Merge c8b3d54cf8 into 7f287b705e

Signed-off-by: bigcat88 <bigcat88@icloud.com>

.coderabbit.yaml

@@ -4,12 +4,12 @@ early_access: false
 tone_instructions: "Only comment on issues introduced by this PR's changes. Do not flag pre-existing problems in moved, re-indented, or reformatted code."
 
 reviews:
-  profile: "chill"
-  request_changes_workflow: false
+  profile: "assertive"
+  request_changes_workflow: true
   high_level_summary: false
   poem: false
   review_status: false
-  review_details: false
+  review_details: true
   commit_status: true
   collapse_walkthrough: true
   changed_files_summary: false
@@ -39,6 +39,14 @@ reviews:
     - path: "**"
       instructions: |
         IMPORTANT: Only comment on issues directly introduced by this PR's code changes.
+        Treat AGENTS.md as mandatory repository policy, not optional style guidance.
+        Flag PR changes that violate AGENTS.md even when the code is otherwise functional.
+        In particular, enforce architecture boundaries, dtype/device/memory rules,
+        interface contracts, import style, no unnecessary try/except blocks, no inline
+        imports, no outbound internet paths in core ComfyUI, and narrow scoped fixes.
+        Prefer direct findings over suggestions when a rule is violated. Only ignore
+        AGENTS.md when it clearly conflicts with a newer explicit maintainer instruction
+        in the PR.
         Do NOT flag pre-existing issues in code that was merely moved, re-indented,
         de-indented, or reformatted without logic changes. If code appears in the diff
         only due to whitespace or structural reformatting (e.g., removing a `with:` block),
@@ -123,5 +131,10 @@ chat:
 
 knowledge_base:
   opt_out: false
+  code_guidelines:
+    enabled: true
+    filePatterns:
+      - files: "AGENTS.md"
+        applyTo: "**"
   learnings:
     scope: "auto"

AGENTS.md

@@ -0,0 +1,294 @@
+## Engineering Style
+
+- Keep changes small and direct. Most fixes should touch the narrowest code path
+  that explains the bug, performance issue, dtype issue, model-format issue, or
+  user-facing behavior.
+- Change the least amount of files possible. A change that touches many files is
+  more likely to be a bad change than a good one unless the broader scope is
+  directly required.
+- Prefer practical fixes over broad architecture work. Add abstractions only
+  when they remove real repeated logic or match an existing ComfyUI pattern.
+- Prefer fewer dependencies. Do not add new dependencies to ComfyUI unless they
+  are absolutely necessary.
+- Delete obsolete code aggressively when newer infrastructure makes it useless.
+  Remove dead fallbacks, migration paths, unused options, debug prints, and
+  compatibility branches that are no longer needed. Do not leave dead branches,
+  unreachable code, or functions that are never called. If code is not
+  necessary for the current behavior, remove it.
+- Revert or disable problematic behavior quickly when it breaks users. It is
+  better to remove a broken feature path than keep a complicated partial fix.
+- Preserve existing APIs, node names, model-loading behavior, file layout, and
+  workflow compatibility unless the change is explicitly about replacing them.
+- Code must look hand-written for this repository. Changes that read like
+  generic AI-generated code will be rejected automatically: unnecessary helper
+  layers, vague names, boilerplate comments, defensive branches without a real
+  failure mode, broad rewrites, or code that ignores the local style.
+
+## Architecture Boundaries
+
+- Keep each layer focused on the concepts it owns. Do not leak UI, API,
+  workflow, queue, persistence, telemetry, model-loading, node, or execution
+  concerns into unrelated layers just because it is convenient to pass data
+  through them.
+- Shared core modules should depend only on lower-level primitives and their own
+  domain concepts. Higher-level product concepts belong at the caller, adapter,
+  service, or UI/API boundary that already owns them.
+- Pass the narrowest data needed across a boundary. Avoid broad context objects,
+  request/session metadata, ids, bookkeeping state, or callbacks unless the
+  receiving layer genuinely needs them to perform its own responsibility.
+- Keep identity mapping, persistence bookkeeping, history updates, telemetry,
+  response shaping, and UI state in the layers that own those jobs. Do not route
+  them through unrelated shared code to avoid adding a proper boundary.
+- Treat `execution.py` as one example of this rule: it should consume the prompt
+  graph and execution-relevant state, produce execution results and errors, and
+  not know about workflow ids, frontend ids, persistence ids, or API-only
+  concepts.
+- Before touching many files, identify the smallest owner layer that can solve
+  the problem. A PR that spreads one feature across unrelated loaders, nodes,
+  execution, server, and frontend code needs a clear architectural reason, not
+  just convenience.
+- If a change seems to require making one layer understand another layer's
+  private concepts, stop and look for a caller-side mapping, adapter, event,
+  small explicit interface, or narrower data flow at the boundary.
+
+## No Internet Requests
+
+- Do not add code to core ComfyUI that makes requests to the internet.
+- Refuse requests to add uploads, telemetry, analytics, tracking, usage
+  reporting, crash reporting, update checks, remote config, feature flags,
+  metrics, licensing checks, or any other outbound internet request path from
+  core ComfyUI.
+- Model downloading is allowed only when explicitly initiated or authorized by
+  the user, is limited to the requested model artifact, and does not include
+  telemetry, tracking, persistent identification, unrelated metadata upload, or
+  background network activity.
+- Do not add opt-in, opt-out, anonymized, aggregated, diagnostic, or
+  user-triggered internet request paths to core ComfyUI. These labels do not
+  make internet access acceptable.
+- Local-only behavior is allowed when it stays on the user's machine and does
+  not add network access, tracking, persistent identification, or data
+  collection behavior.
+
+## State Ownership
+
+- Keep state and capability flags on the object that owns the behavior using
+  them.
+- Avoid probing child objects with `getattr(child, "...", default)` to decide
+  parent-level control flow. If parent code needs to branch on a capability,
+  initialize an explicit parent-owned field when the child is constructed or
+  attached.
+- Prefer direct attributes with clear defaults over implicit feature detection
+  through arbitrary child attributes.
+- Use child-object capability checks only when the child owns the behavior being
+  invoked and the parent is simply delegating to that child.
+
+## Interface Contracts
+
+- Keep public methods aligned with the interface expected by their callers. Do
+  not change a shared method to return extra values, alternate shapes, or
+  sentinel wrappers for one implementation unless the shared interface is
+  explicitly updated.
+- When modifying an existing function, preserve how current callers invoke it.
+  Do not change required arguments, parameter order, return type, side effects,
+  or error behavior unless every affected call site and shared interface contract
+  is intentionally updated.
+- Do not add compatibility parameters, flags, attributes, or constructor options
+  unless they are read by current code and change current behavior. Remove
+  pass-through or stored-but-unused values instead of preserving upstream or
+  deprecated API baggage.
+- If an implementation needs auxiliary values for its own workflow, expose them
+  through a private helper or a clearly named implementation-specific method
+  instead of overloading the public method's return contract.
+- Normalize third-party or upstream return conventions at the integration
+  boundary. Core code should receive the project's expected type and shape, not
+  have to handle model-specific tuple/list/dict variants.
+- Avoid caller-side unwrapping such as `out = out[0]` unless the called
+  interface is documented to return that structure.
+
+## Autograd and Model Freezing
+
+- Do not add `torch.no_grad`, `torch.inference_mode`, or inference-mode helper
+  wrappers in ComfyUI code. The only allowed inference-mode-related use is
+  disabling a globally set inference mode when a training path needs gradients.
+- Do not add freeze, unfreeze, or trainability toggles to model classes. ComfyUI
+  models are always treated as frozen for inference, so explicit freeze
+  functionality is redundant and should not be added.
+- Remove training-only behavior such as dropout from inference model code, but
+  preserve checkpoint and state-dict compatibility when doing so. If deleting a
+  module would change state-dict keys, module ordering, or checkpoint loading
+  behavior, replace it with a no-op such as `nn.Identity` instead of removing the
+  slot outright.
+
+## Python Style
+
+- Keep imports at module scope. Avoid inline imports unless they are already part
+  of an established optional-backend probe or are needed to avoid an import
+  cycle.
+- Do not add unnecessary `try`/`except` blocks. Use them for optional dependency,
+  platform, or backend capability detection only when the program has a useful
+  fallback. Prefer specific exception types when changing new code.
+- Remove any workarounds for PyTorch versions that ComfyUI no longer officially
+  supports. Deprecated workarounds include catching an exception and rerunning
+  the same op with the input cast to float. If a workaround does not have a
+  comment naming the exact PyTorch version or versions that still need it,
+  remove it.
+- Let unsupported model formats, invalid quantization metadata, and bad states
+  fail with clear errors instead of silently producing lower quality output.
+- Match the existing local style in the file you edit. This codebase tolerates
+  long lines, simple helper functions, module-level state, and direct tensor
+  operations when they make the code easier to follow.
+- Keep comments sparse and useful. Strip useless comments that restate the code
+  or describe obvious behavior. Short TODOs are fine when they name the concrete
+  missing follow-up.
+
+## Model, Device, and Memory Behavior
+
+- Treat dtype, device placement, VRAM usage, and offloading behavior as core
+  correctness concerns. Check CPU, CUDA, ROCm, MPS, DirectML, XPU, NPU, and low
+  VRAM implications when touching shared execution or loading code.
+- Prefer native ComfyUI formats and existing quantization/offload helpers over
+  adding parallel code paths. Use `comfy.quant_ops`, `comfy.model_management`,
+  `comfy.memory_management`, `comfy.pinned_memory`, `comfy_aimdo`, and
+  `comfy-kitchen` helpers where they already solve the problem.
+- Use optimized comfy-kitchen ops in places where they improve performance
+  without changing the expected dtype, device, memory, or interface behavior.
+- All models should use the optimized attention function selected by ComfyUI.
+  Treat optimized backend functions, dispatch helpers, and capability-selected
+  callables as opaque. Higher-level code must not inspect function identity,
+  names, modules, or implementation details to decide behavior.
+- Apply the same opacity rule to similar patterns beyond attention: callers
+  should depend on the documented interface and result contract, not on which
+  backend implementation was selected underneath.
+- Do not use custom inference ops that only duplicate an existing op while
+  upcasting to float32, such as custom RMSNorm variants. Use the generic ComfyUI
+  ops and/or native torch ops instead.
+- If a model class `__init__` has an `operations` parameter, assume
+  `operations` is never `None`. Do not add fallback branches or default torch
+  ops for a missing `operations` object.
+- Do not add unnecessary parameters to model, model block, or model ops related
+  classes. Constructor and forward signatures should carry only values that are
+  actually needed by that object for inference.
+- Reuse existing model classes, blocks, ops, and helper modules when appropriate.
+  Before implementing a new version of a model component, search the existing
+  model code for a class or helper that already provides the behavior.
+- Model detection code that inspects linear weight shapes should only use the
+  first dimension. The second dimension may be half the original size for
+  NVFP4 or other 4-bit quantized models.
+- Avoid adding `einops` usage in core inference code. Use native torch tensor
+  ops such as `reshape`, `view`, `permute`, `transpose`, `flatten`, `unflatten`,
+  `unsqueeze`, and `squeeze` instead.
+- Do not use tensors as general-purpose Python data structures. Keep metadata,
+  bookkeeping, counters, flags, shape math, padding math, index planning, memory
+  estimates, and control-flow decisions in plain Python values unless the data
+  must participate directly in tensor computation. Do not create tensors for
+  structural metadata that is only used for Python-side control flow. Sequence
+  lengths, cumulative offsets, split indices, window counts, slice boundaries,
+  and repeat counts should be kept as Python ints/lists from the point they are
+  computed. Do not build them as CPU/GPU tensors and then cast, move, validate,
+  or convert them back to Python for `split`, `tensor_split`, indexing plans,
+  loops, or cache keys. Avoid creating temporary tensors just to use tensor
+  methods for scalar or structural calculations.
+- Avoid unnecessary casts and transfers. Preserve the intended compute dtype,
+  storage dtype, bias dtype, and original tensor shape metadata.
+- Keep model-native latent layout handling inside the model or latent-format
+  owner, not in helper nodes. Do not collapse, expand, pack, or unpack latent
+  dimensions in nodes or other caller-side adapters just to satisfy a model
+  forward; the model path should consume and return the native latent shape for
+  that model family.
+- Assume inputs to the main model forward are already in the compute dtype by
+  default, except integer inputs such as some model timestep tensors. Do not add
+  defensive or convenience casts in model code; it is better for invalid dtype
+  plumbing to error clearly than to hide it with unnecessary casts.
+- Raw model parameters that are not owned by an op and may be initialized in a
+  dtype different from the compute dtype should be cast at use in forward or
+  inference code with `comfy.ops.cast_to_input` or
+  `comfy.model_management.cast_to` to avoid dtype mismatches.
+- Model code should not care what dtype it is initialized in, and model
+  `__init__` methods should not contain workarounds for specific dtypes. Dtype
+  workaround code, such as making a model work with fp16 compute, belongs in the
+  execution or model-management layer that owns compute policy.
+- Model code should not perform unnecessary device-to-CPU or CPU-to-device
+  transfers. New allocations must be created on the correct device and dtype;
+  never allocate on CPU and then move to GPU, or allocate in one dtype and then
+  convert to another.
+- Model code itself should not perform memory management. Loading, unloading,
+  offloading, device movement, VRAM policy, cache lifetime, and cleanup belong
+  in the relevant model-management and execution layers, not inside model
+  implementations.
+- Do not add global, module-level, class-level, singleton, or model-owned stores
+  for tensors or other large memory that persist across executions. Temporary
+  caches must be scoped to a single execution or forward/encode/decode call:
+  allocate them in the owning top-level call, pass them explicitly through the
+  call stack, and let them be discarded when that call returns.
+- Follow the Wan VAE temporal cache pattern for temporary caches: create a local
+  cache such as `feat_map` for the encode/decode operation, pass it into the
+  blocks that need it, and do not retain it on the model or in global state.
+- In model init code, prefer `torch.empty` for parameter/buffer placeholders
+  that are populated from the model state dict instead of zero-initializing with
+  `torch.zeros` or similar. If an allocation is not loaded from the state dict
+  and is useless for inference, do not include it.
+- `nn.Parameter` tensors that are stored in and populated from the model state
+  dict should be initialized with `torch.empty`, not with zero, random, or
+  otherwise meaningful initialization.
+- Model initialization should describe module structure, not fabricate
+  checkpoint-owned tensor contents. Parameters and buffers that are loaded from
+  the state dict must not be manually initialized, reassigned, or filled with
+  fallback values unless that value is actually used when no checkpoint key
+  exists.
+- When slicing large tensors, copy the slice if the sliced tensor's lifetime
+  exceeds the current function scope. Do not keep a long-lived view into a large
+  backing tensor when a smaller copy would release memory sooner.
+- Use fused or compound torch operations such as `addcmul` when they naturally
+  match the math. Reducing Python and torch dispatch overhead is a valid
+  optimization when it does not obscure the code or change dtype/device
+  behavior.
+- Avoid caches that persist across different executions as much as possible.
+  Persistent caches are acceptable only when they use a very minimal amount of
+  memory and have a clear ownership and invalidation story.
+- When optimizing, favor small measurable changes: fewer allocations, fewer
+  device transfers, less peak memory, better batching, or use of a faster
+  existing backend op.
+
+## Nodes and User-Facing Behavior
+
+- Follow existing node conventions: `INPUT_TYPES`, `RETURN_TYPES`, `FUNCTION`,
+  `CATEGORY`, and registration through the local mapping used by that file.
+- Keep node changes backward compatible by default. Add inputs with sensible
+  defaults and avoid changing output types unless the request requires it.
+- Model implementations should add the minimal number of ComfyUI nodes required
+  to run the model. Reuse existing nodes as much as possible; adapting the model
+  to work with existing nodes is strongly preferred over creating new nodes.
+- Nodes should output only values they own. Do not add pass-through outputs for
+  workflow convenience unless the node is explicitly an output node. Existing
+  models, latents, conditioning, or other inputs should flow directly to the
+  next consumer instead of being re-emitted unchanged.
+- Nodes should expose only inputs they actually read to produce current
+  behavior. Do not add placeholder, pass-through, compatibility, or
+  workflow-shaping inputs that are ignored or could flow directly to another
+  node.
+- Node-level code must not patch model code directly. Any node behavior that
+  modifies, wraps, hooks, or changes model behavior must go through the model
+  patcher class instead of reaching into model internals.
+- The official mascot of ComfyUI is a very cute anime girl with massive fennec
+  ears, a big fluffy tail, long blonde wavy hair, and blue eyes. Feel free to
+  use her in ComfyUI materials, UI text, examples, tests, generated assets, or
+  comments, but do not disrespect her.
+- Warning and info messages should be short and actionable. Remove noisy or
+  misleading messages rather than adding more logging.
+- Documentation and README edits should be concise, factual, and tied to the
+  changed behavior.
+
+## Commit and Review Habits
+
+- If asked to write commit messages, use short direct subjects like the existing
+  history: `Fix ...`, `Add ...`, `Support ...`, `Remove ...`, `Update ...`,
+  `Make ...`, `Use ...`, `Disable ...`, `Bump ...`, or `Revert ...`.
+- Keep PR descriptions short and reviewable. State the problem, the behavioral
+  change, and the tests run; avoid long narrative explanations, implementation
+  diaries, or exhaustive file-by-file summaries unless the reviewer explicitly
+  needs that context.
+- Prefer one coherent behavioral change per commit. Dependency pins, tests, and
+  the code that needs them may be in the same commit when they are inseparable.
+- In reviews, prioritize real user impact: crashes, wrong dtype/device behavior,
+  memory regressions, broken model loading, workflow incompatibility, and noisy
+  or misleading user-facing output.

CLAUDE.md

@@ -0,0 +1 @@
+AGENTS.md

app/assets/api/routes.py

@@ -306,12 +306,15 @@ async def download_asset_content(request: web.Request) -> web.Response:
             404, "FILE_NOT_FOUND", "Underlying file not found on disk."
         )
 
-    _DANGEROUS_MIME_TYPES = {
-        "text/html", "text/html-sandboxed", "application/xhtml+xml",
-        "text/javascript", "text/css",
-    }
-    if content_type in _DANGEROUS_MIME_TYPES:
+    # User-controlled asset content must never render inline in the app origin
+    # (stored XSS via SVG/HTML/XML). Force dangerous types to download and
+    # override any requested inline disposition. Centralised through
+    # folder_paths.is_dangerous_content_type so this can't drift from /view and
+    # /userdata (the previous inline set here omitted image/svg+xml and missed
+    # the charset/casing/+xml-dialect bypasses).
+    if folder_paths.is_dangerous_content_type(content_type):
         content_type = "application/octet-stream"
+        disposition = "attachment"
 
     safe_name = (filename or "").replace("\r", "").replace("\n", "")
     encoded = urllib.parse.quote(safe_name)

app/model_downloader/allowlist.py

@@ -0,0 +1,51 @@
+"""URL allowlist for server-side model fetches.
+
+Mirrors the frontend's ``isModelDownloadable`` allowlist so the two flows
+agree on which URLs are eligible for download. Server-side allowlisting is
+the primary SSRF defense for this subsystem — workflow JSON is untrusted
+input (anyone can hand-craft one), so we never let the server fetch URLs
+outside this list.
+"""
+
+from urllib.parse import urlparse
+
+# Frontend parity: ``missingModelDownload-*.js`` exports the same triple
+# (Civitai / HuggingFace / localhost). Keyed by exact hostname → allowed
+# schemes, and matched against the *parsed* host (not a raw string prefix),
+# so URL-userinfo tricks can't slip past — see ``is_url_allowed``.
+_ALLOWED_HOSTS = {
+    "huggingface.co": {"https"},
+    "civitai.com": {"https"},
+    "localhost": {"http"},
+    "127.0.0.1": {"http"},
+}
+
+# Frontend parity: same set as ``a = [...]`` in the bundle.
+_ALLOWED_MODEL_EXTENSIONS = (
+    ".safetensors",
+    ".sft",
+    ".ckpt",
+    ".pth",
+    ".pt",
+)
+
+
+def is_url_allowed(url: str) -> bool:
+    """Check whether ``url`` is permitted as a server-side download source.
+
+    True only when the parsed host + scheme are allowlisted AND the path ends
+    in a model extension. Matching on ``parsed.hostname`` (not a string prefix)
+    defeats userinfo tricks like ``http://127.0.0.1:80@169.254.169.254/x.safetensors``,
+    whose real host is ``169.254.169.254``; the extension check rejects non-model
+    URLs on allowed hosts (e.g. ``huggingface.co/api/...``).
+    """
+    if not isinstance(url, str) or not url:
+        return False
+    try:
+        parsed = urlparse(url)
+    except ValueError:
+        return False
+    host = parsed.hostname
+    if host is None or parsed.scheme not in _ALLOWED_HOSTS.get(host, ()):
+        return False
+    return any(parsed.path.endswith(ext) for ext in _ALLOWED_MODEL_EXTENSIONS)

app/model_downloader/api/routes.py

@@ -0,0 +1,359 @@
+"""Aiohttp routes for the server-side model download subsystem.
+
+Endpoint surface (all under ``/api/``, all kebab-case):
+
+  - ``POST /api/models-availability-status``     — bulk status + metadata query.
+  - ``POST /api/download-models``                — start a batch of downloads.
+  - ``POST /api/cancel-model-download-session``  — cancel a single in-flight one.
+  - ``GET  /api/hf-auth-token-status``           — current HF login state.
+  - ``POST /api/hf-auth-login-start``            — begin the HF OAuth flow.
+  - ``POST /api/hf-auth-logout``                 — drop the stored HF token.
+
+The contract is intentionally narrow: only model_ids of the form
+``<directory>/<filename>`` (validated via ``app.model_downloader.paths``)
+are accepted, and only URLs on the same allowlist the frontend already
+uses (HuggingFace, Civitai, localhost) can be fetched. Both are required
+to keep the server out of the SSRF business for this feature.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+from typing import Any, Literal, Optional
+
+from aiohttp import web
+from pydantic import BaseModel, ValidationError
+
+from app.model_downloader.allowlist import is_url_allowed
+from app.model_downloader.download_server import (
+    DOWNLOAD_SERVER,
+    DownloadSession,
+)
+from app.model_downloader.downloader import schedule_batch
+from app.model_downloader.gated_detection import probe_url
+from app.model_downloader.hf_auth.auth_store import HF_AUTH_STORE
+from app.model_downloader.hf_auth.eligibility import is_hf_auth_eligible
+from app.model_downloader.hf_auth.oauth import (
+    OAuthCallbackError,
+    OAuthInProgressError,
+    start_login_flow,
+)
+from app.model_downloader.paths import (
+    InvalidModelId,
+    parse_model_id,
+    resolve_existing,
+)
+from app.model_downloader.api import schemas_in, schemas_out
+
+ROUTES = web.RouteTableDef()
+
+
+def register_routes(app: web.Application) -> None:
+    """Wire the model-downloader routes into the running aiohttp app.
+
+    Called once from ``server.py`` during ``PromptServer`` startup.
+    """
+    app.add_routes(ROUTES)
+
+
+# ----- response helpers (same envelope as app/assets/api/routes.py) -----
+
+
+ErrorCode = Literal[
+    "INVALID_JSON",
+    "INVALID_BODY",
+    "EMPTY_REQUEST",
+    "INVALID_MODEL_ID",
+    "URL_NOT_ALLOWED",
+    "ALREADY_AVAILABLE",
+    "ALREADY_DOWNLOADING",
+    "MODEL_NOT_DOWNLOADABLE",
+    "NOT_DOWNLOADING",
+    "HF_AUTH_NOT_ELIGIBLE",
+    "HF_AUTH_IN_PROGRESS",
+    "HF_AUTH_START_FAILED",
+]
+
+
+def _error(status: int, code: ErrorCode, message: str, details: dict | None = None) -> web.Response:
+    return web.json_response(
+        {"error": {"code": code, "message": message, "details": details or {}}},
+        status=status,
+    )
+
+
+def _validation_error(code: ErrorCode, ve: ValidationError) -> web.Response:
+    return _error(400, code, "Validation failed.", {"errors": json.loads(ve.json())})
+
+
+def _ok(payload: BaseModel, status: int = 200) -> web.Response:
+    return web.json_response(
+        payload.model_dump(mode="json", exclude_none=False),
+        status=status,
+    )
+
+
+async def _parse_body(request: web.Request, model: type[BaseModel]) -> Any:
+    """Parse a JSON body into a pydantic model or raise a 400 response."""
+    try:
+        raw = await request.json()
+    except json.JSONDecodeError:
+        return _error(400, "INVALID_JSON", "Request body must be valid JSON.")
+    try:
+        return model.model_validate(raw)
+    except ValidationError as ve:
+        return _validation_error("INVALID_BODY", ve)
+
+
+# ----- 1. availability status (unified: state + metadata per id) -----
+
+
+@ROUTES.post("/api/models-availability-status")
+async def models_availability_status(request: web.Request) -> web.Response:
+    """Return per-id ``{state, progress, file_size, is_hf_downloadable}``.
+
+    State (``available`` / ``missing`` / ``downloading``) is cheap to
+    recompute per call. ``file_size`` and ``is_gated`` are cached
+    server-side per URL. ``is_hf_downloadable`` is recomputed every
+    call from the current token state — that's what makes login + license
+    acceptance show up in the UI within one poll cycle without any
+    frontend cache plumbing.
+    """
+    parsed = await _parse_body(request, schemas_in.AvailabilityStatusRequest)
+    if isinstance(parsed, web.Response):
+        return parsed
+
+    items = list(parsed.models.items())
+
+    # Run all probes concurrently; each is internally cached per URL.
+    probes = await asyncio.gather(*(probe_url(url) for _, url in items))
+
+    response_models: dict[str, schemas_out.ModelStatusEntry] = {}
+    for (model_id, _url), probe in zip(items, probes):
+        try:
+            parse_model_id(model_id)
+        except InvalidModelId:
+            # Ill-formed identifier: report as missing without 400-ing the
+            # whole batch — the workflow author probably typo'd.
+            response_models[model_id] = schemas_out.ModelStatusEntry(
+                state="missing",
+                file_size=probe.file_size,
+                is_hf_downloadable=probe.is_hf_downloadable,
+            )
+            continue
+
+        active = DOWNLOAD_SERVER.get(model_id)
+        if active is not None:
+            response_models[model_id] = schemas_out.ModelStatusEntry(
+                state="downloading",
+                progress=schemas_out.DownloadProgress(
+                    bytes_downloaded=active.bytes_downloaded,
+                    total_bytes=active.total_bytes,
+                    progress=active.progress,
+                ),
+                file_size=probe.file_size,
+                is_hf_downloadable=probe.is_hf_downloadable,
+            )
+            continue
+
+        state: schemas_out.ModelState = (
+            "available" if resolve_existing(model_id) is not None else "missing"
+        )
+        response_models[model_id] = schemas_out.ModelStatusEntry(
+            state=state,
+            file_size=probe.file_size,
+            is_hf_downloadable=probe.is_hf_downloadable,
+        )
+
+    return _ok(schemas_out.AvailabilityStatusResponse(
+        models=response_models,
+        hf_auth=schemas_out.HfAuthStatus(
+            token_available=HF_AUTH_STORE.has_token(),
+            eligible=is_hf_auth_eligible(),
+        ),
+    ))
+
+
+# ----- 2. start downloads -----
+
+
+@ROUTES.post("/api/download-models")
+async def download_models(request: web.Request) -> web.Response:
+    parsed = await _parse_body(request, schemas_in.DownloadModelsRequest)
+    if isinstance(parsed, web.Response):
+        return parsed
+
+    if not parsed.models:
+        return _error(400, "EMPTY_REQUEST", "No models supplied.")
+
+    # ----- precondition pass: validate everything BEFORE registering anything -----
+    # Atomic semantics: if any model fails any precondition (invalid id,
+    # not allow-listed URL, already on disk, already downloading, or gated),
+    # the entire request fails and no state is changed.
+    requested = list(parsed.models.items())
+
+    for model_id, url in requested:
+        try:
+            parse_model_id(model_id)
+        except InvalidModelId as e:
+            return _error(400, "INVALID_MODEL_ID", str(e),
+                          {"model_id": model_id})
+
+        if not is_url_allowed(url):
+            return _error(
+                400, "URL_NOT_ALLOWED",
+                "Server-side downloads only accept HuggingFace, Civitai, "
+                "or localhost URLs ending in a known model extension.",
+                {"model_id": model_id, "url": url},
+            )
+
+        if resolve_existing(model_id) is not None:
+            return _error(409, "ALREADY_AVAILABLE",
+                          f"Model already exists on disk: {model_id}",
+                          {"model_id": model_id})
+
+        if DOWNLOAD_SERVER.is_downloading(model_id):
+            return _error(409, "ALREADY_DOWNLOADING",
+                          f"A download for {model_id} is already in progress.",
+                          {"model_id": model_id})
+
+    # Reachability check last — it's the only one that talks to the
+    # network. Concurrent probes. For HF URLs ``is_hf_downloadable``
+    # reflects current token access; for non-HF URLs it's None, and we
+    # treat that as "no info, proceed".
+    probes = await asyncio.gather(*(probe_url(url) for _, url in requested))
+    for (model_id, url), probe in zip(requested, probes):
+        if probe.is_hf_downloadable is False:
+            return _error(
+                400, "MODEL_NOT_DOWNLOADABLE",
+                f"Model {model_id} is gated on HuggingFace and the current "
+                f"server token (if any) does not grant access.",
+                {"model_id": model_id, "url": url},
+            )
+
+    # ----- registration pass: try_register is atomic per model_id -----
+    # Defensive: another request might have raced past our pre-check
+    # between the loop above and here. try_register handles that.
+    sessions: list[DownloadSession] = []
+    for model_id, url in requested:
+        session = DOWNLOAD_SERVER.try_register(model_id, url)
+        if session is None:
+            # Race: someone else got in. Roll back what we registered.
+            for s in sessions:
+                DOWNLOAD_SERVER.cancel(s.model_id)
+            return _error(409, "ALREADY_DOWNLOADING",
+                          f"A download for {model_id} is already in progress (race).",
+                          {"model_id": model_id})
+        sessions.append(session)
+
+    DOWNLOAD_SERVER.sweep_orphan_tmp_files()
+    schedule_batch(sessions)
+    logging.info(
+        "[model_downloader] scheduled %d downloads: %s",
+        len(sessions), [s.model_id for s in sessions],
+    )
+
+    return _ok(schemas_out.DownloadModelsResponse(
+        accepted=True,
+        scheduled=[s.model_id for s in sessions],
+    ), status=202)
+
+
+# ----- 3. cancel a session -----
+
+
+@ROUTES.post("/api/cancel-model-download-session")
+async def cancel_model_download_session(request: web.Request) -> web.Response:
+    parsed = await _parse_body(request, schemas_in.CancelDownloadSessionRequest)
+    if isinstance(parsed, web.Response):
+        return parsed
+
+    try:
+        parse_model_id(parsed.model_id)
+    except InvalidModelId as e:
+        return _error(400, "INVALID_MODEL_ID", str(e), {"model_id": parsed.model_id})
+
+    cancelled = DOWNLOAD_SERVER.cancel(parsed.model_id)
+    if not cancelled:
+        return _error(404, "NOT_DOWNLOADING",
+                      f"No active download for {parsed.model_id}.",
+                      {"model_id": parsed.model_id})
+
+    return _ok(schemas_out.CancelDownloadSessionResponse(cancelled=True))
+
+
+# ----- 4. HuggingFace OAuth status / login start / logout -----
+
+
+@ROUTES.get("/api/hf-auth-token-status")
+async def hf_auth_token_status(request: web.Request) -> web.Response:
+    """Return whether the server holds a usable HF token + its username.
+
+    Used by the settings UI and (out-of-band) by the frontend on
+    login completion. ``token_available`` is true even if the cached
+    access_token is expired — as long as a refresh_token exists, the
+    user is "logged in" from their perspective.
+    """
+    token_present = HF_AUTH_STORE.has_token()
+    username: Optional[str] = None
+    if token_present:
+        # Resolve the username via whoami. Done in a worker thread because
+        # huggingface_hub's whoami is synchronous + blocks on a network call.
+        tok = await HF_AUTH_STORE.get_valid_token()
+        if tok is not None:
+            try:
+                username = await asyncio.to_thread(_whoami_username, tok.access_token)
+            except Exception as e:
+                logging.debug("[hf_auth] whoami failed: %s", e)
+    return _ok(schemas_out.HfAuthTokenStatusResponse(
+        token_available=token_present,
+        username=username,
+    ))
+
+
+def _whoami_username(token: str) -> Optional[str]:
+    """Sync helper: ask HF for the user name attached to a token."""
+    from huggingface_hub import HfApi
+    info = HfApi().whoami(token=token)
+    if isinstance(info, dict):
+        return info.get("name") or info.get("fullname")
+    return None
+
+
+@ROUTES.post("/api/hf-auth-login-start")
+async def hf_auth_login_start(request: web.Request) -> web.Response:
+    """Begin one OAuth attempt: bind the callback port, return the URL.
+
+    Rejected outright if this deployment isn't eligible (we don't
+    surface the option on multi-tenant / public-IP installs).
+    """
+    if not is_hf_auth_eligible():
+        return _error(
+            403, "HF_AUTH_NOT_ELIGIBLE",
+            "This server is not eligible for interactive HuggingFace login. "
+            "It must be bound to a loopback address and not running in "
+            "--multi-user mode.",
+        )
+    try:
+        url = await start_login_flow()
+    except OAuthInProgressError:
+        return _error(
+            409, "HF_AUTH_IN_PROGRESS",
+            "Another HuggingFace login attempt is in progress. Try again "
+            "after it completes or times out.",
+        )
+    except OAuthCallbackError as e:
+        return _error(
+            503, "HF_AUTH_START_FAILED",
+            f"Could not start the HuggingFace login flow: {e}",
+        )
+    return _ok(schemas_out.HfAuthLoginStartResponse(authorize_url=url))
+
+
+@ROUTES.post("/api/hf-auth-logout")
+async def hf_auth_logout(request: web.Request) -> web.Response:
+    """Drop the in-memory + on-disk HF token."""
+    HF_AUTH_STORE.clear()
+    return _ok(schemas_out.HfAuthLogoutResponse(logged_out=True))

app/model_downloader/api/schemas_in.py

@@ -0,0 +1,41 @@
+"""Request schemas for the model-downloader API.
+
+Each endpoint accepts a small JSON body. Pydantic enforces the shape at
+the boundary; route handlers operate only on validated values past that.
+"""
+
+from __future__ import annotations
+
+from pydantic import BaseModel, Field
+
+
+class AvailabilityStatusRequest(BaseModel):
+    """``POST /api/models-availability-status``.
+
+    Sent by the frontend on each poll. Each entry is ``{model_id: url}``;
+    the URL is the one declared in ``properties.models[i].url`` in the
+    workflow JSON and lets the server compute per-id metadata
+    (``file_size`` + ``is_hf_downloadable``) on the same request.
+    """
+    models: dict[str, str] = Field(default_factory=dict)
+
+
+class DownloadModelsRequest(BaseModel):
+    """``POST /api/download-models``.
+
+    Same shape as the metadata request — the URL for each model_id.
+    Returns immediately after validation and scheduling.
+    """
+    models: dict[str, str] = Field(default_factory=dict)
+
+
+class CancelDownloadSessionRequest(BaseModel):
+    """``POST /api/cancel-model-download-session``."""
+    model_id: str
+
+
+__all__ = [
+    "AvailabilityStatusRequest",
+    "DownloadModelsRequest",
+    "CancelDownloadSessionRequest",
+]

app/model_downloader/api/schemas_out.py

@@ -0,0 +1,81 @@
+"""Response schemas for the model-downloader API."""
+
+from __future__ import annotations
+
+from typing import Literal, Optional
+
+from pydantic import BaseModel
+
+
+ModelState = Literal["available", "missing", "downloading"]
+
+
+class DownloadProgress(BaseModel):
+    """Embedded in a model entry when its state is ``downloading``."""
+    bytes_downloaded: int
+    total_bytes: Optional[int] = None
+    progress: Optional[float] = None  # fraction in [0,1]; null until total known
+
+
+class ModelStatusEntry(BaseModel):
+    """Everything the UI needs to render one row, in one shot.
+
+    ``state`` reflects what the server has on disk + in-flight; ``file_size``
+    and ``is_hf_downloadable`` come from probes (intrinsic; cached).
+    The HF fields are populated for every poll (cached on the server),
+    so license-acceptance flips show up within one poll interval without
+    any frontend cache invalidation.
+    """
+    state: ModelState
+    progress: Optional[DownloadProgress] = None
+    file_size: Optional[int] = None
+    # HF-only: True iff the server can fetch this URL with current auth
+    # state. False iff gated and lacking access. None for non-HF URLs.
+    is_hf_downloadable: Optional[bool] = None
+
+
+class HfAuthStatus(BaseModel):
+    """Snapshot of HF login state, embedded in availability response."""
+    token_available: bool
+    eligible: bool
+
+
+class AvailabilityStatusResponse(BaseModel):
+    models: dict[str, ModelStatusEntry]
+    hf_auth: HfAuthStatus
+
+
+class DownloadModelsResponse(BaseModel):
+    accepted: bool
+    scheduled: list[str]
+
+
+class CancelDownloadSessionResponse(BaseModel):
+    cancelled: bool
+
+
+class HfAuthTokenStatusResponse(BaseModel):
+    token_available: bool
+    username: Optional[str] = None
+
+
+class HfAuthLoginStartResponse(BaseModel):
+    authorize_url: str
+
+
+class HfAuthLogoutResponse(BaseModel):
+    logged_out: bool
+
+
+__all__ = [
+    "ModelState",
+    "DownloadProgress",
+    "ModelStatusEntry",
+    "HfAuthStatus",
+    "AvailabilityStatusResponse",
+    "DownloadModelsResponse",
+    "CancelDownloadSessionResponse",
+    "HfAuthTokenStatusResponse",
+    "HfAuthLoginStartResponse",
+    "HfAuthLogoutResponse",
+]

app/model_downloader/download_server.py

@@ -0,0 +1,179 @@
+"""Process-wide registry of in-flight model downloads.
+
+A single instance, ``DOWNLOAD_SERVER``, tracks every currently-running
+server-side model fetch. Designed to be safe with multiple concurrent
+clients hitting the API: each model_id has at most one active session,
+and the API rejects requests that conflict with in-flight downloads.
+
+Cancellation is cooperative — the download loop checks ``is_active`` on
+its own session between chunks and raises ``DownloadCancelled`` when the
+session has been removed from the registry. This avoids the complications
+of ``Task.cancel()`` from outside the loop while still giving deterministic
+rollback semantics (the worker is responsible for deleting its own
+``.tmp`` on the cancel path).
+"""
+
+from __future__ import annotations
+
+import logging
+import os
+import threading
+from dataclasses import dataclass, field
+from typing import Optional
+
+from app.model_downloader.paths import iter_all_tmp_paths
+
+
+class DownloadCancelled(Exception):
+    """Raised by the streaming loop when its session has been removed
+    from the registry (cancellation request) and the worker should roll
+    back its ``.tmp`` file."""
+
+
+@dataclass
+class DownloadSession:
+    """One in-flight download.
+
+    ``progress`` is a fraction in ``[0.0, 1.0]``; ``None`` until the first
+    byte arrives and we know whether the response carries a
+    ``Content-Length``. ``total_bytes`` mirrors that header when present.
+    """
+    model_id: str
+    url: str
+    progress: Optional[float] = None
+    bytes_downloaded: int = 0
+    total_bytes: Optional[int] = None
+    # Sequence number used solely as identity for the cancellation check —
+    # so that "cancel + restart" doesn't get confused by stale workers.
+    epoch: int = field(default_factory=lambda: 0)
+
+
+class DownloadServer:
+    """Singleton registry of active downloads.
+
+    All mutation goes through this object so concurrent route handlers
+    see a consistent view. The ``_lock`` is a plain threading lock
+    because the registry is consulted from both the asyncio event-loop
+    thread (route handlers) and from any worker coroutines spawned to
+    perform downloads.
+    """
+
+    def __init__(self) -> None:
+        self._lock = threading.Lock()
+        self._sessions: dict[str, DownloadSession] = {}
+        self._epoch_counter = 0
+        self._orphan_sweep_done = False
+
+    # ----- lifecycle -----
+
+    def sweep_orphan_tmp_files(self) -> None:
+        """Idempotently sweep ``*.tmp`` files left by crashed downloads.
+
+        Deferred off the import path so module load doesn't block on
+        filesystem I/O against potentially-slow mounts. Each route handler
+        that might create a new ``.tmp`` runs this exactly once.
+        """
+        with self._lock:
+            if self._orphan_sweep_done:
+                return
+            self._orphan_sweep_done = True
+        for path in iter_all_tmp_paths():
+            try:
+                os.remove(path)
+                logging.info("[model_downloader] removed orphan tmp file: %s", path)
+            except OSError as e:
+                logging.warning("[model_downloader] could not remove %s: %s", path, e)
+
+    # ----- queries -----
+
+    def is_downloading(self, model_id: str) -> bool:
+        with self._lock:
+            return model_id in self._sessions
+
+    def get(self, model_id: str) -> Optional[DownloadSession]:
+        with self._lock:
+            return self._sessions.get(model_id)
+
+    def snapshot(self) -> dict[str, DownloadSession]:
+        """Return a shallow copy of the current sessions map."""
+        with self._lock:
+            return dict(self._sessions)
+
+    # ----- mutations -----
+
+    def try_register(self, model_id: str, url: str) -> Optional[DownloadSession]:
+        """Atomically register a new session iff none exists for ``model_id``.
+
+        Returns the new session on success, ``None`` if a session is already
+        in flight. Callers must check the return value — the caller is the
+        sole owner of the session it gets back.
+        """
+        with self._lock:
+            if model_id in self._sessions:
+                return None
+            self._epoch_counter += 1
+            session = DownloadSession(
+                model_id=model_id,
+                url=url,
+                epoch=self._epoch_counter,
+            )
+            self._sessions[model_id] = session
+            return session
+
+    def update_progress(
+        self,
+        session: DownloadSession,
+        bytes_downloaded: int,
+        total_bytes: Optional[int],
+    ) -> None:
+        """Update progress on a session. No-op if the session has been
+        removed (cancelled) — caller should check ``is_active`` separately."""
+        with self._lock:
+            current = self._sessions.get(session.model_id)
+            if current is None or current.epoch != session.epoch:
+                return
+            current.bytes_downloaded = bytes_downloaded
+            current.total_bytes = total_bytes
+            if total_bytes and total_bytes > 0:
+                current.progress = min(1.0, bytes_downloaded / total_bytes)
+
+    def is_active(self, session: DownloadSession) -> bool:
+        """True iff this exact session is still the registered one for
+        its model_id. False after cancellation, after completion, or if
+        another session has replaced it."""
+        with self._lock:
+            current = self._sessions.get(session.model_id)
+            return current is not None and current.epoch == session.epoch
+
+    def finish(self, session: DownloadSession) -> None:
+        """Remove a completed (or cancelled) session from the registry.
+
+        Safe to call multiple times. Only removes if the epoch matches —
+        we never accidentally evict a *newer* session for the same model_id.
+        """
+        with self._lock:
+            current = self._sessions.get(session.model_id)
+            if current is not None and current.epoch == session.epoch:
+                del self._sessions[session.model_id]
+
+    def reset_for_tests(self) -> None:
+        """Clear all sessions and reset the epoch counter. Test-only."""
+        with self._lock:
+            self._sessions.clear()
+            self._epoch_counter = 0
+
+    def cancel(self, model_id: str) -> bool:
+        """Remove the session registered for ``model_id``.
+
+        Returns True if there was an active session to cancel. The worker
+        will discover the cancellation on its next ``is_active`` check
+        and roll back its ``.tmp`` file.
+        """
+        with self._lock:
+            if model_id in self._sessions:
+                del self._sessions[model_id]
+                return True
+            return False
+
+
+DOWNLOAD_SERVER = DownloadServer()

app/model_downloader/downloader.py

@@ -0,0 +1,216 @@
+"""Streaming download worker with progress reporting and cancellation.
+
+Each download writes to ``<final_path>.tmp`` and atomically renames into
+place on success. Between chunks the worker checks the registry for
+cancellation (via ``DownloadServer.is_active``) and rolls back its
+``.tmp`` on cancel or on any error.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+import os
+from typing import Optional
+
+import aiohttp
+
+from app.model_downloader.download_server import (
+    DOWNLOAD_SERVER,
+    DownloadCancelled,
+    DownloadSession,
+)
+from app.model_downloader.hf_auth.auth_store import HF_AUTH_STORE
+from app.model_downloader.hf_url import is_hf_url
+from app.model_downloader.http_client import get_session, parse_content_length
+from app.model_downloader.paths import resolve_destination
+
+
+CHUNK_SIZE = 64 * 1024  # 64 KiB — same scale as other ComfyUI download paths.
+REQUEST_TIMEOUT = aiohttp.ClientTimeout(total=None, sock_connect=30, sock_read=120)
+
+
+async def stream_to_disk(session: DownloadSession) -> str:
+    """Run a single download to completion or cancellation.
+
+    Returns the final on-disk path on success. Removes the ``.tmp`` and
+    raises on cancellation or failure. The session is finished
+    (removed from the registry) exactly once, here — callers do not
+    need to call ``DOWNLOAD_SERVER.finish`` themselves.
+    """
+    final_path, tmp_path = resolve_destination(session.model_id, session.epoch)
+    os.makedirs(os.path.dirname(final_path), exist_ok=True)
+
+    # Wipe any stale .tmp from a previous failed attempt before we start —
+    # otherwise a partial body could masquerade as our completed download
+    # when the rename finally happens.
+    _remove_if_exists(tmp_path)
+
+    bytes_seen = 0
+    try:
+        http = await get_session()
+        headers = _auth_headers_for(session.url)
+        logging.info(
+            "[model_downloader] starting GET %s (auth=%s)",
+            session.url, "yes" if "Authorization" in headers else "no",
+        )
+        async with http.get(
+            session.url,
+            allow_redirects=True,
+            timeout=REQUEST_TIMEOUT,
+            headers=headers,
+        ) as resp:
+            if resp.status != 200:
+                # Capture a snippet of the response body so 4xx/5xx aren't
+                # opaque in the logs — HF returns JSON or HTML with a
+                # human-readable reason on failures.
+                body_snippet = await _read_short(resp)
+                logging.warning(
+                    "[model_downloader] GET %s failed: status=%d final_url=%s body=%s",
+                    session.url, resp.status, str(resp.url), body_snippet,
+                )
+                raise DownloadError(
+                    f"unexpected HTTP {resp.status} fetching {session.url}: {body_snippet}",
+                    status=resp.status,
+                )
+
+            total = parse_content_length(resp.headers.get("Content-Length"))
+            DOWNLOAD_SERVER.update_progress(session, 0, total)
+
+            with open(tmp_path, "wb") as f:
+                async for chunk in resp.content.iter_chunked(CHUNK_SIZE):
+                    # Cancellation check between chunks. Cheap and means
+                    # cancellation latency is bounded by one chunk plus
+                    # one ``write()`` — typically well under a second
+                    # even on slow disks.
+                    if not DOWNLOAD_SERVER.is_active(session):
+                        raise DownloadCancelled()
+                    f.write(chunk)
+                    bytes_seen += len(chunk)
+                    DOWNLOAD_SERVER.update_progress(session, bytes_seen, total)
+
+        # Final cancellation check before we promote the .tmp to the real
+        # filename — avoids the awkward case where cancel arrives during
+        # the very last chunk and we'd otherwise commit anyway.
+        if not DOWNLOAD_SERVER.is_active(session):
+            raise DownloadCancelled()
+
+        # Size verification before commit. aiohttp already raises
+        # ClientPayloadError on a truncated Content-Length/chunked body,
+        # but this also catches the HTTP/1.0-style case (no Content-Length
+        # + Connection: close) where a short read can masquerade as a
+        # complete download.
+        if total is not None and bytes_seen != total:
+            raise DownloadError(
+                f"size mismatch for {session.model_id}: "
+                f"got {bytes_seen} of {total} bytes from {session.url}"
+            )
+
+        # Atomic rename. os.replace is atomic within the same filesystem,
+        # which is guaranteed here because tmp lives alongside final_path.
+        os.replace(tmp_path, final_path)
+        logging.info(
+            "[model_downloader] downloaded %s (%d bytes) from %s",
+            session.model_id, bytes_seen, session.url,
+        )
+        return final_path
+
+    except DownloadCancelled:
+        logging.info("[model_downloader] cancelled: %s", session.model_id)
+        _remove_if_exists(tmp_path)
+        raise
+    except Exception as e:
+        logging.warning(
+            "[model_downloader] failed: %s from %s: %s: %s",
+            session.model_id, session.url, type(e).__name__, e,
+            exc_info=True,
+        )
+        _remove_if_exists(tmp_path)
+        raise
+    finally:
+        # In all terminal states (success / cancel / error) drop the
+        # session from the registry. Idempotent — only removes if we're
+        # still the live epoch for this model_id.
+        DOWNLOAD_SERVER.finish(session)
+
+
+class DownloadError(Exception):
+    """Network / protocol error during a download."""
+
+    def __init__(self, message: str, status: Optional[int] = None) -> None:
+        super().__init__(message)
+        self.status = status
+
+
+async def _read_short(resp: aiohttp.ClientResponse, limit: int = 512) -> str:
+    """Read up to ``limit`` bytes of a response body for logging.
+
+    Used to surface the JSON/HTML reason from an HF non-2xx response in
+    server logs instead of just the status code. Best-effort: any
+    error here is swallowed.
+    """
+    try:
+        raw = await resp.content.read(limit)
+        return raw.decode("utf-8", errors="replace").strip()
+    except Exception:
+        return "<unreadable>"
+
+
+def _auth_headers_for(url: str) -> dict[str, str]:
+    """Return any auth headers we should add to the GET for ``url``.
+
+    For HuggingFace URLs we inject the user's OAuth access token as a
+    Bearer header — this is HF's documented way to access gated repos
+    (see ``huggingface_hub.hf_hub_download``'s wire format). For every
+    other host we send no extra headers; allowlisted public files
+    don't need them and we don't want to leak tokens to other hosts.
+    """
+    if not is_hf_url(url):
+        return {}
+    tok = HF_AUTH_STORE.get_token_sync()
+    if tok is None or not tok.access_token:
+        return {}
+    return {"Authorization": f"Bearer {tok.access_token}"}
+
+
+def _remove_if_exists(path: str) -> None:
+    try:
+        os.remove(path)
+    except FileNotFoundError:
+        pass
+    except OSError as e:
+        logging.warning("[model_downloader] could not remove %s: %s", path, e)
+
+
+async def run_batch_sequential(sessions: list[DownloadSession]) -> None:
+    """Run a list of sessions one after the other.
+
+    Each session is independent: a failure or cancellation of one does
+    not abort the rest. Cancellations are observable via the registry
+    *before* a given download starts, so a session that's been
+    pre-cancelled (cancel before the worker reached it) just gets skipped.
+    """
+    for session in sessions:
+        # If the session got cancelled before its turn, skip without
+        # touching disk. This is what makes the per-request "sequential
+        # but cancellable" semantic work.
+        if not DOWNLOAD_SERVER.is_active(session):
+            DOWNLOAD_SERVER.finish(session)
+            continue
+        try:
+            await stream_to_disk(session)
+        except DownloadCancelled:
+            # Already logged + tmp removed inside stream_to_disk.
+            continue
+        except Exception:
+            # stream_to_disk already logged. Continue with the rest of the batch.
+            continue
+
+
+def schedule_batch(sessions: list[DownloadSession]) -> asyncio.Task:
+    """Kick off ``run_batch_sequential`` on the running event loop.
+
+    Returned task is fire-and-forget; the API handler returns immediately
+    after scheduling and clients observe progress via the polling endpoints.
+    """
+    return asyncio.create_task(run_batch_sequential(sessions))

app/model_downloader/gated_detection.py

@@ -0,0 +1,245 @@
+"""Per-URL probes for the unified availability endpoint.
+
+Three cached/derived facts per URL:
+
+  - ``is_gated``         intrinsic to the model; cached forever once known.
+                         Determined by ``auth_check(repo_id, token=None)``:
+                         ``GatedRepoError`` → True, success → False.
+
+  - ``is_hf_downloadable`` depends on the *current* token; recomputed every
+                         call. For non-gated URLs this is trivially True
+                         (no HF call needed). For gated URLs we run
+                         ``auth_check`` with the stored token each call.
+
+  - ``file_size``        intrinsic to the file. Cached forever once
+                         determined (including ``None`` on transient
+                         failure — we don't retry). We only attempt the
+                         HEAD when we already know the URL is downloadable
+                         to us; that way a failed-because-gated probe
+                         never lands as a cached ``None``.
+
+Caches are per-process, in-memory; small, no eviction needed for the
+workflow-scale (~tens of URLs). Concurrent calls for the same URL
+deduplicate via per-URL ``asyncio.Lock``.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+from dataclasses import dataclass
+from typing import Optional
+
+import aiohttp
+from huggingface_hub import HfApi
+from huggingface_hub.errors import (
+    GatedRepoError,
+    HfHubHTTPError,
+    RepositoryNotFoundError,
+)
+
+from app.model_downloader.allowlist import is_url_allowed
+from app.model_downloader.hf_auth.auth_store import HF_AUTH_STORE
+from app.model_downloader.hf_url import is_hf_url, repo_id_from_url
+from app.model_downloader.http_client import get_session, parse_content_length
+
+
+_HEAD_TIMEOUT = aiohttp.ClientTimeout(total=15)
+
+
+@dataclass
+class ProbeResult:
+    file_size: Optional[int]
+    is_hf_downloadable: Optional[bool]
+
+
+# --- caches -------------------------------------------------------------- #
+
+
+# url → bool. Whether this URL's HF repo gates access. Intrinsic to the
+# model — never changes for a given URL.
+_is_gated_cache: dict[str, bool] = {}
+
+# url → Optional[int]. The file's size in bytes, ``None`` if a probe
+# was attempted and produced no answer. **Only populated when we knew
+# the URL was downloadable to us at probe time** — so gated-without-
+# access never lands a ``None`` here that we'd be stuck with after login.
+_file_size_cache: dict[str, Optional[int]] = {}
+
+# Per-URL locks for single-flight probes — when multiple polls arrive
+# in the same tick for the same URL, exactly one of them runs the HF
+# call and the others wait on the result.
+_locks: dict[str, asyncio.Lock] = {}
+
+
+def _lock_for(url: str) -> asyncio.Lock:
+    lock = _locks.get(url)
+    if lock is None:
+        lock = asyncio.Lock()
+        _locks[url] = lock
+    return lock
+
+
+def clear_caches_for_tests() -> None:
+    """Test-only: drop everything."""
+    _is_gated_cache.clear()
+    _file_size_cache.clear()
+    _locks.clear()
+
+
+# --- public entrypoint --------------------------------------------------- #
+
+
+async def probe_url(url: str) -> ProbeResult:
+    """Return downloadability + size for one URL, using caches where safe."""
+    if not is_url_allowed(url):
+        return ProbeResult(file_size=None, is_hf_downloadable=None)
+    if not is_hf_url(url):
+        # Non-HF: ``is_hf_downloadable`` is "not applicable" (None).
+        # Size we still cache so we don't HEAD on every poll.
+        size = await _get_or_probe_size(url, token=None)
+        return ProbeResult(file_size=size, is_hf_downloadable=None)
+
+    repo_id = repo_id_from_url(url)
+    if repo_id is None:
+        return ProbeResult(file_size=None, is_hf_downloadable=None)
+
+    # Determine intrinsic gating once.
+    gated = await _resolve_is_gated(url, repo_id)
+    if gated is None:
+        return ProbeResult(file_size=None, is_hf_downloadable=None)
+
+    # Compute current-token downloadability per call.
+    tok = await HF_AUTH_STORE.get_valid_token()
+    token_str: Optional[str] = tok.access_token if tok else None
+    if not gated:
+        is_hf_downloadable: Optional[bool] = True
+    else:
+        is_hf_downloadable = await _auth_check_with_token(repo_id, token_str)
+
+    if is_hf_downloadable is True:
+        size = await _get_or_probe_size(url, token=token_str)
+    else:
+        # Skip the HEAD entirely — would 401 and we'd be stuck with
+        # cached None that survives a later login.
+        size = None
+
+    return ProbeResult(file_size=size, is_hf_downloadable=is_hf_downloadable)
+
+
+# --- gated/auth probes --------------------------------------------------- #
+
+
+async def _resolve_is_gated(url: str, repo_id: str) -> Optional[bool]:
+    """Decide once whether ``repo_id`` is a gated repo."""
+    cached = _is_gated_cache.get(url)
+    if cached is not None:
+        return cached
+
+    async with _lock_for(url):
+        cached = _is_gated_cache.get(url)
+        if cached is not None:
+            return cached
+        # Probe anonymously (token=None) on purpose: an unauthenticated
+        # auth_check is what makes HF raise GatedRepoError for gated repos.
+        # With a token, a gated-but-accepted repo would succeed and look
+        # ungated.
+        try:
+            await asyncio.to_thread(_auth_check_sync, repo_id, None)
+            _is_gated_cache[url] = False
+            return False
+        except GatedRepoError:
+            _is_gated_cache[url] = True
+            return True
+        except RepositoryNotFoundError:
+            # Repo doesn't exist publicly. Treat as gated — we can't
+            # serve it without auth, and an authenticated check might
+            # still succeed if it's a private repo the user can see.
+            _is_gated_cache[url] = True
+            return True
+        except (HfHubHTTPError, Exception) as e:
+            logging.debug(
+                "[hf_auth] is_gated probe failed for %s (will retry): %s",
+                repo_id, e,
+            )
+            return None  # don't cache; retry next call
+
+
+async def _auth_check_with_token(
+    repo_id: str, token: Optional[str]
+) -> Optional[bool]:
+    """Auth-check with the supplied token. True/False/None per outcome."""
+    try:
+        await asyncio.to_thread(_auth_check_sync, repo_id, token)
+        return True
+    except GatedRepoError:
+        return False
+    except RepositoryNotFoundError:
+        return False
+    except HfHubHTTPError as e:
+        # 401/403 covers org-SSO-required, revoked tokens, and similar —
+        # all of which mean "can't fetch right now" from the user's POV.
+        status = getattr(getattr(e, "response", None), "status_code", None)
+        if status in (401, 403):
+            return False
+        logging.debug(
+            "[hf_auth] auth_check transient failure for %s: %s", repo_id, e,
+        )
+        return None
+    except Exception as e:
+        logging.warning("[hf_auth] unexpected auth_check error for %s: %s", repo_id, e)
+        return None
+
+
+def _auth_check_sync(repo_id: str, token: Optional[str]) -> None:
+    """Thin sync wrapper around ``HfApi.auth_check`` for ``asyncio.to_thread``."""
+    HfApi().auth_check(repo_id, token=token)
+
+
+# --- size probe ---------------------------------------------------------- #
+
+
+async def _get_or_probe_size(url: str, token: Optional[str]) -> Optional[int]:
+    """Return the cached size or HEAD the URL once and cache the result."""
+    if url in _file_size_cache:
+        return _file_size_cache[url]
+
+    async with _lock_for(url):
+        if url in _file_size_cache:
+            return _file_size_cache[url]
+        size = await _probe_size_once(url, token=token)
+        _file_size_cache[url] = size
+        return size
+
+
+async def _probe_size_once(url: str, token: Optional[str]) -> Optional[int]:
+    """HEAD the URL and return the file size in bytes, or None on failure.
+
+    HuggingFace serves LFS-tracked files via a 302 to a signed CDN URL.
+    The real file size lives in the non-standard ``X-Linked-Size`` header
+    on that 302 response (``Content-Length`` is the redirect-body length).
+    Disabling redirect-follow lets us read either header on the same
+    response:
+
+      - LFS files: 302 + ``X-Linked-Size``
+      - Small/non-LFS files: 200 + ``Content-Length``
+    """
+    headers = {"Authorization": f"Bearer {token}"} if token else {}
+    try:
+        session = await get_session()
+        async with session.head(
+            url, allow_redirects=False, timeout=_HEAD_TIMEOUT, headers=headers,
+        ) as resp:
+            linked = parse_content_length(resp.headers.get("X-Linked-Size"))
+            if linked is not None:
+                return linked
+            if resp.status == 200:
+                return parse_content_length(resp.headers.get("Content-Length"))
+            return None
+    except (aiohttp.ClientError, TimeoutError, OSError):
+        return None
+
+
+# Backward-compat shim so consumers that still import the old name keep
+# building during the refactor; can be removed once routes are updated.
+MetadataProbeResult = ProbeResult

app/model_downloader/hf_auth/auth_store.py

@@ -0,0 +1,121 @@
+"""In-memory token cache with lazy disk persistence + refresh.
+
+Public surface is the ``HF_AUTH_STORE`` singleton. Callers ask
+``get_valid_token()``; the store transparently refreshes from disk
+on first use, refreshes via the OAuth refresh_token if the cached
+access_token is expired, and returns ``None`` if neither path works.
+
+The refresh path imports ``oauth.refresh_access_token`` lazily to
+avoid an import cycle (oauth needs the store to save tokens it
+acquires).
+"""
+
+from __future__ import annotations
+
+import logging
+import threading
+from typing import Optional
+
+from app.model_downloader.hf_auth.token_store import (
+    Token,
+    delete_token,
+    load_token,
+    save_token,
+)
+
+
+class HfAuthStore:
+    def __init__(self) -> None:
+        self._lock = threading.Lock()
+        self._token: Optional[Token] = None
+        self._loaded_from_disk = False
+
+    def _ensure_loaded(self) -> None:
+        """Read the disk token into memory on first access."""
+        if self._loaded_from_disk:
+            return
+        with self._lock:
+            if self._loaded_from_disk:
+                return
+            self._token = load_token()
+            self._loaded_from_disk = True
+
+    def has_token(self) -> bool:
+        """Cheap check: is there any token in memory?
+
+        Does not attempt refresh; an expired-but-refreshable token still
+        counts as "logged in" from the user's perspective.
+        """
+        self._ensure_loaded()
+        return self._token is not None
+
+    def _store_token_locked(self, token: Token) -> None:
+        """Set the in-memory token and persist it to disk.
+
+        Caller must already hold ``self._lock``. Keeping the disk write inside
+        the lock means memory and disk flip together — a concurrent ``clear()``
+        or refresh can't interleave between them.
+        """
+        self._token = token
+        self._loaded_from_disk = True
+        save_token(token)
+
+    def set_token(self, token: Token) -> None:
+        """Replace the in-memory token and persist to disk (atomically)."""
+        with self._lock:
+            self._store_token_locked(token)
+
+    def clear(self) -> None:
+        """Forget the token in memory and on disk (logout)."""
+        with self._lock:
+            self._token = None
+            self._loaded_from_disk = True
+            delete_token()
+
+    def get_token_sync(self) -> Optional[Token]:
+        """Return the cached token without refreshing.
+
+        Sync callers (e.g. constructing an Authorization header in a
+        non-async path) use this. They accept an expired token over
+        ``None``; HF will simply return 401 and the caller can decide
+        what to do.
+        """
+        self._ensure_loaded()
+        return self._token
+
+    async def get_valid_token(self) -> Optional[Token]:
+        """Return a fresh token, refreshing via OAuth if necessary.
+
+        Returns ``None`` if there's no cached token at all, or if the
+        cached token is expired and refresh failed. Callers should
+        treat that as "user is not logged in".
+        """
+        self._ensure_loaded()
+        with self._lock:
+            tok = self._token
+        if tok is None:
+            return None
+        if tok.is_valid():
+            return tok
+        if not tok.refresh_token:
+            return None
+
+        # Lazy import to avoid the oauth ↔ store import cycle.
+        from app.model_downloader.hf_auth.oauth import refresh_access_token
+
+        try:
+            refreshed = await refresh_access_token(tok.refresh_token)
+        except Exception as e:
+            logging.warning("[hf_auth] token refresh failed: %s", e)
+            return None
+
+        with self._lock:
+            # If a logout (clear) or another update replaced the token while we
+            # were awaiting the refresh, don't resurrect the old session.
+            if self._token is not tok:
+                return None
+            self._store_token_locked(refreshed)
+        return refreshed
+
+
+HF_AUTH_STORE = HfAuthStore()

app/model_downloader/hf_auth/eligibility.py

@@ -0,0 +1,55 @@
+"""Whether this deployment is allowed to do interactive HF OAuth.
+
+We only let the server hold a HuggingFace token under a strict trust
+assumption: this is a *single tenant local* install. Concretely:
+
+  - The server is bound to a loopback address. SSH tunneling /
+    reverse-proxies can defeat this, but it's the strongest signal
+    we have without an authentication system.
+  - ``--multi-user`` is off. A shared token used implicitly by multiple
+    declared users would be a footgun — one user's gated downloads
+    would silently authenticate as another.
+
+Anything else and the frontend hides the HF login UI entirely; gated
+models continue to show the "acquire it manually" message.
+"""
+
+from __future__ import annotations
+
+import ipaddress
+import socket
+
+from comfy.cli_args import args
+
+
+def _is_loopback(host: str | None) -> bool:
+    """Duplicates ``server.is_loopback`` (small, no shared module yet).
+
+    Resolves a host or IP literal to whether it lives on the loopback
+    interface (127.0.0.0/8 for IPv4, ::1 for IPv6). Returns False for
+    ``0.0.0.0`` / ``::`` because those are bind-all wildcards, not
+    loopback.
+    """
+    if host is None:
+        return False
+    try:
+        return ipaddress.ip_address(host).is_loopback
+    except ValueError:
+        pass
+
+    loopback = False
+    for family in (socket.AF_INET, socket.AF_INET6):
+        try:
+            r = socket.getaddrinfo(host, None, family, socket.SOCK_STREAM)
+            for _family, _, _, _, sockaddr in r:
+                if not ipaddress.ip_address(sockaddr[0]).is_loopback:
+                    return loopback
+                loopback = True
+        except socket.gaierror:
+            pass
+    return loopback
+
+
+def is_hf_auth_eligible() -> bool:
+    """True iff this deployment may surface the HF OAuth flow."""
+    return _is_loopback(args.listen) and not args.multi_user

app/model_downloader/hf_auth/oauth.py

@@ -0,0 +1,301 @@
+"""OAuth 2.0 PKCE flow against HuggingFace's authorization server.
+
+Wired so that ``POST /api/hf-auth-login-start`` can:
+  1. Generate state + PKCE verifier/challenge in this process.
+  2. Spin up a short-lived loopback HTTP server at port 41954 to
+     receive the redirect callback from HF.
+  3. Return the ``authorize_url`` for the frontend to open in a new tab.
+
+After the user grants consent on huggingface.co, HF redirects to the
+local callback URL with ``code`` and ``state``. The callback server
+validates ``state`` (CSRF), exchanges the code for tokens via PKCE,
+hands the resulting Token to ``HF_AUTH_STORE.set_token``, and shuts
+itself down.
+
+Before this can be exercised end-to-end a maintainer must register a
+HuggingFace OAuth app and substitute the ``HF_CLIENT_ID`` placeholder
+below. See the comment above the constant for the exact steps.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import base64
+import hashlib
+import logging
+import secrets
+import threading
+import time
+
+import aiohttp
+from aiohttp import web
+
+from app.model_downloader.hf_auth.auth_store import HF_AUTH_STORE
+from app.model_downloader.hf_auth.token_store import Token
+from app.model_downloader.http_client import get_session
+
+
+# --- HF OAuth app registration -------------------------------------------- #
+# NOTE: The OAuth client_id below is a placeholder. Before this feature can be
+# exercised end-to-end, a maintainer must register a HuggingFace OAuth app
+# under a Comfy-Org-controlled HF account and substitute its client_id here.
+# Detailed walkthrough is in docs/server-side-model-downloads-handover.html
+# ("HuggingFace OAuth app setup" section). Short version:
+#   1. huggingface.co → Settings → Connected Apps → "Create app"
+#   2. Default Scopes: check ``openid`` + ``profile`` (User Info) and
+#      ``gated-repos`` (Repository Access). Leave everything else off.
+#   3. Redirect URLs: exactly ``http://127.0.0.1:41954/api/auth/huggingface/callback``
+#      — must match ``REDIRECT_URI`` below; change both in lockstep if you
+#      change ``CALLBACK_PORT``.
+#   4. Save → copy the resulting Client ID into ``HF_CLIENT_ID`` below.
+# The client_id is not a secret (it travels through the user's browser in
+# plaintext); HF's "Public app" type means there's no client secret to
+# manage — PKCE replaces it.
+HF_CLIENT_ID = "REPLACE_ME_WITH_COMFY_ORG_HF_OAUTH_CLIENT_ID"
+
+CALLBACK_HOST = "127.0.0.1"
+CALLBACK_PORT = 41954
+CALLBACK_PATH = "/api/auth/huggingface/callback"
+REDIRECT_URI = f"http://{CALLBACK_HOST}:{CALLBACK_PORT}{CALLBACK_PATH}"
+
+AUTHORIZE_URL = "https://huggingface.co/oauth/authorize"
+TOKEN_URL = "https://huggingface.co/oauth/token"
+_TOKEN_REQUEST_TIMEOUT = aiohttp.ClientTimeout(total=30)
+# Minimal scope set for the feature:
+#   - openid       : required by HF when the app uses OIDC at all
+#   - profile      : lets ``HfApi.whoami(token=...)`` return a username for the
+#                    settings UI; cosmetic but expected
+#   - gated-repos  : grants the token enough to call ``auth_check`` and
+#                    download files from public gated repos the user has
+#                    accepted the license for. The wider ``read-repos`` scope
+#                    would also work (it includes ``gated-repos``) but it
+#                    additionally grants private-repo read access, which we
+#                    don't need and which makes the consent screen scarier
+#                    for the user.
+SCOPE = "openid profile gated-repos"
+
+# Maximum time the callback server stays up waiting for the user to
+# complete consent on huggingface.co. Past this, the port closes and
+# the user has to click "Log in" again.
+CALLBACK_TIMEOUT_SECS = 300
+
+
+# Process-wide lock so two simultaneous /api/hf-auth-login-start
+# requests don't fight over port CALLBACK_PORT.
+_OAUTH_LOCK = threading.Lock()
+
+
+class OAuthInProgressError(Exception):
+    """Another OAuth attempt is already running."""
+
+
+class OAuthCallbackError(Exception):
+    """The OAuth callback returned an error (HF denied, port stolen, etc.)."""
+
+
+# --- PKCE primitives ------------------------------------------------------ #
+
+
+def _make_pkce() -> tuple[str, str, str]:
+    """Return ``(verifier, challenge, state)``.
+
+    Verifier never leaves this process. Challenge and state travel
+    through the user's browser. State is checked on the callback to
+    prevent a malicious cross-origin redirect from injecting a token.
+    """
+    verifier = secrets.token_urlsafe(64)
+    challenge = (
+        base64.urlsafe_b64encode(hashlib.sha256(verifier.encode("ascii")).digest())
+        .rstrip(b"=")
+        .decode("ascii")
+    )
+    state = secrets.token_urlsafe(32)
+    return verifier, challenge, state
+
+
+def _build_authorize_url(challenge: str, state: str) -> str:
+    from urllib.parse import urlencode
+
+    params = {
+        "client_id": HF_CLIENT_ID,
+        "redirect_uri": REDIRECT_URI,
+        "response_type": "code",
+        "scope": SCOPE,
+        "state": state,
+        "code_challenge": challenge,
+        "code_challenge_method": "S256",
+    }
+    return f"{AUTHORIZE_URL}?{urlencode(params)}"
+
+
+# --- Token exchange ------------------------------------------------------- #
+
+
+async def _exchange_code(code: str, verifier: str) -> Token:
+    """Trade the authorization code for an access+refresh token pair."""
+    data = {
+        "grant_type": "authorization_code",
+        "code": code,
+        "redirect_uri": REDIRECT_URI,
+        "client_id": HF_CLIENT_ID,
+        "code_verifier": verifier,
+    }
+    session = await get_session()
+    async with session.post(TOKEN_URL, data=data, timeout=_TOKEN_REQUEST_TIMEOUT) as resp:
+        resp.raise_for_status()
+        body = await resp.json()
+    return Token(
+        access_token=body["access_token"],
+        refresh_token=body.get("refresh_token"),
+        expires_at=time.time() + float(body.get("expires_in", 3600)),
+        scope=body.get("scope", SCOPE),
+    )
+
+
+async def refresh_access_token(refresh_token: str) -> Token:
+    """Trade a refresh_token for a new access (+ possibly refresh) token."""
+    data = {
+        "grant_type": "refresh_token",
+        "refresh_token": refresh_token,
+        "client_id": HF_CLIENT_ID,
+    }
+    session = await get_session()
+    async with session.post(TOKEN_URL, data=data, timeout=_TOKEN_REQUEST_TIMEOUT) as resp:
+        resp.raise_for_status()
+        body = await resp.json()
+    return Token(
+        access_token=body["access_token"],
+        # If HF doesn't rotate refresh tokens, keep using the existing one.
+        refresh_token=body.get("refresh_token", refresh_token),
+        expires_at=time.time() + float(body.get("expires_in", 3600)),
+        scope=body.get("scope", SCOPE),
+    )
+
+
+# --- Callback server ------------------------------------------------------ #
+
+
+async def start_login_flow() -> str:
+    """Begin one OAuth attempt: spawn the callback server, return the URL.
+
+    Returns the URL the frontend should open in a new tab. Raises
+    ``OAuthInProgressError`` if another attempt is already running.
+    The callback server runs in the background until the user
+    completes consent or until ``CALLBACK_TIMEOUT_SECS`` elapses;
+    either way the lock + port are released afterward.
+    """
+    if not _OAUTH_LOCK.acquire(blocking=False):
+        raise OAuthInProgressError()
+
+    try:
+        verifier, challenge, state = _make_pkce()
+        authorize_url = _build_authorize_url(challenge, state)
+        ready: asyncio.Future[None] = asyncio.get_event_loop().create_future()
+    except BaseException:
+        # Failed before handing the lock to the callback-server task: release it
+        # here. (Once the task is spawned, it owns releasing the lock.)
+        _OAUTH_LOCK.release()
+        raise
+
+    asyncio.create_task(_run_callback_server(verifier, state, ready))
+    # Don't return the URL until the callback server is actually bound and
+    # listening — otherwise HF could redirect to a port nothing is serving and
+    # the login would silently dead-end. ``ready`` raises if the bind failed.
+    await ready
+    return authorize_url
+
+
+async def _run_callback_server(
+    verifier: str, expected_state: str, ready: "asyncio.Future[None]"
+) -> None:
+    """Listen for HF's redirect once, capture the token, then shut down.
+
+    Signals ``ready`` once the port is bound (or with an exception if the bind
+    fails), so ``start_login_flow`` only hands back a URL on a live server.
+    """
+    received: asyncio.Future[Token] = asyncio.get_event_loop().create_future()
+
+    async def handler(request: web.Request) -> web.Response:
+        try:
+            if request.query.get("state") != expected_state:
+                return web.Response(status=400, text="state mismatch")
+            err = request.query.get("error")
+            if err:
+                received.set_exception(OAuthCallbackError(f"HF returned: {err}"))
+                return web.Response(status=400, text=f"OAuth error: {err}")
+            code = request.query.get("code")
+            if not code:
+                return web.Response(status=400, text="missing code")
+            tok = await _exchange_code(code, verifier)
+            if not received.done():
+                received.set_result(tok)
+            return web.Response(
+                content_type="text/html",
+                text=(
+                    "<html><body style='font-family:sans-serif;padding:40px'>"
+                    "<h2>HuggingFace login successful</h2>"
+                    "<p>You can close this tab and return to ComfyUI.</p>"
+                    "</body></html>"
+                ),
+            )
+        except Exception as exc:
+            if not received.done():
+                received.set_exception(exc)
+            return web.Response(status=500, text=str(exc))
+
+    app = web.Application()
+    app.router.add_get(CALLBACK_PATH, handler)
+    runner = web.AppRunner(app)
+    try:
+        await runner.setup()
+        site = web.TCPSite(runner, CALLBACK_HOST, CALLBACK_PORT, reuse_address=True)
+        await site.start()
+    except Exception as e:
+        # Couldn't bind the callback port (commonly already in use). Tell the
+        # waiting start_login_flow via ``ready`` so it surfaces a clear error
+        # instead of returning a dead URL, and release the lock for next time.
+        logging.warning("[hf_auth] could not start callback server: %s", e)
+        if not ready.done():
+            ready.set_exception(
+                OAuthCallbackError(f"could not bind callback port {CALLBACK_PORT}: {e}")
+            )
+        _OAUTH_LOCK.release()
+        return
+
+    # Bound and listening — now it's safe for start_login_flow to return the URL.
+    if not ready.done():
+        ready.set_result(None)
+
+    try:
+        token = await asyncio.wait_for(received, timeout=CALLBACK_TIMEOUT_SECS)
+    except asyncio.TimeoutError:
+        logging.info("[hf_auth] OAuth login timed out after %ds", CALLBACK_TIMEOUT_SECS)
+        return
+    except OAuthCallbackError as e:
+        logging.warning("[hf_auth] OAuth callback error: %s", e)
+        return
+    except Exception as e:
+        logging.warning("[hf_auth] unexpected OAuth failure: %s", e)
+        return
+    else:
+        HF_AUTH_STORE.set_token(token)
+        logging.info("[hf_auth] OAuth login complete")
+    finally:
+        await runner.cleanup()
+        if _OAUTH_LOCK.locked():
+            _OAUTH_LOCK.release()
+
+
+def is_login_in_progress() -> bool:
+    """True iff a callback server is currently bound + waiting."""
+    return _OAUTH_LOCK.locked()
+
+
+# Re-export for callers that only want the URL builder (e.g. tests).
+__all__ = [
+    "start_login_flow",
+    "refresh_access_token",
+    "is_login_in_progress",
+    "OAuthInProgressError",
+    "CALLBACK_TIMEOUT_SECS",
+]

app/model_downloader/hf_auth/token_store.py

@@ -0,0 +1,94 @@
+"""On-disk persistence for the HuggingFace OAuth token.
+
+The token shape mirrors what HF returns on the token exchange: an
+``access_token``, an optional ``refresh_token``, the absolute epoch at
+which the access token expires, and the granted scope. We persist
+this so logging in once survives ComfyUI restarts under the internal
+``__hf_auth`` system-user directory; the file is mode ``0600`` so only
+the OS user can read it.
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import os
+import stat
+import time
+from dataclasses import asdict, dataclass
+from typing import Optional
+
+import folder_paths
+
+
+# Treat a token as expired this many seconds before its server-reported
+# ``expires_at`` so we don't try to use a token mid-request only for it
+# to flip stale between auth_check and the actual GET.
+EXPIRY_BUFFER_SECS = 60
+
+TOKEN_FILENAME = "hf_auth_token.json"
+
+
+@dataclass
+class Token:
+    """One OAuth token + the metadata we need to use it."""
+    access_token: str
+    refresh_token: Optional[str]
+    expires_at: float  # absolute epoch seconds
+    scope: str = ""
+
+    def is_valid(self) -> bool:
+        """True iff we can use this token right now."""
+        return (
+            bool(self.access_token)
+            and (self.expires_at - time.time() > EXPIRY_BUFFER_SECS)
+        )
+
+
+def _token_dir() -> str:
+    return folder_paths.get_system_user_directory("hf_auth")
+
+
+def _token_path() -> str:
+    return os.path.join(_token_dir(), TOKEN_FILENAME)
+
+
+def load_token() -> Optional[Token]:
+    """Read the persisted token, returning ``None`` if absent or corrupt."""
+    path = _token_path()
+    if not os.path.exists(path):
+        return None
+    try:
+        with open(path, "r", encoding="utf-8") as f:
+            data = json.load(f)
+        return Token(**data)
+    except (OSError, json.JSONDecodeError, TypeError) as e:
+        logging.warning("[hf_auth] could not load token at %s: %s", path, e)
+        return None
+
+
+def save_token(token: Token) -> None:
+    """Atomically write the token with 0600 permissions."""
+    path = _token_path()
+    os.makedirs(os.path.dirname(path), exist_ok=True)
+    tmp = path + ".tmp"
+    fd = os.open(tmp, os.O_WRONLY | os.O_CREAT | os.O_TRUNC, 0o600)
+    with os.fdopen(fd, "w", encoding="utf-8") as f:
+        json.dump(asdict(token), f)
+    os.replace(tmp, path)
+    try:
+        os.chmod(path, stat.S_IRUSR | stat.S_IWUSR)
+    except OSError as e:
+        # On Windows / weird filesystems chmod may be a no-op; not fatal.
+        logging.debug("[hf_auth] chmod 0600 on %s failed: %s", path, e)
+
+
+def delete_token() -> None:
+    """Remove the persisted token; no-op if it doesn't exist."""
+    path = _token_path()
+    try:
+        os.remove(path)
+    except FileNotFoundError:
+        pass
+    except OSError as e:
+        logging.warning("[hf_auth] could not remove token at %s: %s", path, e)

app/model_downloader/hf_url.py

@@ -0,0 +1,41 @@
+"""Parsers for the ``huggingface.co`` URL shape we accept in workflows.
+
+The download API accepts URLs of the form
+``https://huggingface.co/<org>/<repo>/resolve/<rev>/<path/to/file>``.
+We need to recover ``<org>/<repo>`` (the *repo_id*) from such URLs for
+``huggingface_hub`` API calls (notably ``HfApi.auth_check``).
+"""
+
+from __future__ import annotations
+
+from typing import Optional
+from urllib.parse import urlparse
+
+_HF_HOST = "huggingface.co"
+
+
+def is_hf_url(url: str) -> bool:
+    """Cheap host check — does this URL point at huggingface.co?"""
+    try:
+        return urlparse(url).hostname == _HF_HOST
+    except ValueError:
+        return False
+
+
+def repo_id_from_url(url: str) -> Optional[str]:
+    """Extract ``<org>/<repo>`` from an HF model file URL.
+
+    Returns ``None`` if the URL isn't on huggingface.co or doesn't look
+    like a model-file URL. The expected shape is
+    ``/<org>/<repo>/resolve/<rev>/<path>`` — anything else
+    (datasets, spaces, /tree/, /blob/, …) we treat as out of scope here.
+    """
+    if not is_hf_url(url):
+        return None
+    parts = urlparse(url).path.lstrip("/").split("/")
+    if len(parts) < 4 or parts[2] != "resolve":
+        return None
+    org, repo = parts[0], parts[1]
+    if not org or not repo:
+        return None
+    return f"{org}/{repo}"

app/model_downloader/http_client.py

@@ -0,0 +1,63 @@
+"""Lazy module-level aiohttp ClientSession.
+
+A single shared session means TLS handshakes are reused across HEAD probes
+and the subsequent GETs to the same host (HuggingFace is the dominant
+case), which is a noticeable speedup on cold connections.
+
+We deliberately don't close the session at process exit — aiohttp's
+warning about unclosed sessions is benign at shutdown, and adding atexit
+plumbing buys nothing because the OS reclaims the sockets anyway. The
+session lifetime is the lifetime of the Python process.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import ssl
+from typing import Optional
+
+import aiohttp
+import certifi
+
+
+# Larger per-host pool than aiohttp's default (=100 total / =0 per host)
+# so concurrent gated probes + a download to the same host don't queue.
+_CONNECTOR_LIMIT_PER_HOST = 8
+
+_session: Optional[aiohttp.ClientSession] = None
+_lock = asyncio.Lock()
+
+
+def ssl_context() -> ssl.SSLContext:
+    """TLS context pinned to certifi's CA bundle.
+    aiohttp's default context uses the OS trust store, which isn't wired up
+    on some Python installs (python.org macOS, slim containers) — there TLS
+    to huggingface.co fails with CERTIFICATE_VERIFY_FAILED.
+    """
+    return ssl.create_default_context(cafile=certifi.where())
+
+
+async def get_session() -> aiohttp.ClientSession:
+    """Return the shared session, creating it on first call."""
+    global _session
+    if _session is not None and not _session.closed:
+        return _session
+    async with _lock:
+        if _session is None or _session.closed:
+            connector = aiohttp.TCPConnector(
+                limit_per_host=_CONNECTOR_LIMIT_PER_HOST,
+                ssl=ssl_context(),
+            )
+            _session = aiohttp.ClientSession(connector=connector)
+    return _session
+
+
+def parse_content_length(value: Optional[str]) -> Optional[int]:
+    """Parse a byte-count header value, or None if absent/malformed/negative."""
+    if not value:
+        return None
+    try:
+        n = int(value)
+    except ValueError:
+        return None
+    return n if n >= 0 else None

app/model_downloader/paths.py

@@ -0,0 +1,111 @@
+"""Path resolution for model downloads.
+
+Model identifiers used across the download API are *relative destination
+paths* of the form ``<directory>/<filename>`` (e.g. ``loras/my_lora.safetensors``).
+This module turns one of those identifiers into an absolute on-disk path
+under one of ComfyUI's registered model folders, while rejecting unknown
+folders, path traversal, and other ill-formed inputs.
+"""
+
+import os
+import re
+from typing import Optional, Tuple
+
+import folder_paths
+
+
+# Constrain components so a model_id can never escape its target directory.
+# - directory: a single path segment of safe chars
+# - filename: a single path segment of safe chars, must end with a model extension
+_SEGMENT_RE = re.compile(r"^[A-Za-z0-9._-]+$")
+
+# Destination filename must name a model file (same set as the URL allowlist),
+# so a download can't land as e.g. ``foo.txt`` that ComfyUI won't recognise.
+_MODEL_EXTENSIONS = (".safetensors", ".sft", ".ckpt", ".pth", ".pt")
+
+# Distinctive temp suffix so the startup orphan-sweep only removes files THIS
+# subsystem created — never unrelated ``*.tmp`` files in the model dirs.
+_TMP_SUFFIX = ".comfy-download.tmp"
+
+
+class InvalidModelId(ValueError):
+    """Raised when a model_id is syntactically invalid or refers to an
+    unknown model folder."""
+
+
+def parse_model_id(model_id: str) -> Tuple[str, str]:
+    """Split ``<directory>/<filename>`` and validate both components.
+
+    Returns ``(directory, filename)``. Raises ``InvalidModelId`` on
+    malformed input. Does NOT touch the filesystem.
+    """
+    if not isinstance(model_id, str) or "/" not in model_id:
+        raise InvalidModelId(f"model_id must be '<directory>/<filename>', got {model_id!r}")
+    directory, _, filename = model_id.partition("/")
+    if "/" in filename or not directory or not filename:
+        raise InvalidModelId(f"model_id must be exactly one '/' separator, got {model_id!r}")
+    if not _SEGMENT_RE.match(directory):
+        raise InvalidModelId(f"invalid directory segment {directory!r}")
+    if not _SEGMENT_RE.match(filename):
+        raise InvalidModelId(f"invalid filename segment {filename!r}")
+    if not filename.endswith(_MODEL_EXTENSIONS):
+        raise InvalidModelId(
+            f"filename must end with a model extension {_MODEL_EXTENSIONS}, got {filename!r}"
+        )
+    if directory not in folder_paths.folder_names_and_paths:
+        raise InvalidModelId(f"unknown model folder {directory!r}")
+    return directory, filename
+
+
+def resolve_existing(model_id: str) -> Optional[str]:
+    """Return the absolute path of an installed model, or None if missing.
+
+    Honours ``extra_model_paths.yaml`` transparently via
+    ``folder_paths.get_full_path``.
+    """
+    directory, filename = parse_model_id(model_id)
+    return folder_paths.get_full_path(directory, filename)
+
+
+def resolve_destination(model_id: str, epoch: int = 0) -> Tuple[str, str]:
+    """Return ``(final_path, tmp_path)`` for a download.
+
+    Downloads land at the first registered path for the model's directory
+    (the "primary" location). The temp sibling is the write target, atomically
+    renamed onto ``final_path`` on success.
+
+    ``tmp_path`` embeds the session ``epoch`` so a cancel+retry of the same
+    model never shares a temp path between the old (cancelling) worker and the
+    new attempt — otherwise the old worker's rollback could delete the new
+    worker's in-progress file. The distinctive suffix scopes the orphan sweep.
+    """
+    directory, filename = parse_model_id(model_id)
+    roots = folder_paths.get_folder_paths(directory)
+    if not roots:
+        raise InvalidModelId(f"no on-disk path registered for folder {directory!r}")
+    root = roots[0]
+    final_path = os.path.join(root, filename)
+    tmp_path = f"{final_path}.{epoch}{_TMP_SUFFIX}"
+    return final_path, tmp_path
+
+
+def iter_all_tmp_paths():
+    """Yield this subsystem's temp files under every registered model folder.
+
+    Matches only our distinctive ``_TMP_SUFFIX`` (not every ``*.tmp``) so the
+    startup orphan-sweep can't delete temp files created by other tools.
+    """
+    seen_roots: set[str] = set()
+    for directory in folder_paths.folder_names_and_paths.keys():
+        for root in folder_paths.get_folder_paths(directory):
+            if root in seen_roots or not os.path.isdir(root):
+                continue
+            seen_roots.add(root)
+            try:
+                for entry in os.scandir(root):
+                    if entry.is_file() and entry.name.endswith(_TMP_SUFFIX):
+                        yield entry.path
+            except OSError:
+                # Folder might be unreadable / missing on certain mounts —
+                # not fatal, just skip it.
+                continue

app/model_manager.py

@@ -50,21 +50,45 @@ class ModelFileManager:
         @routes.get("/experiment/models/preview/{folder}/{path_index}/{filename:.*}")
         async def get_model_preview(request):
             folder_name = request.match_info.get("folder", None)
-            path_index = int(request.match_info.get("path_index", None))
             filename = request.match_info.get("filename", None)
 
             if folder_name not in folder_paths.folder_names_and_paths:
                 return web.Response(status=404)
 
+            # The "{filename:.*}" capture also matches the empty string, which
+            # would resolve to the folder itself; reject it explicitly.
+            if not filename:
+                return web.Response(status=400)
+
+            try:
+                path_index = int(request.match_info.get("path_index", None))
+            except (TypeError, ValueError):
+                return web.Response(status=400)
+
             folders = folder_paths.folder_names_and_paths[folder_name]
+            if path_index < 0 or path_index >= len(folders[0]):
+                return web.Response(status=404)
             folder = folders[0][path_index]
-            full_filename = os.path.join(folder, filename)
+            full_filename = os.path.normpath(os.path.join(folder, filename))
+
+            # Prevent path traversal: the requested file must stay within the
+            # configured model folder. `filename` is an unrestricted ".*" capture,
+            # so values like "../../../../etc/passwd" would otherwise escape it.
+            if not folder_paths.is_within_directory(folder, full_filename):
+                return web.Response(status=403)
 
             previews = self.get_model_previews(full_filename)
             default_preview = previews[0] if len(previews) > 0 else None
             if default_preview is None or (isinstance(default_preview, str) and not os.path.isfile(default_preview)):
                 return web.Response(status=404)
 
+            # The preview is selected by a glob inside get_model_previews, so a
+            # companion file (e.g. "model.preview.png") could itself be a symlink
+            # resolving outside the model folder. Re-validate the file actually
+            # opened: is_within_directory realpaths it, catching symlink escape.
+            if isinstance(default_preview, str) and not folder_paths.is_within_directory(folder, default_preview):
+                return web.Response(status=403)
+
             try:
                 with Image.open(default_preview) as img:
                     img_bytes = BytesIO()

app/user_manager.py

@@ -6,6 +6,7 @@ import glob
 import shutil
 import logging
 import tempfile
+import mimetypes
 from aiohttp import web
 from urllib import parse
 from comfy.cli_args import args
@@ -336,7 +337,20 @@ class UserManager():
             if not isinstance(path, str):
                 return path
 
-            return web.FileResponse(path)
+            # User data files are arbitrary user-supplied content and are never
+            # meant to render inline. Disable MIME sniffing and force a download
+            # so uploaded markup/scripts can't execute in the app origin (stored
+            # XSS). Content-Disposition: attachment is the load-bearing guard;
+            # the content-type override and nosniff are defence in depth.
+            content_type = mimetypes.guess_type(path)[0] or 'application/octet-stream'
+            if folder_paths.is_dangerous_content_type(content_type):
+                content_type = 'application/octet-stream'
+
+            return web.FileResponse(path, headers={
+                "Content-Type": content_type,
+                "X-Content-Type-Options": "nosniff",
+                "Content-Disposition": "attachment",
+            })
 
         @routes.post("/userdata/{file}")
         async def post_userdata(request):

comfy/cli_args.py

@@ -240,6 +240,7 @@ database_default_path = os.path.abspath(
 )
 parser.add_argument("--database-url", type=str, default=f"sqlite:///{database_default_path}", help="Specify the database URL, e.g. for an in-memory database you can use 'sqlite:///:memory:'.")
 parser.add_argument("--enable-assets", action="store_true", help="Enable the assets system (API routes, database synchronization, and background scanning).")
+parser.add_argument("--enable-asset-hashing", action="store_true", help="Compute blake3 content hashes when scanning assets. Hashing enables future asset-portability features (deduplication, cross-machine model resolution) but adds startup cost and per-output cost on large models directories. Off by default; enable to opt in.")
 parser.add_argument("--feature-flag", type=str, action='append', default=[], metavar="KEY[=VALUE]", help="Set a server feature flag. Use KEY=VALUE to set an explicit value, or bare KEY to set it to true. Can be specified multiple times. Boolean values (true/false) and numbers are auto-converted. Examples: --feature-flag show_signin_button=true  or  --feature-flag show_signin_button")
 parser.add_argument("--list-feature-flags", action="store_true", help="Print the registry of known CLI-settable feature flags as JSON and exit.")
 

comfy/sd1_clip.py

@@ -543,18 +543,24 @@ class SDTokenizer:
     def _try_get_embedding(self, embedding_name:str):
         '''
         Takes a potential embedding name and tries to retrieve it.
-        Returns a Tuple consisting of the embedding and any leftover string, embedding can be None.
+        Returns a Tuple consisting of the embedding, the cleaned embedding name, and any leftover string, embedding can be None.
         '''
         split_embed = embedding_name.split()
         embedding_name = split_embed[0]
         leftover = ' '.join(split_embed[1:])
+
+        match = re.search(r'[<\[]', embedding_name)
+        if match is not None:
+            leftover = embedding_name[match.start():] + (" " + leftover if leftover else "")
+            embedding_name = embedding_name[:match.start()]
+
         embed = load_embed(embedding_name, self.embedding_directory, self.embedding_size, self.embedding_key)
         if embed is None:
             stripped = embedding_name.strip(',')
             if len(stripped) < len(embedding_name):
                 embed = load_embed(stripped, self.embedding_directory, self.embedding_size, self.embedding_key)
-                return (embed, "{} {}".format(embedding_name[len(stripped):], leftover))
-        return (embed, leftover)
+                return (embed, embedding_name, "{} {}".format(embedding_name[len(stripped):], leftover))
+        return (embed, embedding_name, leftover)
 
     def pad_tokens(self, tokens, amount):
         if self.pad_left:
@@ -585,7 +591,7 @@ class SDTokenizer:
         tokens = []
         for weighted_segment, weight in parsed_weights:
             to_tokenize = unescape_important(weighted_segment)
-            split = re.split(' {0}|\n{0}'.format(self.embedding_identifier), to_tokenize)
+            split = re.split(r'(?<=\s){}'.format(re.escape(self.embedding_identifier)), to_tokenize)
             to_tokenize = [split[0]]
             for i in range(1, len(split)):
                 to_tokenize.append("{}{}".format(self.embedding_identifier, split[i]))
@@ -595,7 +601,7 @@ class SDTokenizer:
                 # if we find an embedding, deal with the embedding
                 if word.startswith(self.embedding_identifier) and self.embedding_directory is not None:
                     embedding_name = word[len(self.embedding_identifier):].strip('\n')
-                    embed, leftover = self._try_get_embedding(embedding_name)
+                    embed, embedding_name, leftover = self._try_get_embedding(embedding_name)
                     if embed is None:
                         logging.warning(f"warning, embedding:{embedding_name} does not exist, ignoring")
                     else:

comfy/text_encoders/qwen3vl.py

@@ -167,7 +167,7 @@ class Qwen3VLTokenizer(sd1_clip.SD1Tokenizer):
         embed_count = 0
         for r in tokens[key_name]:
             for i in range(len(r)):
-                if r[i][0] == 151655:  # <|image_pad|>
+                if isinstance(r[i][0], (int, float)) and r[i][0] == 151655:  # <|image_pad|>
                     if len(images) > embed_count:
                         r[i] = ({"type": "image", "data": images[embed_count], "original_type": "image"},) + r[i][1:]
                         embed_count += 1

comfy_api/feature_flags.py

@@ -98,12 +98,24 @@ def _parse_cli_feature_flags() -> dict[str, Any]:
 
 
 # Default server capabilities
+def _hf_auth_eligible_at_startup() -> bool:
+    """Snapshot eligibility once at feature-flag init time.
+
+    Imports lazily because the flags module loads very early in the
+    server boot sequence — earlier than the model_downloader package.
+    """
+    from app.model_downloader.hf_auth.eligibility import is_hf_auth_eligible
+    return is_hf_auth_eligible()
+
+
 _CORE_FEATURE_FLAGS: dict[str, Any] = {
     "supports_preview_metadata": True,
     "max_upload_size": args.max_upload_size * 1024 * 1024, # Convert MB to bytes
     "extension": {"manager": {"supports_v4": True}},
     "node_replacements": True,
     "assets": args.enable_assets,
+    "server_side_model_downloads": True,
+    "hf_auth_eligible": _hf_auth_eligible_at_startup(),
 }
 
 # CLI-provided flags cannot overwrite core flags

comfy_api_nodes/apis/bytedance.py

@@ -1,4 +1,4 @@
-from typing import Literal
+from typing import Any, Literal
 
 from pydantic import BaseModel, Field
 
@@ -316,3 +316,36 @@ VIDEO_TASKS_EXECUTION_TIME = {
         "1080p": 150,
     },
 }
+
+
+class SeedAudioConfig(BaseModel):
+    format: str = Field(default="mp3")
+    sample_rate: int = Field(default=24000)
+    speech_rate: int = Field(default=0)
+    loudness_rate: int = Field(default=0)
+    pitch_rate: int = Field(default=0)
+
+
+class SeedAudioReference(BaseModel):
+    speaker: str | None = Field(default=None)
+    audio_data: str | None = Field(default=None)
+    audio_url: str | None = Field(default=None)
+    image_data: str | None = Field(default=None)
+    image_url: str | None = Field(default=None)
+
+
+class SeedAudioRequest(BaseModel):
+    model: str = Field(default="seed-audio-1.0")
+    text_prompt: str = Field(...)
+    references: list[SeedAudioReference] | None = Field(default=None)
+    audio_config: SeedAudioConfig = Field(default_factory=SeedAudioConfig)
+    watermark: dict[str, Any] = Field(default_factory=dict)
+
+
+class SeedAudioResponse(BaseModel):
+    audio: str | None = Field(default=None)
+    url: str | None = Field(default=None)
+    duration: float | None = Field(default=None)
+    original_duration: float | None = Field(default=None)
+    code: int | None = Field(default=None)
+    message: str | None = Field(default=None)

comfy_api_nodes/apis/gemini.py

@@ -121,6 +121,7 @@ class GeminiGenerationConfig(BaseModel):
     topK: int | None = Field(None, ge=1)
     topP: float | None = Field(None, ge=0.0, le=1.0)
     thinkingConfig: GeminiThinkingConfig | None = Field(None)
+    responseModalities: list[str] | None = Field(None)
 
 
 class GeminiImageOutputOptions(BaseModel):

comfy_api_nodes/apis/ideogram.py

@@ -33,53 +33,6 @@ class IdeogramColorPalette(
     )
 
 
-class ImageRequest(BaseModel):
-    aspect_ratio: Optional[str] = Field(
-        None,
-        description="Optional. The aspect ratio (e.g., 'ASPECT_16_9', 'ASPECT_1_1'). Cannot be used with resolution. Defaults to 'ASPECT_1_1' if unspecified.",
-    )
-    color_palette: Optional[Dict[str, Any]] = Field(
-        None, description='Optional. Color palette object. Only for V_2, V_2_TURBO.'
-    )
-    magic_prompt_option: Optional[str] = Field(
-        None, description="Optional. MagicPrompt usage ('AUTO', 'ON', 'OFF')."
-    )
-    model: str = Field(..., description="The model used (e.g., 'V_2', 'V_2A_TURBO')")
-    negative_prompt: Optional[str] = Field(
-        None,
-        description='Optional. Description of what to exclude. Only for V_1, V_1_TURBO, V_2, V_2_TURBO.',
-    )
-    num_images: Optional[int] = Field(
-        1,
-        description='Optional. Number of images to generate (1-8). Defaults to 1.',
-        ge=1,
-        le=8,
-    )
-    prompt: str = Field(
-        ..., description='Required. The prompt to use to generate the image.'
-    )
-    resolution: Optional[str] = Field(
-        None,
-        description="Optional. Resolution (e.g., 'RESOLUTION_1024_1024'). Only for model V_2. Cannot be used with aspect_ratio.",
-    )
-    seed: Optional[int] = Field(
-        None,
-        description='Optional. A number between 0 and 2147483647.',
-        ge=0,
-        le=2147483647,
-    )
-    style_type: Optional[str] = Field(
-        None,
-        description="Optional. Style type ('AUTO', 'GENERAL', 'REALISTIC', 'DESIGN', 'RENDER_3D', 'ANIME'). Only for models V_2 and above.",
-    )
-
-
-class IdeogramGenerateRequest(BaseModel):
-    image_request: ImageRequest = Field(
-        ..., description='The image generation request parameters.'
-    )
-
-
 class Datum(BaseModel):
     is_image_safe: Optional[bool] = Field(
         None, description='Indicates whether the image is considered safe.'
@@ -113,20 +66,6 @@ class StyleCode(RootModel[str]):
     root: str = Field(..., pattern='^[0-9A-Fa-f]{8}$')
 
 
-class Datum1(BaseModel):
-    is_image_safe: Optional[bool] = None
-    prompt: Optional[str] = None
-    resolution: Optional[str] = None
-    seed: Optional[int] = None
-    style_type: Optional[str] = None
-    url: Optional[str] = None
-
-
-class IdeogramV3IdeogramResponse(BaseModel):
-    created: Optional[datetime] = None
-    data: Optional[List[Datum1]] = None
-
-
 class RenderingSpeed1(str, Enum):
     TURBO = 'TURBO'
     DEFAULT = 'DEFAULT'

comfy_api_nodes/apis/stability.py

@@ -1,147 +0,0 @@
-from enum import Enum
-from typing import Optional
-
-from pydantic import BaseModel, Field, confloat
-
-
-class StabilityFormat(str, Enum):
-    png = 'png'
-    jpeg = 'jpeg'
-    webp = 'webp'
-
-
-class StabilityAspectRatio(str, Enum):
-    ratio_1_1 = "1:1"
-    ratio_16_9 = "16:9"
-    ratio_9_16 = "9:16"
-    ratio_3_2 = "3:2"
-    ratio_2_3 = "2:3"
-    ratio_5_4 = "5:4"
-    ratio_4_5 = "4:5"
-    ratio_21_9 = "21:9"
-    ratio_9_21 = "9:21"
-
-
-def get_stability_style_presets(include_none=True):
-    presets = []
-    if include_none:
-        presets.append("None")
-    return presets + [x.value for x in StabilityStylePreset]
-
-
-class StabilityStylePreset(str, Enum):
-    _3d_model = "3d-model"
-    analog_film = "analog-film"
-    anime = "anime"
-    cinematic = "cinematic"
-    comic_book = "comic-book"
-    digital_art = "digital-art"
-    enhance = "enhance"
-    fantasy_art = "fantasy-art"
-    isometric = "isometric"
-    line_art = "line-art"
-    low_poly = "low-poly"
-    modeling_compound = "modeling-compound"
-    neon_punk = "neon-punk"
-    origami = "origami"
-    photographic = "photographic"
-    pixel_art = "pixel-art"
-    tile_texture = "tile-texture"
-
-
-class Stability_SD3_5_Model(str, Enum):
-    sd3_5_large = "sd3.5-large"
-    # sd3_5_large_turbo = "sd3.5-large-turbo"
-    sd3_5_medium = "sd3.5-medium"
-
-
-class Stability_SD3_5_GenerationMode(str, Enum):
-    text_to_image = "text-to-image"
-    image_to_image = "image-to-image"
-
-
-class StabilityStable3_5Request(BaseModel):
-    model: str = Field(...)
-    mode: str = Field(...)
-    prompt: str = Field(...)
-    negative_prompt: Optional[str] = Field(None)
-    aspect_ratio: Optional[str] = Field(None)
-    seed: Optional[int] = Field(None)
-    output_format: Optional[str] = Field(StabilityFormat.png.value)
-    image: Optional[str] = Field(None)
-    style_preset: Optional[str] = Field(None)
-    cfg_scale: float = Field(...)
-    strength: Optional[confloat(ge=0.0, le=1.0)] = Field(None)
-
-
-class StabilityUpscaleConservativeRequest(BaseModel):
-    prompt: str = Field(...)
-    negative_prompt: Optional[str] = Field(None)
-    seed: Optional[int] = Field(None)
-    output_format: Optional[str] = Field(StabilityFormat.png.value)
-    image: Optional[str] = Field(None)
-    creativity: Optional[confloat(ge=0.2, le=0.5)] = Field(None)
-
-
-class StabilityUpscaleCreativeRequest(BaseModel):
-    prompt: str = Field(...)
-    negative_prompt: Optional[str] = Field(None)
-    seed: Optional[int] = Field(None)
-    output_format: Optional[str] = Field(StabilityFormat.png.value)
-    image: Optional[str] = Field(None)
-    creativity: Optional[confloat(ge=0.1, le=0.5)] = Field(None)
-    style_preset: Optional[str] = Field(None)
-
-
-class StabilityStableUltraRequest(BaseModel):
-    prompt: str = Field(...)
-    negative_prompt: Optional[str] = Field(None)
-    aspect_ratio: Optional[str] = Field(None)
-    seed: Optional[int] = Field(None)
-    output_format: Optional[str] = Field(StabilityFormat.png.value)
-    image: Optional[str] = Field(None)
-    style_preset: Optional[str] = Field(None)
-    strength: Optional[confloat(ge=0.0, le=1.0)] = Field(None)
-
-
-class StabilityStableUltraResponse(BaseModel):
-    image: Optional[str] = Field(None)
-    finish_reason: Optional[str] = Field(None)
-    seed: Optional[int] = Field(None)
-
-
-class StabilityResultsGetResponse(BaseModel):
-    image: Optional[str] = Field(None)
-    finish_reason: Optional[str] = Field(None)
-    seed: Optional[int] = Field(None)
-    id: Optional[str] = Field(None)
-    name: Optional[str] = Field(None)
-    errors: Optional[list[str]] = Field(None)
-    status: Optional[str] = Field(None)
-    result: Optional[str] = Field(None)
-
-
-class StabilityAsyncResponse(BaseModel):
-    id: Optional[str] = Field(None)
-
-
-class StabilityTextToAudioRequest(BaseModel):
-    model: str = Field(...)
-    prompt: str = Field(...)
-    duration: int = Field(190, ge=1, le=190)
-    seed: int = Field(0, ge=0, le=4294967294)
-    steps: int = Field(8, ge=4, le=8)
-    output_format: str = Field("wav")
-
-
-class StabilityAudioToAudioRequest(StabilityTextToAudioRequest):
-    strength: float = Field(0.01, ge=0.01, le=1.0)
-
-
-class StabilityAudioInpaintRequest(StabilityTextToAudioRequest):
-    mask_start: int = Field(30, ge=0, le=190)
-    mask_end: int = Field(190, ge=0, le=190)
-
-
-class StabilityAudioResponse(BaseModel):
-    audio: Optional[str] = Field(None)

comfy_api_nodes/nodes_bytedance.py

@@ -1,3 +1,4 @@
+import base64
 import hashlib
 import logging
 import math
@@ -20,6 +21,10 @@ from comfy_api_nodes.apis.bytedance import (
     GetAssetResponse,
     Image2VideoTaskCreationRequest,
     ImageTaskCreationResponse,
+    SeedAudioConfig,
+    SeedAudioReference,
+    SeedAudioRequest,
+    SeedAudioResponse,
     Seedance2TaskCreationRequest,
     SeedanceCreateAssetRequest,
     SeedanceCreateAssetResponse,
@@ -43,6 +48,8 @@ from comfy_api_nodes.apis.bytedance import (
 )
 from comfy_api_nodes.util import (
     ApiEndpoint,
+    audio_bytes_to_audio_input,
+    audio_input_to_mp3,
     download_url_to_image_tensor,
     download_url_to_video_output,
     downscale_image_tensor_by_max_side,
@@ -51,11 +58,14 @@ from comfy_api_nodes.util import (
     image_tensor_pair_to_batch,
     poll_op,
     sync_op,
+    tensor_to_base64_string,
     upload_audio_to_comfyapi,
     upload_image_to_comfyapi,
     upload_images_to_comfyapi,
     upload_video_to_comfyapi,
+    upscale_image_tensor_to_min_pixels,
     upscale_video_to_min_pixels,
+    validate_audio_duration,
     validate_image_aspect_ratio,
     validate_image_dimensions,
     validate_string,
@@ -2474,6 +2484,311 @@ class ByteDanceCreateVideoAsset(IO.ComfyNode):
         return IO.NodeOutput(asset_id, resolved_group)
 
 
+MODE_TEXT = "text only"
+MODE_AUDIO = "audio reference"
+MODE_IMAGE = "image reference"
+MODE_SPEAKER = "preset voice"
+
+# (speaker_id, display_label) for built-in TTS 2.0 voices; resolvable ids are account-scoped.
+SEED_AUDIO_PRESET_VOICES: list[tuple[str, str]] = [
+    ("zh_female_vv_uranus_bigtts", "Vivi (Female, multilingual)"),
+    ("zh_female_xiaohe_uranus_bigtts", "Mindy (Female, multilingual)"),
+    ("en_female_stokie_uranus_bigtts", "Stokie (Female, English)"),
+    ("en_female_dacey_uranus_bigtts", "Dacey (Female, English)"),
+    ("en_male_tim_uranus_bigtts", "Tim (Male, English)"),
+    ("zh_male_m191_uranus_bigtts", "Kian (Male, multilingual)"),
+    ("zh_male_taocheng_uranus_bigtts", "Cedric (Male, multilingual)"),
+    ("zh_male_sophie_uranus_bigtts", "Sophie (Female, multilingual)"),
+    ("zh_female_yingyujiaoxue_uranus_bigtts", "Jean (Female, multilingual)"),
+    ("zh_male_dayi_uranus_bigtts", "Magnus (Male, multilingual)"),
+    ("zh_female_mizai_uranus_bigtts", "Mabel (Female, multilingual)"),
+    ("zh_female_jitangnv_uranus_bigtts", "Nadia (Female, multilingual)"),
+    ("zh_female_meilinvyou_uranus_bigtts", "Opal (Female, multilingual)"),
+    ("zh_female_liuchangnv_uranus_bigtts", "Pearl (Female, multilingual)"),
+    ("zh_male_ruyayichen_uranus_bigtts", "Quentin (Male, multilingual)"),
+    ("zh_female_vivo_uranus_bigtts", "Vienna (Female, multilingual)"),
+    ("zh_female_xiaoai_uranus_bigtts", "Alina (Female, multilingual)"),
+    ("zh_female_cancan_uranus_bigtts", "Corinne (Female, multilingual)"),
+    ("zh_female_tianmeixiaoyuan_uranus_bigtts", "Esther (Female, multilingual)"),
+    ("zh_female_tianmeitaozi_uranus_bigtts", "Freya (Female, multilingual)"),
+    ("zh_female_shuangkuaisisi_uranus_bigtts", "Gigi (Female, multilingual)"),
+    ("zh_female_peiqi_uranus_bigtts", "Holly (Female, multilingual)"),
+    ("zh_female_xiaoxue_uranus_bigtts", "Lyla (Female, multilingual)"),
+    ("zh_female_yuanqi_uranus_bigtts", "Daisy (Female, multilingual)"),
+    ("zh_female_kefunvsheng_uranus_bigtts", "Tracy (Female, multilingual)"),
+    ("zh_male_shaonianzixin_uranus_bigtts", "Jess (Male, multilingual)"),
+    ("zh_female_linjianvhai_uranus_bigtts", "Pinky (Female, multilingual)"),
+    ("zh_female_kiwi_uranus_bigtts", "Sweety (Female, multilingual)"),
+    ("zh_female_sajiaoxuemei_uranus_bigtts", "Sandy (Female, multilingual)"),
+    ("de_male_seven_uranus_bigtts", "Sven (Male, German)"),
+    ("jp_female_minimi_uranus_bigtts", "Minimi (Female, Japanese)"),
+    ("fr_male_usseau_uranus_bigtts", "Usseau (Male, French)"),
+    ("es_male_felipe_uranus_bigtts", "Felipe (Male, Spanish)"),
+    ("id_male_han_uranus_bigtts", "Han (Male, Indonesian)"),
+    ("pt_male_martins_uranus_bigtts", "Martins (Male, Portuguese)"),
+    ("it_male_enzo_uranus_bigtts", "Enzo (Male, Italian)"),
+    ("kr_male_shane_uranus_bigtts", "Shane (Male, Korean)"),
+    ("zh_male_liufei_uranus_bigtts", "Felix (Male, Chinese)"),
+    ("zh_female_qingxinnvsheng_uranus_bigtts", "Celeste (Female, Chinese)"),
+    ("zh_male_sunwukong_uranus_bigtts", "Monkey King (Male, Chinese)"),
+]
+SEED_AUDIO_VOICE_OPTIONS = [label for _, label in SEED_AUDIO_PRESET_VOICES]
+SEED_AUDIO_VOICE_MAP = {label: speaker_id for speaker_id, label in SEED_AUDIO_PRESET_VOICES}
+
+_AUDIO_TAG_RE = re.compile(r"@Audio(\d+)", re.IGNORECASE)
+
+
+def max_audio_tag(prompt: str) -> int:
+    """Highest N referenced as @AudioN in the prompt (0 if none)."""
+    nums = [int(m) for m in _AUDIO_TAG_RE.findall(prompt or "")]
+    return max(nums) if nums else 0
+
+
+def connected_audio_indices(reference_mode: dict) -> list[int]:
+    """Indices (1-based) of connected reference_audio sockets, in order."""
+    return [
+        i
+        for i in range(1, 3 + 1)
+        if reference_mode.get(f"reference_audio_{i}") is not None
+    ]
+
+
+def validate_seed_audio_inputs(
+    text_prompt: str,
+    mode: str,
+    audio_indices: list[int],
+    has_image: bool,
+    preset_voice: str | None = None,
+) -> None:
+    validate_string(text_prompt, field_name="text_prompt", min_length=1, max_length=3000)
+    max_tag = max_audio_tag(text_prompt)
+
+    if mode == MODE_TEXT:
+        if max_tag:
+            raise ValueError(
+                f"The prompt references @Audio{max_tag}, but reference mode is '{MODE_TEXT}'. "
+                f"Switch to '{MODE_AUDIO}' and connect the reference clip(s)."
+            )
+    elif mode == MODE_AUDIO:
+        if not audio_indices:
+            raise ValueError(
+                f"Reference mode '{MODE_AUDIO}' requires at least one reference_audio input "
+                f"(or switch to '{MODE_TEXT}')."
+            )
+        if audio_indices != list(range(1, len(audio_indices) + 1)):
+            raise ValueError(
+                "Connect reference_audio inputs in order without gaps: reference_audio_1, then _2, then _3."
+            )
+        if max_tag > len(audio_indices):
+            raise ValueError(
+                f"The prompt references @Audio{max_tag}, but only {len(audio_indices)} "
+                f"reference audio(s) are connected."
+            )
+    elif mode == MODE_IMAGE:
+        if not has_image:
+            raise ValueError(f"Reference mode '{MODE_IMAGE}' requires a reference_image input.")
+        if max_tag:
+            raise ValueError(
+                f"@AudioN tags are not used in '{MODE_IMAGE}' mode; the prompt should contain "
+                f"only the text to synthesize."
+            )
+    elif mode == MODE_SPEAKER:
+        if not preset_voice or preset_voice not in SEED_AUDIO_VOICE_MAP:
+            raise ValueError(f"Reference mode '{MODE_SPEAKER}' requires selecting a preset voice.")
+        if max_tag > 1:
+            raise ValueError(
+                f"'{MODE_SPEAKER}' mode uses a single voice, so @Audio{max_tag} is out of range. "
+                f"Remove the @AudioN tags — the whole prompt is read in the selected voice."
+            )
+    else:
+        raise ValueError(f"Unknown reference mode: {mode!r}")
+
+
+class ByteDanceSeedAudioNode(IO.ComfyNode):
+
+    @classmethod
+    def define_schema(cls) -> IO.Schema:
+        return IO.Schema(
+            node_id="ByteDanceSeedAudio",
+            display_name="ByteDance Seed Audio 1.0",
+            category="partner/audio/ByteDance",
+            description=(
+                "Generate speech, music, sound effects and multi-speaker dialogue from a single prompt "
+                "with ByteDance Seed Audio 1.0. Describe the voice(s), emotion, ambience, background music "
+                "and sound effects in the prompt, and include the lines to speak. Optionally pick a built-in "
+                "preset voice, clone voices from up to 3 reference clips (tagged @Audio1-3 in the prompt), "
+                "or derive a voice from a character image. Up to 2 minutes of audio per run."
+            ),
+            inputs=[
+                IO.String.Input(
+                    "text_prompt",
+                    multiline=True,
+                    default="",
+                    tooltip=(
+                        "Describe the voice(s), emotion, pacing, ambience, background music and sound "
+                        "effects, and include the lines to speak (name characters inline for dialogue). "
+                        "In 'audio reference' mode, refer to connected clips by order as @Audio1, @Audio2, "
+                        "@Audio3. Maximum 3000 characters."
+                    ),
+                ),
+                IO.DynamicCombo.Input(
+                    "reference_mode",
+                    options=[
+                        IO.DynamicCombo.Option(MODE_TEXT, []),
+                        IO.DynamicCombo.Option(
+                            MODE_AUDIO,
+                            [
+                                IO.Audio.Input(
+                                    "reference_audio_1",
+                                    optional=True,
+                                    tooltip="Reference clip for voice cloning, tagged @Audio1 in the prompt. "
+                                    "Up to 30s.",
+                                ),
+                                IO.Audio.Input(
+                                    "reference_audio_2",
+                                    optional=True,
+                                    tooltip="Reference clip tagged @Audio2 in the prompt. Up to 30s.",
+                                ),
+                                IO.Audio.Input(
+                                    "reference_audio_3",
+                                    optional=True,
+                                    tooltip="Reference clip tagged @Audio3 in the prompt. Up to 30s.",
+                                ),
+                            ],
+                        ),
+                        IO.DynamicCombo.Option(
+                            MODE_IMAGE,
+                            [
+                                IO.Image.Input(
+                                    "reference_image",
+                                    optional=True,
+                                    tooltip="A single character image; the model derives a voice from it. "
+                                    "Cannot be combined with reference audio.",
+                                ),
+                            ],
+                        ),
+                        IO.DynamicCombo.Option(
+                            MODE_SPEAKER,
+                            [
+                                IO.Combo.Input(
+                                    "preset_voice",
+                                    options=SEED_AUDIO_VOICE_OPTIONS,
+                                    default=SEED_AUDIO_VOICE_OPTIONS[0],
+                                    tooltip="A built-in TTS 2.0 voice that reads the prompt. No reference "
+                                    "clip needed, and @AudioN tags are not used in this mode.",
+                                ),
+                            ],
+                        ),
+                    ],
+                    tooltip=(
+                        "How to condition the voice: 'text only' (describe everything in the prompt), "
+                        "'audio reference' (clone up to 3 voices, tagged @Audio1-3), 'image reference' "
+                        "(derive a voice from one character image), or 'preset voice' (pick a built-in "
+                        "named voice that reads the prompt)."
+                    ),
+                ),
+                IO.Combo.Input(
+                    "sample_rate",
+                    options=["8000", "16000", "24000", "32000", "44100", "48000"],
+                    default="24000",
+                    tooltip="Output sample rate in Hz.",
+                ),
+                IO.Int.Input(
+                    "speech_rate",
+                    default=0,
+                    min=-50,
+                    max=100,
+                    tooltip="Speaking speed. 0 = normal, 100 = 2.0x, -50 = 0.5x.",
+                ),
+                IO.Int.Input(
+                    "loudness_rate",
+                    default=0,
+                    min=-50,
+                    max=100,
+                    tooltip="Loudness. 0 = normal, 100 = 2.0x, -50 = 0.5x.",
+                ),
+                IO.Int.Input(
+                    "pitch_rate",
+                    default=0,
+                    min=-12,
+                    max=12,
+                    tooltip="Pitch shift in semitones (-12 to 12).",
+                ),
+                IO.Int.Input(
+                    "seed",
+                    default=42,
+                    min=0,
+                    max=2147483647,
+                    control_after_generate=True,
+                    tooltip="Seed controls whether the node should re-run; "
+                    "results are non-deterministic regardless of seed.",
+                ),
+            ],
+            outputs=[IO.Audio.Output()],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+            price_badge=IO.PriceBadge(
+                expr="""{"type":"usd","usd": 0.2145, "format":{"suffix":"/minute","approximate":true}}""",
+            ),
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        text_prompt: str,
+        reference_mode: dict,
+        sample_rate: str,
+        speech_rate: int,
+        loudness_rate: int,
+        pitch_rate: int,
+        seed: int,
+    ) -> IO.NodeOutput:
+        mode = reference_mode["reference_mode"]
+        audio_indices = connected_audio_indices(reference_mode)
+        image = reference_mode.get("reference_image")
+        preset_voice = reference_mode.get("preset_voice")
+        validate_seed_audio_inputs(text_prompt, mode, audio_indices, image is not None, preset_voice)
+
+        references: list[SeedAudioReference] | None = None
+        if mode == MODE_AUDIO:
+            references = []
+            for i in audio_indices:
+                clip = reference_mode[f"reference_audio_{i}"]
+                validate_audio_duration(clip, max_duration=30.0)
+                mp3_bytes = audio_input_to_mp3(clip).getvalue()
+                references.append(SeedAudioReference(audio_data=base64.b64encode(mp3_bytes).decode("utf-8")))
+        elif mode == MODE_IMAGE:
+            image = upscale_image_tensor_to_min_pixels(image, 160_000)
+            references = [SeedAudioReference(image_data=tensor_to_base64_string(image, mime_type="image/png"))]
+        elif mode == MODE_SPEAKER:
+            references = [SeedAudioReference(speaker=SEED_AUDIO_VOICE_MAP[preset_voice])]
+
+        response = await sync_op(
+            cls,
+            ApiEndpoint(path="/proxy/byteplus/api/v3/tts/create", method="POST"),
+            response_model=SeedAudioResponse,
+            data=SeedAudioRequest(
+                text_prompt=text_prompt,
+                references=references,
+                audio_config=SeedAudioConfig(
+                    sample_rate=int(sample_rate),
+                    speech_rate=speech_rate,
+                    loudness_rate=loudness_rate,
+                    pitch_rate=pitch_rate,
+                ),
+            ),
+        )
+        if not response.audio:
+            raise Exception(
+                f"Seed Audio returned no audio (code={response.code}): {response.message}"
+            )
+        return IO.NodeOutput(audio_bytes_to_audio_input(base64.b64decode(response.audio)))
+
+
 class ByteDanceExtension(ComfyExtension):
     @override
     async def get_node_list(self) -> list[type[IO.ComfyNode]]:
@@ -2490,6 +2805,7 @@ class ByteDanceExtension(ComfyExtension):
             ByteDance2ReferenceNode,
             ByteDanceCreateImageAsset,
             ByteDanceCreateVideoAsset,
+            ByteDanceSeedAudioNode,
         ]
 
 

comfy_api_nodes/nodes_gemini.py

@@ -13,7 +13,7 @@ import torch
 from typing_extensions import override
 
 import folder_paths
-from comfy_api.latest import IO, ComfyExtension, Input, Types
+from comfy_api.latest import IO, ComfyExtension, Input, InputImpl, Types
 from comfy_api_nodes.apis.gemini import (
     GeminiContent,
     GeminiFileData,
@@ -37,6 +37,7 @@ from comfy_api_nodes.util import (
     audio_to_base64_string,
     bytesio_to_image_tensor,
     download_url_to_image_tensor,
+    download_url_to_video_output,
     get_number_of_images,
     sync_op,
     tensor_to_base64_string,
@@ -45,6 +46,7 @@ from comfy_api_nodes.util import (
     upload_images_to_comfyapi,
     upload_video_to_comfyapi,
     validate_string,
+    validate_video_duration,
     video_to_base64_string,
 )
 
@@ -229,10 +231,29 @@ async def get_image_from_response(response: GeminiGenerateContentResponse, thoug
     return torch.cat(image_tensors, dim=0)
 
 
+async def get_video_from_response(
+    response: GeminiGenerateContentResponse, cls: type[IO.ComfyNode] | None = None
+) -> InputImpl.VideoFromFile:
+    parts = get_parts_by_type(response, "video/*")
+    for part in parts:
+        if part.inlineData and part.inlineData.data:
+            return InputImpl.VideoFromFile(BytesIO(base64.b64decode(part.inlineData.data)))
+        if part.fileData and part.fileData.fileUri:
+            return await download_url_to_video_output(part.fileData.fileUri, cls=cls)
+    model_message = get_text_from_response(response).strip()
+    if model_message:
+        raise ValueError(f"Gemini did not generate a video. Model response: {model_message}")
+    raise ValueError(
+        "Gemini did not generate a video. Try rephrasing your prompt, "
+        "shortening the requested duration, or reducing the number of input images/videos."
+    )
+
+
 def calculate_tokens_price(response: GeminiGenerateContentResponse) -> float | None:
     if not response.modelVersion:
         return None
     # Define prices (Cost per 1,000,000 tokens), see https://cloud.google.com/vertex-ai/generative-ai/pricing
+    output_video_tokens_price = 0.0
     if response.modelVersion == "gemini-2.5-pro":
         input_tokens_price = 1.25
         output_text_tokens_price = 10.0
@@ -265,6 +286,11 @@ def calculate_tokens_price(response: GeminiGenerateContentResponse) -> float | N
         input_tokens_price = 0.25
         output_text_tokens_price = 1.50
         output_image_tokens_price = 30.0
+    elif response.modelVersion == "gemini-omni-flash-preview":
+        input_tokens_price = 2.145
+        output_text_tokens_price = 12.87
+        output_image_tokens_price = 0.0
+        output_video_tokens_price = 25.025
     else:
         return None
     final_price = response.usageMetadata.promptTokenCount * input_tokens_price
@@ -272,6 +298,8 @@ def calculate_tokens_price(response: GeminiGenerateContentResponse) -> float | N
         for i in response.usageMetadata.candidatesTokensDetails:
             if i.modality == Modality.IMAGE:
                 final_price += output_image_tokens_price * i.tokenCount  # for Nano Banana models
+            elif i.modality == Modality.VIDEO:
+                final_price += output_video_tokens_price * i.tokenCount  # for Omni Flash
             else:
                 final_price += output_text_tokens_price * i.tokenCount
     if response.usageMetadata.thoughtsTokenCount:
@@ -1531,6 +1559,149 @@ class GeminiNanoBanana2V2(IO.ComfyNode):
         )
 
 
+OMNI_MAX_IMAGES = 14
+OMNI_MAX_VIDEOS = 3
+
+OMNI_MODELS: dict[str, str] = {
+    "Omni Flash": "gemini-omni-flash-preview",
+}
+
+
+def _omni_flash_inputs() -> list[Input]:
+    """Per-model inputs for the Omni video DynamicCombo (prompt + reference media + sampling)."""
+    return [
+        IO.String.Input(
+            "prompt",
+            multiline=True,
+            default="",
+            tooltip="Describe the video to generate. Specify the length and aspect ratio directly in the "
+            'prompt, e.g. "a 6-second clip in 16:9". Length may be 3-10 seconds; the aspect ratio must be '
+            "16:9 (landscape) or 9:16 (portrait). The output is 720p, 24 FPS, with audio.",
+        ),
+        IO.Autogrow.Input(
+            "images",
+            template=IO.Autogrow.TemplateNames(
+                IO.Image.Input("image"),
+                names=[f"image_{i}" for i in range(1, OMNI_MAX_IMAGES + 1)],
+                min=0,
+            ),
+            tooltip=f"Optional reference image(s) to guide or animate the video. Up to {OMNI_MAX_IMAGES} images.",
+        ),
+        IO.Autogrow.Input(
+            "videos",
+            template=IO.Autogrow.TemplateNames(
+                IO.Video.Input("video"),
+                names=[f"video_{i}" for i in range(1, OMNI_MAX_VIDEOS + 1)],
+                min=0,
+            ),
+            tooltip=f"Optional reference video(s) to guide or edit. Up to {OMNI_MAX_VIDEOS} videos, "
+            f"each up to 10 seconds long.",
+        ),
+        IO.Float.Input(
+            "temperature",
+            default=1.0,
+            min=0.0,
+            max=2.0,
+            step=0.01,
+            tooltip="Controls randomness. Lower is more focused/deterministic, higher is more varied.",
+            advanced=True,
+        ),
+        IO.Float.Input(
+            "top_p",
+            default=0.95,
+            min=0.0,
+            max=1.0,
+            step=0.01,
+            tooltip="Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top_p.",
+            advanced=True,
+        ),
+    ]
+
+
+class GeminiVideoOmni(IO.ComfyNode):
+
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="GeminiVideoOmni",
+            display_name="Google Gemini Omni (Video)",
+            category="partner/video/Gemini",
+            essentials_category="Video Generation",
+            description="Generate a video with audio from a text prompt using Google's Gemini Omni Flash model. "
+            "Optionally provide reference images and/or videos to guide or edit the result. Describe the desired "
+            "length (3-10s) and aspect ratio (16:9 or 9:16) directly in the prompt.",
+            inputs=[
+                IO.DynamicCombo.Input(
+                    "model",
+                    options=[
+                        IO.DynamicCombo.Option("Omni Flash", _omni_flash_inputs()),
+                    ],
+                    tooltip="The Gemini video model used to generate the video.",
+                ),
+                IO.Int.Input(
+                    "seed",
+                    default=42,
+                    min=0,
+                    max=2147483647,
+                    control_after_generate=True,
+                    tooltip="Seed controls whether the node should re-run; "
+                    "results are non-deterministic regardless of seed.",
+                ),
+            ],
+            outputs=[
+                IO.Video.Output(),
+                IO.String.Output(),
+            ],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+            price_badge=IO.PriceBadge(
+                expr='{"type":"usd","usd":0.146,"format":{"suffix":"/second","approximate":true}}'
+            ),
+        )
+
+    @classmethod
+    async def execute(cls, model: dict, seed: int) -> IO.NodeOutput:
+        prompt = model.get("prompt") or ""
+        validate_string(prompt, strip_whitespace=True, min_length=1)
+        model_id = OMNI_MODELS[model["model"]]
+
+        images = [t for t in (model.get("images") or {}).values() if t is not None]
+        videos = [v for v in (model.get("videos") or {}).values() if v is not None]
+        if sum(get_number_of_images(t) for t in images) > OMNI_MAX_IMAGES:
+            raise ValueError(f"The current maximum number of supported images is {OMNI_MAX_IMAGES}.")
+        if len(videos) > OMNI_MAX_VIDEOS:
+            raise ValueError(f"The current maximum number of supported videos is {OMNI_MAX_VIDEOS}.")
+        for video in videos:
+            validate_video_duration(video, max_duration=10)
+
+        parts: list[GeminiPart] = []
+        if images or videos:
+            parts.extend(await build_gemini_media_parts(cls, images, [], videos))
+        parts.append(GeminiPart(text=prompt))
+        response = await sync_op(
+            cls,
+            ApiEndpoint(path=f"{GEMINI_BASE_ENDPOINT}/{model_id}", method="POST"),
+            data=GeminiGenerateContentRequest(
+                contents=[GeminiContent(role=GeminiRole.user, parts=parts)],
+                generationConfig=GeminiGenerationConfig(
+                    responseModalities=["TEXT", "VIDEO"],
+                    temperature=model.get("temperature", 1.0),
+                    topP=model.get("top_p", 0.95),
+                ),
+            ),
+            response_model=GeminiGenerateContentResponse,
+            price_extractor=calculate_tokens_price,
+        )
+        return IO.NodeOutput(
+            await get_video_from_response(response, cls=cls),
+            get_text_from_response(response),
+        )
+
+
 class GeminiExtension(ComfyExtension):
     @override
     async def get_node_list(self) -> list[type[IO.ComfyNode]]:
@@ -1541,6 +1712,7 @@ class GeminiExtension(ComfyExtension):
             GeminiImage2,
             GeminiNanoBanana2,
             GeminiNanoBanana2V2,
+            GeminiVideoOmni,
             GeminiInputFiles,
         ]
 

comfy_api_nodes/nodes_ideogram.py

@@ -5,9 +5,7 @@ from PIL import Image
 import numpy as np
 import torch
 from comfy_api_nodes.apis.ideogram import (
-    IdeogramGenerateRequest,
     IdeogramGenerateResponse,
-    ImageRequest,
     IdeogramV3Request,
     IdeogramV3EditRequest,
     IdeogramV4Request,
@@ -21,101 +19,6 @@ from comfy_api_nodes.util import (
     validate_string,
 )
 
-V1_V1_RES_MAP = {
-  "Auto":"AUTO",
-  "512 x 1536":"RESOLUTION_512_1536",
-  "576 x 1408":"RESOLUTION_576_1408",
-  "576 x 1472":"RESOLUTION_576_1472",
-  "576 x 1536":"RESOLUTION_576_1536",
-  "640 x 1024":"RESOLUTION_640_1024",
-  "640 x 1344":"RESOLUTION_640_1344",
-  "640 x 1408":"RESOLUTION_640_1408",
-  "640 x 1472":"RESOLUTION_640_1472",
-  "640 x 1536":"RESOLUTION_640_1536",
-  "704 x 1152":"RESOLUTION_704_1152",
-  "704 x 1216":"RESOLUTION_704_1216",
-  "704 x 1280":"RESOLUTION_704_1280",
-  "704 x 1344":"RESOLUTION_704_1344",
-  "704 x 1408":"RESOLUTION_704_1408",
-  "704 x 1472":"RESOLUTION_704_1472",
-  "720 x 1280":"RESOLUTION_720_1280",
-  "736 x 1312":"RESOLUTION_736_1312",
-  "768 x 1024":"RESOLUTION_768_1024",
-  "768 x 1088":"RESOLUTION_768_1088",
-  "768 x 1152":"RESOLUTION_768_1152",
-  "768 x 1216":"RESOLUTION_768_1216",
-  "768 x 1232":"RESOLUTION_768_1232",
-  "768 x 1280":"RESOLUTION_768_1280",
-  "768 x 1344":"RESOLUTION_768_1344",
-  "832 x 960":"RESOLUTION_832_960",
-  "832 x 1024":"RESOLUTION_832_1024",
-  "832 x 1088":"RESOLUTION_832_1088",
-  "832 x 1152":"RESOLUTION_832_1152",
-  "832 x 1216":"RESOLUTION_832_1216",
-  "832 x 1248":"RESOLUTION_832_1248",
-  "864 x 1152":"RESOLUTION_864_1152",
-  "896 x 960":"RESOLUTION_896_960",
-  "896 x 1024":"RESOLUTION_896_1024",
-  "896 x 1088":"RESOLUTION_896_1088",
-  "896 x 1120":"RESOLUTION_896_1120",
-  "896 x 1152":"RESOLUTION_896_1152",
-  "960 x 832":"RESOLUTION_960_832",
-  "960 x 896":"RESOLUTION_960_896",
-  "960 x 1024":"RESOLUTION_960_1024",
-  "960 x 1088":"RESOLUTION_960_1088",
-  "1024 x 640":"RESOLUTION_1024_640",
-  "1024 x 768":"RESOLUTION_1024_768",
-  "1024 x 832":"RESOLUTION_1024_832",
-  "1024 x 896":"RESOLUTION_1024_896",
-  "1024 x 960":"RESOLUTION_1024_960",
-  "1024 x 1024":"RESOLUTION_1024_1024",
-  "1088 x 768":"RESOLUTION_1088_768",
-  "1088 x 832":"RESOLUTION_1088_832",
-  "1088 x 896":"RESOLUTION_1088_896",
-  "1088 x 960":"RESOLUTION_1088_960",
-  "1120 x 896":"RESOLUTION_1120_896",
-  "1152 x 704":"RESOLUTION_1152_704",
-  "1152 x 768":"RESOLUTION_1152_768",
-  "1152 x 832":"RESOLUTION_1152_832",
-  "1152 x 864":"RESOLUTION_1152_864",
-  "1152 x 896":"RESOLUTION_1152_896",
-  "1216 x 704":"RESOLUTION_1216_704",
-  "1216 x 768":"RESOLUTION_1216_768",
-  "1216 x 832":"RESOLUTION_1216_832",
-  "1232 x 768":"RESOLUTION_1232_768",
-  "1248 x 832":"RESOLUTION_1248_832",
-  "1280 x 704":"RESOLUTION_1280_704",
-  "1280 x 720":"RESOLUTION_1280_720",
-  "1280 x 768":"RESOLUTION_1280_768",
-  "1280 x 800":"RESOLUTION_1280_800",
-  "1312 x 736":"RESOLUTION_1312_736",
-  "1344 x 640":"RESOLUTION_1344_640",
-  "1344 x 704":"RESOLUTION_1344_704",
-  "1344 x 768":"RESOLUTION_1344_768",
-  "1408 x 576":"RESOLUTION_1408_576",
-  "1408 x 640":"RESOLUTION_1408_640",
-  "1408 x 704":"RESOLUTION_1408_704",
-  "1472 x 576":"RESOLUTION_1472_576",
-  "1472 x 640":"RESOLUTION_1472_640",
-  "1472 x 704":"RESOLUTION_1472_704",
-  "1536 x 512":"RESOLUTION_1536_512",
-  "1536 x 576":"RESOLUTION_1536_576",
-  "1536 x 640":"RESOLUTION_1536_640",
-}
-
-V1_V2_RATIO_MAP = {
-  "1:1":"ASPECT_1_1",
-  "4:3":"ASPECT_4_3",
-  "3:4":"ASPECT_3_4",
-  "16:9":"ASPECT_16_9",
-  "9:16":"ASPECT_9_16",
-  "2:1":"ASPECT_2_1",
-  "1:2":"ASPECT_1_2",
-  "3:2":"ASPECT_3_2",
-  "2:3":"ASPECT_2_3",
-  "4:5":"ASPECT_4_5",
-  "5:4":"ASPECT_5_4",
-}
 
 V3_RATIO_MAP = {
     "1:3":"1x3",
@@ -229,298 +132,6 @@ async def download_and_process_images(image_urls):
     return stacked_tensors
 
 
-class IdeogramV1(IO.ComfyNode):
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="IdeogramV1",
-            display_name="Ideogram V1",
-            category="partner/image/Ideogram",
-            description="Generates images using the Ideogram V1 model.",
-            inputs=[
-                IO.String.Input(
-                    "prompt",
-                    multiline=True,
-                    default="",
-                    tooltip="Prompt for the image generation",
-                ),
-                IO.Boolean.Input(
-                    "turbo",
-                    default=False,
-                    tooltip="Whether to use turbo mode (faster generation, potentially lower quality)",
-                ),
-                IO.Combo.Input(
-                    "aspect_ratio",
-                    options=list(V1_V2_RATIO_MAP.keys()),
-                    default="1:1",
-                    tooltip="The aspect ratio for image generation.",
-                    optional=True,
-                ),
-                IO.Combo.Input(
-                    "magic_prompt_option",
-                    options=["AUTO", "ON", "OFF"],
-                    default="AUTO",
-                    tooltip="Determine if MagicPrompt should be used in generation",
-                    optional=True,
-                    advanced=True,
-                ),
-                IO.Int.Input(
-                    "seed",
-                    default=0,
-                    min=0,
-                    max=2147483647,
-                    step=1,
-                    control_after_generate=True,
-                    display_mode=IO.NumberDisplay.number,
-                    optional=True,
-                ),
-                IO.String.Input(
-                    "negative_prompt",
-                    multiline=True,
-                    default="",
-                    tooltip="Description of what to exclude from the image",
-                    optional=True,
-                ),
-                IO.Int.Input(
-                    "num_images",
-                    default=1,
-                    min=1,
-                    max=8,
-                    step=1,
-                    display_mode=IO.NumberDisplay.number,
-                    optional=True,
-                ),
-            ],
-            outputs=[
-                IO.Image.Output(),
-            ],
-            hidden=[
-                IO.Hidden.auth_token_comfy_org,
-                IO.Hidden.api_key_comfy_org,
-                IO.Hidden.unique_id,
-            ],
-            is_api_node=True,
-            price_badge=IO.PriceBadge(
-                depends_on=IO.PriceBadgeDepends(widgets=["num_images", "turbo"]),
-                expr="""
-                (
-                  $n := widgets.num_images;
-                  $base := (widgets.turbo = true) ? 0.0286 : 0.0858;
-                  {"type":"usd","usd": $round($base * $n, 2)}
-                )
-                """,
-            ),
-        )
-
-    @classmethod
-    async def execute(
-        cls,
-        prompt,
-        turbo=False,
-        aspect_ratio="1:1",
-        magic_prompt_option="AUTO",
-        seed=0,
-        negative_prompt="",
-        num_images=1,
-    ):
-        # Determine the model based on turbo setting
-        aspect_ratio = V1_V2_RATIO_MAP.get(aspect_ratio, None)
-        model = "V_1_TURBO" if turbo else "V_1"
-
-        response = await sync_op(
-            cls,
-            ApiEndpoint(path="/proxy/ideogram/generate", method="POST"),
-            response_model=IdeogramGenerateResponse,
-            data=IdeogramGenerateRequest(
-                image_request=ImageRequest(
-                    prompt=prompt,
-                    model=model,
-                    num_images=num_images,
-                    seed=seed,
-                    aspect_ratio=aspect_ratio if aspect_ratio != "ASPECT_1_1" else None,
-                    magic_prompt_option=(magic_prompt_option if magic_prompt_option != "AUTO" else None),
-                    negative_prompt=negative_prompt if negative_prompt else None,
-                )
-            ),
-            max_retries=1,
-        )
-
-        if not response.data or len(response.data) == 0:
-            raise Exception("No images were generated in the response")
-
-        image_urls = [image_data.url for image_data in response.data if image_data.url]
-        if not image_urls:
-            raise Exception("No image URLs were generated in the response")
-        return IO.NodeOutput(await download_and_process_images(image_urls))
-
-
-class IdeogramV2(IO.ComfyNode):
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="IdeogramV2",
-            display_name="Ideogram V2",
-            category="partner/image/Ideogram",
-            description="Generates images using the Ideogram V2 model.",
-            inputs=[
-                IO.String.Input(
-                    "prompt",
-                    multiline=True,
-                    default="",
-                    tooltip="Prompt for the image generation",
-                ),
-                IO.Boolean.Input(
-                    "turbo",
-                    default=False,
-                    tooltip="Whether to use turbo mode (faster generation, potentially lower quality)",
-                ),
-                IO.Combo.Input(
-                    "aspect_ratio",
-                    options=list(V1_V2_RATIO_MAP.keys()),
-                    default="1:1",
-                    tooltip="The aspect ratio for image generation. Ignored if resolution is not set to AUTO.",
-                    optional=True,
-                ),
-                IO.Combo.Input(
-                    "resolution",
-                    options=list(V1_V1_RES_MAP.keys()),
-                    default="Auto",
-                    tooltip="The resolution for image generation. "
-                            "If not set to AUTO, this overrides the aspect_ratio setting.",
-                    optional=True,
-                ),
-                IO.Combo.Input(
-                    "magic_prompt_option",
-                    options=["AUTO", "ON", "OFF"],
-                    default="AUTO",
-                    tooltip="Determine if MagicPrompt should be used in generation",
-                    optional=True,
-                    advanced=True,
-                ),
-                IO.Int.Input(
-                    "seed",
-                    default=0,
-                    min=0,
-                    max=2147483647,
-                    step=1,
-                    control_after_generate=True,
-                    display_mode=IO.NumberDisplay.number,
-                    optional=True,
-                ),
-                IO.Combo.Input(
-                    "style_type",
-                    options=["AUTO", "GENERAL", "REALISTIC", "DESIGN", "RENDER_3D", "ANIME"],
-                    default="NONE",
-                    tooltip="Style type for generation (V2 only)",
-                    optional=True,
-                    advanced=True,
-                ),
-                IO.String.Input(
-                    "negative_prompt",
-                    multiline=True,
-                    default="",
-                    tooltip="Description of what to exclude from the image",
-                    optional=True,
-                ),
-                IO.Int.Input(
-                    "num_images",
-                    default=1,
-                    min=1,
-                    max=8,
-                    step=1,
-                    display_mode=IO.NumberDisplay.number,
-                    optional=True,
-                ),
-                #"color_palette": (
-                #    IO.STRING,
-                #    {
-                #        "multiline": False,
-                #        "default": "",
-                #        "tooltip": "Color palette preset name or hex colors with weights",
-                #    },
-                #),
-            ],
-            outputs=[
-                IO.Image.Output(),
-            ],
-            hidden=[
-                IO.Hidden.auth_token_comfy_org,
-                IO.Hidden.api_key_comfy_org,
-                IO.Hidden.unique_id,
-            ],
-            is_api_node=True,
-            price_badge=IO.PriceBadge(
-                depends_on=IO.PriceBadgeDepends(widgets=["num_images", "turbo"]),
-                expr="""
-                (
-                  $n := widgets.num_images;
-                  $base := (widgets.turbo = true) ? 0.0715 : 0.1144;
-                  {"type":"usd","usd": $round($base * $n, 2)}
-                )
-                """,
-            ),
-        )
-
-    @classmethod
-    async def execute(
-        cls,
-        prompt,
-        turbo=False,
-        aspect_ratio="1:1",
-        resolution="Auto",
-        magic_prompt_option="AUTO",
-        seed=0,
-        style_type="NONE",
-        negative_prompt="",
-        num_images=1,
-        color_palette="",
-    ):
-        aspect_ratio = V1_V2_RATIO_MAP.get(aspect_ratio, None)
-        resolution = V1_V1_RES_MAP.get(resolution, None)
-        # Determine the model based on turbo setting
-        model = "V_2_TURBO" if turbo else "V_2"
-
-        # Handle resolution vs aspect_ratio logic
-        # If resolution is not AUTO, it overrides aspect_ratio
-        final_resolution = None
-        final_aspect_ratio = None
-
-        if resolution != "AUTO":
-            final_resolution = resolution
-        else:
-            final_aspect_ratio = aspect_ratio if aspect_ratio != "ASPECT_1_1" else None
-
-        response = await sync_op(
-            cls,
-            endpoint=ApiEndpoint(path="/proxy/ideogram/generate", method="POST"),
-            response_model=IdeogramGenerateResponse,
-            data=IdeogramGenerateRequest(
-                image_request=ImageRequest(
-                    prompt=prompt,
-                    model=model,
-                    num_images=num_images,
-                    seed=seed,
-                    aspect_ratio=final_aspect_ratio,
-                    resolution=final_resolution,
-                    magic_prompt_option=(magic_prompt_option if magic_prompt_option != "AUTO" else None),
-                    style_type=style_type if style_type != "NONE" else None,
-                    negative_prompt=negative_prompt if negative_prompt else None,
-                    color_palette=color_palette if color_palette else None,
-                )
-            ),
-            max_retries=1,
-        )
-        if not response.data or len(response.data) == 0:
-            raise Exception("No images were generated in the response")
-
-        image_urls = [image_data.url for image_data in response.data if image_data.url]
-        if not image_urls:
-            raise Exception("No image URLs were generated in the response")
-        return IO.NodeOutput(await download_and_process_images(image_urls))
-
-
 class IdeogramV3(IO.ComfyNode):
 
     @classmethod
@@ -917,8 +528,6 @@ class IdeogramExtension(ComfyExtension):
     @override
     async def get_node_list(self) -> list[type[IO.ComfyNode]]:
         return [
-            IdeogramV1,
-            IdeogramV2,
             IdeogramV3,
             IdeogramV4,
         ]

comfy_api_nodes/nodes_stability.py

@@ -1,932 +0,0 @@
-from inspect import cleandoc
-from typing import Optional
-from typing_extensions import override
-
-from comfy_api.latest import ComfyExtension, Input, IO
-from comfy_api_nodes.apis.stability import (
-    StabilityUpscaleConservativeRequest,
-    StabilityUpscaleCreativeRequest,
-    StabilityAsyncResponse,
-    StabilityResultsGetResponse,
-    StabilityStable3_5Request,
-    StabilityStableUltraRequest,
-    StabilityStableUltraResponse,
-    StabilityAspectRatio,
-    Stability_SD3_5_Model,
-    Stability_SD3_5_GenerationMode,
-    get_stability_style_presets,
-    StabilityTextToAudioRequest,
-    StabilityAudioToAudioRequest,
-    StabilityAudioInpaintRequest,
-    StabilityAudioResponse,
-)
-from comfy_api_nodes.util import (
-    validate_audio_duration,
-    validate_string,
-    audio_input_to_mp3,
-    bytesio_to_image_tensor,
-    tensor_to_bytesio,
-    audio_bytes_to_audio_input,
-    sync_op,
-    poll_op,
-    ApiEndpoint,
-)
-
-import torch
-import base64
-from io import BytesIO
-from enum import Enum
-
-
-class StabilityPollStatus(str, Enum):
-    finished = "finished"
-    in_progress = "in_progress"
-    failed = "failed"
-
-
-def get_async_dummy_status(x: StabilityResultsGetResponse):
-    if x.name is not None or x.errors is not None:
-        return StabilityPollStatus.failed
-    elif x.finish_reason is not None:
-        return StabilityPollStatus.finished
-    return StabilityPollStatus.in_progress
-
-
-class StabilityStableImageUltraNode(IO.ComfyNode):
-    """
-    Generates images synchronously based on prompt and resolution.
-    """
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="StabilityStableImageUltraNode",
-            display_name="Stability AI Stable Image Ultra",
-            category="partner/image/Stability AI",
-            description=cleandoc(cls.__doc__ or ""),
-            inputs=[
-                IO.String.Input(
-                    "prompt",
-                    multiline=True,
-                    default="",
-                    tooltip="What you wish to see in the output image. A strong, descriptive prompt that clearly defines" +
-                                    "elements, colors, and subjects will lead to better results. " +
-                                    "To control the weight of a given word use the format `(word:weight)`," +
-                                    "where `word` is the word you'd like to control the weight of and `weight`" +
-                                    "is a value between 0 and 1. For example: `The sky was a crisp (blue:0.3) and (green:0.8)`" +
-                                    "would convey a sky that was blue and green, but more green than blue.",
-                ),
-                IO.Combo.Input(
-                    "aspect_ratio",
-                    options=StabilityAspectRatio,
-                    default=StabilityAspectRatio.ratio_1_1,
-                    tooltip="Aspect ratio of generated image.",
-                ),
-                IO.Combo.Input(
-                    "style_preset",
-                    options=get_stability_style_presets(),
-                    tooltip="Optional desired style of generated image.",
-                    advanced=True,
-                ),
-                IO.Int.Input(
-                    "seed",
-                    default=0,
-                    min=0,
-                    max=4294967294,
-                    step=1,
-                    display_mode=IO.NumberDisplay.number,
-                    control_after_generate=True,
-                    tooltip="The random seed used for creating the noise.",
-                ),
-                IO.Image.Input(
-                    "image",
-                    optional=True,
-                ),
-                IO.String.Input(
-                    "negative_prompt",
-                    default="",
-                    tooltip="A blurb of text describing what you do not wish to see in the output image. This is an advanced feature.",
-                    force_input=True,
-                    optional=True,
-                    advanced=True,
-                ),
-                IO.Float.Input(
-                    "image_denoise",
-                    default=0.5,
-                    min=0.0,
-                    max=1.0,
-                    step=0.01,
-                    tooltip="Denoise of input image; 0.0 yields image identical to input, 1.0 is as if no image was provided at all.",
-                    optional=True,
-                ),
-            ],
-            outputs=[
-                IO.Image.Output(),
-            ],
-            hidden=[
-                IO.Hidden.auth_token_comfy_org,
-                IO.Hidden.api_key_comfy_org,
-                IO.Hidden.unique_id,
-            ],
-            is_api_node=True,
-            price_badge=IO.PriceBadge(
-                expr="""{"type":"usd","usd":0.08}""",
-            ),
-        )
-
-    @classmethod
-    async def execute(
-        cls,
-        prompt: str,
-        aspect_ratio: str,
-        style_preset: str,
-        seed: int,
-        image: Optional[torch.Tensor] = None,
-        negative_prompt: str = "",
-        image_denoise: Optional[float] = 0.5,
-    ) -> IO.NodeOutput:
-        validate_string(prompt, strip_whitespace=False)
-        # prepare image binary if image present
-        image_binary = None
-        if image is not None:
-            image_binary = tensor_to_bytesio(image, total_pixels=1504*1504).read()
-        else:
-            image_denoise = None
-
-        if not negative_prompt:
-            negative_prompt = None
-        if style_preset == "None":
-            style_preset = None
-
-        files = {
-            "image": image_binary
-        }
-
-        response_api = await sync_op(
-            cls,
-            ApiEndpoint(path="/proxy/stability/v2beta/stable-image/generate/ultra", method="POST"),
-            response_model=StabilityStableUltraResponse,
-            data=StabilityStableUltraRequest(
-                prompt=prompt,
-                negative_prompt=negative_prompt,
-                aspect_ratio=aspect_ratio,
-                seed=seed,
-                strength=image_denoise,
-                style_preset=style_preset,
-            ),
-            files=files,
-            content_type="multipart/form-data",
-        )
-
-        if response_api.finish_reason != "SUCCESS":
-            raise Exception(f"Stable Image Ultra generation failed: {response_api.finish_reason}.")
-
-        image_data = base64.b64decode(response_api.image)
-        returned_image = bytesio_to_image_tensor(BytesIO(image_data))
-
-        return IO.NodeOutput(returned_image)
-
-
-class StabilityStableImageSD_3_5Node(IO.ComfyNode):
-    """
-    Generates images synchronously based on prompt and resolution.
-    """
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="StabilityStableImageSD_3_5Node",
-            display_name="Stability AI Stable Diffusion 3.5 Image",
-            category="partner/image/Stability AI",
-            description=cleandoc(cls.__doc__ or ""),
-            inputs=[
-                IO.String.Input(
-                    "prompt",
-                    multiline=True,
-                    default="",
-                    tooltip="What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results.",
-                ),
-                IO.Combo.Input(
-                    "model",
-                    options=Stability_SD3_5_Model,
-                ),
-                IO.Combo.Input(
-                    "aspect_ratio",
-                    options=StabilityAspectRatio,
-                    default=StabilityAspectRatio.ratio_1_1,
-                    tooltip="Aspect ratio of generated image.",
-                ),
-                IO.Combo.Input(
-                    "style_preset",
-                    options=get_stability_style_presets(),
-                    tooltip="Optional desired style of generated image.",
-                    advanced=True,
-                ),
-                IO.Float.Input(
-                    "cfg_scale",
-                    default=4.0,
-                    min=1.0,
-                    max=10.0,
-                    step=0.1,
-                    tooltip="How strictly the diffusion process adheres to the prompt text (higher values keep your image closer to your prompt)",
-                ),
-                IO.Int.Input(
-                    "seed",
-                    default=0,
-                    min=0,
-                    max=4294967294,
-                    step=1,
-                    display_mode=IO.NumberDisplay.number,
-                    control_after_generate=True,
-                    tooltip="The random seed used for creating the noise.",
-                ),
-                IO.Image.Input(
-                    "image",
-                    optional=True,
-                ),
-                IO.String.Input(
-                    "negative_prompt",
-                    default="",
-                    tooltip="Keywords of what you do not wish to see in the output image. This is an advanced feature.",
-                    force_input=True,
-                    optional=True,
-                    advanced=True,
-                ),
-                IO.Float.Input(
-                    "image_denoise",
-                    default=0.5,
-                    min=0.0,
-                    max=1.0,
-                    step=0.01,
-                    tooltip="Denoise of input image; 0.0 yields image identical to input, 1.0 is as if no image was provided at all.",
-                    optional=True,
-                ),
-            ],
-            outputs=[
-                IO.Image.Output(),
-            ],
-            hidden=[
-                IO.Hidden.auth_token_comfy_org,
-                IO.Hidden.api_key_comfy_org,
-                IO.Hidden.unique_id,
-            ],
-            is_api_node=True,
-            price_badge=IO.PriceBadge(
-                depends_on=IO.PriceBadgeDepends(widgets=["model"]),
-                expr="""
-                (
-                  $contains(widgets.model,"large")
-                    ? {"type":"usd","usd":0.065}
-                    : {"type":"usd","usd":0.035}
-                )
-                """,
-            ),
-        )
-
-    @classmethod
-    async def execute(
-        cls,
-        model: str,
-        prompt: str,
-        aspect_ratio: str,
-        style_preset: str,
-        seed: int,
-        cfg_scale: float,
-        image: Optional[torch.Tensor] = None,
-        negative_prompt: str = "",
-        image_denoise: Optional[float] = 0.5,
-    ) -> IO.NodeOutput:
-        validate_string(prompt, strip_whitespace=False)
-        # prepare image binary if image present
-        image_binary = None
-        mode = Stability_SD3_5_GenerationMode.text_to_image
-        if image is not None:
-            image_binary = tensor_to_bytesio(image, total_pixels=1504*1504).read()
-            mode = Stability_SD3_5_GenerationMode.image_to_image
-            aspect_ratio = None
-        else:
-            image_denoise = None
-
-        if not negative_prompt:
-            negative_prompt = None
-        if style_preset == "None":
-            style_preset = None
-
-        files = {
-            "image": image_binary
-        }
-
-        response_api = await sync_op(
-            cls,
-            ApiEndpoint(path="/proxy/stability/v2beta/stable-image/generate/sd3", method="POST"),
-            response_model=StabilityStableUltraResponse,
-            data=StabilityStable3_5Request(
-                prompt=prompt,
-                negative_prompt=negative_prompt,
-                aspect_ratio=aspect_ratio,
-                seed=seed,
-                strength=image_denoise,
-                style_preset=style_preset,
-                cfg_scale=cfg_scale,
-                model=model,
-                mode=mode,
-            ),
-            files=files,
-            content_type="multipart/form-data",
-        )
-
-        if response_api.finish_reason != "SUCCESS":
-            raise Exception(f"Stable Diffusion 3.5 Image generation failed: {response_api.finish_reason}.")
-
-        image_data = base64.b64decode(response_api.image)
-        returned_image = bytesio_to_image_tensor(BytesIO(image_data))
-
-        return IO.NodeOutput(returned_image)
-
-
-class StabilityUpscaleConservativeNode(IO.ComfyNode):
-    """
-    Upscale image with minimal alterations to 4K resolution.
-    """
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="StabilityUpscaleConservativeNode",
-            display_name="Stability AI Upscale Conservative",
-            category="partner/image/Stability AI",
-            description=cleandoc(cls.__doc__ or ""),
-            inputs=[
-                IO.Image.Input("image"),
-                IO.String.Input(
-                    "prompt",
-                    multiline=True,
-                    default="",
-                    tooltip="What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results.",
-                ),
-                IO.Float.Input(
-                    "creativity",
-                    default=0.35,
-                    min=0.2,
-                    max=0.5,
-                    step=0.01,
-                    tooltip="Controls the likelihood of creating additional details not heavily conditioned by the init image.",
-                ),
-                IO.Int.Input(
-                    "seed",
-                    default=0,
-                    min=0,
-                    max=4294967294,
-                    step=1,
-                    display_mode=IO.NumberDisplay.number,
-                    control_after_generate=True,
-                    tooltip="The random seed used for creating the noise.",
-                ),
-                IO.String.Input(
-                    "negative_prompt",
-                    default="",
-                    tooltip="Keywords of what you do not wish to see in the output image. This is an advanced feature.",
-                    force_input=True,
-                    optional=True,
-                    advanced=True,
-                ),
-            ],
-            outputs=[
-                IO.Image.Output(),
-            ],
-            hidden=[
-                IO.Hidden.auth_token_comfy_org,
-                IO.Hidden.api_key_comfy_org,
-                IO.Hidden.unique_id,
-            ],
-            is_api_node=True,
-            price_badge=IO.PriceBadge(
-                expr="""{"type":"usd","usd":0.4}""",
-            ),
-        )
-
-    @classmethod
-    async def execute(
-        cls,
-        image: torch.Tensor,
-        prompt: str,
-        creativity: float,
-        seed: int,
-        negative_prompt: str = "",
-    ) -> IO.NodeOutput:
-        validate_string(prompt, strip_whitespace=False)
-        image_binary = tensor_to_bytesio(image, total_pixels=1024*1024).read()
-
-        if not negative_prompt:
-            negative_prompt = None
-
-        files = {
-            "image": image_binary
-        }
-
-        response_api = await sync_op(
-            cls,
-            ApiEndpoint(path="/proxy/stability/v2beta/stable-image/upscale/conservative", method="POST"),
-            response_model=StabilityStableUltraResponse,
-            data=StabilityUpscaleConservativeRequest(
-                prompt=prompt,
-                negative_prompt=negative_prompt,
-                creativity=round(creativity,2),
-                seed=seed,
-            ),
-            files=files,
-            content_type="multipart/form-data",
-        )
-
-        if response_api.finish_reason != "SUCCESS":
-            raise Exception(f"Stability Upscale Conservative generation failed: {response_api.finish_reason}.")
-
-        image_data = base64.b64decode(response_api.image)
-        returned_image = bytesio_to_image_tensor(BytesIO(image_data))
-
-        return IO.NodeOutput(returned_image)
-
-
-class StabilityUpscaleCreativeNode(IO.ComfyNode):
-    """
-    Upscale image with minimal alterations to 4K resolution.
-    """
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="StabilityUpscaleCreativeNode",
-            display_name="Stability AI Upscale Creative",
-            category="partner/image/Stability AI",
-            description=cleandoc(cls.__doc__ or ""),
-            inputs=[
-                IO.Image.Input("image"),
-                IO.String.Input(
-                    "prompt",
-                    multiline=True,
-                    default="",
-                    tooltip="What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results.",
-                ),
-                IO.Float.Input(
-                    "creativity",
-                    default=0.3,
-                    min=0.1,
-                    max=0.5,
-                    step=0.01,
-                    tooltip="Controls the likelihood of creating additional details not heavily conditioned by the init image.",
-                ),
-                IO.Combo.Input(
-                    "style_preset",
-                    options=get_stability_style_presets(),
-                    tooltip="Optional desired style of generated image.",
-                    advanced=True,
-                ),
-                IO.Int.Input(
-                    "seed",
-                    default=0,
-                    min=0,
-                    max=4294967294,
-                    step=1,
-                    display_mode=IO.NumberDisplay.number,
-                    control_after_generate=True,
-                    tooltip="The random seed used for creating the noise.",
-                ),
-                IO.String.Input(
-                    "negative_prompt",
-                    default="",
-                    tooltip="Keywords of what you do not wish to see in the output image. This is an advanced feature.",
-                    force_input=True,
-                    optional=True,
-                    advanced=True,
-                ),
-            ],
-            outputs=[
-                IO.Image.Output(),
-            ],
-            hidden=[
-                IO.Hidden.auth_token_comfy_org,
-                IO.Hidden.api_key_comfy_org,
-                IO.Hidden.unique_id,
-            ],
-            is_api_node=True,
-            price_badge=IO.PriceBadge(
-                expr="""{"type":"usd","usd":0.6}""",
-            ),
-        )
-
-    @classmethod
-    async def execute(
-        cls,
-        image: torch.Tensor,
-        prompt: str,
-        creativity: float,
-        style_preset: str,
-        seed: int,
-        negative_prompt: str = "",
-    ) -> IO.NodeOutput:
-        validate_string(prompt, strip_whitespace=False)
-        image_binary = tensor_to_bytesio(image, total_pixels=1024*1024).read()
-
-        if not negative_prompt:
-            negative_prompt = None
-        if style_preset == "None":
-            style_preset = None
-
-        files = {
-            "image": image_binary
-        }
-
-        response_api = await sync_op(
-            cls,
-            ApiEndpoint(path="/proxy/stability/v2beta/stable-image/upscale/creative", method="POST"),
-            response_model=StabilityAsyncResponse,
-            data=StabilityUpscaleCreativeRequest(
-                prompt=prompt,
-                negative_prompt=negative_prompt,
-                creativity=round(creativity,2),
-                style_preset=style_preset,
-                seed=seed,
-            ),
-            files=files,
-            content_type="multipart/form-data",
-        )
-
-        response_poll = await poll_op(
-            cls,
-            ApiEndpoint(path=f"/proxy/stability/v2beta/results/{response_api.id}"),
-            response_model=StabilityResultsGetResponse,
-            poll_interval=3,
-            status_extractor=lambda x: get_async_dummy_status(x),
-        )
-
-        if response_poll.finish_reason != "SUCCESS":
-            raise Exception(f"Stability Upscale Creative generation failed: {response_poll.finish_reason}.")
-
-        image_data = base64.b64decode(response_poll.result)
-        returned_image = bytesio_to_image_tensor(BytesIO(image_data))
-
-        return IO.NodeOutput(returned_image)
-
-
-class StabilityUpscaleFastNode(IO.ComfyNode):
-    """
-    Quickly upscales an image via Stability API call to 4x its original size; intended for upscaling low-quality/compressed images.
-    """
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="StabilityUpscaleFastNode",
-            display_name="Stability AI Upscale Fast",
-            category="partner/image/Stability AI",
-            description=cleandoc(cls.__doc__ or ""),
-            inputs=[
-                IO.Image.Input("image"),
-            ],
-            outputs=[
-                IO.Image.Output(),
-            ],
-            hidden=[
-                IO.Hidden.auth_token_comfy_org,
-                IO.Hidden.api_key_comfy_org,
-                IO.Hidden.unique_id,
-            ],
-            is_api_node=True,
-            price_badge=IO.PriceBadge(
-                expr="""{"type":"usd","usd":0.02}""",
-            ),
-        )
-
-    @classmethod
-    async def execute(cls, image: torch.Tensor) -> IO.NodeOutput:
-        image_binary = tensor_to_bytesio(image, total_pixels=4096*4096).read()
-
-        files = {
-            "image": image_binary
-        }
-
-        response_api = await sync_op(
-            cls,
-            ApiEndpoint(path="/proxy/stability/v2beta/stable-image/upscale/fast", method="POST"),
-            response_model=StabilityStableUltraResponse,
-            files=files,
-            content_type="multipart/form-data",
-        )
-
-        if response_api.finish_reason != "SUCCESS":
-            raise Exception(f"Stability Upscale Fast failed: {response_api.finish_reason}.")
-
-        image_data = base64.b64decode(response_api.image)
-        returned_image = bytesio_to_image_tensor(BytesIO(image_data))
-
-        return IO.NodeOutput(returned_image)
-
-
-class StabilityTextToAudio(IO.ComfyNode):
-    """Generates high-quality music and sound effects from text descriptions."""
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="StabilityTextToAudio",
-            display_name="Stability AI Text To Audio",
-            category="partner/audio/Stability AI",
-            essentials_category="Audio",
-            description=cleandoc(cls.__doc__ or ""),
-            inputs=[
-                IO.Combo.Input(
-                    "model",
-                    options=["stable-audio-2.5"],
-                ),
-                IO.String.Input("prompt", multiline=True, default=""),
-                IO.Int.Input(
-                    "duration",
-                    default=190,
-                    min=1,
-                    max=190,
-                    step=1,
-                    tooltip="Controls the duration in seconds of the generated audio.",
-                    optional=True,
-                ),
-                IO.Int.Input(
-                    "seed",
-                    default=0,
-                    min=0,
-                    max=4294967294,
-                    step=1,
-                    display_mode=IO.NumberDisplay.number,
-                    control_after_generate=True,
-                    tooltip="The random seed used for generation.",
-                    optional=True,
-                ),
-                IO.Int.Input(
-                    "steps",
-                    default=8,
-                    min=4,
-                    max=8,
-                    step=1,
-                    tooltip="Controls the number of sampling steps.",
-                    optional=True,
-                    advanced=True,
-                ),
-            ],
-            outputs=[
-                IO.Audio.Output(),
-            ],
-            hidden=[
-                IO.Hidden.auth_token_comfy_org,
-                IO.Hidden.api_key_comfy_org,
-                IO.Hidden.unique_id,
-            ],
-            is_api_node=True,
-            price_badge=IO.PriceBadge(
-                expr="""{"type":"usd","usd":0.2}""",
-            ),
-        )
-
-    @classmethod
-    async def execute(cls, model: str, prompt: str, duration: int, seed: int, steps: int) -> IO.NodeOutput:
-        validate_string(prompt, max_length=10000)
-        payload = StabilityTextToAudioRequest(prompt=prompt, model=model, duration=duration, seed=seed, steps=steps)
-        response_api = await sync_op(
-            cls,
-            ApiEndpoint(path="/proxy/stability/v2beta/audio/stable-audio-2/text-to-audio", method="POST"),
-            response_model=StabilityAudioResponse,
-            data=payload,
-            content_type="multipart/form-data",
-        )
-        if not response_api.audio:
-            raise ValueError("No audio file was received in response.")
-        return IO.NodeOutput(audio_bytes_to_audio_input(base64.b64decode(response_api.audio)))
-
-
-class StabilityAudioToAudio(IO.ComfyNode):
-    """Transforms existing audio samples into new high-quality compositions using text instructions."""
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="StabilityAudioToAudio",
-            display_name="Stability AI Audio To Audio",
-            category="partner/audio/Stability AI",
-            description=cleandoc(cls.__doc__ or ""),
-            inputs=[
-                IO.Combo.Input(
-                    "model",
-                    options=["stable-audio-2.5"],
-                ),
-                IO.String.Input("prompt", multiline=True, default=""),
-                IO.Audio.Input("audio", tooltip="Audio must be between 6 and 190 seconds long."),
-                IO.Int.Input(
-                    "duration",
-                    default=190,
-                    min=1,
-                    max=190,
-                    step=1,
-                    tooltip="Controls the duration in seconds of the generated audio.",
-                    optional=True,
-                ),
-                IO.Int.Input(
-                    "seed",
-                    default=0,
-                    min=0,
-                    max=4294967294,
-                    step=1,
-                    display_mode=IO.NumberDisplay.number,
-                    control_after_generate=True,
-                    tooltip="The random seed used for generation.",
-                    optional=True,
-                ),
-                IO.Int.Input(
-                    "steps",
-                    default=8,
-                    min=4,
-                    max=8,
-                    step=1,
-                    tooltip="Controls the number of sampling steps.",
-                    optional=True,
-                    advanced=True,
-                ),
-                IO.Float.Input(
-                    "strength",
-                    default=1,
-                    min=0.01,
-                    max=1.0,
-                    step=0.01,
-                    display_mode=IO.NumberDisplay.slider,
-                    tooltip="Parameter controls how much influence the audio parameter has on the generated audio.",
-                    optional=True,
-                ),
-            ],
-            outputs=[
-                IO.Audio.Output(),
-            ],
-            hidden=[
-                IO.Hidden.auth_token_comfy_org,
-                IO.Hidden.api_key_comfy_org,
-                IO.Hidden.unique_id,
-            ],
-            is_api_node=True,
-            price_badge=IO.PriceBadge(
-                expr="""{"type":"usd","usd":0.2}""",
-            ),
-        )
-
-    @classmethod
-    async def execute(
-        cls, model: str, prompt: str, audio: Input.Audio, duration: int, seed: int, steps: int, strength: float
-    ) -> IO.NodeOutput:
-        validate_string(prompt, max_length=10000)
-        validate_audio_duration(audio, 6, 190)
-        payload = StabilityAudioToAudioRequest(
-            prompt=prompt, model=model, duration=duration, seed=seed, steps=steps, strength=strength
-        )
-        response_api = await sync_op(
-            cls,
-            ApiEndpoint(path="/proxy/stability/v2beta/audio/stable-audio-2/audio-to-audio", method="POST"),
-            response_model=StabilityAudioResponse,
-            data=payload,
-            content_type="multipart/form-data",
-            files={"audio": audio_input_to_mp3(audio)},
-        )
-        if not response_api.audio:
-            raise ValueError("No audio file was received in response.")
-        return IO.NodeOutput(audio_bytes_to_audio_input(base64.b64decode(response_api.audio)))
-
-
-class StabilityAudioInpaint(IO.ComfyNode):
-    """Transforms part of existing audio sample using text instructions."""
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="StabilityAudioInpaint",
-            display_name="Stability AI Audio Inpaint",
-            category="partner/audio/Stability AI",
-            description=cleandoc(cls.__doc__ or ""),
-            inputs=[
-                IO.Combo.Input(
-                    "model",
-                    options=["stable-audio-2.5"],
-                ),
-                IO.String.Input("prompt", multiline=True, default=""),
-                IO.Audio.Input("audio", tooltip="Audio must be between 6 and 190 seconds long."),
-                IO.Int.Input(
-                    "duration",
-                    default=190,
-                    min=1,
-                    max=190,
-                    step=1,
-                    tooltip="Controls the duration in seconds of the generated audio.",
-                    optional=True,
-                ),
-                IO.Int.Input(
-                    "seed",
-                    default=0,
-                    min=0,
-                    max=4294967294,
-                    step=1,
-                    display_mode=IO.NumberDisplay.number,
-                    control_after_generate=True,
-                    tooltip="The random seed used for generation.",
-                    optional=True,
-                ),
-                IO.Int.Input(
-                    "steps",
-                    default=8,
-                    min=4,
-                    max=8,
-                    step=1,
-                    tooltip="Controls the number of sampling steps.",
-                    optional=True,
-                    advanced=True,
-                ),
-                IO.Int.Input(
-                    "mask_start",
-                    default=30,
-                    min=0,
-                    max=190,
-                    step=1,
-                    optional=True,
-                    advanced=True,
-                ),
-                IO.Int.Input(
-                    "mask_end",
-                    default=190,
-                    min=0,
-                    max=190,
-                    step=1,
-                    optional=True,
-                    advanced=True,
-                ),
-            ],
-            outputs=[
-                IO.Audio.Output(),
-            ],
-            hidden=[
-                IO.Hidden.auth_token_comfy_org,
-                IO.Hidden.api_key_comfy_org,
-                IO.Hidden.unique_id,
-            ],
-            is_api_node=True,
-            price_badge=IO.PriceBadge(
-                expr="""{"type":"usd","usd":0.2}""",
-            ),
-        )
-
-    @classmethod
-    async def execute(
-        cls,
-        model: str,
-        prompt: str,
-        audio: Input.Audio,
-        duration: int,
-        seed: int,
-        steps: int,
-        mask_start: int,
-        mask_end: int,
-    ) -> IO.NodeOutput:
-        validate_string(prompt, max_length=10000)
-        if mask_end <= mask_start:
-            raise ValueError(f"Value of mask_end({mask_end}) should be greater then mask_start({mask_start})")
-        validate_audio_duration(audio, 6, 190)
-
-        payload = StabilityAudioInpaintRequest(
-            prompt=prompt,
-            model=model,
-            duration=duration,
-            seed=seed,
-            steps=steps,
-            mask_start=mask_start,
-            mask_end=mask_end,
-        )
-        response_api = await sync_op(
-            cls,
-            endpoint=ApiEndpoint(path="/proxy/stability/v2beta/audio/stable-audio-2/inpaint", method="POST"),
-            response_model=StabilityAudioResponse,
-            data=payload,
-            content_type="multipart/form-data",
-            files={"audio": audio_input_to_mp3(audio)},
-        )
-        if not response_api.audio:
-            raise ValueError("No audio file was received in response.")
-        return IO.NodeOutput(audio_bytes_to_audio_input(base64.b64decode(response_api.audio)))
-
-
-class StabilityExtension(ComfyExtension):
-    @override
-    async def get_node_list(self) -> list[type[IO.ComfyNode]]:
-        return [
-            StabilityStableImageUltraNode,
-            StabilityStableImageSD_3_5Node,
-            StabilityUpscaleConservativeNode,
-            StabilityUpscaleCreativeNode,
-            StabilityUpscaleFastNode,
-            StabilityTextToAudio,
-            StabilityAudioToAudio,
-            StabilityAudioInpaint,
-        ]
-
-
-async def comfy_entrypoint() -> StabilityExtension:
-    return StabilityExtension()

comfy_api_nodes/util/__init__.py

@@ -26,6 +26,7 @@ from .conversions import (
     text_filepath_to_base64_string,
     text_filepath_to_data_uri,
     trim_video,
+    upscale_image_tensor_to_min_pixels,
     upscale_video_to_min_pixels,
     video_to_base64_string,
 )
@@ -99,6 +100,7 @@ __all__ = [
     "text_filepath_to_base64_string",
     "text_filepath_to_data_uri",
     "trim_video",
+    "upscale_image_tensor_to_min_pixels",
     "upscale_video_to_min_pixels",
     "video_to_base64_string",
     # Validation utilities

comfy_api_nodes/util/conversions.py

@@ -448,6 +448,15 @@ def _compute_upscale_dims(src_w: int, src_h: int, total_pixels: int) -> tuple[in
     return new_w, new_h
 
 
+def upscale_image_tensor_to_min_pixels(image: torch.Tensor, total_pixels: int) -> torch.Tensor:
+    samples = image.movedim(-1, 1)
+    dims = _compute_upscale_dims(samples.shape[3], samples.shape[2], int(total_pixels))
+    if dims is None:
+        return image
+    new_w, new_h = dims
+    return common_upscale(samples, new_w, new_h, "lanczos", "disabled").movedim(1, -1)
+
+
 def upscale_video_to_min_pixels(video: Input.Video, min_pixels: int) -> Input.Video:
     """Upscale a video to meet at least ``min_pixels`` (w * h), preserving aspect ratio.
 

comfy_extras/nodes_color.py

@@ -16,23 +16,30 @@ class ColorToRGBInt(io.ComfyNode):
             ],
             outputs=[
                 io.Int.Output(display_name="rgb_int"),
-                io.Color.Output(display_name="hex")
+                io.Color.Output(display_name="hex"),
+                io.Float.Output(display_name="alpha"),
             ],
         )
 
     @classmethod
     def execute(cls, color: str) -> io.NodeOutput:
-        # expect format #RRGGBB
-        if len(color) != 7 or color[0] != "#":
-            raise ValueError("Color must be in format #RRGGBB")
+        # expect format #RRGGBB or #RRGGBBAA
+        if len(color) not in (7, 9) or color[0] != "#":
+            raise ValueError("Color must be in format #RRGGBB or #RRGGBBAA")
         try:
             int(color[1:], 16)
         except ValueError:
-            raise ValueError("Color must be in format #RRGGBB") from None
+            raise ValueError("Color must be in format #RRGGBB or #RRGGBBAA") from None
+
+        alpha = 1.0
+        if len(color) == 9:
+            alpha = int(color[7:9], 16) / 255.0
+            color = color[:7]
+
         r, g, b = hex_to_rgb(color)
 
         rgb_int = r * 256 * 256 + g * 256 + b
-        return io.NodeOutput(rgb_int, color)
+        return io.NodeOutput(rgb_int, color, alpha)
 
 
 class ColorExtension(ComfyExtension):

comfy_extras/nodes_cond.py

@@ -8,7 +8,8 @@ class CLIPTextEncodeControlnet(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="CLIPTextEncodeControlnet",
-            category="experimental/conditioning",
+            display_name="CLIP Text Encode (Controlnet)",
+            category="model/conditioning",
             inputs=[
                 io.Clip.Input("clip"),
                 io.Conditioning.Input("conditioning"),
@@ -35,11 +36,12 @@ class T5TokenizerOptions(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="T5TokenizerOptions",
-            category="experimental/conditioning",
+            display_name="T5 Tokenizer Options",
+            category="model/conditioning",
             inputs=[
                 io.Clip.Input("clip"),
-                io.Int.Input("min_padding", default=0, min=0, max=10000, step=1, advanced=True),
-                io.Int.Input("min_length", default=0, min=0, max=10000, step=1, advanced=True),
+                io.Int.Input("min_padding", default=0, min=0, max=10000, step=1),
+                io.Int.Input("min_length", default=0, min=0, max=10000, step=1),
             ],
             outputs=[io.Clip.Output()],
             is_experimental=True,

comfy_extras/nodes_custom_sampler.py

@@ -1070,7 +1070,7 @@ class AddNoise(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="AddNoise",
-            category="experimental/custom_sampling/noise",
+            category="model/sampling/noise",
             is_experimental=True,
             inputs=[
                 io.Model.Input("model"),
@@ -1120,7 +1120,7 @@ class ManualSigmas(io.ComfyNode):
         return io.Schema(
             node_id="ManualSigmas",
             search_aliases=["custom noise schedule", "define sigmas"],
-            category="experimental/custom_sampling",
+            category="model/sampling/sigmas",
             is_experimental=True,
             inputs=[
                 io.String.Input("sigmas", default="1, 0.5", multiline=False)

comfy_extras/nodes_photomaker.py

@@ -123,7 +123,8 @@ class PhotoMakerLoader(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="PhotoMakerLoader",
-            category="experimental/photomaker",
+            display_name="Load PhotoMaker Model",
+            category="model/loaders",
             inputs=[
                 io.Combo.Input("photomaker_model_name", options=folder_paths.get_filename_list("photomaker")),
             ],
@@ -149,7 +150,8 @@ class PhotoMakerEncode(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="PhotoMakerEncode",
-            category="experimental/photomaker",
+            display_name="PhotoMaker Encode",
+            category="model/conditioning/photomaker",
             inputs=[
                 io.Photomaker.Input("photomaker"),
                 io.Image.Input("image"),

comfy_extras/nodes_stable_cascade.py

@@ -119,7 +119,7 @@ class StableCascade_SuperResolutionControlnet(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="StableCascade_SuperResolutionControlnet",
-            category="experimental/stable_cascade",
+            category="experimental/stable cascade",
             is_experimental=True,
             inputs=[
                 io.Image.Input("image"),

comfy_extras/nodes_triposplat.py

@@ -143,7 +143,7 @@ class VAEDecodeTripoSplat(IO.ComfyNode):
         return IO.Schema(
             node_id="VAEDecodeTripoSplat",
             display_name="TripoSplat Decode",
-            category="3d/latent",
+            category="model/latent/triposplat",
             description="Decode the sampled TripoSplat latent into a 3D gaussian splat. "
                         "Modify the number of gaussians to vary the density.",
             inputs=[
@@ -188,7 +188,7 @@ class TripoSplatSamplingPreview(IO.ComfyNode):
         return IO.Schema(
             node_id="TripoSplatSamplingPreview",
             display_name="TripoSplat Sampling Preview",
-            category="3d/latent",
+            category="model/latent/triposplat",
             description="Patch the TripoSplat model for the standard Ksampler node to show a live decoded "
                         "gaussian splat preview at each step.",
             inputs=[

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.26.0"
+__version__ = "0.27.0"

folder_paths.py

@@ -264,6 +264,59 @@ def annotated_filepath(name: str) -> tuple[str, str | None]:
     return name, base_dir
 
 
+# Content types a browser may execute or render inline. File endpoints that
+# serve user-controlled content must force these to download (and ideally set
+# Content-Disposition: attachment) to avoid stored XSS. Centralised here so the
+# /view and /userdata handlers can't drift apart. mimetypes.guess_type may
+# return either the text/* or application/* spelling depending on platform, so
+# both are listed.
+DANGEROUS_CONTENT_TYPES = {
+    'text/html', 'text/html-sandboxed', 'application/xhtml+xml',
+    'text/javascript', 'application/javascript', 'application/x-javascript',
+    'application/ecmascript', 'text/css',
+    'image/svg+xml', 'application/xml', 'text/xml',
+    # message/rfc822 (.mht/.mhtml) can carry script in some browsers.
+    'message/rfc822',
+}
+
+
+def is_dangerous_content_type(content_type: str | None) -> bool:
+    """Return True if a browser may execute or render `content_type` inline.
+
+    Normalises before matching so the check can't be slipped past with a
+    charset/boundary parameter (``text/html; charset=utf-8``) or casing
+    (``TEXT/HTML``). Any XML dialect (``*+xml`` or ``*/xml``) is treated as
+    dangerous because XML can carry inline script via stylesheet/entity tricks,
+    which also covers the ``application/{xslt,rss,atom,rdf}+xml`` family without
+    enumerating each one. Endpoints serving user-controlled content should route
+    a dangerous type to ``application/octet-stream`` + ``Content-Disposition:
+    attachment`` + ``X-Content-Type-Options: nosniff``.
+    """
+    if not content_type:
+        return False
+    normalized = content_type.split(';', 1)[0].strip().lower()
+    if normalized in DANGEROUS_CONTENT_TYPES:
+        return True
+    return normalized.endswith('+xml') or normalized.endswith('/xml')
+
+
+def is_within_directory(directory: str, target: str) -> bool:
+    """Return True if `target` resolves to a path inside `directory`.
+
+    Uses realpath on both operands so that a symlink placed inside `directory`
+    that points elsewhere cannot escape the containment check at open time.
+    """
+    try:
+        directory = os.path.realpath(directory)
+        target = os.path.realpath(target)
+        return os.path.commonpath((directory, target)) == directory
+    except ValueError:
+        # ValueError is raised by realpath() on a path with an embedded null
+        # byte, and by commonpath() on Windows when the paths are on different
+        # drives. In either case the target is not safely within the directory.
+        return False
+
+
 def get_annotated_filepath(name: str, default_dir: str | None=None) -> str:
     name, base_dir = annotated_filepath(name)
 
@@ -273,7 +326,12 @@ def get_annotated_filepath(name: str, default_dir: str | None=None) -> str:
         else:
             base_dir = get_input_directory()  # fallback path
 
-    return os.path.join(base_dir, name)
+    filepath = os.path.abspath(os.path.join(base_dir, name))
+    # Prevent path traversal: the resolved path must stay within base_dir.
+    # repr() the name in the message so a crafted value can't inject log lines.
+    if not is_within_directory(base_dir, filepath):
+        raise ValueError("Invalid file path: {!r}".format(name))
+    return filepath
 
 
 def exists_annotated_filepath(name) -> bool:
@@ -282,7 +340,10 @@ def exists_annotated_filepath(name) -> bool:
     if base_dir is None:
         base_dir = get_input_directory()  # fallback path
 
-    filepath = os.path.join(base_dir, name)
+    filepath = os.path.abspath(os.path.join(base_dir, name))
+    # Treat traversal attempts as non-existent rather than probing the filesystem.
+    if not is_within_directory(base_dir, filepath):
+        return False
     return os.path.exists(filepath)
 
 

main.py

@@ -403,7 +403,7 @@ def prompt_worker(q, server_instance):
                 hook_breaker_ac10a0.restore_functions()
 
                 if not asset_seeder.is_disabled():
-                    asset_seeder.enqueue_enrich(roots=("output",), compute_hashes=True)
+                    asset_seeder.enqueue_enrich(roots=("output",), compute_hashes=args.enable_asset_hashing)
                 asset_seeder.resume()
 
 
@@ -458,7 +458,7 @@ def setup_database():
         if dependencies_available():
             init_db()
             if args.enable_assets:
-                if asset_seeder.start(roots=("models", "input", "output"), prune_first=True, compute_hashes=True):
+                if asset_seeder.start(roots=("models", "input", "output"), prune_first=True, compute_hashes=args.enable_asset_hashing):
                     logging.info("Background asset scan initiated for models, input, output")
     except Exception as e:
         if "database is locked" in str(e):

nodes.py

@@ -349,7 +349,7 @@ class VAEDecodeTiled:
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "decode"
 
-    CATEGORY = "experimental"
+    CATEGORY = "model/latent"
 
     def decode(self, vae, samples, tile_size, overlap=64, temporal_size=64, temporal_overlap=8):
         if tile_size < overlap * 4:
@@ -396,7 +396,7 @@ class VAEEncodeTiled:
     RETURN_TYPES = ("LATENT",)
     FUNCTION = "encode"
 
-    CATEGORY = "experimental"
+    CATEGORY = "model/latent"
 
     def encode(self, vae, pixels, tile_size, overlap, temporal_size=64, temporal_overlap=8):
         t = vae.encode_tiled(pixels, tile_x=tile_size, tile_y=tile_size, overlap=overlap, tile_t=temporal_size, overlap_t=temporal_overlap)
@@ -514,7 +514,7 @@ class SaveLatent:
 
     OUTPUT_NODE = True
 
-    CATEGORY = "experimental"
+    CATEGORY = "model/latent"
 
     def save(self, samples, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None):
         full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
@@ -559,7 +559,7 @@ class LoadLatent:
         files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f)) and f.endswith(".latent")]
         return {"required": {"latent": [sorted(files), ]}, }
 
-    CATEGORY = "experimental"
+    CATEGORY = "model/latent"
 
     RETURN_TYPES = ("LATENT", )
     FUNCTION = "load"
@@ -2155,6 +2155,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "GLIGENTextBoxApply": "Apply GLIGEN Text Box",
     "ConditioningZeroOut": "Conditioning Zero Out",
     # Latent
+    "LoadLatent": "Load Latent",
+    "SaveLatent": "Save Latent",
     "VAEEncodeForInpaint": "VAE Encode (for Inpainting)",
     "SetLatentNoiseMask": "Set Latent Noise Mask",
     "VAEDecode": "VAE Decode",
@@ -2189,7 +2191,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ImageSharpen": "Sharpen Image",
     "ImageScaleToTotalPixels": "Scale Image to Total Pixels",
     "GetImageSize": "Get Image Size",
-    # experimental
     "VAEDecodeTiled": "VAE Decode (Tiled)",
     "VAEEncodeTiled": "VAE Encode (Tiled)",
 }

openapi.yaml

@@ -188,6 +188,49 @@ components:
                 - id
                 - updated_at
             type: object
+        AvailabilityStatusRequest:
+            description: |
+                Models to query — each entry is `model_id → URL`. The URL lets
+                the server compute file_size + is_hf_downloadable on the same
+                request, eliminating the need for a separate metadata endpoint.
+            properties:
+                models:
+                    additionalProperties:
+                        type: string
+                    description: model_id → URL declared in the workflow.
+                    type: object
+            required:
+                - models
+            type: object
+        AvailabilityStatusResponse:
+            description: Per-model state + metadata + HF auth snapshot.
+            properties:
+                hf_auth:
+                    $ref: '#/components/schemas/HfAuthStatus'
+                models:
+                    additionalProperties:
+                        $ref: '#/components/schemas/ModelStatusEntry'
+                    type: object
+            required:
+                - models
+                - hf_auth
+            type: object
+        CancelDownloadSessionRequest:
+            description: Request to cancel an in-flight download for a given model_id.
+            properties:
+                model_id:
+                    type: string
+            required:
+                - model_id
+            type: object
+        CancelDownloadSessionResponse:
+            description: Result of a cancellation request.
+            properties:
+                cancelled:
+                    type: boolean
+            required:
+                - cancelled
+            type: object
         CreateWorkflowRequest:
             description: Request body for creating a new saved workflow.
             properties:
@@ -230,6 +273,51 @@ components:
                 - base_version
                 - workflow_json
             type: object
+        DownloadModelsRequest:
+            description: Map of model_id → URL of files to fetch into the model folders.
+            properties:
+                models:
+                    additionalProperties:
+                        type: string
+                    description: model_id → URL of models to download.
+                    type: object
+            required:
+                - models
+            type: object
+        DownloadModelsResponse:
+            description: Acknowledgement that downloads have been scheduled.
+            properties:
+                accepted:
+                    description: Always true; the request was scheduled.
+                    type: boolean
+                scheduled:
+                    description: The list of model_ids whose downloads are now in-flight.
+                    items:
+                        type: string
+                    type: array
+            required:
+                - accepted
+                - scheduled
+            type: object
+        DownloadProgress:
+            description: In-flight download progress; embedded in ModelStatusEntry.
+            properties:
+                bytes_downloaded:
+                    format: int64
+                    type: integer
+                progress:
+                    description: Fraction in [0,1]; null until total_bytes is known.
+                    format: float
+                    nullable: true
+                    type: number
+                total_bytes:
+                    description: Content-Length when supplied by the source.
+                    format: int64
+                    nullable: true
+                    type: integer
+            required:
+                - bytes_downloaded
+            type: object
         ErrorResponse:
             description: Standard error response with a machine-readable code and human-readable message.
             properties:
@@ -394,6 +482,46 @@ components:
                 - name
                 - info
             type: object
+        HfAuthLoginStartResponse:
+            description: URL the frontend should open in a new tab to complete login.
+            properties:
+                authorize_url:
+                    type: string
+            required:
+                - authorize_url
+            type: object
+        HfAuthLogoutResponse:
+            description: Result of the logout call (always logged_out = true).
+            properties:
+                logged_out:
+                    type: boolean
+            required:
+                - logged_out
+            type: object
+        HfAuthStatus:
+            description: Inline snapshot of the server's HuggingFace OAuth state.
+            properties:
+                eligible:
+                    description: True iff this deployment can surface interactive HF login.
+                    type: boolean
+                token_available:
+                    description: True iff a token (possibly expired but refreshable) is stored.
+                    type: boolean
+            required:
+                - token_available
+                - eligible
+            type: object
+        HfAuthTokenStatusResponse:
+            description: Whether the server holds an HF OAuth token + resolved username.
+            properties:
+                token_available:
+                    type: boolean
+                username:
+                    nullable: true
+                    type: string
+            required:
+                - token_available
+            type: object
         HistoryDetailEntry:
             description: History entry with full prompt data
             properties:
@@ -798,6 +926,41 @@ components:
                 - name
                 - folders
             type: object
+        ModelStatusEntry:
+            description: Everything the UI needs to render one row of the model.
+            properties:
+                file_size:
+                    description: Bytes, when known. Cached server-side per URL.
+                    format: int64
+                    nullable: true
+                    type: integer
+                is_hf_downloadable:
+                    description: |
+                        HuggingFace-only signal. True if the server can fetch this
+                        URL with its current auth state (public, or gated-with-access).
+                        False if gated and lacking access. Null for non-HF URLs and
+                        for HF URLs whose probe failed entirely.
+                    nullable: true
+                    type: boolean
+                progress:
+                    type: object
+                    allOf:
+                        - $ref: '#/components/schemas/DownloadProgress'
+                    description: Present when `state == downloading`.
+                    nullable: true
+                state:
+                    description: |
+                        `available` — file is on disk.
+                        `missing` — not on disk and no download in flight.
+                        `downloading` — server is currently fetching the file.
+                    enum:
+                        - available
+                        - missing
+                        - downloading
+                    type: string
+            required:
+                - state
+            type: object
         NodeInfo:
             description: Metadata describing a single ComfyUI node type and its inputs/outputs.
             properties:
@@ -2350,6 +2513,72 @@ paths:
             summary: Get tag histogram for filtered assets
             tags:
                 - file
+    /api/cancel-model-download-session:
+        post:
+            description: |
+                Cancels the download session for the given model_id. The worker
+                observes the cancellation between chunks, removes its partial `.tmp`
+                file, and exits without writing the destination path.
+            operationId: postCancelModelDownloadSession
+            requestBody:
+                content:
+                    application/json:
+                        schema:
+                            $ref: '#/components/schemas/CancelDownloadSessionRequest'
+                required: true
+            responses:
+                "200":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/CancelDownloadSessionResponse'
+                    description: Session cancelled.
+                "404":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: No active download for that model_id.
+            summary: Cancel an in-flight server-side model download
+            tags:
+                - model
+    /api/download-models:
+        post:
+            description: |
+                Schedules downloads for every model_id in the request map. Returns
+                immediately after validation; progress is observed via
+                `/api/models-availability-status`. Fails atomically if any model
+                is already on disk, already downloading, gated, or has a URL that
+                is not on the server's allowlist (HuggingFace, Civitai, localhost).
+            operationId: postDownloadModels
+            requestBody:
+                content:
+                    application/json:
+                        schema:
+                            $ref: '#/components/schemas/DownloadModelsRequest'
+                required: true
+            responses:
+                "202":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/DownloadModelsResponse'
+                    description: Downloads accepted and scheduled.
+                "400":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: One of the requested models is invalid, gated, or has a non-allowed URL.
+                "409":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: One of the requested models is already on disk or downloading.
+            summary: Start a server-side download of one or more models
+            tags:
+                - model
     /api/embeddings:
         get:
             description: Returns the list of text-encoder embeddings available on disk.
@@ -2655,6 +2884,74 @@ paths:
             summary: Get a specific subgraph blueprint
             tags:
                 - workflow
+    /api/hf-auth-login-start:
+        post:
+            description: |
+                Spawns a short-lived loopback callback server (port 41954) and
+                returns the URL the frontend should open in a new tab. After the
+                user grants consent, HF redirects back to the callback URL with
+                an authorization code; the server exchanges that for a token and
+                persists it. Subsequent `/api/hf-auth-token-status` calls will
+                return `token_available: true`. Rejected with 403 if the
+                deployment is not eligible (not loopback or in --multi-user mode);
+                409 if another login attempt is already in progress.
+            operationId: postHfAuthLoginStart
+            responses:
+                "200":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/HfAuthLoginStartResponse'
+                    description: Login flow started; `authorize_url` is ready.
+                "403":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Deployment is not eligible for interactive HF login.
+                "409":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Another login attempt is already in progress.
+            summary: Begin a HuggingFace OAuth login flow
+            tags:
+                - model
+    /api/hf-auth-logout:
+        post:
+            description: Clears the in-memory cache and removes the on-disk token file.
+            operationId: postHfAuthLogout
+            responses:
+                "200":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/HfAuthLogoutResponse'
+                    description: Logged out (idempotent — succeeds even if no token was held).
+            summary: Drop the stored HuggingFace OAuth token
+            tags:
+                - model
+    /api/hf-auth-token-status:
+        get:
+            description: |
+                Returns `token_available: true` when the server has a token
+                in memory (or on disk) for HuggingFace, irrespective of whether
+                the access_token is currently fresh — an expired one with a
+                refresh_token still counts as "logged in" because we'll refresh
+                transparently on next use. If a username is resolvable via
+                `HfApi.whoami` we return that too, for the settings UI.
+            operationId: getHfAuthTokenStatus
+            responses:
+                "200":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/HfAuthTokenStatusResponse'
+                    description: Token status.
+            summary: Whether the server holds a usable HuggingFace OAuth token
+            tags:
+                - model
     /api/history:
         post:
             deprecated: true
@@ -3157,6 +3454,48 @@ paths:
             summary: Cancel multiple jobs
             tags:
                 - workflow
+    /api/models-availability-status:
+        post:
+            description: |
+                Given a map of `{model_id: url}` (model_id is
+                `<directory>/<filename>`), returns per-id state plus the
+                metadata the UI needs to render the row:
+
+                  - `state` — one of `available` / `missing` / `downloading`
+                  - `progress` — embedded when `state == downloading`
+                  - `file_size` — bytes (when known)
+                  - `is_hf_downloadable` — for HF URLs only: true if the
+                    server can currently fetch the file with its stored auth
+                    state, false if gated and lacking access, null otherwise
+
+                Designed for 1 Hz polling. `file_size` and the intrinsic
+                "is this model gated" check are cached server-side per URL;
+                `is_hf_downloadable` is recomputed per call so license
+                acceptance and login/logout transitions show up within one
+                poll interval without any client-side cache plumbing.
+            operationId: postModelsAvailabilityStatus
+            requestBody:
+                content:
+                    application/json:
+                        schema:
+                            $ref: '#/components/schemas/AvailabilityStatusRequest'
+                required: true
+            responses:
+                "200":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/AvailabilityStatusResponse'
+                    description: Per-model status and metadata.
+                "400":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Malformed request body.
+            summary: Unified per-model status + metadata for the polling UI
+            tags:
+                - model
     /api/node_replacements:
         get:
             description: |
@@ -5103,3 +5442,5 @@ tags:
       name: queue
     - description: Job lifecycle queries
       name: job
+    - description: Server-side model availability and downloads
+      name: model

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.26.0"
+version = "0.27.0"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.10"

requirements.txt

@@ -1,5 +1,5 @@
 comfyui-frontend-package==1.45.20
-comfyui-workflow-templates==0.10.7
+comfyui-workflow-templates==0.11.2
 comfyui-embedded-docs==0.5.6
 torch
 torchsde
@@ -9,6 +9,7 @@ numpy>=1.25.0
 einops
 transformers>=4.50.3
 tokenizers>=0.13.3
+huggingface_hub
 sentencepiece
 safetensors>=0.4.2
 aiohttp>=3.11.8

server.py

@@ -47,6 +47,7 @@ from app.assets.seeder import asset_seeder
 from app.assets.api.routes import register_assets_routes
 from app.assets.services.ingest import register_file_in_place
 from app.assets.services.asset_management import resolve_hash_to_path
+from app.model_downloader.api.routes import register_routes as register_model_downloader_routes
 
 from app.user_manager import UserManager
 from app.model_manager import ModelFileManager
@@ -127,6 +128,7 @@ def create_cors_middleware(allowed_origin: str):
 
     return cors_middleware
 
+
 def is_loopback(host):
     if host is None:
         return False
@@ -256,6 +258,7 @@ class PromptServer():
         else:
             register_assets_routes(self.app)
             asset_seeder.disable()
+        register_model_downloader_routes(self.app)
         routes = web.RouteTableDef()
         self.routes = routes
         self.last_node_id = None
@@ -616,15 +619,30 @@ class PromptServer():
                             or 'application/octet-stream'
                         )
 
-                        # For security, force certain mimetypes to download instead of display
-                        if content_type in {'text/html', 'text/html-sandboxed', 'application/xhtml+xml', 'text/javascript', 'text/css'}:
-                            content_type = 'application/octet-stream'  # Forces download
+                        # For security, force renderable/active types (HTML, JS,
+                        # CSS, SVG, XML — anything that can carry inline <script>
+                        # and execute in the page origin) to download instead of
+                        # displaying inline, preventing stored XSS. The
+                        # attachment disposition is the load-bearing guard: a
+                        # bare filename= hint does not force a download per
+                        # RFC 6266, so we only attach it on the dangerous branch
+                        # to avoid breaking inline display of legitimate images.
+                        # Escape backslash/quote per RFC 6266 quoted-string so a
+                        # filename containing a double quote (which passes the
+                        # ".."/leading-slash filter above) can't break out of the
+                        # header's quoted-string and malform the disposition.
+                        safe_filename = filename.replace("\\", "\\\\").replace('"', '\\"')
+                        disposition = f"filename=\"{safe_filename}\""
+                        if folder_paths.is_dangerous_content_type(content_type):
+                            content_type = 'application/octet-stream'
+                            disposition = f"attachment; filename=\"{safe_filename}\""
 
                         return web.FileResponse(
                             file,
                             headers={
-                                "Content-Disposition": f"filename=\"{filename}\"",
-                                "Content-Type": content_type
+                                "Content-Disposition": disposition,
+                                "Content-Type": content_type,
+                                "X-Content-Type-Options": "nosniff"
                             }
                         )
 

tests-unit/app_test/hf_auth_test.py

@@ -0,0 +1,708 @@
+"""Unit tests for the HuggingFace auth subsystem.
+
+Covers:
+  - token store: save/load roundtrip, chmod 0600, atomic write, delete
+  - eligibility under various CLI-arg combinations
+  - URL parsing (huggingface.co host detection + repo_id extraction)
+  - HF-aware gated_detection.probe_url (mocked auth_check)
+  - HF auth routes (token status, login start with eligibility gate, logout)
+  - PKCE primitives + authorize URL shape
+
+The OAuth callback server itself isn't exercised end-to-end here — that
+requires a real HF server. We test the components (state checking,
+URL building, code-exchange request shape) instead.
+"""
+
+from __future__ import annotations
+
+import os
+import stat
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+from aiohttp import web
+
+from app.model_downloader.api.routes import register_routes
+from app.model_downloader.hf_auth import oauth
+from app.model_downloader.hf_auth.auth_store import HF_AUTH_STORE, HfAuthStore
+from app.model_downloader.hf_auth.token_store import (
+    EXPIRY_BUFFER_SECS,
+    Token,
+    delete_token,
+    load_token,
+    save_token,
+)
+from app.model_downloader.hf_url import is_hf_url, repo_id_from_url
+
+
+# --------------------------------------------------------------------------- #
+# Fixtures
+# --------------------------------------------------------------------------- #
+
+
+@pytest.fixture
+def patched_user_dir(tmp_path):
+    """Redirect ``folder_paths.get_user_directory`` so the token file
+    lands in an isolated tmp_path instead of the real user dir."""
+    user_dir = tmp_path / "user"
+    user_dir.mkdir()
+    with patch("folder_paths.get_user_directory", return_value=str(user_dir)):
+        yield user_dir
+
+
+def _token_file_path(user_dir) -> str:
+    return os.path.join(user_dir, "__hf_auth", "hf_auth_token.json")
+
+
+@pytest.fixture
+def fresh_auth_store():
+    """Wipe singleton state between tests: auth + probe caches."""
+    from app.model_downloader import gated_detection
+
+    HF_AUTH_STORE._token = None
+    HF_AUTH_STORE._loaded_from_disk = False
+    gated_detection.clear_caches_for_tests()
+    yield HF_AUTH_STORE
+    HF_AUTH_STORE._token = None
+    HF_AUTH_STORE._loaded_from_disk = False
+    gated_detection.clear_caches_for_tests()
+
+
+@pytest.fixture
+def app(patched_user_dir, fresh_auth_store):
+    app = web.Application()
+    register_routes(app)
+    return app
+
+
+# --------------------------------------------------------------------------- #
+# URL parsing
+# --------------------------------------------------------------------------- #
+
+
+def test_is_hf_url_recognises_huggingface_co():
+    assert is_hf_url("https://huggingface.co/x/y/resolve/main/z.safetensors")
+    assert is_hf_url("https://huggingface.co/abc")
+    assert not is_hf_url("https://hf-mirror.com/x/y/resolve/main/z.safetensors")
+    assert not is_hf_url("https://civitai.com/x.safetensors")
+
+
+def test_repo_id_from_url_extracts_org_and_repo():
+    url = "https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-HDR/resolve/main/x.safetensors"
+    assert repo_id_from_url(url) == "Lightricks/LTX-2.3-22b-IC-LoRA-HDR"
+
+
+def test_repo_id_from_url_handles_nested_path():
+    url = "https://huggingface.co/Comfy-Org/ltx-2.3/resolve/main/split_files/loras/x.safetensors"
+    assert repo_id_from_url(url) == "Comfy-Org/ltx-2.3"
+
+
+def test_repo_id_from_url_returns_none_for_non_hf():
+    assert repo_id_from_url("https://civitai.com/x.safetensors") is None
+
+
+def test_repo_id_from_url_returns_none_for_non_resolve_paths():
+    assert repo_id_from_url("https://huggingface.co/org/repo/blob/main/x.safetensors") is None
+    assert repo_id_from_url("https://huggingface.co/org") is None
+
+
+# --------------------------------------------------------------------------- #
+# Token store
+# --------------------------------------------------------------------------- #
+
+
+def test_token_store_roundtrip(patched_user_dir):
+    tok = Token(
+        access_token="hf_abc",
+        refresh_token="rf_def",
+        expires_at=9999999999.0,
+        scope="openid profile",
+    )
+    save_token(tok)
+    loaded = load_token()
+    assert loaded == tok
+
+
+def test_token_store_writes_0600(patched_user_dir):
+    tok = Token(access_token="x", refresh_token=None, expires_at=0.0)
+    save_token(tok)
+    path = _token_file_path(patched_user_dir)
+    mode = stat.S_IMODE(os.stat(path).st_mode)
+    # On Windows we silently no-op chmod; allow either the intended
+    # mode or whatever umask the OS gave us.
+    if os.name == "posix":
+        assert mode == 0o600
+
+
+def test_token_store_delete_removes_file(patched_user_dir):
+    tok = Token(access_token="x", refresh_token=None, expires_at=0.0)
+    save_token(tok)
+    delete_token()
+    path = _token_file_path(patched_user_dir)
+    assert not os.path.exists(path)
+    # Idempotent: second delete is fine.
+    delete_token()
+
+
+def test_token_store_load_returns_none_for_missing_file(patched_user_dir):
+    assert load_token() is None
+
+
+def test_token_store_load_returns_none_for_corrupt_file(patched_user_dir):
+    path = _token_file_path(patched_user_dir)
+    os.makedirs(os.path.dirname(path), exist_ok=True)
+    with open(path, "w") as f:
+        f.write("not json {")
+    assert load_token() is None
+
+
+def test_token_is_valid_uses_buffer(patched_user_dir):
+    import time
+
+    fresh = Token(access_token="x", refresh_token=None, expires_at=time.time() + 3600)
+    nearly_expired = Token(
+        access_token="x",
+        refresh_token=None,
+        expires_at=time.time() + EXPIRY_BUFFER_SECS - 1,
+    )
+    assert fresh.is_valid()
+    assert not nearly_expired.is_valid()
+
+
+def test_token_is_valid_rejects_empty_access_token():
+    import time
+
+    tok = Token(access_token="", refresh_token=None, expires_at=time.time() + 3600)
+    assert not tok.is_valid()
+
+
+def test_token_is_valid_rejects_at_exact_buffer_boundary():
+    import time
+
+    tok = Token(
+        access_token="x",
+        refresh_token=None,
+        expires_at=time.time() + EXPIRY_BUFFER_SECS,
+    )
+    assert not tok.is_valid()
+
+
+# --------------------------------------------------------------------------- #
+# Auth store
+# --------------------------------------------------------------------------- #
+
+
+def test_auth_store_loads_lazily(patched_user_dir):
+    tok = Token(access_token="x", refresh_token=None, expires_at=9999999999.0)
+    save_token(tok)
+    store = HfAuthStore()
+    assert store.has_token()
+    assert store.get_token_sync() == tok
+
+
+def test_auth_store_set_persists(patched_user_dir):
+    store = HfAuthStore()
+    tok = Token(access_token="x", refresh_token=None, expires_at=9999999999.0)
+    store.set_token(tok)
+    # Token is on disk now — a fresh store sees it.
+    assert HfAuthStore().get_token_sync() == tok
+
+
+def test_auth_store_clear_removes_in_memory_and_on_disk(patched_user_dir):
+    store = HfAuthStore()
+    tok = Token(access_token="x", refresh_token=None, expires_at=9999999999.0)
+    store.set_token(tok)
+    store.clear()
+    assert not store.has_token()
+    assert HfAuthStore().get_token_sync() is None
+
+
+def test_auth_store_has_token_true_when_expired_but_refreshable(patched_user_dir):
+    import time
+
+    store = HfAuthStore()
+    expired = Token(
+        access_token="old",
+        refresh_token="rf",
+        expires_at=time.time() - 100,
+    )
+    store.set_token(expired)
+    assert store.has_token()
+    assert not expired.is_valid()
+
+
+def test_auth_store_get_token_sync_returns_expired_without_refresh(patched_user_dir):
+    import time
+
+    store = HfAuthStore()
+    expired = Token(
+        access_token="old",
+        refresh_token=None,
+        expires_at=time.time() - 100,
+    )
+    store.set_token(expired)
+    assert store.get_token_sync() == expired
+
+
+@pytest.mark.asyncio
+async def test_auth_store_get_valid_returns_none_when_expired_without_refresh(
+    patched_user_dir,
+):
+    import time
+
+    store = HfAuthStore()
+    expired = Token(
+        access_token="old",
+        refresh_token=None,
+        expires_at=time.time() - 100,
+    )
+    store.set_token(expired)
+    with patch(
+        "app.model_downloader.hf_auth.oauth.refresh_access_token",
+        new=AsyncMock(),
+    ) as refresh_mock:
+        result = await store.get_valid_token()
+    assert result is None
+    refresh_mock.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_auth_store_get_valid_returns_fresh_token(patched_user_dir):
+    store = HfAuthStore()
+    import time
+
+    tok = Token(access_token="x", refresh_token=None, expires_at=time.time() + 3600)
+    store.set_token(tok)
+    fetched = await store.get_valid_token()
+    assert fetched == tok
+
+
+@pytest.mark.asyncio
+async def test_auth_store_get_valid_refresh_on_expired(patched_user_dir):
+    store = HfAuthStore()
+    import time
+
+    expired = Token(
+        access_token="old",
+        refresh_token="rf",
+        expires_at=time.time() - 100,
+    )
+    store.set_token(expired)
+    refreshed = Token(
+        access_token="new",
+        refresh_token="rf",
+        expires_at=time.time() + 3600,
+    )
+    with patch(
+        "app.model_downloader.hf_auth.oauth.refresh_access_token",
+        new=AsyncMock(return_value=refreshed),
+    ):
+        result = await store.get_valid_token()
+    assert result == refreshed
+
+
+@pytest.mark.asyncio
+async def test_auth_store_get_valid_token_does_not_resurrect_after_logout(
+    patched_user_dir,
+):
+    """A logout landing *during* an in-flight refresh must not be undone by
+    the refresh writing the token back (the resurrection race)."""
+    store = HfAuthStore()
+    import time
+
+    expired = Token(
+        access_token="old", refresh_token="rf", expires_at=time.time() - 100
+    )
+    store.set_token(expired)
+    refreshed = Token(
+        access_token="new", refresh_token="rf", expires_at=time.time() + 3600
+    )
+
+    async def fake_refresh(_refresh_token):
+        # Simulate the user clicking "Log out" while the refresh is in flight.
+        store.clear()
+        return refreshed
+
+    with patch(
+        "app.model_downloader.hf_auth.oauth.refresh_access_token",
+        new=fake_refresh,
+    ):
+        result = await store.get_valid_token()
+
+    # The refresh result is discarded — logout wins, in memory and on disk.
+    assert result is None
+    assert not store.has_token()
+    assert load_token() is None
+
+
+@pytest.mark.asyncio
+async def test_auth_store_get_valid_returns_none_on_refresh_failure(patched_user_dir):
+    store = HfAuthStore()
+    import time
+
+    expired = Token(
+        access_token="old",
+        refresh_token="rf",
+        expires_at=time.time() - 100,
+    )
+    store.set_token(expired)
+    with patch(
+        "app.model_downloader.hf_auth.oauth.refresh_access_token",
+        new=AsyncMock(side_effect=RuntimeError("HF down")),
+    ):
+        result = await store.get_valid_token()
+    assert result is None
+
+
+# --------------------------------------------------------------------------- #
+# Eligibility
+# --------------------------------------------------------------------------- #
+
+
+@pytest.mark.parametrize(
+    "listen,multi_user,expected",
+    [
+        ("127.0.0.1", False, True),
+        ("127.0.0.1", True, False),    # multi-user disables it
+        ("0.0.0.0", False, False),     # bind-all is not loopback
+        ("0.0.0.0", True, False),
+        ("192.168.1.5", False, False), # LAN address
+        ("::1", False, True),          # IPv6 loopback
+    ],
+)
+def test_eligibility(listen, multi_user, expected, monkeypatch):
+    from app.model_downloader.hf_auth import eligibility
+    from comfy.cli_args import args
+
+    monkeypatch.setattr(args, "listen", listen)
+    monkeypatch.setattr(args, "multi_user", multi_user)
+    assert eligibility.is_hf_auth_eligible() is expected
+
+
+# --------------------------------------------------------------------------- #
+# gated_detection HF probe
+# --------------------------------------------------------------------------- #
+
+
+@pytest.mark.asyncio
+async def test_probe_url_hf_public(fresh_auth_store):
+    """auth_check succeeds with no token → is_hf_downloadable = True."""
+    from app.model_downloader.gated_detection import probe_url
+
+    url = "https://huggingface.co/public/repo/resolve/main/x.safetensors"
+    with patch("app.model_downloader.gated_detection._auth_check_sync"), patch(
+        "app.model_downloader.gated_detection._probe_size_once",
+        new=AsyncMock(return_value=1024),
+    ):
+        result = await probe_url(url)
+    assert result.is_hf_downloadable is True
+    assert result.file_size == 1024
+
+
+@pytest.mark.asyncio
+async def test_probe_url_hf_gated_no_access(fresh_auth_store):
+    """auth_check raises GatedRepoError → is_hf_downloadable = False."""
+    from huggingface_hub.errors import GatedRepoError
+
+    from app.model_downloader.gated_detection import probe_url
+
+    url = "https://huggingface.co/gated/repo/resolve/main/x.safetensors"
+    fake_response = MagicMock(status_code=403)
+    with patch(
+        "app.model_downloader.gated_detection._auth_check_sync",
+        side_effect=GatedRepoError("gated", response=fake_response),
+    ), patch(
+        "app.model_downloader.gated_detection._probe_size_once",
+        new=AsyncMock(return_value=None),
+    ):
+        result = await probe_url(url)
+    assert result.is_hf_downloadable is False
+
+
+@pytest.mark.asyncio
+async def test_probe_url_non_hf_skips_auth_check():
+    """Non-HF URLs never call auth_check; is_hf_downloadable stays None."""
+    from app.model_downloader.gated_detection import probe_url
+
+    url = "https://civitai.com/api/download/models/1.safetensors"
+    with patch(
+        "app.model_downloader.gated_detection._auth_check_sync",
+    ) as mocked, patch(
+        "app.model_downloader.gated_detection._probe_size_once",
+        new=AsyncMock(return_value=2048),
+    ):
+        result = await probe_url(url)
+    assert result.is_hf_downloadable is None
+    assert result.file_size == 2048
+    mocked.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_is_gated_cached_across_calls(fresh_auth_store):
+    """Intrinsic ``is_gated`` should be determined exactly once per URL.
+
+    Subsequent ``probe_url`` calls for the same URL must not re-issue
+    the null-token auth_check — that's the whole point of the cache."""
+    from app.model_downloader.gated_detection import probe_url
+
+    url = "https://huggingface.co/public/repo/resolve/main/x.safetensors"
+    with patch(
+        "app.model_downloader.gated_detection._auth_check_sync"
+    ) as mocked, patch(
+        "app.model_downloader.gated_detection._probe_size_once",
+        new=AsyncMock(return_value=1024),
+    ):
+        await probe_url(url)
+        await probe_url(url)
+        await probe_url(url)
+    # Three probe_url calls × public-only-needs-1-auth_check = 1 call total.
+    assert mocked.call_count == 1
+
+
+@pytest.mark.asyncio
+async def test_file_size_cached_across_calls(fresh_auth_store):
+    """Once a successful HEAD lands, subsequent calls don't re-HEAD."""
+    from app.model_downloader.gated_detection import probe_url
+
+    url = "https://huggingface.co/public/repo/resolve/main/x.safetensors"
+    with patch(
+        "app.model_downloader.gated_detection._auth_check_sync"
+    ), patch(
+        "app.model_downloader.gated_detection._probe_size_once",
+        new=AsyncMock(return_value=2048),
+    ) as size_probe:
+        r1 = await probe_url(url)
+        r2 = await probe_url(url)
+    assert r1.file_size == 2048
+    assert r2.file_size == 2048
+    assert size_probe.call_count == 1
+
+
+@pytest.mark.asyncio
+async def test_file_size_not_probed_for_gated_no_access(fresh_auth_store):
+    """When ``is_hf_downloadable`` is False we must NOT HEAD the URL —
+    otherwise a 401-due-to-gating would land as a cached ``None`` that
+    survives a later successful login."""
+    from app.model_downloader.gated_detection import probe_url
+    from huggingface_hub.errors import GatedRepoError
+    from unittest.mock import MagicMock
+
+    url = "https://huggingface.co/gated/repo/resolve/main/x.safetensors"
+    fake_resp = MagicMock(status_code=403)
+    with patch(
+        "app.model_downloader.gated_detection._auth_check_sync",
+        side_effect=GatedRepoError("gated", response=fake_resp),
+    ), patch(
+        "app.model_downloader.gated_detection._probe_size_once",
+        new=AsyncMock(return_value=None),
+    ) as size_probe:
+        result = await probe_url(url)
+    assert result.is_hf_downloadable is False
+    assert result.file_size is None
+    assert size_probe.call_count == 0
+
+
+@pytest.mark.asyncio
+async def test_probe_url_passes_token_when_available(fresh_auth_store, patched_user_dir):
+    """For a gated URL, auth_check runs twice: once with token=None to
+    determine the intrinsic ``is_gated`` flag (cached forever), and once
+    with the stored access_token to determine ``is_hf_downloadable`` for
+    the current user."""
+    from app.model_downloader import gated_detection
+    from app.model_downloader.gated_detection import probe_url
+    from huggingface_hub.errors import GatedRepoError
+    from unittest.mock import MagicMock
+
+    gated_detection.clear_caches_for_tests()
+    fresh_auth_store.set_token(Token(
+        access_token="hf_test_token",
+        refresh_token=None,
+        expires_at=9999999999.0,
+    ))
+    url = "https://huggingface.co/private/repo/resolve/main/x.safetensors"
+
+    fake_resp = MagicMock(status_code=403)
+
+    def fake_auth_check(repo_id, token):
+        # Null-token call → repo is gated. Subsequent call with the real
+        # token succeeds (user has access).
+        if token is None:
+            raise GatedRepoError("gated", response=fake_resp)
+
+    with patch(
+        "app.model_downloader.gated_detection._auth_check_sync",
+        side_effect=fake_auth_check,
+    ) as mocked, patch(
+        "app.model_downloader.gated_detection._probe_size_once",
+        new=AsyncMock(return_value=None),
+    ):
+        result = await probe_url(url)
+
+    # is_hf_downloadable should be True (token-authed call succeeded).
+    assert result.is_hf_downloadable is True
+    # Two calls: (repo_id, None) then (repo_id, <token>).
+    assert mocked.call_count == 2
+    assert mocked.call_args_list[0].args == ("private/repo", None)
+    assert mocked.call_args_list[1].args == ("private/repo", "hf_test_token")
+
+
+# --------------------------------------------------------------------------- #
+# OAuth primitives
+# --------------------------------------------------------------------------- #
+
+
+def test_make_pkce_returns_distinct_high_entropy_values():
+    verifier1, challenge1, state1 = oauth._make_pkce()
+    verifier2, challenge2, state2 = oauth._make_pkce()
+    assert verifier1 != verifier2
+    assert challenge1 != challenge2
+    assert state1 != state2
+    # Verifier should be at least 43 chars per PKCE spec.
+    assert len(verifier1) >= 43
+
+
+def test_build_authorize_url_includes_pkce_and_state():
+    url = oauth._build_authorize_url("challenge123", "state456")
+    assert url.startswith(oauth.AUTHORIZE_URL)
+    assert "client_id=" + oauth.HF_CLIENT_ID in url
+    assert "code_challenge=challenge123" in url
+    assert "code_challenge_method=S256" in url
+    assert "state=state456" in url
+    assert "response_type=code" in url
+
+
+# --------------------------------------------------------------------------- #
+# Routes
+# --------------------------------------------------------------------------- #
+
+
+@pytest.mark.asyncio
+async def test_hf_auth_token_status_empty(aiohttp_client, app):
+    """No token set → token_available=false, username=null."""
+    client = await aiohttp_client(app)
+    resp = await client.get("/api/hf-auth-token-status")
+    assert resp.status == 200
+    data = await resp.json()
+    assert data == {"token_available": False, "username": None}
+
+
+@pytest.mark.asyncio
+async def test_hf_auth_token_status_with_token(
+    aiohttp_client, app, fresh_auth_store, patched_user_dir
+):
+    """Token present, whoami works → username is returned."""
+    fresh_auth_store.set_token(Token(
+        access_token="x", refresh_token=None, expires_at=9999999999.0,
+    ))
+    with patch(
+        "app.model_downloader.api.routes._whoami_username",
+        return_value="alice",
+    ):
+        client = await aiohttp_client(app)
+        resp = await client.get("/api/hf-auth-token-status")
+    assert resp.status == 200
+    assert (await resp.json()) == {"token_available": True, "username": "alice"}
+
+
+@pytest.mark.asyncio
+async def test_hf_auth_login_start_403_when_ineligible(aiohttp_client, app, monkeypatch):
+    """Not loopback / multi-user → 403."""
+    monkeypatch.setattr(
+        "app.model_downloader.api.routes.is_hf_auth_eligible",
+        lambda: False,
+    )
+    client = await aiohttp_client(app)
+    resp = await client.post("/api/hf-auth-login-start")
+    assert resp.status == 403
+    assert (await resp.json())["error"]["code"] == "HF_AUTH_NOT_ELIGIBLE"
+
+
+@pytest.mark.asyncio
+async def test_hf_auth_login_start_returns_authorize_url(aiohttp_client, app, monkeypatch):
+    """Eligible + first attempt → 200 with authorize_url."""
+    monkeypatch.setattr(
+        "app.model_downloader.api.routes.is_hf_auth_eligible",
+        lambda: True,
+    )
+    monkeypatch.setattr(
+        "app.model_downloader.api.routes.start_login_flow",
+        AsyncMock(return_value="https://huggingface.co/oauth/authorize?fake=1"),
+    )
+    client = await aiohttp_client(app)
+    resp = await client.post("/api/hf-auth-login-start")
+    assert resp.status == 200
+    assert (await resp.json())["authorize_url"].startswith(
+        "https://huggingface.co/oauth/authorize"
+    )
+
+
+@pytest.mark.asyncio
+async def test_hf_auth_login_start_409_when_in_progress(aiohttp_client, app, monkeypatch):
+    """Lock already held → 409."""
+    from app.model_downloader.hf_auth.oauth import OAuthInProgressError
+
+    monkeypatch.setattr(
+        "app.model_downloader.api.routes.is_hf_auth_eligible",
+        lambda: True,
+    )
+    monkeypatch.setattr(
+        "app.model_downloader.api.routes.start_login_flow",
+        AsyncMock(side_effect=OAuthInProgressError()),
+    )
+    client = await aiohttp_client(app)
+    resp = await client.post("/api/hf-auth-login-start")
+    assert resp.status == 409
+    assert (await resp.json())["error"]["code"] == "HF_AUTH_IN_PROGRESS"
+
+
+@pytest.mark.asyncio
+async def test_hf_auth_login_start_503_when_callback_bind_fails(
+    aiohttp_client, app, monkeypatch
+):
+    """Callback server failed to bind (e.g. port busy) → 503, not a dead URL."""
+    from app.model_downloader.hf_auth.oauth import OAuthCallbackError
+
+    monkeypatch.setattr(
+        "app.model_downloader.api.routes.is_hf_auth_eligible",
+        lambda: True,
+    )
+    monkeypatch.setattr(
+        "app.model_downloader.api.routes.start_login_flow",
+        AsyncMock(side_effect=OAuthCallbackError("could not bind callback port")),
+    )
+    client = await aiohttp_client(app)
+    resp = await client.post("/api/hf-auth-login-start")
+    assert resp.status == 503
+    assert (await resp.json())["error"]["code"] == "HF_AUTH_START_FAILED"
+
+
+@pytest.mark.asyncio
+async def test_hf_auth_logout_clears_store(
+    aiohttp_client, app, fresh_auth_store, patched_user_dir
+):
+    fresh_auth_store.set_token(Token(
+        access_token="x", refresh_token=None, expires_at=9999999999.0,
+    ))
+    client = await aiohttp_client(app)
+    resp = await client.post("/api/hf-auth-logout")
+    assert resp.status == 200
+    assert (await resp.json()) == {"logged_out": True}
+    assert not fresh_auth_store.has_token()
+
+
+@pytest.mark.asyncio
+async def test_availability_includes_hf_auth_snapshot(aiohttp_client, app, monkeypatch):
+    """The availability response embeds {token_available, eligible}."""
+    monkeypatch.setattr(
+        "app.model_downloader.api.routes.is_hf_auth_eligible",
+        lambda: True,
+    )
+    client = await aiohttp_client(app)
+    resp = await client.post(
+        "/api/models-availability-status",
+        json={"models": {}},
+    )
+    assert resp.status == 200
+    data = await resp.json()
+    assert "hf_auth" in data
+    assert data["hf_auth"] == {"token_available": False, "eligible": True}

tests-unit/app_test/model_downloader_test.py

@@ -0,0 +1,514 @@
+"""Unit tests for the server-side model download subsystem.
+
+Covers the pieces that don't require talking to a real network:
+
+  - path parsing & allowlist (pure functions)
+  - DownloadServer registry lifecycle (in-memory state)
+  - API routes via aiohttp_client + folder_paths/probe_url patches
+
+Streaming downloads themselves are exercised indirectly — the route-level
+tests stub out the network probe so we can verify the gating logic in
+``download_models`` without making real HTTP calls.
+"""
+
+from __future__ import annotations
+
+import asyncio
+from unittest.mock import patch, AsyncMock
+
+import pytest
+from aiohttp import web
+
+from app.model_downloader.allowlist import is_url_allowed
+from app.model_downloader.api.routes import register_routes
+from app.model_downloader.download_server import DownloadServer
+from app.model_downloader.gated_detection import MetadataProbeResult
+from app.model_downloader.paths import (
+    InvalidModelId,
+    parse_model_id,
+    resolve_destination,
+    resolve_existing,
+)
+
+# --------------------------------------------------------------------------- #
+# Fixtures
+# --------------------------------------------------------------------------- #
+
+
+@pytest.fixture
+def model_root(tmp_path):
+    """A fake ``models/`` root with two registered folder types."""
+    loras_dir = tmp_path / "loras"
+    checkpoints_dir = tmp_path / "checkpoints"
+    loras_dir.mkdir()
+    checkpoints_dir.mkdir()
+    return tmp_path, loras_dir, checkpoints_dir
+
+
+@pytest.fixture
+def patched_folder_paths(model_root):
+    """Point folder_paths at our fake roots for the duration of one test."""
+    _root, loras_dir, checkpoints_dir = model_root
+    mapping = {
+        "loras": ([str(loras_dir)], {".safetensors"}),
+        "checkpoints": ([str(checkpoints_dir)], {".safetensors"}),
+    }
+    with patch(
+        "folder_paths.folder_names_and_paths", mapping
+    ), patch(
+        "folder_paths.get_folder_paths",
+        side_effect=lambda name: mapping.get(name, ([], set()))[0],
+    ):
+        yield mapping
+
+
+@pytest.fixture
+def fresh_download_server():
+    """Reset the module-level singleton between tests so registry state
+    doesn't leak across tests sharing the singleton."""
+    from app.model_downloader.download_server import DOWNLOAD_SERVER
+
+    DOWNLOAD_SERVER.reset_for_tests()
+    yield DOWNLOAD_SERVER
+    DOWNLOAD_SERVER.reset_for_tests()
+
+
+@pytest.fixture
+def app(patched_folder_paths, fresh_download_server):
+    app = web.Application()
+    register_routes(app)
+    return app
+
+
+# --------------------------------------------------------------------------- #
+# Pure helpers: allowlist + path parsing
+# --------------------------------------------------------------------------- #
+
+
+def test_allowlist_accepts_hf_safetensors():
+    assert is_url_allowed("https://huggingface.co/x/y/resolve/main/z.safetensors")
+
+
+def test_allowlist_accepts_civitai_pth():
+    assert is_url_allowed("https://civitai.com/api/download/models/123.pth")
+
+
+def test_allowlist_rejects_unknown_host():
+    assert not is_url_allowed("https://example.com/x.safetensors")
+
+
+def test_allowlist_rejects_api_path_on_hf():
+    # On an allowlisted host but not pointing at a model file.
+    assert not is_url_allowed("https://huggingface.co/api/models")
+
+
+def test_allowlist_rejects_non_https_except_localhost():
+    assert not is_url_allowed("http://huggingface.co/x/y.safetensors")
+    assert is_url_allowed("http://localhost:8000/x.safetensors")
+
+
+def test_parse_model_id_valid(patched_folder_paths):
+    assert parse_model_id("loras/foo.safetensors") == ("loras", "foo.safetensors")
+
+
+def test_parse_model_id_rejects_traversal(patched_folder_paths):
+    with pytest.raises(InvalidModelId):
+        parse_model_id("../etc/passwd")
+
+
+def test_parse_model_id_rejects_unknown_folder(patched_folder_paths):
+    with pytest.raises(InvalidModelId):
+        parse_model_id("nope/x.safetensors")
+
+
+def test_parse_model_id_rejects_double_slash(patched_folder_paths):
+    with pytest.raises(InvalidModelId):
+        parse_model_id("loras/sub/x.safetensors")
+
+
+def test_resolve_existing_returns_path_when_present(model_root, patched_folder_paths):
+    _root, loras_dir, _ = model_root
+    target = loras_dir / "foo.safetensors"
+    target.write_bytes(b"x")
+    assert resolve_existing("loras/foo.safetensors") == str(target)
+
+
+def test_resolve_existing_returns_none_when_absent(patched_folder_paths):
+    assert resolve_existing("loras/missing.safetensors") is None
+
+
+def test_resolve_destination_returns_tmp_pair(model_root, patched_folder_paths):
+    _root, loras_dir, _ = model_root
+    final, tmp = resolve_destination("loras/foo.safetensors", epoch=7)
+    assert final == str(loras_dir / "foo.safetensors")
+    # Temp path embeds the session epoch (so cancel+retry can't collide on it)
+    # and uses the subsystem-specific suffix the startup sweep matches.
+    assert tmp == f"{final}.7.comfy-download.tmp"
+
+
+# --------------------------------------------------------------------------- #
+# DownloadServer registry: lifecycle, races, cancellation epoch semantics
+# --------------------------------------------------------------------------- #
+
+
+def test_register_is_exclusive():
+    server = DownloadServer()
+    s1 = server.try_register("loras/x.safetensors", "https://huggingface.co/a")
+    s2 = server.try_register("loras/x.safetensors", "https://huggingface.co/b")
+    assert s1 is not None
+    assert s2 is None
+    assert server.is_downloading("loras/x.safetensors")
+
+
+def test_cancel_removes_session():
+    server = DownloadServer()
+    server.try_register("loras/x.safetensors", "https://huggingface.co/a")
+    assert server.cancel("loras/x.safetensors") is True
+    assert not server.is_downloading("loras/x.safetensors")
+
+
+def test_cancel_returns_false_when_absent():
+    server = DownloadServer()
+    assert server.cancel("loras/never.safetensors") is False
+
+
+def test_finish_only_clears_matching_epoch():
+    """If a session is cancelled and a new one for the same id is
+    registered, ``finish`` from the original worker must not evict the
+    newer session."""
+    server = DownloadServer()
+    s_old = server.try_register("loras/x.safetensors", "u1")
+    server.cancel("loras/x.safetensors")
+    s_new = server.try_register("loras/x.safetensors", "u2")
+    assert s_new is not None and s_new.epoch != s_old.epoch
+    # Old worker's late finish() is a no-op:
+    server.finish(s_old)
+    assert server.is_downloading("loras/x.safetensors")
+    server.finish(s_new)
+    assert not server.is_downloading("loras/x.safetensors")
+
+
+def test_is_active_follows_cancellation():
+    server = DownloadServer()
+    s = server.try_register("loras/x.safetensors", "u")
+    assert server.is_active(s)
+    server.cancel("loras/x.safetensors")
+    assert not server.is_active(s)
+
+
+def test_update_progress_tracks_fraction():
+    server = DownloadServer()
+    s = server.try_register("loras/x.safetensors", "u")
+    server.update_progress(s, 50, 100)
+    snap = server.snapshot()["loras/x.safetensors"]
+    assert snap.bytes_downloaded == 50
+    assert snap.total_bytes == 100
+    assert snap.progress == 0.5
+
+
+def test_update_progress_with_unknown_total_keeps_progress_none():
+    server = DownloadServer()
+    s = server.try_register("loras/x.safetensors", "u")
+    server.update_progress(s, 50, None)
+    assert server.snapshot()["loras/x.safetensors"].progress is None
+
+
+def test_cleanup_orphan_tmp_files(model_root):
+    """Orphan temp left by a crashed download must be swept on first use,
+    while unrelated *.tmp files in the model dir are left untouched."""
+    _root, loras_dir, _ = model_root
+    orphan = loras_dir / "stale.safetensors.3.comfy-download.tmp"
+    orphan.write_bytes(b"partial")
+    unrelated = loras_dir / "someothertool.tmp"
+    unrelated.write_bytes(b"not ours")
+    mapping = {"loras": ([str(loras_dir)], {".safetensors"})}
+    with patch("folder_paths.folder_names_and_paths", mapping), patch(
+        "folder_paths.get_folder_paths",
+        side_effect=lambda name: mapping.get(name, ([], set()))[0],
+    ):
+        server = DownloadServer()
+        assert orphan.exists(), "sweep must not run at construction time"
+        server.sweep_orphan_tmp_files()
+        assert not orphan.exists()
+        assert unrelated.exists(), "unrelated .tmp must not be swept"
+        # Idempotent — a second call is a cheap no-op.
+        server.sweep_orphan_tmp_files()
+
+
+# --------------------------------------------------------------------------- #
+# Route: POST /api/models-availability-status
+# --------------------------------------------------------------------------- #
+
+
+@pytest.mark.asyncio
+async def test_availability_partitions_correctly(
+    aiohttp_client, app, model_root, fresh_download_server
+):
+    _root, loras_dir, _ = model_root
+    (loras_dir / "present.safetensors").write_bytes(b"x")
+    fresh_download_server.try_register(
+        "loras/inflight.safetensors", "http://localhost:8000/x.safetensors"
+    )
+    client = await aiohttp_client(app)
+
+    # Stub probes — we're testing state assignment, not network calls.
+    with patch(
+        "app.model_downloader.api.routes.probe_url",
+        new=AsyncMock(return_value=MetadataProbeResult(
+            file_size=None, is_hf_downloadable=None,
+        )),
+    ):
+        body = {
+            "models": {
+                "loras/present.safetensors": "http://localhost:8000/p.safetensors",
+                "loras/missing.safetensors": "http://localhost:8000/m.safetensors",
+                "loras/inflight.safetensors": "http://localhost:8000/x.safetensors",
+            }
+        }
+        resp = await client.post("/api/models-availability-status", json=body)
+    assert resp.status == 200
+    data = await resp.json()
+    models = data["models"]
+    assert models["loras/present.safetensors"]["state"] == "available"
+    assert models["loras/missing.safetensors"]["state"] == "missing"
+    assert models["loras/inflight.safetensors"]["state"] == "downloading"
+    assert "hf_auth" in data
+
+
+@pytest.mark.asyncio
+async def test_availability_invalid_id_classified_as_missing(aiohttp_client, app):
+    client = await aiohttp_client(app)
+    with patch(
+        "app.model_downloader.api.routes.probe_url",
+        new=AsyncMock(return_value=MetadataProbeResult(
+            file_size=None, is_hf_downloadable=None,
+        )),
+    ):
+        resp = await client.post(
+            "/api/models-availability-status",
+            json={"models": {"../etc/passwd": "http://localhost:8000/x.safetensors"}},
+        )
+    assert resp.status == 200
+    data = await resp.json()
+    assert data["models"]["../etc/passwd"]["state"] == "missing"
+
+
+# --------------------------------------------------------------------------- #
+# Route: POST /api/download-models  — precondition gating
+# --------------------------------------------------------------------------- #
+
+
+@pytest.mark.asyncio
+async def test_download_rejects_url_not_in_allowlist(aiohttp_client, app):
+    client = await aiohttp_client(app)
+    resp = await client.post(
+        "/api/download-models",
+        json={"models": {"loras/x.safetensors": "https://evil.com/x.safetensors"}},
+    )
+    assert resp.status == 400
+    err = (await resp.json())["error"]
+    assert err["code"] == "URL_NOT_ALLOWED"
+
+
+@pytest.mark.asyncio
+async def test_download_rejects_already_available(
+    aiohttp_client, app, model_root
+):
+    _root, loras_dir, _ = model_root
+    (loras_dir / "x.safetensors").write_bytes(b"x")
+    client = await aiohttp_client(app)
+    resp = await client.post(
+        "/api/download-models",
+        json={"models": {
+            "loras/x.safetensors": "https://huggingface.co/a/b/resolve/main/x.safetensors"
+        }},
+    )
+    assert resp.status == 409
+    assert (await resp.json())["error"]["code"] == "ALREADY_AVAILABLE"
+
+
+@pytest.mark.asyncio
+async def test_download_rejects_already_downloading(
+    aiohttp_client, app, fresh_download_server
+):
+    fresh_download_server.try_register(
+        "loras/x.safetensors", "https://huggingface.co/u.safetensors"
+    )
+    client = await aiohttp_client(app)
+    resp = await client.post(
+        "/api/download-models",
+        json={"models": {
+            "loras/x.safetensors": "https://huggingface.co/a/b/resolve/main/x.safetensors"
+        }},
+    )
+    assert resp.status == 409
+    assert (await resp.json())["error"]["code"] == "ALREADY_DOWNLOADING"
+
+
+@pytest.mark.asyncio
+async def test_download_rejects_gated_model(aiohttp_client, app):
+    client = await aiohttp_client(app)
+    with patch(
+        "app.model_downloader.api.routes.probe_url",
+        new=AsyncMock(return_value=MetadataProbeResult(file_size=None, is_hf_downloadable=False)),
+    ):
+        resp = await client.post(
+            "/api/download-models",
+            json={"models": {
+                "loras/x.safetensors": "https://huggingface.co/g/r/resolve/main/x.safetensors"
+            }},
+        )
+    assert resp.status == 400
+    assert (await resp.json())["error"]["code"] == "MODEL_NOT_DOWNLOADABLE"
+
+
+@pytest.mark.asyncio
+async def test_download_rejects_invalid_model_id(aiohttp_client, app):
+    client = await aiohttp_client(app)
+    resp = await client.post(
+        "/api/download-models",
+        json={"models": {"../etc/passwd": "https://huggingface.co/x.safetensors"}},
+    )
+    assert resp.status == 400
+    assert (await resp.json())["error"]["code"] == "INVALID_MODEL_ID"
+
+
+@pytest.mark.asyncio
+async def test_download_atomic_failure_does_not_register_partial(
+    aiohttp_client, app, model_root, fresh_download_server
+):
+    """If one model in a batch fails, none get registered."""
+    _root, loras_dir, _ = model_root
+    (loras_dir / "already.safetensors").write_bytes(b"x")
+    client = await aiohttp_client(app)
+    resp = await client.post(
+        "/api/download-models",
+        json={
+            "models": {
+                "loras/already.safetensors":
+                    "https://huggingface.co/a/b/resolve/main/already.safetensors",
+                "loras/new.safetensors":
+                    "https://huggingface.co/a/b/resolve/main/new.safetensors",
+            }
+        },
+    )
+    assert resp.status == 409
+    # The "new" model should not have been registered as part of the
+    # failed batch.
+    assert not fresh_download_server.is_downloading("loras/new.safetensors")
+
+
+@pytest.mark.asyncio
+async def test_download_schedules_when_all_preconditions_pass(
+    aiohttp_client, app, fresh_download_server
+):
+    """Verify the precondition pass, registration pass, and async
+    scheduling all wire up correctly. We patch the streamer to avoid
+    real HTTP while still letting the route execute end-to-end."""
+    started = asyncio.Event()
+    finish_signal = asyncio.Event()
+
+    async def fake_stream(session):
+        started.set()
+        await finish_signal.wait()
+        from app.model_downloader.download_server import DOWNLOAD_SERVER
+        DOWNLOAD_SERVER.finish(session)
+        return "/dev/null"
+
+    with patch(
+        "app.model_downloader.api.routes.probe_url",
+        new=AsyncMock(return_value=MetadataProbeResult(file_size=42, is_hf_downloadable=True)),
+    ), patch(
+        "app.model_downloader.downloader.stream_to_disk", new=fake_stream
+    ):
+        client = await aiohttp_client(app)
+        resp = await client.post(
+            "/api/download-models",
+            json={"models": {
+                "loras/new.safetensors":
+                    "https://huggingface.co/a/b/resolve/main/new.safetensors"
+            }},
+        )
+        assert resp.status == 202
+        body = await resp.json()
+        assert body["accepted"] is True
+        assert body["scheduled"] == ["loras/new.safetensors"]
+        # Wait for the worker to actually start.
+        await asyncio.wait_for(started.wait(), timeout=2.0)
+        assert fresh_download_server.is_downloading("loras/new.safetensors")
+        finish_signal.set()
+
+
+# --------------------------------------------------------------------------- #
+# Route: POST /api/cancel-model-download-session
+# --------------------------------------------------------------------------- #
+
+
+@pytest.mark.asyncio
+async def test_cancel_removes_active_session(
+    aiohttp_client, app, fresh_download_server
+):
+    fresh_download_server.try_register(
+        "loras/x.safetensors", "https://huggingface.co/u.safetensors"
+    )
+    client = await aiohttp_client(app)
+    resp = await client.post(
+        "/api/cancel-model-download-session",
+        json={"model_id": "loras/x.safetensors"},
+    )
+    assert resp.status == 200
+    assert (await resp.json())["cancelled"] is True
+    assert not fresh_download_server.is_downloading("loras/x.safetensors")
+
+
+@pytest.mark.asyncio
+async def test_cancel_returns_404_when_none(aiohttp_client, app):
+    client = await aiohttp_client(app)
+    resp = await client.post(
+        "/api/cancel-model-download-session",
+        json={"model_id": "loras/nothing.safetensors"},
+    )
+    assert resp.status == 404
+    assert (await resp.json())["error"]["code"] == "NOT_DOWNLOADING"
+
+
+# --------------------------------------------------------------------------- #
+# Unified availability response embeds metadata per id
+# --------------------------------------------------------------------------- #
+
+
+@pytest.mark.asyncio
+async def test_availability_embeds_metadata(aiohttp_client, app):
+    """``file_size`` + ``is_hf_downloadable`` come back on the same
+    request as the state — no separate metadata endpoint."""
+    results = {
+        "https://huggingface.co/a/b/resolve/main/free.safetensors":
+            MetadataProbeResult(file_size=1024, is_hf_downloadable=True),
+        "https://huggingface.co/g/r/resolve/main/gated.safetensors":
+            MetadataProbeResult(file_size=None, is_hf_downloadable=False),
+    }
+
+    async def fake_probe(url):
+        return results[url]
+
+    with patch(
+        "app.model_downloader.api.routes.probe_url", new=fake_probe
+    ):
+        client = await aiohttp_client(app)
+        resp = await client.post(
+            "/api/models-availability-status",
+            json={
+                "models": {
+                    "loras/free.safetensors":
+                        "https://huggingface.co/a/b/resolve/main/free.safetensors",
+                    "loras/gated.safetensors":
+                        "https://huggingface.co/g/r/resolve/main/gated.safetensors",
+                }
+            },
+        )
+    assert resp.status == 200
+    models = (await resp.json())["models"]
+    assert models["loras/free.safetensors"]["file_size"] == 1024
+    assert models["loras/free.safetensors"]["is_hf_downloadable"] is True
+    assert models["loras/gated.safetensors"]["file_size"] is None
+    assert models["loras/gated.safetensors"]["is_hf_downloadable"] is False

tests-unit/assets_test/test_downloads.py

@@ -1,3 +1,5 @@
+import contextlib
+import json
 import time
 import uuid
 from datetime import datetime
@@ -9,6 +11,40 @@ import requests
 from helpers import get_asset_filename, trigger_sync_seed_assets
 
 
+def test_download_svg_forced_to_attachment(http: requests.Session, api_base: str):
+    """GHSA-779p-m5rp-r4h4 CISA-5 (sibling route): an uploaded SVG must never be
+    served inline from GET /api/assets/{id}/content, or an inline <script> runs
+    in the app origin (stored XSS). Even with disposition=inline requested, a
+    dangerous content type must be forced to application/octet-stream +
+    Content-Disposition: attachment + nosniff. Regression guard for the stale
+    inline blocklist that previously omitted image/svg+xml and ignored the
+    centralized folder_paths.is_dangerous_content_type check.
+    """
+    svg = b'<svg xmlns="http://www.w3.org/2000/svg"><script>alert(1)</script></svg>'
+    files = {"file": ("evil.svg", svg, "image/svg+xml")}
+    form_data = {
+        "tags": json.dumps(["models", "checkpoints", "unit-tests", "svgxss"]),
+        "name": "evil.svg",
+    }
+    up = http.post(api_base + "/api/assets", files=files, data=form_data, timeout=120)
+    body = up.json()
+    assert up.status_code in (200, 201), body
+    aid = body["id"]
+    try:
+        r = http.get(f"{api_base}/api/assets/{aid}/content?disposition=inline", timeout=120)
+        r.content
+        assert r.status_code == 200
+        ct = r.headers.get("Content-Type", "").lower()
+        cd = r.headers.get("Content-Disposition", "").lower()
+        assert "svg" not in ct, f"SVG served with a renderable content type: {ct!r}"
+        assert ct.startswith("application/octet-stream"), f"expected octet-stream, got {ct!r}"
+        assert "attachment" in cd, f"inline disposition not overridden to attachment: {cd!r}"
+        assert r.headers.get("X-Content-Type-Options", "").lower() == "nosniff"
+    finally:
+        with contextlib.suppress(Exception):
+            http.delete(f"{api_base}/api/assets/{aid}", timeout=30)
+
+
 def test_download_attachment_and_inline(http: requests.Session, api_base: str, seeded_asset: dict):
     aid = seeded_asset["id"]
 

tests-unit/comfy_test/folder_path_test.py

@@ -53,8 +53,11 @@ def test_annotated_filepath():
 
 def test_get_annotated_filepath():
     default_dir = "/default/dir"
-    assert folder_paths.get_annotated_filepath("test.txt", default_dir) == os.path.join(default_dir, "test.txt")
-    assert folder_paths.get_annotated_filepath("test.txt [output]") == os.path.join(folder_paths.get_output_directory(), "test.txt")
+    # get_annotated_filepath now normalizes with os.path.abspath (part of the
+    # GHSA-779p traversal hardening), so compare against the normalized form —
+    # on Windows abspath also prepends the current drive letter.
+    assert folder_paths.get_annotated_filepath("test.txt", default_dir) == os.path.abspath(os.path.join(default_dir, "test.txt"))
+    assert folder_paths.get_annotated_filepath("test.txt [output]") == os.path.abspath(os.path.join(folder_paths.get_output_directory(), "test.txt"))
 
 def test_add_model_folder_path_append(clear_folder_paths):
     folder_paths.add_model_folder_path("test_folder", "/default/path", is_default=True)

tests-unit/security_test/test_ghsa_779p_02_preview_traversal.py

@@ -0,0 +1,192 @@
+"""CI unit tests for FIX #2 of GHSA-779p-m5rp-r4h4.
+
+Path traversal / hardening in app/model_manager.py get_model_preview
+(route /experiment/models/preview/{folder}/{path_index}/{filename:.*}).
+
+Reference: https://github.com/Comfy-Org/ComfyUI/security/advisories/GHSA-779p-m5rp-r4h4
+"""
+import pytest
+import yarl
+from io import BytesIO
+from PIL import Image
+from aiohttp import web
+from unittest.mock import patch
+from app.model_manager import ModelFileManager
+
+pytestmark = (
+    pytest.mark.asyncio
+)  # This applies the asyncio mark to all test functions in the module
+
+@pytest.fixture
+def model_manager():
+    return ModelFileManager()
+
+@pytest.fixture
+def app(model_manager):
+    app = web.Application()
+    routes = web.RouteTableDef()
+    model_manager.add_routes(routes)
+    app.add_routes(routes)
+    return app
+
+
+async def test_legit_preview_returns_200(aiohttp_client, app, tmp_path):
+    """Sanity: a real preview PNG inside the model folder is served as webp 200."""
+    img = Image.new('RGB', (16, 16), color=(255, 0, 128))
+    img.save(tmp_path / "test_model.png", format='PNG')
+
+    with patch('folder_paths.folder_names_and_paths', {
+        'test_folder': ([str(tmp_path)], None)
+    }):
+        client = await aiohttp_client(app)
+        response = await client.get('/experiment/models/preview/test_folder/0/test_model.png')
+
+        assert response.status == 200
+        assert response.content_type == 'image/webp'
+
+        img_bytes = BytesIO(await response.read())
+        served = Image.open(img_bytes)
+        assert served.format
+        assert served.format.lower() == 'webp'
+        served.close()
+
+
+async def test_non_integer_path_index_returns_400(aiohttp_client, app, tmp_path):
+    """A non-integer path_index segment must be rejected with 400."""
+    with patch('folder_paths.folder_names_and_paths', {
+        'test_folder': ([str(tmp_path)], None)
+    }):
+        client = await aiohttp_client(app)
+        response = await client.get('/experiment/models/preview/test_folder/abc/test_model.png')
+
+        assert response.status == 400
+
+
+async def test_out_of_range_path_index_returns_404(aiohttp_client, app, tmp_path):
+    """A path_index beyond the configured folder list must return 404."""
+    with patch('folder_paths.folder_names_and_paths', {
+        'test_folder': ([str(tmp_path)], None)
+    }):
+        client = await aiohttp_client(app)
+        response = await client.get('/experiment/models/preview/test_folder/99/test_model.png')
+
+        assert response.status == 404
+
+
+async def test_empty_filename_returns_400(aiohttp_client, app, tmp_path):
+    """The "{filename:.*}" capture also matches the empty string (trailing
+    slash). It would resolve to the folder itself and must be rejected with 400."""
+    with patch('folder_paths.folder_names_and_paths', {
+        'test_folder': ([str(tmp_path)], None)
+    }):
+        client = await aiohttp_client(app)
+        response = await client.get('/experiment/models/preview/test_folder/0/')
+
+        assert response.status == 400
+
+
+async def test_path_traversal_in_filename_returns_403(aiohttp_client, app, tmp_path):
+    """Path traversal in {filename} must be rejected with 403 and must NOT read
+    a file outside the configured model directory.
+
+    GOTCHA: aiohttp/yarl collapses literal ``../`` dot-segments out of the URL
+    path before it reaches the handler, which would make this test vacuously
+    pass (the request would hit a different/non-existent route). We percent-encode
+    the dots and slashes (``%2e%2e%2f``) and send the URL with
+    ``yarl.URL(..., encoded=True)`` so the bytes survive client-side normalization
+    untouched; aiohttp's router then percent-decodes them into ``match_info``,
+    delivering the literal ``../`` traversal to the handler's ``{filename:.*}``
+    capture.
+
+    Without the fix the handler computes
+    ``os.path.normpath(os.path.join(folder, "../../../../etc/hosts"))``, which
+    escapes ``tmp_path`` and would be passed straight to get_model_previews ->
+    Image.open, serving bytes from outside the model dir (200/served bytes). The
+    is_within_directory() containment check is the load-bearing fix that turns
+    that escape into a 403.
+    """
+    # Sanity-anchor: a legit preview exists inside tmp_path, so a 200 path is
+    # genuinely reachable — proving the 403 below is the containment check
+    # firing, not an unrelated 404.
+    img = Image.new('RGB', (16, 16), color=(255, 0, 128))
+    img.save(tmp_path / "test_model.png", format='PNG')
+
+    # Percent-encoded "../../../../etc/hosts" so yarl does not collapse the
+    # dot-segments before the request leaves the client.
+    encoded_traversal = '%2e%2e%2f' * 4 + 'etc%2fhosts'
+    raw_path = '/experiment/models/preview/test_folder/0/' + encoded_traversal
+    url = yarl.URL(raw_path, encoded=True)
+
+    with patch('folder_paths.folder_names_and_paths', {
+        'test_folder': ([str(tmp_path)], None)
+    }):
+        client = await aiohttp_client(app)
+        response = await client.get(url)
+
+        # Confirm the traversal actually reached the handler intact: a 200 here
+        # would mean either normalization stripped the ``../`` (vacuous pass) or
+        # the containment check failed open and served outside-dir bytes.
+        assert response.status == 403, (
+            f"expected 403 from is_within_directory() containment check, "
+            f"got {response.status}; traversal may have been normalized away "
+            f"or the fix failed open"
+        )
+        body = await response.read()
+        assert body == b"", "403 response must not carry any file bytes"
+
+
+async def test_symlink_companion_preview_returns_403(aiohttp_client, app, tmp_path):
+    """A companion preview file is selected by a glob inside get_model_previews
+    and then opened. If that companion is a symlink whose path is in-dir but
+    whose target escapes the model folder, it must be rejected with 403 — not
+    served. The requested path itself stays in-dir (so the first containment
+    check passes); the load-bearing fix is the SECOND is_within_directory check
+    on the file actually opened.
+    """
+    model_dir = tmp_path / "models"
+    model_dir.mkdir()
+    secret_dir = tmp_path / "secret"
+    secret_dir.mkdir()
+    # A real image OUTSIDE the model dir — valid, so without the fix Image.open
+    # would succeed and its bytes would be served (200).
+    secret = secret_dir / "secret.png"
+    Image.new('RGB', (8, 8), color=(0, 0, 0)).save(secret, format='PNG')
+    # Companion preview, in-dir by name but a symlink escaping the model dir.
+    # (No real model file is needed — get_model_previews globs companions by
+    # basename, and omitting a .safetensors avoids the metadata-header read.)
+    companion = model_dir / "model.preview.png"
+    try:
+        companion.symlink_to(secret)
+    except (OSError, NotImplementedError):
+        pytest.skip("symlinks not supported on this platform/filesystem")
+
+    with patch('folder_paths.folder_names_and_paths', {
+        'test_folder': ([str(model_dir)], None)
+    }):
+        client = await aiohttp_client(app)
+        response = await client.get('/experiment/models/preview/test_folder/0/model.safetensors')
+
+        assert response.status == 403, (
+            f"expected 403 — the globbed companion preview is a symlink resolving "
+            f"outside the model dir and must not be served; got {response.status}"
+        )
+        assert await response.read() == b""
+
+
+async def test_null_byte_in_filename_no_500(aiohttp_client, app, tmp_path):
+    """A NUL byte in the filename must yield a clean client rejection, not a 500
+    from an uncaught ValueError in is_within_directory's realpath() call."""
+    raw_path = '/experiment/models/preview/test_folder/0/' + 'a%00b'
+    url = yarl.URL(raw_path, encoded=True)
+
+    with patch('folder_paths.folder_names_and_paths', {
+        'test_folder': ([str(tmp_path)], None)
+    }):
+        client = await aiohttp_client(app)
+        response = await client.get(url)
+
+        assert response.status != 500, (
+            f"NUL byte produced a 500 (uncaught ValueError); expected a clean "
+            f"4xx rejection, got {response.status}"
+        )
+        assert 400 <= response.status < 500

tests-unit/security_test/test_ghsa_779p_03_annotated_traversal.py

@@ -0,0 +1,165 @@
+"""Security tests for GHSA-779p-m5rp-r4h4 — FIX #3.
+
+Path traversal in folder_paths.get_annotated_filepath / exists_annotated_filepath,
+plus the shared is_within_directory() containment helper.
+
+These are pure-function tests (no running server). The input/output/temp
+directories are pointed at tmp_path via the folder_paths setters, so a crafted
+name containing `../`, an absolute path, or a symlink that escapes the base
+directory must be rejected.
+
+Reference: https://github.com/Comfy-Org/ComfyUI/security/advisories/GHSA-779p-m5rp-r4h4
+"""
+import os
+
+import pytest
+
+import folder_paths
+from comfy.options import enable_args_parsing
+enable_args_parsing()
+
+
+@pytest.fixture
+def sandbox(tmp_path):
+    """Point folder_paths' input/output/temp dirs at a real temp sandbox.
+
+    Yields the realpath'd base, input, output and temp directories. The original
+    directory values are restored afterward so tests stay isolated.
+    """
+    base = os.path.realpath(str(tmp_path))
+    input_dir = os.path.join(base, "input")
+    output_dir = os.path.join(base, "output")
+    temp_dir = os.path.join(base, "temp")
+    for d in (input_dir, output_dir, temp_dir):
+        os.makedirs(d, exist_ok=True)
+
+    orig_input = folder_paths.get_input_directory()
+    orig_output = folder_paths.get_output_directory()
+    orig_temp = folder_paths.get_temp_directory()
+
+    folder_paths.set_input_directory(input_dir)
+    folder_paths.set_output_directory(output_dir)
+    folder_paths.set_temp_directory(temp_dir)
+
+    yield {
+        "base": base,
+        "input": input_dir,
+        "output": output_dir,
+        "temp": temp_dir,
+    }
+
+    folder_paths.set_input_directory(orig_input)
+    folder_paths.set_output_directory(orig_output)
+    folder_paths.set_temp_directory(orig_temp)
+
+
+# ---------------------------------------------------------------------------
+# is_within_directory() — the shared containment helper
+# ---------------------------------------------------------------------------
+
+def test_is_within_directory_legit_child(sandbox):
+    base = sandbox["input"]
+    child = os.path.join(base, "sub", "image.png")
+    assert folder_paths.is_within_directory(base, child) is True
+
+
+def test_is_within_directory_dotdot_escape(sandbox):
+    base = sandbox["input"]
+    escape = os.path.join(base, "..", "..", "etc", "passwd")
+    assert folder_paths.is_within_directory(base, escape) is False
+
+
+def test_is_within_directory_symlink_escape(sandbox):
+    """A symlink created INSIDE base that points OUTSIDE base must not pass.
+
+    This is the key new hardening: is_within_directory realpath()s both operands,
+    so a symlink planted in the base directory can't be used to read files
+    elsewhere. We create a real on-disk symlink and a real secret target to
+    verify the check actually resolves the link.
+    """
+    base = sandbox["input"]
+
+    # A directory living outside the base, holding a secret file.
+    outside = os.path.join(sandbox["base"], "outside_secret_dir")
+    os.makedirs(outside, exist_ok=True)
+    secret = os.path.join(outside, "secret.txt")
+    with open(secret, "w") as f:
+        f.write("top secret")
+
+    # Plant a symlink inside base that points at the outside directory.
+    # symlink creation can require elevated privileges / Developer Mode on
+    # Windows, so skip cleanly where it isn't available (same guard as the
+    # sibling test in test_ghsa_779p_02_preview_traversal.py).
+    link = os.path.join(base, "escape_link")
+    try:
+        os.symlink(outside, link)
+    except (OSError, NotImplementedError):
+        pytest.skip("symlinks not supported on this platform/filesystem")
+
+    # Accessing the secret "through" the in-base symlink must be rejected.
+    target_via_link = os.path.join(link, "secret.txt")
+    assert folder_paths.is_within_directory(base, target_via_link) is False
+
+
+# ---------------------------------------------------------------------------
+# get_annotated_filepath()
+# ---------------------------------------------------------------------------
+
+def test_get_annotated_filepath_legit_name(sandbox):
+    result = folder_paths.get_annotated_filepath("image.png")
+    assert result == os.path.join(sandbox["input"], "image.png")
+    assert folder_paths.is_within_directory(sandbox["input"], result)
+
+
+def test_get_annotated_filepath_input_annotation(sandbox):
+    result = folder_paths.get_annotated_filepath("image.png [input]")
+    assert result == os.path.join(sandbox["input"], "image.png")
+
+
+def test_get_annotated_filepath_output_annotation(sandbox):
+    result = folder_paths.get_annotated_filepath("image.png [output]")
+    assert result == os.path.join(sandbox["output"], "image.png")
+
+
+def test_get_annotated_filepath_temp_annotation(sandbox):
+    result = folder_paths.get_annotated_filepath("image.png [temp]")
+    assert result == os.path.join(sandbox["temp"], "image.png")
+
+
+def test_get_annotated_filepath_dotdot_raises(sandbox):
+    with pytest.raises(ValueError):
+        folder_paths.get_annotated_filepath("../etc/passwd")
+
+
+def test_get_annotated_filepath_dotdot_with_annotation_raises(sandbox):
+    with pytest.raises(ValueError):
+        folder_paths.get_annotated_filepath("../../etc/passwd [output]")
+
+
+def test_get_annotated_filepath_absolute_escape_raises(sandbox):
+    with pytest.raises(ValueError):
+        folder_paths.get_annotated_filepath("/etc/passwd")
+
+
+# ---------------------------------------------------------------------------
+# exists_annotated_filepath()
+# ---------------------------------------------------------------------------
+
+def test_exists_annotated_filepath_existing_legit_file(sandbox):
+    real = os.path.join(sandbox["input"], "real.png")
+    with open(real, "w") as f:
+        f.write("data")
+    assert folder_paths.exists_annotated_filepath("real.png") is True
+
+
+def test_exists_annotated_filepath_traversal_returns_false(sandbox):
+    """A traversal name must return False without raising and without probing
+    outside the base directory (must never reach os.path.exists for the escape).
+    """
+    # /etc/passwd exists on POSIX; the function must still report False because
+    # the resolved path escapes the input directory.
+    assert folder_paths.exists_annotated_filepath("../../../../../../etc/passwd") is False
+
+
+def test_exists_annotated_filepath_absolute_returns_false(sandbox):
+    assert folder_paths.exists_annotated_filepath("/etc/passwd") is False

tests-unit/security_test/test_ghsa_779p_04_userdata_xss.py

@@ -0,0 +1,147 @@
+"""
+CI unit tests for FIX #4 of GHSA-779p-m5rp-r4h4.
+
+Stored-XSS hardening on GET /userdata/{file} in app/user_manager.py.
+
+User data files are arbitrary user-supplied content and must never render
+inline in the app origin. The getuserdata handler:
+  - forces Content-Type to application/octet-stream for any type in
+    folder_paths.DANGEROUS_CONTENT_TYPES (text/html, image/svg+xml,
+    text/javascript, ...),
+  - sets X-Content-Type-Options: nosniff,
+  - sets Content-Disposition: attachment.
+
+These tests pre-create files in tmp_path and GET them back, asserting the
+secure response headers. They mirror the aiohttp_client pattern in
+tests-unit/prompt_server_test/user_manager_test.py.
+"""
+
+import pytest
+import os
+from aiohttp import web
+from app.user_manager import UserManager
+
+pytestmark = (
+    pytest.mark.asyncio
+)  # This applies the asyncio mark to all test functions in the module
+
+
+@pytest.fixture
+def user_manager(tmp_path):
+    um = UserManager()
+    um.get_request_user_filepath = lambda req, file, **kwargs: os.path.join(
+        tmp_path, file
+    ) if file else tmp_path
+    return um
+
+
+@pytest.fixture
+def app(user_manager):
+    app = web.Application()
+    routes = web.RouteTableDef()
+    user_manager.add_routes(routes)
+    app.add_routes(routes)
+    return app
+
+
+async def test_html_served_as_octet_stream(aiohttp_client, app, tmp_path):
+    (tmp_path / "evil.html").write_text(
+        "<script>console.log('xss-marker-ghsa-779p')</script>"
+    )
+
+    client = await aiohttp_client(app)
+    resp = await client.get("/userdata/evil.html")
+
+    assert resp.status == 200
+    ct = resp.headers.get("Content-Type", "")
+    # The load-bearing assertion: a .html file must NOT be served as text/html.
+    assert "text/html" not in ct.lower(), (
+        f"Content-Type {ct!r} would let a browser render/execute the file (stored XSS)."
+    )
+    assert ct == "application/octet-stream"
+    assert resp.headers.get("X-Content-Type-Options") == "nosniff"
+    assert "attachment" in resp.headers.get("Content-Disposition", "")
+
+
+async def test_svg_served_as_octet_stream(aiohttp_client, app, tmp_path):
+    (tmp_path / "evil.svg").write_text(
+        '<?xml version="1.0"?>'
+        '<svg xmlns="http://www.w3.org/2000/svg">'
+        '<script>console.log("xss-marker-ghsa-779p")</script>'
+        "</svg>"
+    )
+
+    client = await aiohttp_client(app)
+    resp = await client.get("/userdata/evil.svg")
+
+    assert resp.status == 200
+    ct = resp.headers.get("Content-Type", "")
+    # SVG can carry inline <script>; it must not be served as image/svg+xml.
+    assert "svg" not in ct.lower(), (
+        f"Content-Type {ct!r} would let a browser render the SVG and execute embedded scripts."
+    )
+    assert ct == "application/octet-stream"
+    assert resp.headers.get("X-Content-Type-Options") == "nosniff"
+    assert "attachment" in resp.headers.get("Content-Disposition", "")
+
+
+async def test_js_served_as_octet_stream(aiohttp_client, app, tmp_path):
+    (tmp_path / "evil.js").write_text("alert('xss-marker-ghsa-779p')")
+
+    client = await aiohttp_client(app)
+    resp = await client.get("/userdata/evil.js")
+
+    assert resp.status == 200
+    ct = resp.headers.get("Content-Type", "").lower()
+    # Must not be served as any executable JavaScript content type.
+    assert "javascript" not in ct, (
+        f"Content-Type {ct!r} is an executable JS type."
+    )
+    assert "ecmascript" not in ct, (
+        f"Content-Type {ct!r} is an executable JS type."
+    )
+    assert ct == "application/octet-stream"
+    assert resp.headers.get("X-Content-Type-Options") == "nosniff"
+    assert "attachment" in resp.headers.get("Content-Disposition", "")
+
+
+async def test_xml_dialect_served_as_octet_stream(aiohttp_client, app, tmp_path):
+    """An XML dialect outside the original blocklist (.xslt -> application/xslt+xml)
+    must still be forced to download. This pins the normalised *+xml family rule
+    in folder_paths.is_dangerous_content_type(); a plain set-membership test would
+    have served this inline."""
+    (tmp_path / "evil.xslt").write_text(
+        '<?xml version="1.0"?>'
+        '<xsl:stylesheet version="1.0" '
+        'xmlns:xsl="http://www.w3.org/1999/XSL/Transform">'
+        "<!-- xss-marker-ghsa-779p -->"
+        "</xsl:stylesheet>"
+    )
+
+    client = await aiohttp_client(app)
+    resp = await client.get("/userdata/evil.xslt")
+
+    assert resp.status == 200
+    ct = resp.headers.get("Content-Type", "")
+    assert ct == "application/octet-stream", (
+        f"Content-Type {ct!r}: an *+xml dialect must be forced to octet-stream "
+        f"(it can carry inline script via stylesheet/entity tricks)."
+    )
+    assert resp.headers.get("X-Content-Type-Options") == "nosniff"
+    assert "attachment" in resp.headers.get("Content-Disposition", "")
+
+
+async def test_benign_txt_still_served(aiohttp_client, app, tmp_path):
+    (tmp_path / "note.txt").write_text("just a harmless note")
+
+    client = await aiohttp_client(app)
+    resp = await client.get("/userdata/note.txt")
+
+    assert resp.status == 200
+    assert await resp.text() == "just a harmless note"
+    ct = resp.headers.get("Content-Type", "")
+    # text/plain is not in the dangerous set, so it is acceptable here. The
+    # defence-in-depth headers must still be present regardless.
+    assert "text/plain" in ct.lower()
+    assert resp.headers.get("X-Content-Type-Options") == "nosniff"
+    assert "attachment" in resp.headers.get("Content-Disposition", "")

tests-unit/security_test/test_ghsa_779p_05_dangerous_content_types.py

@@ -0,0 +1,138 @@
+"""CI unit guard for FIX #5 of GHSA-779p-m5rp-r4h4 — the /view forced-download set.
+
+Vuln #5 was stored XSS via SVG upload: the /view endpoint's Content-Type
+blocklist covered text/html, text/javascript, etc. but was missing
+image/svg+xml, so an uploaded SVG carrying an inline <script> was served as
+image/svg+xml and executed in the page origin when rendered.
+
+The /view forced-download decision lives in the view_image closure registered by
+server.PromptServer.add_routes (server.py ~line 596), which calls
+`folder_paths.is_dangerous_content_type(content_type)` — a normalising check that
+strips charset/boundary parameters and casing and folds in the whole */xml and
+*+xml dialect family — rather than a bypassable raw
+`content_type in folder_paths.DANGEROUS_CONTENT_TYPES` membership test. On a match
+it rewrites the response to application/octet-stream with a
+Content-Disposition: attachment header. server.py cannot be imported in a unit
+test (importing it spins up the full PromptServer/aiohttp app and its global side
+effects), so these tests pin the underlying dangerous-content data
+(folder_paths.DANGEROUS_CONTENT_TYPES) and the normalising is_dangerous_content_type()
+helper that the closure actually calls.
+
+The end-to-end /view assertion (upload an SVG, GET /view, confirm the response
+is not served as image/svg+xml) lives in the live POC at
+.security/pocs/test_security_ghsa_779p.py::TestViewSvgContentType, which
+requires a running server. This file is the fast, server-free CI guard on the
+set contents so the blocklist can't silently regress.
+"""
+
+import folder_paths
+
+
+# Active/renderable content types that must be forced to download. Each of these
+# can carry an inline <script> (or otherwise execute) in the page origin if a
+# browser renders it. image/svg+xml is the original missing item that caused
+# vuln #5.
+DANGEROUS = [
+    'image/svg+xml',
+    'application/xml',
+    'text/xml',
+    'text/html',
+    'text/html-sandboxed',
+    'application/xhtml+xml',
+    'text/javascript',
+    'application/javascript',
+    'application/x-javascript',
+    'application/ecmascript',
+    'text/css',
+]
+
+# Benign image types that browsers display inline and that must keep rendering;
+# forcing these to download would break legitimate previews.
+BENIGN_INLINE_IMAGES = [
+    'image/png',
+    'image/jpeg',
+    'image/webp',
+    'image/gif',
+]
+
+
+def test_dangerous_content_types_is_a_set():
+    assert isinstance(folder_paths.DANGEROUS_CONTENT_TYPES, set)
+
+
+def test_svg_is_in_the_blocklist():
+    """The specific item whose absence caused vuln #5."""
+    assert 'image/svg+xml' in folder_paths.DANGEROUS_CONTENT_TYPES, (
+        "image/svg+xml missing from DANGEROUS_CONTENT_TYPES — this is exactly "
+        "the regression that reopens GHSA-779p-m5rp-r4h4 vuln #5 (stored XSS "
+        "via SVG upload on /view)."
+    )
+
+
+def test_all_dangerous_types_present():
+    missing = [ct for ct in DANGEROUS if ct not in folder_paths.DANGEROUS_CONTENT_TYPES]
+    assert not missing, (
+        f"DANGEROUS_CONTENT_TYPES is missing required active/renderable types: "
+        f"{missing}. The /view closure only forces a download for content types "
+        f"in this set; anything missing here is served inline and can execute."
+    )
+
+
+def test_benign_inline_image_types_absent():
+    leaked = [ct for ct in BENIGN_INLINE_IMAGES if ct in folder_paths.DANGEROUS_CONTENT_TYPES]
+    assert not leaked, (
+        f"Benign inline-displayable image types found in DANGEROUS_CONTENT_TYPES: "
+        f"{leaked}. Forcing these to download would break legitimate image "
+        f"previews in /view — they must keep rendering inline."
+    )
+
+
+# ---------------------------------------------------------------------------
+# is_dangerous_content_type() — the normalising check the /view and /userdata
+# handlers now call instead of a raw `in DANGEROUS_CONTENT_TYPES` membership
+# test. An exact-string membership test was bypassable with a charset parameter
+# or odd casing, and missed the wider XML dialect family; these tests pin the
+# normalisation so that bypass can't reopen.
+# ---------------------------------------------------------------------------
+
+def test_function_matches_plain_dangerous_types():
+    for ct in DANGEROUS:
+        assert folder_paths.is_dangerous_content_type(ct) is True, ct
+
+
+def test_function_strips_parameters_and_casing():
+    """A charset/boundary parameter or casing must not slip a type past the check.
+
+    This is the bypass surfaced by review: the /view blake3 branch can serve an
+    attacker-controlled, unvalidated asset mime_type like 'text/html; charset=utf-8',
+    which an exact-string set test missed.
+    """
+    for ct in (
+        'text/html; charset=utf-8',
+        'TEXT/HTML',
+        'Text/HTML; charset=UTF-8',
+        'image/svg+xml; charset=utf-8',
+        '  text/html  ',
+    ):
+        assert folder_paths.is_dangerous_content_type(ct) is True, ct
+
+
+def test_function_covers_xml_dialect_family():
+    """Any *+xml / */xml dialect is dangerous without enumerating each one."""
+    for ct in (
+        'application/xslt+xml',
+        'application/rss+xml',
+        'application/atom+xml',
+        'application/rdf+xml',
+        'application/mathml+xml',
+        'message/rfc822',
+    ):
+        assert folder_paths.is_dangerous_content_type(ct) is True, ct
+
+
+def test_function_allows_benign_and_empty():
+    for ct in BENIGN_INLINE_IMAGES + ['application/octet-stream', 'text/plain']:
+        assert folder_paths.is_dangerous_content_type(ct) is False, ct
+    # None / empty (mimetypes.guess_type miss) must not be treated as dangerous.
+    assert folder_paths.is_dangerous_content_type(None) is False
+    assert folder_paths.is_dangerous_content_type('') is False