ComfyUI/app/assets/api/schemas_in.py
Simon Pinfold 55a15f87ce
feat(assets): add namespaced model_type tags and align tag semantics (#14511)
* feat(assets): add namespaced model type tags

* fix(assets): mark path-derived upload tags automatic

* fix(assets): merge duplicate scan specs

* test(assets): make duplicate path normalization portable

* feat(assets): add loader_path as the authoritative loader locator (#14796)

* fix(assets): filter model_type tags by bucket extension sets

Buckets sharing a base directory (e.g. diffusion_models and a custom
unet_gguf) tagged every file in the directory regardless of whether the
bucket could load it, so .safetensors files were tagged
model_type:unet_gguf and vice versa. Carry each bucket's registered
extension set through get_comfy_models_folders and only emit a
model_type tag when the file extension matches, keeping the empty-set
match-all convention from folder_paths.filter_files_extensions.

Files under a model base matching no bucket now keep only the models
tag instead of every directory-matching model_type tag.

* feat(assets): replace response file_path with persisted loader_path

The old file_path response field was a namespaced storage locator
(models/checkpoints/foo.safetensors): not an absolute path, not unique
identity, and not the value a loader consumes. Nothing needs that shape
on the wire (hash/ID-based locating is the long-term direction), so it
is dropped rather than renamed; the storage-root matching stays internal,
powering display_name.

What loaders DO need is the in-root loader path (category dropped:
models/checkpoints/foo/bar.safetensors -> foo/bar.safetensors). Serve it
as a first-class loader_path field, persisted on asset_references
(migration 0006) and written by every ingest pipeline at insert, so
responses read the column verbatim.

Like the model_type tags, loader_path is a seed-time derivative of the
model folder registry, maintained by the same scan lifecycle (new files seed
fresh values, pruning retires rows whose bucket disappeared). Rows
predating the column serve a null loader_path; databases from before
this stack already need recreating for the base branch's tag changes.

loader_path resolves every registered base including extra_model_paths
entries; display_name only the canonical storage roots. A file can
therefore be loadable with no display name (extra-path models) or the
reverse (unregistered files under the models root), and loader_path is
null exactly when no loader can resolve the file.

* test(assets): lock loader_path matrix (asymmetry, null, persist/read)

Cover the behaviour that has no production change but is easy to regress:
the extra-path asymmetry (loadable but no storage namespace), null
loader_path persistence for orphan files, and the response reading the
stored column with a compute fallback for un-backfilled rows.

* fix(assets): persist subfolder-qualified loader_path for ingested outputs

ingest_existing_file built its seed spec with the file's basename, so
outputs saved into a subfolder persisted loader_path (and the
user_metadata filename that preview URLs split for their subfolder
param) as just the basename: the served locator pointed at a file that
does not exist at that path. Scanner and seeder specs already derive
fname via compute_loader_path; use the same derivation here.

* fix(assets): only extension-matching buckets contribute a loader_path

The model-base match in get_asset_category_and_relative_path ignored
each bucket's extension set, so a file inside a registered base whose
extension the bucket cannot load (e.g. a .txt uploaded into
model_type:checkpoints) advertised a loader_path that no loader list
would ever resolve, while the tag side of the same stack already
excluded it. Apply the extension check used for backend tags (empty set
accepts any extension), keeping loader_path null exactly when no loader
can resolve the file.

* fix(assets): refresh loader_path when re-ingesting an existing reference

upsert_reference only wrote loader_path on the INSERT branch, so
re-ingesting an existing reference (an output overwritten in place, or a
file re-registered after its loader_path derivation changed) kept the
stale or NULL value forever. Write it on the UPDATE branch too, with a
null-safe change guard so a loader_path difference alone is enough to
trigger the update, and identical values stay a no-op.

* fix(assets): repair semantic merge breakage from #14796 and master

Two textually-clean but semantically-broken merges:

- routes.py lost its folder_paths import when #14796's import block
  superseded the base's, while the content-type hardening added via the
  base's master merge still calls folder_paths.is_dangerous_content_type.
- master's SVG download-hardening test uploads with the pre-namespacing
  bare checkpoints tag, which this branch's destination validation
  rejects; use model_type:checkpoints.

---------

Co-authored-by: guill <jacob.e.segal@gmail.com>
2026-07-08 22:00:08 -07:00

339 lines
11 KiB
Python

import json
from dataclasses import dataclass
from typing import Any, Literal
from app.assets.helpers import validate_blake3_hash
from pydantic import (
BaseModel,
ConfigDict,
Field,
conint,
field_validator,
model_validator,
)
class UploadError(Exception):
"""Error during upload parsing with HTTP status and code."""
def __init__(self, status: int, code: str, message: str):
super().__init__(message)
self.status = status
self.code = code
self.message = message
class AssetValidationError(Exception):
"""Validation error in asset processing (invalid tags, metadata, etc.)."""
def __init__(self, code: str, message: str):
super().__init__(message)
self.code = code
self.message = message
@dataclass
class ParsedUpload:
"""Result of parsing a multipart upload request."""
file_present: bool
file_written: int
file_client_name: str | None
tmp_path: str | None
tags_raw: list[str]
provided_name: str | None
user_metadata_raw: str | None
provided_hash: str | None
provided_hash_exists: bool | None
provided_mime_type: str | None = None
provided_preview_id: str | None = None
class ListAssetsQuery(BaseModel):
include_tags: list[str] = Field(default_factory=list)
exclude_tags: list[str] = Field(default_factory=list)
name_contains: str | None = None
# Accept either a JSON string (query param) or a dict
metadata_filter: dict[str, Any] | None = None
limit: conint(ge=1, le=500) = 20
offset: conint(ge=0) = 0
# Opaque keyset cursor. When supplied, `offset` is ignored. Cursor pagination
# is supported for sort values `created_at`, `updated_at`, `name`, `size`.
# Supplying `after` together with `sort=last_access_time` returns
# 400 INVALID_CURSOR; that sort only supports offset/limit.
after: str | None = None
sort: Literal["name", "created_at", "updated_at", "size", "last_access_time"] = (
"created_at"
)
order: Literal["asc", "desc"] = "desc"
@field_validator("include_tags", "exclude_tags", mode="before")
@classmethod
def _split_csv_tags(cls, v):
# Accept "a,b,c" or ["a","b"] (we are liberal in what we accept)
if v is None:
return []
if isinstance(v, str):
return [t.strip() for t in v.split(",") if t.strip()]
if isinstance(v, list):
out: list[str] = []
for item in v:
if isinstance(item, str):
out.extend([t.strip() for t in item.split(",") if t.strip()])
return out
return v
@field_validator("metadata_filter", mode="before")
@classmethod
def _parse_metadata_json(cls, v):
if v is None or isinstance(v, dict):
return v
if isinstance(v, str) and v.strip():
try:
parsed = json.loads(v)
except Exception as e:
raise ValueError(f"metadata_filter must be JSON: {e}") from e
if not isinstance(parsed, dict):
raise ValueError("metadata_filter must be a JSON object")
return parsed
return None
class UpdateAssetBody(BaseModel):
name: str | None = None
user_metadata: dict[str, Any] | None = None
preview_id: str | None = None # references an asset_reference id, not an asset id
@model_validator(mode="after")
def _validate_at_least_one_field(self):
if all(
v is None
for v in (self.name, self.user_metadata, self.preview_id)
):
raise ValueError(
"Provide at least one of: name, user_metadata, preview_id."
)
return self
class CreateFromHashBody(BaseModel):
model_config = ConfigDict(extra="ignore", str_strip_whitespace=True)
hash: str
name: str | None = None
tags: list[str] = Field(default_factory=list)
user_metadata: dict[str, Any] = Field(default_factory=dict)
mime_type: str | None = None
preview_id: str | None = None # references an asset_reference id, not an asset id
@field_validator("hash")
@classmethod
def _require_blake3(cls, v):
return validate_blake3_hash(v or "")
@field_validator("tags", mode="before")
@classmethod
def _normalize_tags_field(cls, v):
if v is None:
return []
if isinstance(v, list):
out = [str(t).strip() for t in v if str(t).strip()]
seen = set()
dedup = []
for t in out:
if t not in seen:
seen.add(t)
dedup.append(t)
return dedup
if isinstance(v, str):
return list(dict.fromkeys(t.strip() for t in v.split(",") if t.strip()))
return []
class TagsRefineQuery(BaseModel):
include_tags: list[str] = Field(default_factory=list)
exclude_tags: list[str] = Field(default_factory=list)
name_contains: str | None = None
metadata_filter: dict[str, Any] | None = None
limit: conint(ge=1, le=1000) = 100
@field_validator("include_tags", "exclude_tags", mode="before")
@classmethod
def _split_csv_tags(cls, v):
if v is None:
return []
if isinstance(v, str):
return [t.strip() for t in v.split(",") if t.strip()]
if isinstance(v, list):
out: list[str] = []
for item in v:
if isinstance(item, str):
out.extend([t.strip() for t in item.split(",") if t.strip()])
return out
return v
@field_validator("metadata_filter", mode="before")
@classmethod
def _parse_metadata_json(cls, v):
if v is None or isinstance(v, dict):
return v
if isinstance(v, str) and v.strip():
try:
parsed = json.loads(v)
except Exception as e:
raise ValueError(f"metadata_filter must be JSON: {e}") from e
if not isinstance(parsed, dict):
raise ValueError("metadata_filter must be a JSON object")
return parsed
return None
class TagsListQuery(BaseModel):
model_config = ConfigDict(extra="ignore", str_strip_whitespace=True)
prefix: str | None = Field(None, min_length=1, max_length=256)
limit: int = Field(100, ge=1, le=1000)
offset: int = Field(0, ge=0, le=10_000_000)
order: Literal["count_desc", "name_asc"] = "count_desc"
include_zero: bool = True
@field_validator("prefix")
@classmethod
def normalize_prefix(cls, v: str | None) -> str | None:
if v is None:
return v
v = v.strip()
return v or None
class TagsAdd(BaseModel):
model_config = ConfigDict(extra="ignore")
tags: list[str] = Field(..., min_length=1)
@field_validator("tags")
@classmethod
def normalize_tags(cls, v: list[str]) -> list[str]:
out = []
for t in v:
if not isinstance(t, str):
raise TypeError("tags must be strings")
tnorm = t.strip()
if tnorm:
out.append(tnorm)
seen = set()
deduplicated = []
for x in out:
if x not in seen:
seen.add(x)
deduplicated.append(x)
return deduplicated
class TagsRemove(TagsAdd):
pass
class UploadAssetSpec(BaseModel):
"""Upload Asset operation.
- tags: labels plus one destination role ('models'|'input'|'output') for new bytes;
if role == 'models', exactly one model_type:<folder_name> tag is required
- name: display name
- user_metadata: arbitrary JSON object (optional)
- hash: optional canonical 'blake3:<hex>' for validation / fast-path
- mime_type: optional MIME type override
- preview_id: optional asset_reference ID for preview
Files are stored using the content hash as filename stem.
"""
model_config = ConfigDict(extra="ignore", str_strip_whitespace=True)
tags: list[str] = Field(default_factory=list)
name: str | None = Field(default=None, max_length=512, description="Display Name")
user_metadata: dict[str, Any] = Field(default_factory=dict)
hash: str | None = Field(default=None)
mime_type: str | None = Field(default=None)
preview_id: str | None = Field(default=None) # references an asset_reference id
@field_validator("hash", mode="before")
@classmethod
def _parse_hash(cls, v):
if v is None:
return None
s = str(v).strip()
if not s:
return None
return validate_blake3_hash(s)
@field_validator("tags", mode="before")
@classmethod
def _parse_tags(cls, v):
"""
Accepts a list of strings (possibly multiple form fields),
where each string can be:
- JSON array (e.g., '["models","loras","foo"]')
- comma-separated ('models, loras, foo')
- single token ('models')
Returns a normalized, deduplicated, ordered list.
"""
items: list[str] = []
if v is None:
return []
if isinstance(v, str):
v = [v]
if isinstance(v, list):
for item in v:
if item is None:
continue
s = str(item).strip()
if not s:
continue
if s.startswith("["):
try:
arr = json.loads(s)
if isinstance(arr, list):
items.extend(str(x) for x in arr)
continue
except Exception:
pass # fallback to CSV parse below
items.extend([p for p in s.split(",") if p.strip()])
else:
return []
# normalize + dedupe
norm = []
seen = set()
for t in items:
tnorm = str(t).strip()
if tnorm and tnorm not in seen:
seen.add(tnorm)
norm.append(tnorm)
return norm
@field_validator("user_metadata", mode="before")
@classmethod
def _parse_metadata_json(cls, v):
if v is None or isinstance(v, dict):
return v or {}
if isinstance(v, str):
s = v.strip()
if not s:
return {}
try:
parsed = json.loads(s)
except Exception as e:
raise ValueError(f"user_metadata must be JSON: {e}") from e
if not isinstance(parsed, dict):
raise ValueError("user_metadata must be a JSON object")
return parsed
return {}
@model_validator(mode="after")
def _validate_order(self):
return self