps its clean stem id.
|
||||
d = tmp_path / "loras"
|
||||
d.mkdir()
|
||||
(d / "foo.safetensors").write_bytes(b"x")
|
||||
(d / "foo.gguf").write_bytes(b"y")
|
||||
(d / "solo.safetensors").write_bytes(b"z")
|
||||
monkeypatch.setattr(dl, "loras_dir", lambda: d)
|
||||
by_id = {e.id: e for e in dl.list_loras()}
|
||||
assert "foo.safetensors" in by_id and "foo.gguf" in by_id
|
||||
assert by_id["foo.safetensors"].fmt == "safetensors"
|
||||
assert by_id["foo.gguf"].fmt == "gguf"
|
||||
assert "solo" in by_id # unique stem is untouched
|
||||
|
||||
|
||||
def test_resolve_one_rejects_traversal_weight_name(tmp_path, monkeypatch):
|
||||
# A client-supplied weight file with traversal / absolute path is rejected before it
|
||||
# can reach the downloader (it must stay a plain filename inside the repo).
|
||||
monkeypatch.setattr(dl, "loras_dir", lambda: tmp_path)
|
||||
for bad in ("owner/name:../secret.safetensors", "owner/name:/etc/x.safetensors"):
|
||||
with pytest.raises(ValueError):
|
||||
dl.resolve_one(bad, 1.0)
|
||||
|
||||
|
||||
# ── Request-model validation ────────────────────────────────────────────────
|
||||
|
||||
|
||||
|
|
@ -264,3 +308,21 @@ def test_diffusers_apply_rejects_unsupported_quant():
|
|||
[("styleA", 1.0)],
|
||||
threading.Event(),
|
||||
)
|
||||
|
||||
|
||||
def test_diffusers_apply_rejects_gguf_adapter(monkeypatch):
|
||||
# A .gguf adapter (discoverable in the shared catalog) cannot load on the diffusers
|
||||
# engine; it must be rejected as a clean 400 before touching the pipe.
|
||||
import threading
|
||||
|
||||
monkeypatch.setattr(
|
||||
dl,
|
||||
"resolve_specs",
|
||||
lambda specs, **_: [
|
||||
dl.ResolvedLora(i, dl.sanitize_alias(i), f"/{i}.gguf", "gguf", w) for i, w in specs
|
||||
],
|
||||
)
|
||||
pipe = _FakePipe()
|
||||
with pytest.raises(ValueError, match = "GGUF LoRA"):
|
||||
_backend()._apply_loras(_fake_state(pipe), [("styleA", 1.0)], threading.Event())
|
||||
assert pipe.loaded == [] # never touched the pipe
|
||||
|
|
|
|||
|
|
@ -1002,7 +1002,12 @@ export function ImagesPage({ active = true }: { active?: boolean }) {
|
|||
setLoras((prev) => prev.filter((s) => ids.has(s.id)));
|
||||
})
|
||||
.catch(() => {
|
||||
if (!cancelled) setAvailableLoras([]);
|
||||
if (cancelled) return;
|
||||
// Clear the SELECTED adapters too, not just the options: leaving a stale `loras`
|
||||
// selection in state (with the picker now hidden/empty) would still be posted by
|
||||
// handleGenerate and could apply adapters from the previous model, or fail.
|
||||
setAvailableLoras([]);
|
||||
setLoras([]);
|
||||
});
|
||||
return () => {
|
||||
cancelled = true;
|
||||
|
|
@ -2031,7 +2036,7 @@ export function ImagesPage({ active = true }: { active?: boolean }) {
|
|||
<div className="space-y-2">
|
||||
{loras.map((sel, i) => (
|
||||
<div
|
||||
key={i}
|
||||
key={sel.id || i}
|
||||
className="space-y-1.5 rounded-lg border border-border bg-muted/30 p-2"
|
||||
>
|
||||
<div className="flex items-center gap-2">
|
||||
|
|
@ -2111,7 +2116,7 @@ export function ImagesPage({ active = true }: { active?: boolean }) {
|
|||
hint="Condition the image on a control map (edges / depth / pose). Union models cover many types. Use 'Canny' to trace edges from your image, or 'Passthrough' if it is already a control map."
|
||||
>
|
||||
<div className="space-y-2 rounded-lg border border-border bg-muted/30 p-2">
|
||||
<Select value={controlnetId} onValueChange={setControlnetId}>
|
||||
<Select value={controlnetId || undefined} onValueChange={setControlnetId}>
|
||||
<SelectTrigger className="h-8 w-full text-xs">
|
||||
<SelectValue placeholder="Select a ControlNet" />
|
||||
</SelectTrigger>
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue