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12 Commits

Author SHA1 Message Date
1339cb570d Coalesce empty query params to None in /node_startup_errors route
?source= or ?module_name= or ?pack_id= (param present but blank) would have returned {} because the helper treated the empty string as an exact-match filter. Coalesce to None at the route boundary so a present-but-blank query param behaves the same as the param being absent. The helper's own behaviour is unchanged and locked in by a new assertion.

Amp-Thread-ID: https://ampcode.com/threads/T-019e86fd-b68f-74de-8c91-d2662377424a
Co-authored-by: Amp <amp@ampcode.com>
2026-06-01 23:39:32 -07:00
4eef53041e Match PyProjectConfig shape for pyproject; add pack_id/module_name/source query filters
Two reviewer-requested improvements to GET /node_startup_errors:

1. Emit the pyproject metadata in the same {project: {...}, tool_comfy: {...}}
   shape that comfy_config.config_parser.extract_node_configuration already
   returns, instead of inventing a flat {pack_id, display_name, ...} bag.
   API consumers can now parse the pyproject block straight through the
   shared PyProjectConfig pydantic model. Empty / default-valued leaves
   are pruned by a small recursive _prune_empty helper so the payload
   stays compact, but nesting and field names match the source-of-truth.

2. Add optional source, module_name, and pack_id query parameters
   (combined with AND) so a frontend / Manager can ask ?pack_id=foo
   instead of grep'ing through the whole grouped response. pack_id
   resolves against pyproject.project.name; entries without a parsed
   pyproject are naturally excluded from a pack_id query.

The grouping + filtering + module_path stripping moves into

odes.filter_node_startup_errors so the route handler is a one-liner and
the helper is unit-testable without spinning up an aiohttp app.

Tests: 5 new unit tests covering each filter branch, AND-combination, and
empty-result behaviour, plus an updated pyproject-metadata assertion that
checks the nested PyProjectConfig shape, plus a focused test for the
_prune_empty helper.
2026-06-01 23:33:37 -07:00
7259e664ef Defer record_node_startup_error in prestartup error path; add docstrings
Buffer prestartup failures into a module-level list inside main.py
instead of importing 'nodes' (and therefore 'torch') from within the
exception handler. After the normal 'import nodes' line, drain the
buffer via nodes.record_node_startup_error so bootstrap order stays
deterministic regardless of whether a prestartup script succeeded.

Also convert the explanatory '#' comment on the new
/node_startup_errors endpoint into a proper docstring and add a
docstring to execute_prestartup_script, addressing CodeRabbit's
docstring-coverage warning on this PR.

Addresses review feedback on PR #13184.

Amp-Thread-ID: https://ampcode.com/threads/T-019e2f90-26fe-7048-9855-5ff39d08a3e0
Co-authored-by: Amp <amp@ampcode.com>
2026-05-21 14:09:01 -07:00
ae539cfa0a Merge branch 'master' into feature/custom-node-startup-errors 2026-05-21 12:58:06 -07:00
8f82b16993 Merge branch 'master' into feature/custom-node-startup-errors 2026-05-15 16:31:50 -07:00
72fe66a18b Hoist 'import traceback' to top of main.py
Minor cleanup from code review: traceback is stdlib so there's no circular-import concern keeping it inline. The 'from nodes import record_node_startup_error' stays inline because nodes.py imports from contexts that would create a cycle at module load time.

Ref: ComfyUI-Launcher#303
Amp-Thread-ID: https://ampcode.com/threads/T-019e23a1-2acc-7619-bd0e-f783d1368ef3
Co-authored-by: Amp <amp@ampcode.com>
2026-05-15 00:48:23 -07:00
07ff14ae02 Use module_parent string directly as 'source'; drop fixed-enum mapping
The public 'source' field on each NODE_STARTUP_ERRORS entry is now the same string as the internal module_parent passed to load_custom_node ('custom_nodes', 'comfy_extras', 'comfy_api_nodes'), rather than being translated to a separate fixed enum. Treating it as a free-form string keeps the contract durable in case the node-source layout evolves (e.g. comfy_api_nodes eventually moving out of core).

The API endpoint now also dynamically groups by whatever sources are present rather than hardcoding the three known top-level keys; consumers should not assume any particular set of keys is always present.

Drops the _NODE_SOURCE_BY_PARENT map, _node_source_from_parent helper, and the related test. Adds a test covering an arbitrary unknown module_parent value passing through unchanged.

Ref: ComfyUI-Launcher#303
Amp-Thread-ID: https://ampcode.com/threads/T-019e23a1-2acc-7619-bd0e-f783d1368ef3
Co-authored-by: Amp <amp@ampcode.com>
2026-05-14 20:49:35 -07:00
ba1c039a04 Rename /custom_node_startup_errors -> /node_startup_errors
The endpoint covers comfy_extras and comfy_api_nodes failures too, not just user-installed custom nodes, so the path should not pretend otherwise.

Ref: ComfyUI-Launcher#303
Amp-Thread-ID: https://ampcode.com/threads/T-019e23a1-2acc-7619-bd0e-f783d1368ef3
Co-authored-by: Amp <amp@ampcode.com>
2026-05-13 21:05:15 -07:00
6220400ad5 Strip absolute module_path from /custom_node_startup_errors response
The absolute on-disk path is internal detail the frontend/Manager has no use for. Keep it in the in-memory NODE_STARTUP_ERRORS dict for server-side debugging, but exclude it from the public API payload. The user-facing identifier remains module_name (and pyproject.pack_id when available).

Ref: ComfyUI-Launcher#303
Amp-Thread-ID: https://ampcode.com/threads/T-019e23a1-2acc-7619-bd0e-f783d1368ef3
Co-authored-by: Amp <amp@ampcode.com>
2026-05-13 18:10:50 -07:00
af55a2308f Attach pyproject.toml node-pack identity to startup error entries
When a failing module has a pyproject.toml, parse it via comfy_config.config_parser and attach a 'pyproject' field with the Comfy Registry-style identity (pack_id, display_name, publisher_id, version, repository). This gives the frontend/Manager a stable, user-recognizable handle for the failed pack beyond the on-disk folder name.

The lookup is best-effort and never raises: missing toml, missing pydantic-settings dependency, or any parse error simply omits the 'pyproject' key.

Ref: ComfyUI-Launcher#303
Amp-Thread-ID: https://ampcode.com/threads/T-019e23a1-2acc-7619-bd0e-f783d1368ef3
Co-authored-by: Amp <amp@ampcode.com>
2026-05-13 16:31:44 -07:00
3a649984f2 Categorize startup errors by source (custom_node / comfy_extra / api_node)
Expand custom-node startup error tracking to differentiate between user-installed custom_nodes, built-in comfy_extras, and partner comfy_api_nodes. Each NODE_STARTUP_ERRORS entry now carries a 'source' field and is keyed by '<source>:<module_name>' so colliding module names across the three locations don't overwrite each other. The /custom_node_startup_errors endpoint returns errors grouped by source so the frontend/Manager can render distinct sections.

Also captures previously-missed failures from comfy_entrypoint() (phase='entrypoint').

Introduces nodes.record_node_startup_error() helper used by load_custom_node and main.execute_prestartup_script.

Adds tests-unit/node_startup_errors_test.py (6 tests) covering field shape, source mapping for each module_parent, cross-source collisions, and default fallback.

Ref: ComfyUI-Launcher#303
Amp-Thread-ID: https://ampcode.com/threads/T-019e23a1-2acc-7619-bd0e-f783d1368ef3
Co-authored-by: Amp <amp@ampcode.com>
2026-05-13 16:29:17 -07:00
a145651cc0 Track custom node startup errors and expose via API endpoint
Store import and prestartup errors in NODE_STARTUP_ERRORS dict (nodes.py,
main.py) and add GET /custom_node_startup_errors endpoint (server.py) so
the frontend/Manager can distinguish failed imports from missing nodes.

Ref: ComfyUI-Launcher#303
Amp-Thread-ID: https://ampcode.com/threads/T-019d2346-6e6f-75e0-a97f-cdb6e26859f7
Co-authored-by: Amp <amp@ampcode.com>
2026-03-24 23:41:01 -07:00
383 changed files with 13791 additions and 81583 deletions

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@ -1,4 +1,5 @@
As of the time of writing this you need a recent driver. Updating to the latest driver is recommended.
As of the time of writing this you need this driver for best results:
https://www.amd.com/en/resources/support-articles/release-notes/RN-AMDGPU-WINDOWS-PYTORCH-7-1-1.html
HOW TO RUN:
@ -6,9 +7,9 @@ If you have a AMD gpu:
run_amd_gpu.bat
If you have memory issues you can try enabling the new dynamic memory management by running comfyui with:
If you have memory issues you can try disabling the smart memory management by running comfyui with:
run_amd_gpu_enable_dynamic_vram.bat
run_amd_gpu_disable_smart_memory.bat
IF YOU GET A RED ERROR IN THE UI MAKE SURE YOU HAVE A MODEL/CHECKPOINT IN: ComfyUI\models\checkpoints

View File

@ -1,519 +0,0 @@
name: Backport Release
on:
workflow_dispatch:
inputs:
commit:
description: 'Full 40-char SHA of the tip commit of the backport source branch (the PR head commit that passed tests). The branch is resolved from this SHA and must be unique.'
required: true
type: string
permissions:
contents: read
pull-requests: read
checks: read
jobs:
backport-release:
name: Create backport release
runs-on: ubuntu-latest
environment: backport release
steps:
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@bcd2ba49218906704ab6c1aa796996da409d3eb1
with:
app-id: ${{ secrets.FEN_RELEASE_APP_ID }}
private-key: ${{ secrets.FEN_RELEASE_PRIVATE_KEY }}
- name: Checkout repository
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
with:
token: ${{ steps.app-token.outputs.token }}
fetch-depth: 0
fetch-tags: true
- name: Configure git
run: |
git config user.name "fen-release[bot]"
git config user.email "fen-release[bot]@users.noreply.github.com"
- name: Resolve source branch from commit SHA
id: resolve
env:
SOURCE_COMMIT: ${{ inputs.commit }}
DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
run: |
set -euo pipefail
# Require a full 40-char lowercase-hex SHA. Short SHAs are ambiguous
# and we will be comparing this value against API responses (PR head
# SHA, ref tips) that always return the full form.
if [[ ! "${SOURCE_COMMIT}" =~ ^[0-9a-f]{40}$ ]]; then
echo "::error::Input commit '${SOURCE_COMMIT}' is not a full 40-char lowercase hex SHA."
exit 1
fi
# Fetch all remote branches so we can search for which one(s) point
# at this SHA. `actions/checkout` with fetch-depth: 0 fetches full
# history of the checked-out ref but does not necessarily populate
# every refs/remotes/origin/*, so do it explicitly.
git fetch --prune origin '+refs/heads/*:refs/remotes/origin/*'
# Verify the commit actually exists in this repo's object DB.
if ! git cat-file -e "${SOURCE_COMMIT}^{commit}" 2>/dev/null; then
echo "::error::Commit ${SOURCE_COMMIT} was not found in the repository."
exit 1
fi
# Find every remote branch whose tip == SOURCE_COMMIT. Exactly one
# branch must point at it. If zero, the commit isn't anyone's tip
# (likely stale, force-pushed past, or never the PR head). If more
# than one, the (branch -> SHA) mapping is ambiguous and we refuse
# to guess — the operator must give us a unique branch to release.
mapfile -t matching_branches < <(
git for-each-ref \
--format='%(refname:strip=3)' \
--points-at="${SOURCE_COMMIT}" \
refs/remotes/origin/ \
| grep -vx 'HEAD' || true
)
if [[ "${#matching_branches[@]}" -eq 0 ]]; then
echo "::error::No branch on origin has ${SOURCE_COMMIT} as its tip."
echo "::error::Either the branch was updated after you copied this SHA, or this commit was never the head of a branch."
exit 1
fi
if [[ "${#matching_branches[@]}" -gt 1 ]]; then
echo "::error::More than one branch on origin has ${SOURCE_COMMIT} as its tip; cannot pick one:"
for b in "${matching_branches[@]}"; do
echo "::error:: - ${b}"
done
echo "::error::Refusing to proceed with an ambiguous source branch."
exit 1
fi
source_branch="${matching_branches[0]}"
if [[ "${source_branch}" == "${DEFAULT_BRANCH}" ]]; then
echo "::error::Source branch must not be the default branch ('${DEFAULT_BRANCH}')."
exit 1
fi
echo "Resolved commit ${SOURCE_COMMIT} to branch '${source_branch}'."
echo "source_branch=${source_branch}" >> "$GITHUB_OUTPUT"
- name: Determine latest stable release
id: latest
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
run: |
set -euo pipefail
# List all tags matching vMAJOR.MINOR.PATCH and pick the highest by numeric
# comparison of each component. We DO NOT use `sort -V` because it treats
# v0.19.99 as higher than v0.20.1.
latest_tag="$(
git tag --list 'v[0-9]*.[0-9]*.[0-9]*' \
| grep -E '^v[0-9]+\.[0-9]+\.[0-9]+$' \
| awk -F'[v.]' '{ printf "%010d %010d %010d %s\n", $2, $3, $4, $0 }' \
| sort -k1,1n -k2,2n -k3,3n \
| tail -n1 \
| awk '{print $4}'
)"
if [[ -z "${latest_tag}" ]]; then
echo "::error::No stable release tags (vMAJOR.MINOR.PATCH) were found."
exit 1
fi
# Parse components
ver="${latest_tag#v}"
major="${ver%%.*}"
rest="${ver#*.}"
minor="${rest%%.*}"
patch="${rest#*.}"
new_patch=$((patch + 1))
new_version="v${major}.${minor}.${new_patch}"
release_branch="release/v${major}.${minor}"
latest_sha="$(git rev-list -n 1 "refs/tags/${latest_tag}")"
echo "latest_tag=${latest_tag}" >> "$GITHUB_OUTPUT"
echo "latest_sha=${latest_sha}" >> "$GITHUB_OUTPUT"
echo "major=${major}" >> "$GITHUB_OUTPUT"
echo "minor=${minor}" >> "$GITHUB_OUTPUT"
echo "patch=${patch}" >> "$GITHUB_OUTPUT"
echo "new_version=${new_version}" >> "$GITHUB_OUTPUT"
echo "new_version_no_v=${major}.${minor}.${new_patch}" >> "$GITHUB_OUTPUT"
echo "release_branch=${release_branch}" >> "$GITHUB_OUTPUT"
echo "Latest stable release: ${latest_tag} (${latest_sha})"
echo "New version will be: ${new_version}"
echo "Release branch: ${release_branch}"
- name: Validate source branch is cut directly from the latest stable release
env:
SOURCE_BRANCH: ${{ steps.resolve.outputs.source_branch }}
SOURCE_COMMIT: ${{ inputs.commit }}
LATEST_TAG_SHA: ${{ steps.latest.outputs.latest_sha }}
LATEST_TAG: ${{ steps.latest.outputs.latest_tag }}
run: |
set -euo pipefail
# Use the user-provided SHA directly rather than re-resolving the branch
# tip — the resolve step already proved the branch tip equals SOURCE_COMMIT,
# and pinning to the SHA here makes the rest of the job TOCTOU-safe against
# someone pushing to the branch mid-run.
source_sha="${SOURCE_COMMIT}"
# Walking first-parent from the source tip must reach LATEST_TAG_SHA.
# We capture rev-list into a variable and grep against a here-string
# rather than piping `rev-list | grep -q`: under `set -o pipefail`,
# `grep -q` would exit on first match and SIGPIPE the still-streaming
# `rev-list`, propagating exit 141 as a spurious "not found".
first_parent_chain="$(git rev-list --first-parent "${source_sha}")"
if ! grep -Fxq "${LATEST_TAG_SHA}" <<< "${first_parent_chain}"; then
echo "::error::Source branch '${SOURCE_BRANCH}' is not cut from '${LATEST_TAG}'."
echo "::error::Its first-parent history does not include ${LATEST_TAG_SHA}."
exit 1
fi
# Additionally, every commit added on top of the tag (the set we are
# about to publish) must itself be a descendant of the tag along
# first-parent — i.e. no sibling commits from master sneak in via a
# non-first-parent path. Enforce by requiring that the symmetric
# difference is empty in one direction: commits in source that are
# NOT first-parent-reachable from source starting at the tag.
# We do this by intersecting:
# A = commits reachable from source but not from tag (full DAG)
# B = commits on the first-parent chain from source down to tag
# and requiring A == B.
all_added="$(git rev-list "${LATEST_TAG_SHA}..${source_sha}" | sort)"
first_parent_added="$(
git rev-list --first-parent "${LATEST_TAG_SHA}..${source_sha}" | sort
)"
if [[ "${all_added}" != "${first_parent_added}" ]]; then
echo "::error::Source branch '${SOURCE_BRANCH}' contains commits not on its first-parent chain from '${LATEST_TAG}'."
echo "::error::This usually means the branch was cut from master (not from the tag) or contains a merge from master."
echo "Commits reachable but not on first-parent chain:"
comm -23 <(printf '%s\n' "${all_added}") <(printf '%s\n' "${first_parent_added}") \
| while read -r sha; do
echo " $(git log -1 --format='%h %s' "${sha}")"
done
exit 1
fi
added_count="$(printf '%s\n' "${all_added}" | grep -c . || true)"
echo "Source branch is cut directly from ${LATEST_TAG} with ${added_count} commit(s) on top."
- name: Validate PR exists, is open, named correctly, has latest commit, and checks pass
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
SOURCE_BRANCH: ${{ steps.resolve.outputs.source_branch }}
SOURCE_COMMIT: ${{ inputs.commit }}
NEW_VERSION: ${{ steps.latest.outputs.new_version }}
REPO: ${{ github.repository }}
run: |
set -euo pipefail
expected_title="ComfyUI backport release ${NEW_VERSION}"
# Find open PRs from this branch into master. The --state open filter
# is load-bearing: a closed/merged PR with passing checks must not be
# accepted as authorization for a new release.
pr_json="$(
gh pr list \
--repo "${REPO}" \
--state open \
--head "${SOURCE_BRANCH}" \
--base master \
--json number,title,headRefOid,state \
--limit 10
)"
pr_count="$(echo "${pr_json}" | jq 'length')"
if [[ "${pr_count}" -eq 0 ]]; then
echo "::error::No open PR found from '${SOURCE_BRANCH}' into 'master'. The PR must exist and be open."
exit 1
fi
# Pick the PR matching the expected title
pr_number="$(echo "${pr_json}" | jq -r --arg t "${expected_title}" '
map(select(.title == $t)) | .[0].number // empty
')"
pr_head_sha="$(echo "${pr_json}" | jq -r --arg t "${expected_title}" '
map(select(.title == $t)) | .[0].headRefOid // empty
')"
if [[ -z "${pr_number}" ]]; then
echo "::error::No open PR from '${SOURCE_BRANCH}' into 'master' is titled '${expected_title}'."
echo "Found PRs:"
echo "${pr_json}" | jq -r '.[] | " #\(.number): \(.title)"'
exit 1
fi
# The PR's current head commit must equal the SHA the operator gave us.
# This is what closes the door on releasing stale code: if anyone has
# pushed to the branch since the operator validated tests passed, the
# PR head will have advanced past SOURCE_COMMIT and we abort. (The
# resolve step already proved the branch tip == SOURCE_COMMIT; this
# ties that same SHA to the PR that authorizes the release.)
if [[ "${pr_head_sha}" != "${SOURCE_COMMIT}" ]]; then
echo "::error::PR #${pr_number} head commit is ${pr_head_sha}, but the operator-provided commit is ${SOURCE_COMMIT}."
echo "::error::The PR has new commits since this release was authorized. Re-run with the new head SHA after verifying its checks."
exit 1
fi
echo "Found open PR #${pr_number} titled '${expected_title}' at head ${pr_head_sha} (matches operator-provided commit)."
# Verify all check runs on the head commit have completed successfully.
# A check is considered passing if conclusion is success, neutral, or skipped.
checks_json="$(
gh api \
--paginate \
"repos/${REPO}/commits/${pr_head_sha}/check-runs" \
--jq '.check_runs[] | {name: .name, status: .status, conclusion: .conclusion}'
)"
if [[ -z "${checks_json}" ]]; then
echo "::error::No check runs found on PR head commit ${pr_head_sha}."
exit 1
fi
echo "Check runs on ${pr_head_sha}:"
echo "${checks_json}" | jq -s '.'
failing="$(echo "${checks_json}" | jq -s '
map(select(
.status != "completed"
or (.conclusion as $c
| ["success","neutral","skipped"]
| index($c) | not)
))
')"
failing_count="$(echo "${failing}" | jq 'length')"
if [[ "${failing_count}" -gt 0 ]]; then
echo "::error::One or more checks have not passed on PR head commit ${pr_head_sha}:"
echo "${failing}" | jq -r '.[] | " - \(.name): status=\(.status) conclusion=\(.conclusion)"'
exit 1
fi
echo "All checks have passed on ${pr_head_sha}."
- name: Prepare release branch
id: prepare
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
REPO: ${{ github.repository }}
RELEASE_BRANCH: ${{ steps.latest.outputs.release_branch }}
LATEST_TAG: ${{ steps.latest.outputs.latest_tag }}
LATEST_TAG_SHA: ${{ steps.latest.outputs.latest_sha }}
PATCH: ${{ steps.latest.outputs.patch }}
run: |
set -euo pipefail
# Try to fetch the release branch. If patch == 0, it shouldn't exist yet
# and we'll create it from the latest stable tag. If patch > 0, it must
# already exist and its tip must equal the latest stable tag commit (i.e.
# the previous patch release).
if git ls-remote --exit-code --heads origin "${RELEASE_BRANCH}" >/dev/null 2>&1; then
echo "Release branch '${RELEASE_BRANCH}' already exists on origin."
git fetch origin "refs/heads/${RELEASE_BRANCH}:refs/remotes/origin/${RELEASE_BRANCH}"
git checkout -B "${RELEASE_BRANCH}" "refs/remotes/origin/${RELEASE_BRANCH}"
current_tip="$(git rev-parse HEAD)"
if [[ "${current_tip}" != "${LATEST_TAG_SHA}" ]]; then
echo "::error::Release branch '${RELEASE_BRANCH}' tip (${current_tip}) is not at the latest stable release '${LATEST_TAG}' (${LATEST_TAG_SHA})."
echo "::error::Refusing to release on top of a divergent branch."
exit 1
fi
echo "branch_existed=true" >> "$GITHUB_OUTPUT"
else
if [[ "${PATCH}" != "0" ]]; then
echo "::error::Release branch '${RELEASE_BRANCH}' does not exist on origin, but the latest stable release '${LATEST_TAG}' has patch=${PATCH} (>0). This is inconsistent."
exit 1
fi
echo "Release branch '${RELEASE_BRANCH}' does not exist. Creating from ${LATEST_TAG}."
git checkout -B "${RELEASE_BRANCH}" "refs/tags/${LATEST_TAG}"
echo "branch_existed=false" >> "$GITHUB_OUTPUT"
fi
- name: Fast-forward merge source branch into release branch
env:
SOURCE_BRANCH: ${{ steps.resolve.outputs.source_branch }}
SOURCE_COMMIT: ${{ inputs.commit }}
RELEASE_BRANCH: ${{ steps.latest.outputs.release_branch }}
run: |
set -euo pipefail
# --ff-only guarantees no merge commit is created. If a fast-forward is
# not possible (i.e. the release branch has commits the source branch
# doesn't), the merge will fail and we abort. Because we already validated
# that the source branch is rooted on the latest stable tag, and the
# release branch tip equals that same tag, this fast-forward should
# always succeed for a well-formed backport branch.
#
# We merge the operator-provided SHA, not the branch ref, so a push to
# the branch in the window between resolve and now cannot smuggle new
# commits into the release.
if ! git merge --ff-only "${SOURCE_COMMIT}"; then
echo "::error::Cannot fast-forward '${RELEASE_BRANCH}' to ${SOURCE_COMMIT} (tip of '${SOURCE_BRANCH}'). A merge commit would be required. Aborting."
exit 1
fi
echo "Fast-forwarded '${RELEASE_BRANCH}' to ${SOURCE_COMMIT} (tip of '${SOURCE_BRANCH}')."
- name: Bump version files
env:
NEW_VERSION_NO_V: ${{ steps.latest.outputs.new_version_no_v }}
run: |
set -euo pipefail
if [[ ! -f comfyui_version.py ]]; then
echo "::error::comfyui_version.py not found in repo root."
exit 1
fi
if [[ ! -f pyproject.toml ]]; then
echo "::error::pyproject.toml not found in repo root."
exit 1
fi
# Replace the version string in comfyui_version.py.
# Expected format: __version__ = "X.Y.Z"
python3 - "$NEW_VERSION_NO_V" <<'PY'
import re, sys, pathlib
new = sys.argv[1]
p = pathlib.Path("comfyui_version.py")
src = p.read_text()
new_src, n = re.subn(
r'(__version__\s*=\s*[\'"])[^\'"]+([\'"])',
lambda m: f'{m.group(1)}{new}{m.group(2)}',
src,
count=1,
)
if n != 1:
sys.exit("Could not find __version__ assignment in comfyui_version.py")
p.write_text(new_src)
p = pathlib.Path("pyproject.toml")
src = p.read_text()
# Replace the first `version = "..."` inside [project] or [tool.poetry].
new_src, n = re.subn(
r'(?m)^(version\s*=\s*")[^"]+(")',
lambda m: f'{m.group(1)}{new}{m.group(2)}',
src,
count=1,
)
if n != 1:
sys.exit("Could not find version assignment in pyproject.toml")
p.write_text(new_src)
PY
echo "Updated version to ${NEW_VERSION_NO_V} in comfyui_version.py and pyproject.toml."
git --no-pager diff -- comfyui_version.py pyproject.toml
- name: Commit version bump and tag release
env:
NEW_VERSION: ${{ steps.latest.outputs.new_version }}
run: |
set -euo pipefail
git add comfyui_version.py pyproject.toml
git commit -m "ComfyUI ${NEW_VERSION}"
if git rev-parse -q --verify "refs/tags/${NEW_VERSION}" >/dev/null; then
echo "::error::Tag ${NEW_VERSION} already exists locally."
exit 1
fi
git tag "${NEW_VERSION}"
- name: Verify tag does not already exist on origin
env:
NEW_VERSION: ${{ steps.latest.outputs.new_version }}
run: |
set -euo pipefail
if git ls-remote --exit-code --tags origin "refs/tags/${NEW_VERSION}" >/dev/null 2>&1; then
echo "::error::Tag ${NEW_VERSION} already exists on origin. Aborting."
exit 1
fi
- name: Push release branch and tag
env:
RELEASE_BRANCH: ${{ steps.latest.outputs.release_branch }}
NEW_VERSION: ${{ steps.latest.outputs.new_version }}
run: |
set -euo pipefail
# Push the branch first, then the tag. Atomic-ish: if the branch push
# fails we never publish the tag.
git push origin "refs/heads/${RELEASE_BRANCH}:refs/heads/${RELEASE_BRANCH}"
git push origin "refs/tags/${NEW_VERSION}"
echo "Released ${NEW_VERSION} on ${RELEASE_BRANCH}."
- name: Delete remote source branch
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
REPO: ${{ github.repository }}
SOURCE_BRANCH: ${{ steps.resolve.outputs.source_branch }}
SOURCE_COMMIT: ${{ inputs.commit }}
RELEASE_BRANCH: ${{ steps.latest.outputs.release_branch }}
DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
run: |
set -euo pipefail
# Belt-and-braces: the resolve step already refuses the default branch,
# but never delete the default or the release branch under any
# circumstances.
if [[ "${SOURCE_BRANCH}" == "${DEFAULT_BRANCH}" || "${SOURCE_BRANCH}" == "${RELEASE_BRANCH}" ]]; then
echo "::error::Refusing to delete '${SOURCE_BRANCH}' (matches default or release branch)."
exit 1
fi
# Delete the source branch on origin, but only if its tip is still the
# SHA we released from. If someone pushed new commits to it after we
# resolved it, leave it alone — those commits would be silently lost.
current_tip="$(git ls-remote origin "refs/heads/${SOURCE_BRANCH}" | awk '{print $1}')"
if [[ -z "${current_tip}" ]]; then
echo "Source branch '${SOURCE_BRANCH}' no longer exists on origin; nothing to delete."
exit 0
fi
if [[ "${current_tip}" != "${SOURCE_COMMIT}" ]]; then
echo "::warning::Source branch '${SOURCE_BRANCH}' tip (${current_tip}) no longer matches released commit (${SOURCE_COMMIT}). Leaving it in place."
exit 0
fi
git push origin --delete "refs/heads/${SOURCE_BRANCH}"
echo "Deleted remote branch '${SOURCE_BRANCH}'."
- name: Summary
if: always()
env:
NEW_VERSION: ${{ steps.latest.outputs.new_version }}
RELEASE_BRANCH: ${{ steps.latest.outputs.release_branch }}
LATEST_TAG: ${{ steps.latest.outputs.latest_tag }}
SOURCE_BRANCH: ${{ steps.resolve.outputs.source_branch }}
SOURCE_COMMIT: ${{ inputs.commit }}
run: |
# SOURCE_BRANCH is empty if the resolve step never produced an output
# (e.g. the workflow failed in or before that step). Show a placeholder
# in that case so the summary table still renders cleanly.
source_branch_display="${SOURCE_BRANCH:-(unresolved)}"
{
echo "## Backport release"
echo ""
echo "| Field | Value |"
echo "|---|---|"
echo "| Source commit | \`${SOURCE_COMMIT}\` |"
echo "| Source branch | \`${source_branch_display}\` |"
echo "| Previous stable | \`${LATEST_TAG}\` |"
echo "| New version | \`${NEW_VERSION}\` |"
echo "| Release branch | \`${RELEASE_BRANCH}\` |"
} >> "$GITHUB_STEP_SUMMARY"

View File

@ -17,7 +17,7 @@ jobs:
- name: Check for Windows line endings (CRLF)
run: |
# Get the list of changed files in the PR
CHANGED_FILES=$(git diff --name-only ${{ github.event.pull_request.base.sha }}..${{ github.event.pull_request.head.sha }} -- ':!.ci')
CHANGED_FILES=$(git diff --name-only ${{ github.event.pull_request.base.sha }}..${{ github.event.pull_request.head.sha }})
# Flag to track if CRLF is found
CRLF_FOUND=false

View File

@ -1,24 +0,0 @@
name: Detect Unreviewed Merge
# SOC 2 compliance — reusable workflow lives in Comfy-Org/github-workflows,
# tracking issues are filed in Comfy-Org/unreviewed-merges.
on:
push:
branches: [master]
concurrency:
group: detect-unreviewed-merge-${{ github.sha }}
cancel-in-progress: false
permissions:
contents: read
pull-requests: read
jobs:
detect:
uses: Comfy-Org/github-workflows/.github/workflows/detect-unreviewed-merge.yml@4d9cb6b87f953bb7cd69954280e1465fb9bd2040 # v1
with:
approval-mode: latest-per-reviewer
secrets:
UNREVIEWED_MERGES_TOKEN: ${{ secrets.UNREVIEWED_MERGES_TOKEN }}

View File

@ -20,7 +20,7 @@
[website-url]: https://www.comfy.org/
<!-- Workaround to display total user from https://github.com/badges/shields/issues/4500#issuecomment-2060079995 -->
[discord-shield]: https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Finvites%2Fcomfyorg%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&logo=discord&logoColor=white&label=Discord&color=green&suffix=%20total
[discord-url]: https://discord.com/invite/comfyorg
[discord-url]: https://www.comfy.org/discord
[twitter-shield]: https://img.shields.io/twitter/follow/ComfyUI
[twitter-url]: https://x.com/ComfyUI
@ -140,7 +140,7 @@ ComfyUI follows a weekly release cycle targeting Monday but this regularly chang
- Commits outside of the stable release tags may be very unstable and break many custom nodes.
- Serves as the foundation for the desktop release
2. **[Comfy Desktop](https://github.com/Comfy-Org/Comfy-Desktop)**
2. **[ComfyUI Desktop](https://github.com/Comfy-Org/desktop)**
- Builds a new release using the latest stable core version
3. **[ComfyUI Frontend](https://github.com/Comfy-Org/ComfyUI_frontend)**
@ -309,7 +309,7 @@ After this you should have everything installed and can proceed to running Comfy
#### Apple Mac silicon
You can install ComfyUI in Apple Mac silicon (M1, M2, M3 or M4) with any recent macOS version.
You can install ComfyUI in Apple Mac silicon (M1 or M2) with any recent macOS version.
1. Install pytorch nightly. For instructions, read the [Accelerated PyTorch training on Mac](https://developer.apple.com/metal/pytorch/) Apple Developer guide (make sure to install the latest pytorch nightly).
1. Follow the [ComfyUI manual installation](#manual-install-windows-linux) instructions for Windows and Linux.
@ -364,7 +364,7 @@ For models compatible with Iluvatar Extension for PyTorch. Here's a step-by-step
| Flag | Description |
|------|-------------|
| `--enable-manager` | Enable ComfyUI-Manager |
| `--enable-manager-legacy-ui` | Use the legacy manager UI instead of the new UI (implies `--enable-manager`) |
| `--enable-manager-legacy-ui` | Use the legacy manager UI instead of the new UI (requires `--enable-manager`) |
| `--disable-manager-ui` | Disable the manager UI and endpoints while keeping background features like security checks and scheduled installation completion (requires `--enable-manager`) |
@ -382,7 +382,11 @@ For AMD 7600 and maybe other RDNA3 cards: ```HSA_OVERRIDE_GFX_VERSION=11.0.0 pyt
### AMD ROCm Tips
You can try setting this env variable `PYTORCH_TUNABLEOP_ENABLED=1` which might speed things up at the cost of a very slow initial run.
You can enable experimental memory efficient attention on recent pytorch in ComfyUI on some AMD GPUs using this command, it should already be enabled by default on RDNA3. If this improves speed for you on latest pytorch on your GPU please report it so that I can enable it by default.
```TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL=1 python main.py --use-pytorch-cross-attention```
You can also try setting this env variable `PYTORCH_TUNABLEOP_ENABLED=1` which might speed things up at the cost of a very slow initial run.
# Notes
@ -429,7 +433,7 @@ See also: [https://www.comfy.org/](https://www.comfy.org/)
## Frontend Development
As of August 15, 2024, we have transitioned to a new frontend, which is now hosted in a separate repository: [ComfyUI Frontend](https://github.com/Comfy-Org/ComfyUI_frontend). The compiled JS files (from TS/Vue) are published to [pypi](https://pypi.org/project/comfyui-frontend-package) and installed as a dependency in ComfyUI.
As of August 15, 2024, we have transitioned to a new frontend, which is now hosted in a separate repository: [ComfyUI Frontend](https://github.com/Comfy-Org/ComfyUI_frontend). This repository now hosts the compiled JS (from TS/Vue) under the `web/` directory.
### Reporting Issues and Requesting Features
@ -458,6 +462,16 @@ To use the most up-to-date frontend version:
This approach allows you to easily switch between the stable fortnightly release and the cutting-edge daily updates, or even specific versions for testing purposes.
### Accessing the Legacy Frontend
If you need to use the legacy frontend for any reason, you can access it using the following command line argument:
```
--front-end-version Comfy-Org/ComfyUI_legacy_frontend@latest
```
This will use a snapshot of the legacy frontend preserved in the [ComfyUI Legacy Frontend repository](https://github.com/Comfy-Org/ComfyUI_legacy_frontend).
# QA
### Which GPU should I buy for this?

View File

@ -1,39 +0,0 @@
"""
Drop the vestigial tags.tag_type column.
tag_type was always "user" in practice — no code path ever set it to anything
else (no system/seeded classification was ever wired up) and nothing queried it.
The column, its index (ix_tags_tag_type), and the corresponding API field were
dead weight, so they are removed.
Revision ID: 0004_drop_tag_type
Revises: 0003_add_metadata_job_id
Create Date: 2026-06-03
"""
from alembic import op
import sqlalchemy as sa
revision = "0004_drop_tag_type"
down_revision = "0003_add_metadata_job_id"
branch_labels = None
depends_on = None
def upgrade() -> None:
with op.batch_alter_table("tags") as batch_op:
batch_op.drop_index("ix_tags_tag_type")
batch_op.drop_column("tag_type")
def downgrade() -> None:
with op.batch_alter_table("tags") as batch_op:
batch_op.add_column(
sa.Column(
"tag_type",
sa.String(length=32),
nullable=False,
server_default="user",
)
)
batch_op.create_index("ix_tags_tag_type", ["tag_type"])

View File

@ -1,118 +0,0 @@
"""
Download manager schema.
Adds the three tables that back the server-side model download manager
(PRD section 7): transient job/queue state (``downloads`` + per-segment
``download_segments``) and one-API-key-per-host auth (``host_credentials``).
The local file catalog / dedup index is intentionally NOT added here — it
is owned by the assets system (``assets`` / ``asset_references``).
Revision ID: 0005_download_manager
Revises: 0004_drop_tag_type
Create Date: 2026-06-27
"""
from alembic import op
import sqlalchemy as sa
revision = "0005_download_manager"
down_revision = "0004_drop_tag_type"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"downloads",
sa.Column("id", sa.String(length=36), primary_key=True),
sa.Column("url", sa.Text(), nullable=False),
sa.Column("final_url", sa.Text(), nullable=True),
sa.Column("model_id", sa.String(length=1024), nullable=False),
sa.Column("dest_path", sa.Text(), nullable=False),
sa.Column("temp_path", sa.Text(), nullable=False),
sa.Column("status", sa.String(length=16), nullable=False),
sa.Column("priority", sa.Integer(), nullable=False, server_default="0"),
sa.Column("total_bytes", sa.BigInteger(), nullable=True),
sa.Column("bytes_done", sa.BigInteger(), nullable=False, server_default="0"),
sa.Column("etag", sa.String(length=512), nullable=True),
sa.Column("last_modified", sa.String(length=128), nullable=True),
sa.Column(
"accept_ranges", sa.Boolean(), nullable=False, server_default=sa.text("false")
),
sa.Column("expected_sha256", sa.String(length=64), nullable=True),
sa.Column("credential_id", sa.String(length=36), nullable=True),
sa.Column(
"allow_any_extension",
sa.Boolean(),
nullable=False,
server_default=sa.text("false"),
),
sa.Column("attempts", sa.Integer(), nullable=False, server_default="0"),
sa.Column("error", sa.Text(), nullable=True),
sa.Column("created_at", sa.BigInteger(), nullable=False),
sa.Column("updated_at", sa.BigInteger(), nullable=False),
sa.CheckConstraint("bytes_done >= 0", name="ck_downloads_bytes_done_nonneg"),
sa.CheckConstraint(
"total_bytes IS NULL OR total_bytes >= 0",
name="ck_downloads_total_bytes_nonneg",
),
)
op.create_index("ix_downloads_status", "downloads", ["status"])
op.create_index("ix_downloads_priority", "downloads", ["priority"])
op.create_index("ix_downloads_model_id", "downloads", ["model_id"])
op.create_table(
"download_segments",
sa.Column(
"download_id",
sa.String(length=36),
sa.ForeignKey("downloads.id", ondelete="CASCADE"),
nullable=False,
),
sa.Column("idx", sa.Integer(), nullable=False),
sa.Column("start_offset", sa.BigInteger(), nullable=False),
sa.Column("end_offset", sa.BigInteger(), nullable=False),
sa.Column("bytes_done", sa.BigInteger(), nullable=False, server_default="0"),
sa.PrimaryKeyConstraint("download_id", "idx", name="pk_download_segments"),
sa.CheckConstraint("bytes_done >= 0", name="ck_segments_bytes_done_nonneg"),
sa.CheckConstraint("end_offset >= start_offset", name="ck_segments_range"),
)
op.create_table(
"host_credentials",
sa.Column("id", sa.String(length=36), primary_key=True),
sa.Column("host", sa.String(length=255), nullable=False),
sa.Column(
"match_subdomains",
sa.Boolean(),
nullable=False,
server_default=sa.text("false"),
),
sa.Column("label", sa.String(length=255), nullable=True),
sa.Column(
"auth_scheme", sa.String(length=16), nullable=False, server_default="bearer"
),
sa.Column("header_name", sa.String(length=255), nullable=True),
sa.Column("query_param", sa.String(length=255), nullable=True),
sa.Column("secret", sa.Text(), nullable=False),
sa.Column("secret_last4", sa.String(length=4), nullable=True),
sa.Column("enabled", sa.Boolean(), nullable=False, server_default=sa.text("true")),
sa.Column("created_at", sa.BigInteger(), nullable=False),
sa.Column("updated_at", sa.BigInteger(), nullable=False),
)
op.create_index(
"uq_host_credentials_host", "host_credentials", ["host"], unique=True
)
def downgrade() -> None:
op.drop_index("uq_host_credentials_host", table_name="host_credentials")
op.drop_table("host_credentials")
op.drop_table("download_segments")
op.drop_index("ix_downloads_model_id", table_name="downloads")
op.drop_index("ix_downloads_priority", table_name="downloads")
op.drop_index("ix_downloads_status", table_name="downloads")
op.drop_table("downloads")

View File

@ -39,7 +39,6 @@ from app.assets.services import (
update_asset_metadata,
upload_from_temp_path,
)
from app.assets.services.cursor import InvalidCursorError
from app.assets.services.tagging import list_tag_histogram
ROUTES = web.RouteTableDef()
@ -161,12 +160,10 @@ def _build_asset_response(result: schemas.AssetDetailResult | schemas.UploadResu
preview_url = None
else:
preview_url = _build_preview_url_from_view(result.tags, result.ref.user_metadata)
asset_content_hash = result.asset.hash if result.asset else None
return schemas_out.Asset(
id=result.ref.id,
name=result.ref.name,
hash=asset_content_hash,
asset_hash=asset_content_hash,
asset_hash=result.asset.hash if result.asset else None,
size=int(result.asset.size_bytes) if result.asset else None,
mime_type=result.asset.mime_type if result.asset else None,
tags=result.tags,
@ -175,7 +172,7 @@ def _build_asset_response(result: schemas.AssetDetailResult | schemas.UploadResu
user_metadata=result.ref.user_metadata or {},
metadata=result.ref.system_metadata,
job_id=result.ref.job_id,
prompt_id=result.ref.job_id, # deprecated alias of job_id, kept for compatibility
prompt_id=result.ref.job_id, # deprecated: mirrors job_id for cloud compat
created_at=result.ref.created_at,
updated_at=result.ref.updated_at,
last_access_time=result.ref.last_access_time,
@ -212,37 +209,24 @@ async def list_assets_route(request: web.Request) -> web.Response:
order_candidate = (q.order or "desc").lower()
order = order_candidate if order_candidate in {"asc", "desc"} else "desc"
try:
result = list_assets_page(
owner_id=USER_MANAGER.get_request_user_id(request),
include_tags=q.include_tags,
exclude_tags=q.exclude_tags,
name_contains=q.name_contains,
metadata_filter=q.metadata_filter,
limit=q.limit,
offset=q.offset,
sort=sort,
order=order,
after=q.after,
)
except InvalidCursorError as e:
return _build_error_response(400, "INVALID_CURSOR", str(e))
result = list_assets_page(
owner_id=USER_MANAGER.get_request_user_id(request),
include_tags=q.include_tags,
exclude_tags=q.exclude_tags,
name_contains=q.name_contains,
metadata_filter=q.metadata_filter,
limit=q.limit,
offset=q.offset,
sort=sort,
order=order,
)
summaries = [_build_asset_response(item) for item in result.items]
# has_more semantics differ by mode:
# - cursor mode: a non-empty next_cursor means there are more results.
# - offset mode: derived from total - (offset + page size).
if q.after is not None:
has_more = result.next_cursor is not None
else:
has_more = (q.offset + len(summaries)) < result.total
payload = schemas_out.AssetsList(
assets=summaries,
total=result.total,
has_more=has_more,
next_cursor=result.next_cursor,
has_more=(q.offset + len(summaries)) < result.total,
)
return web.json_response(payload.model_dump(mode="json", exclude_none=True))
@ -533,14 +517,18 @@ async def update_asset_route(request: web.Request) -> web.Response:
@_require_assets_feature_enabled
async def delete_asset_route(request: web.Request) -> web.Response:
reference_id = str(uuid.UUID(request.match_info["id"]))
delete_content_param = request.query.get("delete_content")
delete_content = (
False
if delete_content_param is None
else delete_content_param.lower() not in {"0", "false", "no"}
)
try:
# Deleting an asset is a soft delete of the reference; the underlying
# content is preserved (it may be shared with other references).
deleted = delete_asset_reference(
reference_id=reference_id,
owner_id=USER_MANAGER.get_request_user_id(request),
delete_content_if_orphan=False,
delete_content_if_orphan=delete_content,
)
except Exception:
logging.exception(
@ -585,8 +573,8 @@ async def get_tags(request: web.Request) -> web.Response:
)
tags = [
schemas_out.TagUsage(name=name, count=count)
for (name, count) in rows
schemas_out.TagUsage(name=name, count=count, type=tag_type)
for (name, tag_type, count) in rows
]
payload = schemas_out.TagsList(
tags=tags, total=total, has_more=(query.offset + len(tags)) < total

View File

@ -59,11 +59,6 @@ class ListAssetsQuery(BaseModel):
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"

View File

@ -10,7 +10,6 @@ class Asset(BaseModel):
id: str
name: str
hash: str | None = None
asset_hash: str | None = None
size: int | None = None
mime_type: str | None = None
@ -41,13 +40,12 @@ class AssetsList(BaseModel):
assets: list[Asset]
total: int
has_more: bool
# Opaque cursor for the next page. Omitted when there are no more results.
next_cursor: str | None = None
class TagUsage(BaseModel):
name: str
count: int
type: str
class TagsList(BaseModel):

View File

@ -227,6 +227,7 @@ class Tag(Base):
__tablename__ = "tags"
name: Mapped[str] = mapped_column(String(512), primary_key=True)
tag_type: Mapped[str] = mapped_column(String(32), nullable=False, default="user")
asset_reference_links: Mapped[list[AssetReferenceTag]] = relationship(
back_populates="tag",
@ -239,5 +240,7 @@ class Tag(Base):
overlaps="asset_reference_links,tag_links,tags,asset_reference",
)
__table_args__ = (Index("ix_tags_tag_type", "tag_type"),)
def __repr__(self) -> str:
return f"<Tag {self.name}>"

View File

@ -266,18 +266,9 @@ def list_references_page(
metadata_filter: dict | None = None,
sort: str | None = None,
order: str | None = None,
after_cursor_value: object | None = None,
after_cursor_id: str | None = None,
) -> tuple[list[AssetReference], dict[str, list[str]], int]:
"""List references with pagination, filtering, and sorting.
When ``after_cursor_value``/``after_cursor_id`` are supplied the query uses
keyset pagination — ``offset`` is ignored and a WHERE clause selects rows
strictly after the given ``(sort_col, id)`` position in the active sort
direction. The cursor value must already be typed for the column
(datetime for time sorts, int for size, str for name); the caller decodes
the opaque cursor string and resolves to the typed value.
Returns (references, tag_map, total_count).
"""
base = (
@ -306,31 +297,9 @@ def list_references_page(
"size": Asset.size_bytes,
}
sort_col = sort_map.get(sort, AssetReference.created_at)
descending = order == "desc"
sort_exp = sort_col.desc() if order == "desc" else sort_col.asc()
# Keyset WHERE: (sort_col, id) strictly less-than / greater-than the cursor.
# Equivalent to: sort_col <op> v OR (sort_col = v AND id <op> cursor_id).
if after_cursor_value is not None and after_cursor_id is not None:
if descending:
keyset = sa.or_(
sort_col < after_cursor_value,
sa.and_(sort_col == after_cursor_value, AssetReference.id < after_cursor_id),
)
else:
keyset = sa.or_(
sort_col > after_cursor_value,
sa.and_(sort_col == after_cursor_value, AssetReference.id > after_cursor_id),
)
base = base.where(keyset)
# Secondary ORDER BY id (matching the primary direction) gives the keyset
# comparison a deterministic tiebreaker on duplicate sort_col values.
id_exp = AssetReference.id.desc() if descending else AssetReference.id.asc()
sort_exp = sort_col.desc() if descending else sort_col.asc()
base = base.order_by(sort_exp, id_exp).limit(limit)
if after_cursor_id is None:
base = base.offset(offset)
base = base.order_by(sort_exp).limit(limit).offset(offset)
count_stmt = (
select(sa.func.count())

View File

@ -55,11 +55,13 @@ def validate_tags_exist(session: Session, tags: list[str]) -> None:
raise ValueError(f"Unknown tags: {missing}")
def ensure_tags_exist(session: Session, names: Iterable[str]) -> None:
def ensure_tags_exist(
session: Session, names: Iterable[str], tag_type: str = "user"
) -> None:
wanted = normalize_tags(list(names))
if not wanted:
return
rows = [{"name": n} for n in list(dict.fromkeys(wanted))]
rows = [{"name": n, "tag_type": tag_type} for n in list(dict.fromkeys(wanted))]
ins = (
sqlite.insert(Tag)
.values(rows)
@ -95,7 +97,7 @@ def set_reference_tags(
to_remove = [t for t in current if t not in desired]
if to_add:
ensure_tags_exist(session, to_add)
ensure_tags_exist(session, to_add, tag_type="user")
session.add_all(
[
AssetReferenceTag(
@ -140,7 +142,7 @@ def add_tags_to_reference(
return AddTagsResult(added=[], already_present=[], total_tags=total)
if create_if_missing:
ensure_tags_exist(session, norm)
ensure_tags_exist(session, norm, tag_type="user")
current = set(get_reference_tags(session, reference_id))
@ -287,6 +289,7 @@ def list_tags_with_usage(
q = (
select(
Tag.name,
Tag.tag_type,
func.coalesce(counts_sq.c.cnt, 0).label("count"),
)
.select_from(Tag)
@ -328,7 +331,7 @@ def list_tags_with_usage(
rows = (session.execute(q.limit(limit).offset(offset))).all()
total = (session.execute(total_q)).scalar_one()
rows_norm = [(name, int(count or 0)) for (name, count) in rows]
rows_norm = [(name, ttype, int(count or 0)) for (name, ttype, count) in rows]
return rows_norm, int(total or 0)

View File

@ -33,7 +33,6 @@ from app.assets.services.file_utils import (
verify_file_unchanged,
)
from app.assets.services.hashing import HashCheckpoint, compute_blake3_hash
from app.assets.services.image_dimensions import extract_image_dimensions
from app.assets.services.metadata_extract import extract_file_metadata
from app.assets.services.path_utils import (
compute_relative_filename,
@ -355,7 +354,7 @@ def insert_asset_specs(specs: list[SeedAssetSpec], tag_pool: set[str]) -> int:
return 0
with create_session() as sess:
if tag_pool:
ensure_tags_exist(sess, tag_pool)
ensure_tags_exist(sess, tag_pool, tag_type="user")
result = batch_insert_seed_assets(sess, specs=specs, owner_id="")
sess.commit()
return result.inserted_refs
@ -507,10 +506,6 @@ def enrich_asset(
if extract_metadata and metadata:
system_metadata = metadata.to_user_metadata()
if mime_type and mime_type.startswith("image/"):
dims = extract_image_dimensions(file_path, mime_type=mime_type)
if dims:
system_metadata.update(dims)
set_reference_system_metadata(session, reference_id, system_metadata)
if full_hash:

View File

@ -1,19 +1,8 @@
import contextlib
import mimetypes
import os
from datetime import timezone
from typing import Sequence
from app.assets.services.cursor import (
CursorPayload,
InvalidCursorError,
decode_cursor,
decode_cursor_int,
decode_cursor_time,
encode_cursor,
encode_cursor_from_time,
)
from app.assets.database.models import Asset
from app.assets.database.queries import (
@ -160,16 +149,6 @@ def delete_asset_reference(
owner_id: str,
delete_content_if_orphan: bool = True,
) -> bool:
"""Delete an asset reference.
With ``delete_content_if_orphan=False`` (a soft delete), the reference is
hidden and the underlying content is preserved. With ``True``, the content
is also removed once it becomes orphaned.
Note: the public DELETE /api/assets/{id} endpoint always soft-deletes
(passes ``False``); the orphan-reclamation path is intentionally
internal-only, retained for a future GC/admin caller.
"""
with create_session() as session:
if not delete_content_if_orphan:
# Soft delete: mark the reference as deleted but keep everything
@ -263,11 +242,6 @@ def get_asset_by_hash(asset_hash: str) -> AssetData | None:
return extract_asset_data(asset)
# Sort fields that support cursor pagination. `last_access_time` is not
# in this list — it falls back to offset/limit.
_CURSOR_SORT_FIELDS = ("created_at", "updated_at", "name", "size")
def list_assets_page(
owner_id: str = "",
include_tags: Sequence[str] | None = None,
@ -278,39 +252,7 @@ def list_assets_page(
offset: int = 0,
sort: str = "created_at",
order: str = "desc",
after: str | None = None,
) -> ListAssetsResult:
"""List assets with optional cursor pagination.
When ``after`` is supplied it overrides ``offset``. The cursor's sort field
must match ``sort`` and be in the cursor-supported allowlist; mismatches
raise InvalidCursorError so the handler can map to 400 INVALID_CURSOR.
"""
cursor_value: object | None = None
cursor_id: str | None = None
# Mint next_cursor on every page where the sort is cursor-supported, not
# only when the request itself arrived with a cursor. Otherwise a first
# request (no `after`) returns next_cursor=None and the client can never
# enter cursor mode.
mint_cursor = sort in _CURSOR_SORT_FIELDS
if after is not None:
if sort not in _CURSOR_SORT_FIELDS:
raise InvalidCursorError(
f"cursor pagination is not supported for sort={sort!r}"
)
payload = decode_cursor(after, _CURSOR_SORT_FIELDS, expected_order=order)
if payload.sort_field != sort:
raise InvalidCursorError(
f"cursor sort field {payload.sort_field!r} does not match request sort {sort!r}"
)
cursor_value, cursor_id = _resolve_cursor_value(payload), payload.id
# Over-fetch by one row so we can distinguish "exactly `limit` rows total
# remaining" from "more rows past this page" without a second query. Drop
# the sentinel before returning.
fetch_limit = limit + 1 if mint_cursor else limit
with create_session() as session:
refs, tag_map, total = list_references_page(
session,
@ -319,22 +261,12 @@ def list_assets_page(
exclude_tags=exclude_tags,
name_contains=name_contains,
metadata_filter=metadata_filter,
limit=fetch_limit,
limit=limit,
offset=offset,
sort=sort,
order=order,
after_cursor_value=cursor_value,
after_cursor_id=cursor_id,
)
next_cursor: str | None = None
if mint_cursor and len(refs) > limit:
# There's at least one more row past this page — mint a cursor from
# the last row of the page (i.e. index `limit - 1`, since we
# over-fetched), and drop the sentinel.
next_cursor = _encode_next_cursor(refs[limit - 1], sort, order)
refs = refs[:limit]
items: list[AssetSummaryData] = []
for ref in refs:
items.append(
@ -345,39 +277,7 @@ def list_assets_page(
)
)
return ListAssetsResult(items=items, total=total, next_cursor=next_cursor)
def _resolve_cursor_value(payload: CursorPayload) -> object:
"""Map a decoded cursor payload to a column-typed Python value."""
if payload.sort_field in ("created_at", "updated_at"):
# DB stores naive UTC; strip tzinfo so the comparison binds against a
# `TIMESTAMP WITHOUT TIME ZONE` column without an offset shift.
return decode_cursor_time(payload).replace(tzinfo=None)
if payload.sort_field == "size":
return decode_cursor_int(payload)
return payload.value # name, str-typed
def _encode_next_cursor(ref, sort: str, order: str) -> str | None:
"""Mint a cursor pointing at *ref* for the given sort dimension.
Returns None when the boundary row carries a NULL sort value (e.g. an asset
record whose size_bytes hasn't been backfilled). Continuing pagination
across a NULL boundary is undefined under keyset ordering — better to
truncate cleanly here than to mint a cursor that mis-positions.
"""
if sort == "name":
return encode_cursor("name", ref.name, ref.id, order=order)
if sort == "size":
if ref.asset is None or ref.asset.size_bytes is None:
return None
return encode_cursor("size", str(ref.asset.size_bytes), ref.id, order=order)
# created_at / updated_at — DB datetimes are naive UTC; attach tz before encoding.
value = ref.created_at if sort == "created_at" else ref.updated_at
if value is None:
return None
return encode_cursor_from_time(sort, value.replace(tzinfo=timezone.utc), ref.id, order=order)
return ListAssetsResult(items=items, total=total)
def resolve_hash_to_path(

View File

@ -1,213 +0,0 @@
"""Opaque keyset-pagination cursor for /api/assets.
Payload JSON uses short keys to keep the encoded length small:
{"s": <sort_field>, "v": <value>, "id": <id>, "o": <order>}
The `o` key binds the cursor to the sort direction it was minted under,
so replaying a `desc` cursor against an `asc` request fails with
``INVALID_CURSOR`` rather than silently walking the wrong direction.
`o` is mandatory on every payload — a cursor without it is rejected as
malformed.
Encoding is base64url with no padding. Cursors are opaque tokens: the
payload format is internal to this server, and clients must treat a
cursor as a black box handed back via `next_cursor`. No byte-level
compatibility with any other implementation is required.
Time values are serialized as Unix microseconds (UTC) — microsecond
precision is sufficient to round-trip the timestamps stored by the
database without rounding rows in the same millisecond bucket.
"""
from __future__ import annotations
import base64
import json
from dataclasses import dataclass
from datetime import datetime, timezone
from typing import Iterable, Optional
class InvalidCursorError(ValueError):
"""Raised on a malformed, oversized, or unsupported-sort-field cursor.
Map to a 400 response with code ``INVALID_CURSOR`` at the handler.
"""
# Wire-format length caps. Cursors are user-controlled, so caps protect the
# decode path from oversized allocations and downstream SQL predicates from
# unbounded strings.
#
# MAX_CURSOR_VALUE_LENGTH is 512 to fit the `AssetReference.name` column max
# (`String(512)`) — otherwise a long-named asset would mint a cursor the same
# server then refuses on the next request.
#
# MAX_ENCODED_CURSOR_LENGTH is the decode-path guard, sized comfortably above
# the largest cursor the per-field caps can produce. Worst case is value + id
# at their caps with every character JSON-escaping to the six-byte `\uXXXX`
# form (control characters), which is ~5.2 KB once base64url-encoded. At 8192
# the encoder can never mint a cursor that exceeds it, so a freshly minted
# cursor always decodes on the next request and there is no user-visible
# "cursor too long" failure.
MAX_ENCODED_CURSOR_LENGTH = 8192
MAX_CURSOR_VALUE_LENGTH = 512
MAX_CURSOR_ID_LENGTH = 128
@dataclass(frozen=True)
class CursorPayload:
sort_field: str
value: str
id: str
order: str
_VALID_ORDERS = ("asc", "desc")
def encode_cursor(sort_field: str, value: str, id: str, order: str = "desc") -> str:
"""Encode a cursor payload as a base64url (no-padding) string.
`order` binds the cursor to the sort direction it was minted under so a
later request with a flipped `order` query parameter is rejected with
``INVALID_CURSOR`` rather than silently walking the wrong direction.
"""
if order not in _VALID_ORDERS:
raise InvalidCursorError(f"order must be one of {_VALID_ORDERS}, got {order!r}")
# Symmetric input validation: the encoder must reject anything the
# decoder rejects, or the same server will mint cursors it then 400s on
# the next request.
if not id:
raise InvalidCursorError("id must be non-empty")
if len(id) > MAX_CURSOR_ID_LENGTH:
raise InvalidCursorError("id exceeds maximum length")
if len(value) > MAX_CURSOR_VALUE_LENGTH:
raise InvalidCursorError("value exceeds maximum length")
payload = {"s": sort_field, "v": value, "id": id, "o": order}
raw = json.dumps(payload, separators=(",", ":"), ensure_ascii=False)
# No mint-time length guard is needed: the per-field caps above bound the
# encoded length well below MAX_ENCODED_CURSOR_LENGTH (see its definition),
# so the encoder can never produce a cursor the decode path would reject.
return base64.urlsafe_b64encode(raw.encode("utf-8")).rstrip(b"=").decode("ascii")
def encode_cursor_from_time(sort_field: str, t: datetime, id: str, order: str = "desc") -> str:
"""Encode a time-typed cursor at Unix microsecond precision.
Accepts an aware datetime (any timezone) and normalizes to UTC. Naive
datetimes are rejected so callers can't accidentally encode the local
wall-clock value of a UTC-stored timestamp.
"""
if t.tzinfo is None:
raise ValueError("encode_cursor_from_time requires an aware datetime")
micros = _datetime_to_unix_micros(t.astimezone(timezone.utc))
return encode_cursor(sort_field, str(micros), id, order=order)
def decode_cursor(
cursor: str,
allowed_sort_fields: Iterable[str],
expected_order: str | None = None,
) -> CursorPayload:
"""Parse an opaque cursor.
``allowed_sort_fields`` is the endpoint's accepted sort-field list — a
cursor carrying a field outside this set is rejected so a cursor minted
for one column can't be replayed against another (e.g. a ``created_at``
timestamp string compared against a ``name`` column).
``expected_order`` (``"asc"``/``"desc"``), when supplied, must match the
payload's ``o`` field. ``o`` is required on every payload; a cursor
missing it is rejected as malformed.
Passing no allowed fields rejects every cursor.
"""
if len(cursor) > MAX_ENCODED_CURSOR_LENGTH:
raise InvalidCursorError("cursor exceeds maximum length")
try:
# urlsafe_b64decode requires correct padding; we strip on encode, so
# restore the trailing '=' pad here.
padding = "=" * (-len(cursor) % 4)
raw = base64.urlsafe_b64decode(cursor + padding)
except (ValueError, base64.binascii.Error) as e:
raise InvalidCursorError(f"encoding: {e}") from e
try:
decoded = json.loads(raw)
except (json.JSONDecodeError, UnicodeDecodeError) as e:
raise InvalidCursorError(f"payload: {e}") from e
if not isinstance(decoded, dict):
raise InvalidCursorError("payload: expected object")
sort_field = decoded.get("s")
value = decoded.get("v")
id = decoded.get("id")
order = decoded.get("o")
if not isinstance(sort_field, str) or not isinstance(value, str) or not isinstance(id, str):
raise InvalidCursorError("payload: missing or non-string s/v/id")
if id == "":
raise InvalidCursorError("missing id")
if len(id) > MAX_CURSOR_ID_LENGTH:
raise InvalidCursorError("id exceeds maximum length")
if len(value) > MAX_CURSOR_VALUE_LENGTH:
raise InvalidCursorError("value exceeds maximum length")
if sort_field not in allowed_sort_fields:
raise InvalidCursorError(f"unsupported sort field {sort_field!r}")
if not isinstance(order, str):
raise InvalidCursorError("missing or non-string o")
if order not in _VALID_ORDERS:
raise InvalidCursorError(f"unsupported order {order!r}")
if expected_order is not None and order != expected_order:
raise InvalidCursorError(
f"cursor order {order!r} does not match request order {expected_order!r}"
)
return CursorPayload(sort_field=sort_field, value=value, id=id, order=order)
def decode_cursor_time(payload: Optional[CursorPayload]) -> datetime:
"""Parse a time-typed cursor value as Unix microseconds, returning UTC."""
if payload is None:
raise InvalidCursorError("nil cursor payload")
try:
micros = int(payload.value)
except ValueError as e:
raise InvalidCursorError(f"value is not a valid timestamp: {e}") from e
try:
return _unix_micros_to_datetime(micros)
except (OverflowError, OSError, ValueError) as e:
# Crafted out-of-range microseconds (e.g. > datetime.MAX_YEAR) blow up
# in fromtimestamp / datetime construction. Map to 400, not 500.
raise InvalidCursorError(f"value is out of representable range: {e}") from e
def decode_cursor_int(payload: Optional[CursorPayload]) -> int:
"""Parse a cursor value as a base-10 integer."""
if payload is None:
raise InvalidCursorError("nil cursor payload")
try:
return int(payload.value)
except ValueError as e:
raise InvalidCursorError(f"value is not a valid integer: {e}") from e
_EPOCH = datetime(1970, 1, 1, tzinfo=timezone.utc)
def _datetime_to_unix_micros(t: datetime) -> int:
"""Convert an aware UTC datetime to Unix microseconds (integer math)."""
delta = t - _EPOCH
return (delta.days * 86_400 + delta.seconds) * 1_000_000 + delta.microseconds
def _unix_micros_to_datetime(micros: int) -> datetime:
"""Convert Unix microseconds to a UTC datetime, preserving precision."""
seconds, micro_remainder = divmod(micros, 1_000_000)
return datetime.fromtimestamp(seconds, tz=timezone.utc).replace(microsecond=micro_remainder)

View File

@ -1,63 +0,0 @@
"""Image dimension extraction for asset ingest.
Reads only the image header via Pillow to capture width/height cheaply,
without a full pixel decode. Returns a metadata dict suitable for merging
into ``AssetReference.system_metadata``.
"""
from __future__ import annotations
import logging
from typing import Any
logger = logging.getLogger(__name__)
def extract_image_dimensions(
file_path: str, mime_type: str | None = None
) -> dict[str, Any] | None:
"""Extract image dimensions for the file at ``file_path``.
Args:
file_path: Absolute path to a file on disk.
mime_type: Optional MIME type hint. When provided and not prefixed
with ``image/``, extraction is skipped without touching the file.
Returns:
``{"kind": "image", "width": W, "height": H}`` when the file is a
recognizable image with positive dimensions, otherwise ``None``.
The dict shape is intended to be merged into ``system_metadata`` so the
asset response surfaces ``metadata.kind`` plus dimension fields for image
assets. Forward-compatible: future media kinds (e.g. ``"video"`` with
duration/fps) can extend this shape without schema changes.
"""
if mime_type is not None and not mime_type.startswith("image/"):
return None
try:
from PIL import Image, UnidentifiedImageError
except ImportError:
logger.debug(
"Pillow not available; skipping image dimension extraction for %s",
file_path,
)
return None
try:
with Image.open(file_path) as img:
width, height = img.size
except (OSError, UnidentifiedImageError, ValueError) as exc:
logger.debug(
"Failed to read image dimensions from %s: %s", file_path, exc
)
return None
if (
not isinstance(width, int)
or not isinstance(height, int)
or width <= 0
or height <= 0
):
return None
return {"kind": "image", "width": width, "height": height}

View File

@ -17,11 +17,9 @@ from app.assets.database.queries import (
get_reference_by_file_path,
get_reference_tags,
get_or_create_reference,
list_references_by_asset_id,
reference_exists,
remove_missing_tag_for_asset_id,
set_reference_metadata,
set_reference_system_metadata,
set_reference_tags,
update_asset_hash_and_mime,
upsert_asset,
@ -31,7 +29,6 @@ from app.assets.database.queries import (
from app.assets.helpers import get_utc_now, normalize_tags
from app.assets.services.bulk_ingest import batch_insert_seed_assets
from app.assets.services.file_utils import get_size_and_mtime_ns
from app.assets.services.image_dimensions import extract_image_dimensions
from app.assets.services.path_utils import (
compute_relative_filename,
get_name_and_tags_from_asset_path,
@ -121,14 +118,6 @@ def _ingest_file_from_path(
user_metadata=user_metadata,
)
_maybe_store_image_dimensions(
session,
reference_id=reference_id,
file_path=locator,
mime_type=mime_type,
current_system_metadata=ref.system_metadata,
)
try:
remove_missing_tag_for_asset_id(session, asset_id=asset.id)
except Exception:
@ -299,13 +288,6 @@ def _register_existing_asset(
user_metadata=new_meta,
)
_backfill_image_dimensions_from_siblings(
session,
asset_id=asset.id,
new_reference_id=ref.id,
current_system_metadata=ref.system_metadata,
)
if tags is not None:
set_reference_tags(
session,
@ -352,87 +334,6 @@ def _update_metadata_with_filename(
)
_IMAGE_DIMENSION_KEYS = ("kind", "width", "height")
def _maybe_store_image_dimensions(
session: Session,
reference_id: str,
file_path: str,
mime_type: str | None,
current_system_metadata: dict | None,
) -> None:
"""Populate ``kind``/``width``/``height`` on system_metadata for image refs.
Non-image MIME types are a no-op. Pre-existing keys (e.g. enricher-written
safetensors metadata, download provenance) are preserved by merge.
"""
if not mime_type or not mime_type.startswith("image/"):
return
dims = extract_image_dimensions(file_path, mime_type=mime_type)
if not dims:
return
current = current_system_metadata or {}
merged = dict(current)
merged.update(dims)
if merged != current:
set_reference_system_metadata(
session,
reference_id=reference_id,
system_metadata=merged,
)
def _backfill_image_dimensions_from_siblings(
session: Session,
asset_id: str,
new_reference_id: str,
current_system_metadata: dict | None,
) -> None:
"""Copy image dimension keys from any sibling reference of the same asset.
The from-hash path doesn't read the file bytes, so dimensions can't be
extracted there directly. When another reference of the same asset already
carries image dimensions, copy them onto the new reference so consumers
see consistent metadata regardless of how the asset was registered.
Best-effort: missing siblings, non-image siblings, or absent dimension
keys leave the target reference unchanged.
"""
current = current_system_metadata or {}
if current.get("kind") == "image" and "width" in current and "height" in current:
return
for sibling in list_references_by_asset_id(session, asset_id):
if sibling.id == new_reference_id:
continue
meta = sibling.system_metadata or {}
if meta.get("kind") != "image":
continue
width = meta.get("width")
height = meta.get("height")
if (
type(width) is not int
or type(height) is not int
or width <= 0
or height <= 0
):
continue
merged = dict(current)
merged["kind"] = "image"
merged["width"] = width
merged["height"] = height
if merged != current:
set_reference_system_metadata(
session,
reference_id=new_reference_id,
system_metadata=merged,
)
return
def _sanitize_filename(name: str | None, fallback: str) -> str:
n = os.path.basename((name or "").strip() or fallback)
return n if n else fallback

View File

@ -4,6 +4,7 @@ Tier 1: Filesystem metadata (zero parsing)
Tier 2: Safetensors header metadata (fast JSON read only)
"""
from __future__ import annotations
import json
import logging

View File

@ -56,6 +56,7 @@ class IngestResult:
class TagUsage(NamedTuple):
name: str
tag_type: str
count: int
@ -70,7 +71,6 @@ class AssetSummaryData:
class ListAssetsResult:
items: list[AssetSummaryData]
total: int
next_cursor: str | None = None
@dataclass(frozen=True)

View File

@ -75,7 +75,7 @@ def list_tags(
owner_id=owner_id,
)
return [TagUsage(name, count) for name, count in rows], total
return [TagUsage(name, tag_type, count) for name, tag_type, count in rows], total
def list_tag_histogram(

View File

@ -1,3 +1,5 @@
from __future__ import annotations
import os
import folder_paths
import glob

View File

@ -21,7 +21,6 @@ try:
from app.database.models import Base
import app.assets.database.models # noqa: F401 — register models with Base.metadata
import app.model_downloader.database.models # noqa: F401 — register models with Base.metadata
_DB_AVAILABLE = True
except ImportError as e:

View File

@ -1,3 +1,4 @@
from __future__ import annotations
import argparse
import logging
import os
@ -61,8 +62,6 @@ def get_comfy_package_versions():
def check_comfy_packages_versions():
"""Warn for every comfy* package whose installed version is below requirements.txt."""
from packaging.version import InvalidVersion, parse as parse_pep440
outdated_packages = []
for pkg in get_comfy_package_versions():
installed_str = pkg["installed"]
required_str = pkg["required"]
@ -74,26 +73,19 @@ def check_comfy_packages_versions():
logging.error(f"Failed to check {pkg['name']} version: {e}")
continue
if outdated:
outdated_packages.append((pkg["name"], installed_str, required_str))
else:
logging.info("{} version: {}".format(pkg["name"], installed_str))
if outdated_packages:
package_warnings = "\n".join(
f"Installed {name} version {installed} is lower than the recommended version {required}."
for name, installed, required in outdated_packages
)
app.logger.log_startup_warning(
f"""
app.logger.log_startup_warning(
f"""
________________________________________________________________________
WARNING WARNING WARNING WARNING WARNING
{package_warnings}
Installed {pkg["name"]} version {installed_str} is lower than the recommended version {required_str}.
{get_missing_requirements_message()}
________________________________________________________________________
""".strip()
)
)
else:
logging.info("{} version: {}".format(pkg["name"], installed_str))
REQUEST_TIMEOUT = 10 # seconds

View File

@ -5,40 +5,6 @@ import logging
import sys
import threading
ANSI_NAMED_COLORS = {
'black': '\033[30m',
'red': '\033[31m',
'green': '\033[32m',
'yellow': '\033[33m',
'blue': '\033[34m',
'magenta': '\033[35m',
'cyan': '\033[36m',
'white': '\033[37m',
}
ANSI_LEVEL_COLORS = {
'DEBUG': ANSI_NAMED_COLORS['cyan'],
'INFO': ANSI_NAMED_COLORS['green'],
'WARNING': ANSI_NAMED_COLORS['yellow'],
'ERROR': ANSI_NAMED_COLORS['red'],
'CRITICAL': ANSI_NAMED_COLORS['magenta'],
}
ANSI_RESET = '\033[0m'
ANSI_BOLD = '\033[1m'
class ColoredFormatter(logging.Formatter):
def format(self, record):
color = ANSI_LEVEL_COLORS.get(record.levelname, '')
bold = ANSI_BOLD if record.levelno >= logging.WARNING else ''
level_tag = f"{bold}{color}[{record.levelname}]{ANSI_RESET} "
message = super().format(record)
line_color = ANSI_NAMED_COLORS.get(getattr(record, 'color', ''), '')
if line_color:
return f"{level_tag}{line_color}{message}{ANSI_RESET}"
return level_tag + message
logs = None
stdout_interceptor = None
stderr_interceptor = None
@ -102,10 +68,8 @@ def setup_logger(log_level: str = 'INFO', capacity: int = 300, use_stdout: bool
logger = logging.getLogger()
logger.setLevel(log_level)
formatter = ColoredFormatter("%(message)s")
stream_handler = logging.StreamHandler()
stream_handler.setFormatter(formatter)
stream_handler.setFormatter(logging.Formatter("%(message)s"))
if use_stdout:
# Only errors and critical to stderr
@ -113,7 +77,7 @@ def setup_logger(log_level: str = 'INFO', capacity: int = 300, use_stdout: bool
# Lesser to stdout
stdout_handler = logging.StreamHandler(sys.stdout)
stdout_handler.setFormatter(formatter)
stdout_handler.setFormatter(logging.Formatter("%(message)s"))
stdout_handler.addFilter(lambda record: record.levelno < logging.ERROR)
logger.addHandler(stdout_handler)

View File

@ -1,203 +0,0 @@
"""aiohttp routes for the download manager.
Endpoint surface (all under ``/api/download``), mirroring the response
envelope used by ``app/assets/api/routes.py``:
POST /api/download/enqueue
GET /api/download
POST /api/download/availability
POST /api/download/credentials
GET /api/download/credentials
GET /api/download/credentials/{id}
DELETE /api/download/credentials/{id}
GET /api/download/{id}
POST /api/download/{id}/pause
POST /api/download/{id}/resume
POST /api/download/{id}/cancel
POST /api/download/{id}/priority
Note on ordering: the static ``credentials`` routes are registered before the
dynamic ``/api/download/{id}`` route so a request to ``.../credentials`` is not
captured as ``id == "credentials"``.
"""
from __future__ import annotations
import json
from aiohttp import web
from pydantic import BaseModel, ValidationError
from app.model_downloader.api import schemas_in, schemas_out
from app.model_downloader.credentials.store import (
CREDENTIAL_STORE,
CredentialValidationError,
)
from app.model_downloader.manager import DOWNLOAD_MANAGER, DownloadError
ROUTES = web.RouteTableDef()
def register_routes(app: web.Application) -> None:
"""Wire the download-manager routes into the running aiohttp app."""
app.add_routes(ROUTES)
# ----- envelope helpers (same shape as app/assets/api/routes.py) -----
def _error(status: int, code: str, message: str, details: dict | None = None) -> web.Response:
return web.json_response(
{"error": {"code": code, "message": message, "details": details or {}}},
status=status,
)
def _ok(payload, status: int = 200) -> web.Response:
return web.json_response(payload, status=status)
async def _parse(request: web.Request, model: type[BaseModel]):
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 _error(400, "INVALID_BODY", "Validation failed.", {"errors": json.loads(ve.json())})
def _from_download_error(e: DownloadError) -> web.Response:
return _error(e.http_status, e.code, e.message)
# ----- downloads: collection + enqueue + availability -----
@ROUTES.post("/api/download/enqueue")
async def enqueue(request: web.Request) -> web.Response:
parsed = await _parse(request, schemas_in.EnqueueRequest)
if isinstance(parsed, web.Response):
return parsed
try:
download_id = await DOWNLOAD_MANAGER.enqueue(
parsed.url,
parsed.model_id,
priority=parsed.priority,
expected_sha256=parsed.expected_sha256,
allow_any_extension=parsed.allow_any_extension,
credential_id=parsed.credential_id,
)
except DownloadError as e:
return _from_download_error(e)
return _ok({"download_id": download_id, "accepted": True}, status=202)
@ROUTES.get("/api/download")
async def list_downloads(request: web.Request) -> web.Response:
return _ok({"downloads": await DOWNLOAD_MANAGER.list()})
@ROUTES.post("/api/download/availability")
async def availability(request: web.Request) -> web.Response:
parsed = await _parse(request, schemas_in.AvailabilityRequest)
if isinstance(parsed, web.Response):
return parsed
return _ok({"models": await DOWNLOAD_MANAGER.availability(parsed.models)})
# ----- credentials (secrets are write-only) — must precede /{id} -----
@ROUTES.post("/api/download/credentials")
async def upsert_credential(request: web.Request) -> web.Response:
parsed = await _parse(request, schemas_in.CredentialUpsertRequest)
if isinstance(parsed, web.Response):
return parsed
try:
view = await CREDENTIAL_STORE.upsert(
parsed.host,
parsed.secret,
auth_scheme=parsed.auth_scheme,
header_name=parsed.header_name,
query_param=parsed.query_param,
label=parsed.label,
match_subdomains=parsed.match_subdomains,
enabled=parsed.enabled,
)
except CredentialValidationError as e:
return _error(400, "INVALID_CREDENTIAL", str(e))
return _ok(schemas_out.credential_to_dict(view), status=201)
@ROUTES.get("/api/download/credentials")
async def list_credentials(request: web.Request) -> web.Response:
views = await CREDENTIAL_STORE.list()
return _ok({"credentials": [schemas_out.credential_to_dict(v) for v in views]})
@ROUTES.get("/api/download/credentials/{id}")
async def get_credential(request: web.Request) -> web.Response:
view = await CREDENTIAL_STORE.get(request.match_info["id"])
if view is None:
return _error(404, "NOT_FOUND", "No such credential.")
return _ok(schemas_out.credential_to_dict(view))
@ROUTES.delete("/api/download/credentials/{id}")
async def delete_credential(request: web.Request) -> web.Response:
deleted = await CREDENTIAL_STORE.delete(request.match_info["id"])
if not deleted:
return _error(404, "NOT_FOUND", "No such credential.")
return _ok({"deleted": True})
# ----- single download by id (dynamic; registered last) -----
@ROUTES.get("/api/download/{id}")
async def get_download(request: web.Request) -> web.Response:
view = await DOWNLOAD_MANAGER.status(request.match_info["id"])
if view is None:
return _error(404, "NOT_FOUND", "No such download.")
return _ok(view)
@ROUTES.post("/api/download/{id}/pause")
async def pause(request: web.Request) -> web.Response:
try:
await DOWNLOAD_MANAGER.pause(request.match_info["id"])
except DownloadError as e:
return _from_download_error(e)
return _ok({"ok": True})
@ROUTES.post("/api/download/{id}/resume")
async def resume(request: web.Request) -> web.Response:
try:
await DOWNLOAD_MANAGER.resume(request.match_info["id"])
except DownloadError as e:
return _from_download_error(e)
return _ok({"ok": True})
@ROUTES.post("/api/download/{id}/cancel")
async def cancel(request: web.Request) -> web.Response:
try:
await DOWNLOAD_MANAGER.cancel(request.match_info["id"])
except DownloadError as e:
return _from_download_error(e)
return _ok({"ok": True})
@ROUTES.post("/api/download/{id}/priority")
async def set_priority(request: web.Request) -> web.Response:
parsed = await _parse(request, schemas_in.PriorityRequest)
if isinstance(parsed, web.Response):
return parsed
try:
await DOWNLOAD_MANAGER.set_priority(request.match_info["id"], parsed.priority)
except DownloadError as e:
return _from_download_error(e)
return _ok({"ok": True})

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@ -1,51 +0,0 @@
"""Request schemas for the download manager API.
Pydantic enforces shape at the boundary; handlers operate only on validated
values past that point.
"""
from __future__ import annotations
from typing import Optional
from pydantic import BaseModel, Field
from app.model_downloader.constants import AUTH_SCHEME_BEARER
class EnqueueRequest(BaseModel):
url: str
model_id: str
priority: int = 0
expected_sha256: Optional[str] = None
allow_any_extension: bool = False
credential_id: Optional[str] = None
class PriorityRequest(BaseModel):
priority: int
class AvailabilityRequest(BaseModel):
"""``{model_id: url}`` — the URLs declared in the workflow JSON."""
models: dict[str, str] = Field(default_factory=dict)
class CredentialUpsertRequest(BaseModel):
host: str
secret: str
auth_scheme: str = AUTH_SCHEME_BEARER
header_name: Optional[str] = None
query_param: Optional[str] = None
label: Optional[str] = None
match_subdomains: bool = False
enabled: bool = True
__all__ = [
"EnqueueRequest",
"PriorityRequest",
"AvailabilityRequest",
"CredentialUpsertRequest",
]

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@ -1,26 +0,0 @@
"""Response helpers for the download manager API.
The download/status read models are plain dicts produced by the manager. This
module only needs to mask credentials for output (the secret is never returned).
"""
from __future__ import annotations
from app.model_downloader.credentials.store import CredentialView
def credential_to_dict(view: CredentialView) -> dict:
"""API-safe credential representation — never includes the secret."""
return {
"id": view.id,
"host": view.host,
"auth_scheme": view.auth_scheme,
"header_name": view.header_name,
"query_param": view.query_param,
"label": view.label,
"match_subdomains": view.match_subdomains,
"enabled": view.enabled,
"secret_last4": view.secret_last4,
"created_at": view.created_at,
"updated_at": view.updated_at,
}

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@ -1,38 +0,0 @@
"""Shared constants for the download manager.
Status values are persisted as TEXT in the ``downloads`` table; keep them
stable. The lifecycle is (PRD section 6):
queued -> active -> verifying -> completed
| |-> paused -> (resume) -> active
| |-> failed (network, retryable) -> queued (backoff)
|-> cancelled
"""
from __future__ import annotations
# Auth schemes for HostCredential (PRD section 9.4.1).
AUTH_SCHEME_BEARER = "bearer"
AUTH_SCHEME_HEADER = "header"
AUTH_SCHEME_QUERY = "query"
AUTH_SCHEMES = (AUTH_SCHEME_BEARER, AUTH_SCHEME_HEADER, AUTH_SCHEME_QUERY)
class DownloadStatus:
QUEUED = "queued"
ACTIVE = "active"
PAUSED = "paused"
VERIFYING = "verifying"
COMPLETED = "completed"
FAILED = "failed"
CANCELLED = "cancelled"
#: States from which a worker is doing (or about to do) network I/O.
LIVE = (QUEUED, ACTIVE, VERIFYING)
#: Terminal states — the job will not transition again on its own.
TERMINAL = (COMPLETED, FAILED, CANCELLED)
# Default temp-file suffix. Distinctive so the startup orphan sweep only
# removes files THIS subsystem created, never unrelated *.tmp files.
TMP_SUFFIX = ".comfy-download.part"

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@ -1,99 +0,0 @@
"""Turn a stored credential into a per-hop request modifier (PRD section 9.4.2).
The critical rule: a credential is only ever attached when *the current hop's
host* matches a stored credential, and only over https. This is recomputed
from scratch on every redirect hop, so a token bound to ``huggingface.co`` is
silently dropped when the request is redirected to a presigned CDN host —
which is exactly what these hubs expect.
"""
from __future__ import annotations
import asyncio
from dataclasses import dataclass, field
from typing import Optional
from urllib.parse import parse_qsl, urlencode, urlsplit, urlunsplit
from app.model_downloader.constants import (
AUTH_SCHEME_BEARER,
AUTH_SCHEME_HEADER,
AUTH_SCHEME_QUERY,
)
from app.model_downloader.credentials.store import normalize_host
from app.model_downloader.database import queries
from app.model_downloader.database.models import HostCredential
@dataclass
class RequestAuth:
"""How to modify a single request to carry a credential."""
headers: dict[str, str] = field(default_factory=dict)
query: dict[str, str] = field(default_factory=dict)
def apply_to_url(self, url: str) -> str:
if not self.query:
return url
parts = urlsplit(url)
params = dict(parse_qsl(parts.query, keep_blank_values=True))
params.update(self.query)
return urlunsplit(parts._replace(query=urlencode(params)))
def _matches(cred: HostCredential, hop_host: str) -> bool:
cred_host = cred.host
if hop_host == cred_host:
return True
if cred.match_subdomains:
# Label-boundary suffix: api.example.com matches example.com, but
# evil-example.com does NOT.
return hop_host.endswith("." + cred_host)
return False
def _build_auth(cred: HostCredential) -> RequestAuth:
if cred.auth_scheme == AUTH_SCHEME_BEARER:
return RequestAuth(headers={"Authorization": f"Bearer {cred.secret}"})
if cred.auth_scheme == AUTH_SCHEME_HEADER:
name = cred.header_name or "Authorization"
return RequestAuth(headers={name: cred.secret})
if cred.auth_scheme == AUTH_SCHEME_QUERY and cred.query_param:
return RequestAuth(query={cred.query_param: cred.secret})
return RequestAuth()
def _resolve_sync(
host: str, scheme: str, explicit_credential_id: Optional[str]
) -> Optional[RequestAuth]:
# Never attach a secret over a non-https hop (PRD section 9.4.2).
if scheme.lower() != "https":
return None
hop_host = normalize_host(host)
if not hop_host:
return None
if explicit_credential_id is not None:
cred = queries.get_credential(explicit_credential_id)
# An explicit credential is still subject to the per-hop host check —
# it is not forced onto a non-matching host.
if cred is None or not cred.enabled or not _matches(cred, hop_host):
return None
return _build_auth(cred)
# Auto-resolve: exact host first, then any subdomain-matching credential.
cred = queries.get_credential_by_host(hop_host)
if cred is not None and cred.enabled:
return _build_auth(cred)
for sub in queries.list_subdomain_credentials():
if sub.enabled and _matches(sub, hop_host):
return _build_auth(sub)
return None
async def resolve_auth_for_hop(
host: str, scheme: str, *, explicit_credential_id: Optional[str] = None
) -> Optional[RequestAuth]:
"""Resolve the credential (if any) to attach for one request hop."""
return await asyncio.to_thread(
_resolve_sync, host, scheme, explicit_credential_id
)

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@ -1,137 +0,0 @@
"""The credential store: one API key per host (PRD section 9.4).
Secrets are write-only over the API — :class:`CredentialView` carries only
masked metadata (``secret_last4`` + scheme + label), never the secret itself.
At-rest protection for v1 is filesystem permissions on the shared DB (the DB
is the trust boundary); encryption-at-rest is a noted future seam.
"""
from __future__ import annotations
import asyncio
from dataclasses import dataclass
from typing import Optional
from app.model_downloader.constants import (
AUTH_SCHEME_BEARER,
AUTH_SCHEME_HEADER,
AUTH_SCHEME_QUERY,
AUTH_SCHEMES,
)
from app.model_downloader.database import queries
from app.model_downloader.database.models import HostCredential
def normalize_host(host: str) -> str:
"""Lowercase, strip port, IDNA-encode (PRD section 9.4.3)."""
if not host:
return ""
host = host.strip().lower()
if host.startswith("[") and "]" in host: # bracketed IPv6 literal
host = host[1 : host.index("]")]
elif host.count(":") == 1: # host:port (not IPv6)
host = host.split(":", 1)[0]
try:
host = host.encode("idna").decode("ascii")
except (UnicodeError, ValueError):
pass
return host
@dataclass(frozen=True)
class CredentialView:
"""Masked, API-safe view of a credential — never includes the secret."""
id: str
host: str
auth_scheme: str
header_name: Optional[str]
query_param: Optional[str]
label: Optional[str]
match_subdomains: bool
enabled: bool
secret_last4: Optional[str]
created_at: int
updated_at: int
def _to_view(row: HostCredential) -> CredentialView:
return CredentialView(
id=row.id,
host=row.host,
auth_scheme=row.auth_scheme,
header_name=row.header_name,
query_param=row.query_param,
label=row.label,
match_subdomains=row.match_subdomains,
enabled=row.enabled,
secret_last4=row.secret_last4,
created_at=row.created_at,
updated_at=row.updated_at,
)
class CredentialValidationError(ValueError):
"""A credential upsert had inconsistent fields."""
class CredentialStore:
"""Async facade over the ``host_credentials`` table.
DB access is synchronous (SQLite) and offloaded via ``asyncio.to_thread``.
"""
async def upsert(
self,
host: str,
secret: str,
*,
auth_scheme: str = AUTH_SCHEME_BEARER,
header_name: Optional[str] = None,
query_param: Optional[str] = None,
label: Optional[str] = None,
match_subdomains: bool = False,
enabled: bool = True,
) -> CredentialView:
host = normalize_host(host)
if not host:
raise CredentialValidationError("host is required")
if not secret:
raise CredentialValidationError("secret is required")
if auth_scheme not in AUTH_SCHEMES:
raise CredentialValidationError(
f"auth_scheme must be one of {AUTH_SCHEMES}, got {auth_scheme!r}"
)
if auth_scheme == AUTH_SCHEME_HEADER and not header_name:
header_name = "Authorization"
if auth_scheme == AUTH_SCHEME_QUERY and not query_param:
raise CredentialValidationError(
"query_param is required when auth_scheme='query'"
)
values = {
"host": host,
"secret": secret,
"secret_last4": secret[-4:] if len(secret) >= 4 else secret,
"auth_scheme": auth_scheme,
"header_name": header_name,
"query_param": query_param,
"label": label,
"match_subdomains": match_subdomains,
"enabled": enabled,
}
row = await asyncio.to_thread(queries.upsert_credential, values)
return _to_view(row)
async def list(self) -> list[CredentialView]:
rows = await asyncio.to_thread(queries.list_credentials)
return [_to_view(r) for r in rows]
async def get(self, credential_id: str) -> Optional[CredentialView]:
row = await asyncio.to_thread(queries.get_credential, credential_id)
return _to_view(row) if row is not None else None
async def delete(self, credential_id: str) -> bool:
return await asyncio.to_thread(queries.delete_credential, credential_id)
CREDENTIAL_STORE = CredentialStore()

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@ -1,162 +0,0 @@
"""SQLAlchemy models for the download manager.
Three tables (PRD section 7):
- ``downloads`` one row per requested file (job + queue state).
- ``download_segments`` per-segment byte progress, for segmented resume.
- ``host_credentials`` one API key per host, reused across downloads.
The local file catalog / dedup index is NOT here — that is owned by the
assets system (``assets`` / ``asset_references``). On completion a finished
file is registered into the assets catalog; ``downloads`` is kept only as
job history.
"""
from __future__ import annotations
import time
import uuid
from sqlalchemy import (
BigInteger,
Boolean,
CheckConstraint,
ForeignKey,
Index,
Integer,
String,
Text,
)
from sqlalchemy.orm import Mapped, mapped_column, relationship
from app.database.models import Base
def _uuid() -> str:
return str(uuid.uuid4())
def _now() -> int:
return int(time.time())
class Download(Base):
__tablename__ = "downloads"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=_uuid)
# Original requested URL and the final URL after validated redirects.
url: Mapped[str] = mapped_column(Text, nullable=False)
final_url: Mapped[str | None] = mapped_column(Text, nullable=True)
# Canonical "<directory>/<filename>" identifier (resolved via folder_paths).
model_id: Mapped[str] = mapped_column(String(1024), nullable=False)
# Final on-disk location and the .part write target.
dest_path: Mapped[str] = mapped_column(Text, nullable=False)
temp_path: Mapped[str] = mapped_column(Text, nullable=False)
status: Mapped[str] = mapped_column(String(16), nullable=False)
priority: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
total_bytes: Mapped[int | None] = mapped_column(BigInteger, nullable=True)
bytes_done: Mapped[int] = mapped_column(BigInteger, nullable=False, default=0)
etag: Mapped[str | None] = mapped_column(String(512), nullable=True)
last_modified: Mapped[str | None] = mapped_column(String(128), nullable=True)
accept_ranges: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
# Optional hub-provided checksum to verify against (NOT the dedup key).
expected_sha256: Mapped[str | None] = mapped_column(String(64), nullable=True)
# Explicit credential override; otherwise auto-resolved by host.
credential_id: Mapped[str | None] = mapped_column(String(36), nullable=True)
allow_any_extension: Mapped[bool] = mapped_column(
Boolean, nullable=False, default=False
)
# How many retryable failures we have seen (for backoff capping).
attempts: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
error: Mapped[str | None] = mapped_column(Text, nullable=True)
created_at: Mapped[int] = mapped_column(BigInteger, nullable=False, default=_now)
updated_at: Mapped[int] = mapped_column(
BigInteger, nullable=False, default=_now, onupdate=_now
)
segments: Mapped[list[DownloadSegment]] = relationship(
"DownloadSegment",
back_populates="download",
cascade="all,delete-orphan",
passive_deletes=True,
order_by="DownloadSegment.idx",
)
__table_args__ = (
Index("ix_downloads_status", "status"),
Index("ix_downloads_priority", "priority"),
Index("ix_downloads_model_id", "model_id"),
CheckConstraint("bytes_done >= 0", name="ck_downloads_bytes_done_nonneg"),
CheckConstraint(
"total_bytes IS NULL OR total_bytes >= 0",
name="ck_downloads_total_bytes_nonneg",
),
)
def __repr__(self) -> str:
return f"<Download id={self.id} model_id={self.model_id!r} status={self.status}>"
class DownloadSegment(Base):
__tablename__ = "download_segments"
download_id: Mapped[str] = mapped_column(
String(36),
ForeignKey("downloads.id", ondelete="CASCADE"),
primary_key=True,
)
idx: Mapped[int] = mapped_column(Integer, primary_key=True)
start_offset: Mapped[int] = mapped_column(BigInteger, nullable=False)
end_offset: Mapped[int] = mapped_column(BigInteger, nullable=False)
bytes_done: Mapped[int] = mapped_column(BigInteger, nullable=False, default=0)
download: Mapped[Download] = relationship("Download", back_populates="segments")
__table_args__ = (
CheckConstraint("bytes_done >= 0", name="ck_segments_bytes_done_nonneg"),
CheckConstraint("end_offset >= start_offset", name="ck_segments_range"),
)
def __repr__(self) -> str:
return (
f"<DownloadSegment {self.download_id}#{self.idx} "
f"{self.start_offset}-{self.end_offset} done={self.bytes_done}>"
)
class HostCredential(Base):
__tablename__ = "host_credentials"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=_uuid)
# Normalized lowercase hostname, e.g. "civitai.com".
host: Mapped[str] = mapped_column(String(255), nullable=False)
match_subdomains: Mapped[bool] = mapped_column(
Boolean, nullable=False, default=False
)
label: Mapped[str | None] = mapped_column(String(255), nullable=True)
auth_scheme: Mapped[str] = mapped_column(
String(16), nullable=False, default="bearer"
)
header_name: Mapped[str | None] = mapped_column(String(255), nullable=True)
query_param: Mapped[str | None] = mapped_column(String(255), nullable=True)
# The API key itself. Write-only over the API; never returned. See PRD 9.4.4.
secret: Mapped[str] = mapped_column(Text, nullable=False)
secret_last4: Mapped[str | None] = mapped_column(String(4), nullable=True)
enabled: Mapped[bool] = mapped_column(Boolean, nullable=False, default=True)
created_at: Mapped[int] = mapped_column(BigInteger, nullable=False, default=_now)
updated_at: Mapped[int] = mapped_column(
BigInteger, nullable=False, default=_now, onupdate=_now
)
__table_args__ = (
Index("uq_host_credentials_host", "host", unique=True),
)
def __repr__(self) -> str:
return f"<HostCredential id={self.id} host={self.host!r} scheme={self.auth_scheme}>"

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@ -1,235 +0,0 @@
"""Synchronous DB access for the download manager.
All functions open their own short-lived session via ``create_session`` and
commit before returning, mirroring ``app/assets`` usage. They are blocking
(SQLite) and should be called from async code through ``asyncio.to_thread``.
"""
from __future__ import annotations
import time
from typing import Optional
from sqlalchemy import select
from app.database.db import create_session
from app.model_downloader.constants import DownloadStatus
from app.model_downloader.database.models import (
Download,
DownloadSegment,
HostCredential,
)
# ----- downloads -----
def insert_download(values: dict) -> None:
with create_session() as session:
session.add(Download(**values))
session.commit()
def get_download(download_id: str) -> Optional[Download]:
with create_session() as session:
row = session.get(Download, download_id)
if row is not None:
session.expunge_all()
return row
def list_downloads() -> list[Download]:
with create_session() as session:
rows = list(
session.execute(
select(Download).order_by(Download.created_at.desc())
).scalars()
)
session.expunge_all()
return rows
def list_segments(download_id: str) -> list[DownloadSegment]:
with create_session() as session:
rows = list(
session.execute(
select(DownloadSegment)
.where(DownloadSegment.download_id == download_id)
.order_by(DownloadSegment.idx)
).scalars()
)
session.expunge_all()
return rows
def update_download(download_id: str, **fields) -> None:
if not fields:
return
fields.setdefault("updated_at", int(time.time()))
with create_session() as session:
row = session.get(Download, download_id)
if row is None:
return
for key, value in fields.items():
setattr(row, key, value)
session.commit()
def delete_download(download_id: str) -> None:
with create_session() as session:
row = session.get(Download, download_id)
if row is not None:
session.delete(row)
session.commit()
def replace_segments(download_id: str, segments: list[dict]) -> None:
"""Atomically replace the segment plan for a download."""
with create_session() as session:
session.query(DownloadSegment).filter(
DownloadSegment.download_id == download_id
).delete()
for seg in segments:
session.add(DownloadSegment(download_id=download_id, **seg))
session.commit()
def update_segment_progress(download_id: str, idx: int, bytes_done: int) -> None:
with create_session() as session:
row = session.get(DownloadSegment, {"download_id": download_id, "idx": idx})
if row is None:
return
row.bytes_done = bytes_done
session.commit()
def list_queued_downloads() -> list[Download]:
"""Queued rows ordered for admission (priority desc, then FIFO)."""
with create_session() as session:
rows = list(
session.execute(
select(Download)
.where(Download.status == DownloadStatus.QUEUED)
.order_by(Download.priority.desc(), Download.created_at.asc())
).scalars()
)
session.expunge_all()
return rows
def reconcile_live_downloads() -> list[Download]:
"""Reset any ``active``/``verifying`` rows left by a previous run.
On a clean restart there can be no live worker, so anything still marked
live is stale. Move it back to ``queued`` (offsets are preserved on the
segment rows) so the scheduler re-admits it. Returns the rows that should
be re-queued by the scheduler (queued + paused).
"""
with create_session() as session:
stale = list(
session.execute(
select(Download).where(
Download.status.in_([DownloadStatus.ACTIVE, DownloadStatus.VERIFYING])
)
).scalars()
)
now = int(time.time())
for row in stale:
row.status = DownloadStatus.QUEUED
row.updated_at = now
session.commit()
resumable = list(
session.execute(
select(Download)
.where(Download.status == DownloadStatus.QUEUED)
.order_by(Download.priority.desc(), Download.created_at.asc())
).scalars()
)
session.expunge_all()
return resumable
# ----- host credentials -----
def get_credential(credential_id: str) -> Optional[HostCredential]:
with create_session() as session:
row = session.get(HostCredential, credential_id)
if row is not None:
session.expunge_all()
return row
def get_credential_by_host(host: str) -> Optional[HostCredential]:
with create_session() as session:
row = (
session.execute(
select(HostCredential).where(HostCredential.host == host).limit(1)
)
.scalars()
.first()
)
if row is not None:
session.expunge_all()
return row
def list_credentials() -> list[HostCredential]:
with create_session() as session:
rows = list(
session.execute(
select(HostCredential).order_by(HostCredential.host)
).scalars()
)
session.expunge_all()
return rows
def list_subdomain_credentials() -> list[HostCredential]:
"""Credentials that opted into subdomain matching, for suffix checks."""
with create_session() as session:
rows = list(
session.execute(
select(HostCredential).where(HostCredential.match_subdomains.is_(True))
).scalars()
)
session.expunge_all()
return rows
def upsert_credential(values: dict) -> HostCredential:
"""Insert or update a credential keyed by ``host``."""
host = values["host"]
now = int(time.time())
with create_session() as session:
row = (
session.execute(
select(HostCredential).where(HostCredential.host == host).limit(1)
)
.scalars()
.first()
)
if row is None:
row = HostCredential(**values)
row.created_at = now
row.updated_at = now
session.add(row)
else:
for key, value in values.items():
setattr(row, key, value)
row.updated_at = now
session.commit()
session.refresh(row)
session.expunge(row)
return row
def delete_credential(credential_id: str) -> bool:
with create_session() as session:
row = session.get(HostCredential, credential_id)
if row is None:
return False
session.delete(row)
session.commit()
return True

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@ -1,443 +0,0 @@
"""The per-download worker (PRD sections 5, 6, 8, 12).
One :class:`DownloadJob` drives a single file from probe to verified, cataloged
completion. It supports cooperative pause / resume / cancel, segmented
multi-connection transfer with positioned writes, and a verification gate
(size + structural + optional sha256) before the atomic rename into place.
Control is cooperative: external callers flip ``_control`` via
:meth:`request_pause` / :meth:`request_cancel`; segment loops observe it between
chunks and raise, which unwinds cleanly and persists resume offsets.
"""
from __future__ import annotations
import asyncio
import logging
import os
import time
from dataclasses import dataclass, field
from typing import Callable, Optional
from comfy.cli_args import args
from app.model_downloader.constants import DownloadStatus
from app.model_downloader.database import queries
from app.model_downloader.engine.planner import (
SegmentPlan,
effective_segment_count,
plan_segments,
)
from app.model_downloader.engine.writer import FileWriter
from app.model_downloader.net.http import open_validated
from app.model_downloader.net.probe import probe
from app.model_downloader.verify import checksum, dedup, structural
_RETRYABLE_STATUSES = {408, 429, 500, 502, 503, 504}
_PERSIST_INTERVAL = 2.0 # seconds between throttled progress persists
class Paused(Exception):
pass
class Cancelled(Exception):
pass
class RemoteChanged(Exception):
"""The remote file changed under a resume (got 200 where 206 expected)."""
class RetryableError(Exception):
pass
class FatalError(Exception):
"""Non-retryable: 4xx, checksum mismatch, structural failure, gated, etc."""
@dataclass
class SegmentRuntime:
idx: int
start: int
end: int # inclusive; may be -1 for unknown-size single stream
bytes_done: int = 0
@property
def length(self) -> int:
return self.end - self.start + 1
@dataclass
class RuntimeState:
download_id: str
model_id: str
url: str
priority: int
status: str
total_bytes: Optional[int] = None
bytes_done: int = 0
error: Optional[str] = None
segments: list[SegmentRuntime] = field(default_factory=list)
started_at: float = field(default_factory=time.monotonic)
_last_bytes: int = 0
_last_time: float = field(default_factory=time.monotonic)
speed_bps: float = 0.0
@property
def progress(self) -> Optional[float]:
if not self.total_bytes:
return None
return min(1.0, self.bytes_done / self.total_bytes)
@property
def eta_seconds(self) -> Optional[float]:
if not self.total_bytes or self.speed_bps <= 0:
return None
remaining = max(0, self.total_bytes - self.bytes_done)
return remaining / self.speed_bps
@dataclass
class JobSpec:
download_id: str
url: str
model_id: str
dest_path: str
temp_path: str
priority: int = 0
credential_id: Optional[str] = None
expected_sha256: Optional[str] = None
allow_any_extension: bool = False
etag: Optional[str] = None
attempts: int = 0
class DownloadJob:
def __init__(
self, spec: JobSpec, notify_cb: Optional[Callable[[str], None]] = None
) -> None:
self.spec = spec
self._notify = notify_cb
self._control = "run" # run | pause | cancel
self.state = RuntimeState(
download_id=spec.download_id,
model_id=spec.model_id,
url=spec.url,
priority=spec.priority,
status=DownloadStatus.QUEUED,
)
self._writer: Optional[FileWriter] = None
self._etag: Optional[str] = spec.etag
self._last_persist = 0.0
# ----- external control -----
def request_pause(self) -> None:
if self._control == "run":
self._control = "pause"
def request_cancel(self) -> None:
self._control = "cancel"
def _check_control(self) -> None:
if self._control == "cancel":
raise Cancelled()
if self._control == "pause":
raise Paused()
# ----- lifecycle -----
async def run(self) -> str:
"""Run to a terminal/paused state; returns the final status string."""
self._set_status(DownloadStatus.ACTIVE, error=None)
try:
pr = await self._probe_and_plan()
await self._transfer(pr)
await self._finalize()
self._set_status(DownloadStatus.COMPLETED)
except Paused:
await self._persist_progress(force=True)
self._set_status(DownloadStatus.PAUSED)
except Cancelled:
await self._close_writer()
self._remove_temp()
self._set_status(DownloadStatus.CANCELLED)
except RemoteChanged:
await self._reset_for_restart()
self._set_status(
DownloadStatus.QUEUED, error="remote file changed; restarting"
)
except RetryableError as e:
await self._persist_progress(force=True)
self._set_status(DownloadStatus.QUEUED, error=str(e))
except FatalError as e:
await self._close_writer()
self._remove_temp()
self._set_status(DownloadStatus.FAILED, error=str(e))
except Exception as e: # unexpected -> treat as retryable
logging.warning(
"[model_downloader] %s unexpected error: %s",
self.spec.model_id, e, exc_info=True,
)
await self._persist_progress(force=True)
self._set_status(DownloadStatus.QUEUED, error=f"{type(e).__name__}: {e}")
finally:
await self._close_writer()
return self.state.status
# ----- probe + plan -----
async def _probe_and_plan(self):
pr = await probe(self.spec.url, credential_id=self.spec.credential_id)
if not pr.ok:
if pr.gated:
raise FatalError(
f"{self.spec.url} requires authentication. Add an API key for "
f"this host at /api/download/credentials and retry."
)
if pr.status == 0 or pr.status in _RETRYABLE_STATUSES:
raise RetryableError(pr.error or "probe failed")
raise FatalError(pr.error or f"probe returned HTTP {pr.status}")
self._etag = pr.etag or self._etag
self.state.total_bytes = pr.total_bytes
queries.update_download(
self.spec.download_id,
final_url=pr.final_url,
total_bytes=pr.total_bytes,
accept_ranges=pr.accept_ranges,
etag=pr.etag,
last_modified=pr.last_modified,
)
seg_count = effective_segment_count(
pr.total_bytes, pr.accept_ranges, max(1, args.download_segments)
)
existing = queries.list_segments(self.spec.download_id)
if (
seg_count > 1
and existing
and pr.total_bytes is not None
and existing[-1].end_offset == pr.total_bytes - 1
):
# Resume an existing segmented plan.
self.state.segments = [
SegmentRuntime(s.idx, s.start_offset, s.end_offset, s.bytes_done)
for s in existing
]
elif seg_count > 1 and pr.total_bytes is not None:
plans = plan_segments(pr.total_bytes, seg_count)
queries.replace_segments(
self.spec.download_id,
[
{"idx": p.idx, "start_offset": p.start, "end_offset": p.end, "bytes_done": 0}
for p in plans
],
)
self.state.segments = [SegmentRuntime(p.idx, p.start, p.end, 0) for p in plans]
else:
# Single-stream: one logical segment; bytes_done tracked on the row.
row = queries.get_download(self.spec.download_id)
resume_from = row.bytes_done if row else 0
end = (pr.total_bytes - 1) if pr.total_bytes else -1
self.state.segments = [SegmentRuntime(0, 0, end, resume_from)]
self._recompute_bytes_done()
return pr
# ----- transfer -----
async def _transfer(self, pr) -> None:
self._writer = FileWriter(self.spec.temp_path)
await self._writer.open()
segmented = len(self.state.segments) > 1
if segmented and self.state.total_bytes:
await self._writer.preallocate(self.state.total_bytes)
await self._run_segmented()
else:
await self._run_single()
await self._writer.flush()
async def _run_segmented(self) -> None:
pending = [
asyncio.ensure_future(self._run_segment(seg))
for seg in self.state.segments
if seg.bytes_done < seg.length
]
if not pending:
return
done, not_done = await asyncio.wait(
pending, return_when=asyncio.FIRST_EXCEPTION
)
first_exc: Optional[BaseException] = None
for task in done:
exc = task.exception()
if exc is not None and first_exc is None:
first_exc = exc
if first_exc is not None:
for task in not_done:
task.cancel()
await asyncio.gather(*not_done, return_exceptions=True)
raise first_exc
async def _run_segment(self, seg: SegmentRuntime) -> None:
offset = seg.start + seg.bytes_done
headers = {
"Range": f"bytes={offset}-{seg.end}",
"Accept-Encoding": "identity",
}
if self._etag:
headers["If-Range"] = self._etag
async with open_validated(
"GET", self.spec.url, credential_id=self.spec.credential_id, headers=headers
) as (resp, _final):
if resp.status == 200:
# Server ignored the range -> remote changed / no resume support.
raise RemoteChanged()
if resp.status not in (206,):
self._raise_for_status(resp.status)
async for chunk in resp.content.iter_chunked(args.download_chunk_size):
self._check_control()
await self._writer.write_at(offset, chunk)
offset += len(chunk)
seg.bytes_done += len(chunk)
self._recompute_bytes_done()
await self._persist_progress()
async def _run_single(self) -> None:
seg = self.state.segments[0]
offset = seg.bytes_done # resume from here for single-stream
headers = {"Accept-Encoding": "identity"}
if offset > 0:
headers["Range"] = f"bytes={offset}-"
if self._etag:
headers["If-Range"] = self._etag
async with open_validated(
"GET", self.spec.url, credential_id=self.spec.credential_id, headers=headers
) as (resp, _final):
if offset > 0 and resp.status == 200:
# Resume not honoured -> start over from the beginning.
offset = 0
seg.bytes_done = 0
elif offset > 0 and resp.status != 206:
self._raise_for_status(resp.status)
elif offset == 0 and resp.status != 200:
self._raise_for_status(resp.status)
async for chunk in resp.content.iter_chunked(args.download_chunk_size):
self._check_control()
await self._writer.write_at(offset, chunk)
offset += len(chunk)
seg.bytes_done = offset
self.state.bytes_done = offset
await self._persist_progress()
def _raise_for_status(self, status: int) -> None:
if status in (401, 403):
raise FatalError(
f"{self.spec.url} returned {status}; add/update an API key for "
f"this host at /api/download/credentials."
)
if status in _RETRYABLE_STATUSES:
raise RetryableError(f"HTTP {status}")
raise FatalError(f"unexpected HTTP {status}")
# ----- finalize / verify (PRD section 8.4) -----
async def _finalize(self) -> None:
self._check_control()
await self._close_writer()
self._set_status(DownloadStatus.VERIFYING)
total = self.state.total_bytes
actual_size = os.path.getsize(self.spec.temp_path)
if total is not None and actual_size != total:
raise FatalError(
f"size mismatch: wrote {actual_size} of {total} bytes"
)
# Structural gate (cheap, no full read) then optional sha256 (full read).
await asyncio.to_thread(structural.validate, self.spec.temp_path)
if self.spec.expected_sha256:
await asyncio.to_thread(
checksum.verify_sha256, self.spec.temp_path, self.spec.expected_sha256
)
os.makedirs(os.path.dirname(self.spec.dest_path), exist_ok=True)
os.replace(self.spec.temp_path, self.spec.dest_path)
logging.info(
"[model_downloader] completed %s (%d bytes)",
self.spec.model_id, actual_size,
)
# Catalog into the assets system (blake3 dedup identity). Best-effort.
await dedup.register_completed(self.spec.dest_path)
# ----- helpers -----
def _recompute_bytes_done(self) -> None:
self.state.bytes_done = sum(s.bytes_done for s in self.state.segments)
now = time.monotonic()
dt = now - self.state._last_time
if dt >= 0.5:
self.state.speed_bps = (self.state.bytes_done - self.state._last_bytes) / dt
self.state._last_bytes = self.state.bytes_done
self.state._last_time = now
async def _persist_progress(self, force: bool = False) -> None:
now = time.monotonic()
if not force and now - self._last_persist < _PERSIST_INTERVAL:
if self._notify:
self._notify(self.spec.download_id)
return
self._last_persist = now
queries.update_download(self.spec.download_id, bytes_done=self.state.bytes_done)
for seg in self.state.segments:
if seg.end >= seg.start: # skip unknown-size sentinel
queries.update_segment_progress(
self.spec.download_id, seg.idx, seg.bytes_done
)
if self._notify:
self._notify(self.spec.download_id)
async def _reset_for_restart(self) -> None:
await self._close_writer()
self._remove_temp()
for seg in self.state.segments:
seg.bytes_done = 0
self.state.bytes_done = 0
queries.update_download(self.spec.download_id, bytes_done=0)
if queries.list_segments(self.spec.download_id):
queries.replace_segments(self.spec.download_id, [])
async def _close_writer(self) -> None:
if self._writer is not None:
try:
await self._writer.close()
except Exception:
logging.debug("[model_downloader] writer close error", exc_info=True)
self._writer = None
def _remove_temp(self) -> None:
try:
os.remove(self.spec.temp_path)
except FileNotFoundError:
pass
except OSError as e:
logging.warning(
"[model_downloader] could not remove %s: %s", self.spec.temp_path, e
)
def _set_status(self, status: str, error: Optional[str] = None) -> None:
self.state.status = status
if error is not None:
self.state.error = error
fields = {"status": status, "bytes_done": self.state.bytes_done}
if error is not None:
fields["error"] = error
if status == DownloadStatus.QUEUED:
fields["attempts"] = self.spec.attempts + 1
self.spec.attempts += 1
queries.update_download(self.spec.download_id, **fields)
if self._notify:
self._notify(self.spec.download_id)

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@ -1,51 +0,0 @@
"""Segment planning (PRD section 5.2).
Split a known byte range into S roughly-equal segments, each fetched by its
own coroutine with ``Range: bytes=start-end``. Falls back to a single segment
when the server doesn't support ranges or the size is unknown/too small for
segmentation to be worthwhile.
"""
from __future__ import annotations
from dataclasses import dataclass
# Below this size, the per-connection setup cost outweighs any parallelism.
_MIN_SEGMENT_BYTES = 1 * 1024 * 1024
@dataclass(frozen=True)
class SegmentPlan:
idx: int
start: int
end: int # inclusive
@property
def length(self) -> int:
return self.end - self.start + 1
def effective_segment_count(
total_bytes: int | None, accept_ranges: bool, configured: int
) -> int:
"""How many segments to actually use for this file."""
if not accept_ranges or total_bytes is None or total_bytes <= 0:
return 1
by_size = max(1, total_bytes // _MIN_SEGMENT_BYTES)
return max(1, min(configured, by_size))
def plan_segments(total_bytes: int, num_segments: int) -> list[SegmentPlan]:
"""Return ``num_segments`` contiguous, inclusive byte ranges covering [0, total)."""
if total_bytes <= 0 or num_segments <= 1:
return [SegmentPlan(idx=0, start=0, end=max(0, total_bytes - 1))]
base = total_bytes // num_segments
plans: list[SegmentPlan] = []
start = 0
for i in range(num_segments):
# Last segment soaks up the remainder.
length = base if i < num_segments - 1 else total_bytes - start
end = start + length - 1
plans.append(SegmentPlan(idx=i, start=start, end=end))
start = end + 1
return plans

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@ -1,61 +0,0 @@
"""Positioned, off-loop file writes (PRD section 4 + 5.2).
Network I/O stays on the event loop; every blocking disk op (preallocate,
positioned write, fsync) is run in a bounded thread pool via
``run_in_executor`` so downloads never stall inference or the web server.
A single file descriptor is opened for the whole download. Segments write to
their own offsets with ``os.pwrite`` — which is offset-addressed and atomic
per call, so concurrent segment writers need no extra locking. Per-chunk
fsync is avoided; we fsync once at completion.
"""
from __future__ import annotations
import asyncio
import os
from concurrent.futures import ThreadPoolExecutor
from typing import Optional
# One shared, bounded pool for all download disk I/O.
_EXECUTOR = ThreadPoolExecutor(max_workers=8, thread_name_prefix="dl-writer")
class FileWriter:
"""Owns the ``.part`` file descriptor for one download."""
def __init__(self, path: str) -> None:
self.path = path
self._fd: Optional[int] = None
def _open(self) -> None:
os.makedirs(os.path.dirname(self.path), exist_ok=True)
self._fd = os.open(self.path, os.O_RDWR | os.O_CREAT, 0o644)
async def open(self) -> None:
await asyncio.get_running_loop().run_in_executor(_EXECUTOR, self._open)
async def preallocate(self, size: int) -> None:
"""Grow the file to ``size`` so segments write to their offsets."""
if self._fd is None or size <= 0:
return
await asyncio.get_running_loop().run_in_executor(
_EXECUTOR, os.ftruncate, self._fd, size
)
async def write_at(self, offset: int, data: bytes) -> None:
assert self._fd is not None, "writer not opened"
await asyncio.get_running_loop().run_in_executor(
_EXECUTOR, os.pwrite, self._fd, data, offset
)
async def flush(self) -> None:
if self._fd is None:
return
await asyncio.get_running_loop().run_in_executor(_EXECUTOR, os.fsync, self._fd)
async def close(self) -> None:
if self._fd is None:
return
fd, self._fd = self._fd, None
await asyncio.get_running_loop().run_in_executor(_EXECUTOR, os.close, fd)

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@ -1,294 +0,0 @@
"""Public facade for the download manager (PRD section 10).
This is the only object the server imports. It validates requests, owns the
:class:`Scheduler`, and exposes a small async API plus read models for status.
"""
from __future__ import annotations
import asyncio
import logging
import uuid
from typing import Callable, Optional
from app.model_downloader.constants import DownloadStatus
from app.model_downloader.database import queries
from app.model_downloader.scheduler import SCHEDULER
from app.model_downloader.security import paths
from app.model_downloader.security.allowlist import is_url_allowed
from app.model_downloader.security.paths import InvalidModelId
# Non-terminal statuses: an existing row in one of these blocks a re-enqueue.
_LIVE_STATUSES = (
DownloadStatus.QUEUED,
DownloadStatus.ACTIVE,
DownloadStatus.PAUSED,
DownloadStatus.VERIFYING,
)
class DownloadError(Exception):
"""A user-facing error with a stable machine-readable code."""
def __init__(self, code: str, message: str, status: int = 400) -> None:
super().__init__(message)
self.code = code
self.message = message
self.http_status = status
class DownloadManager:
def __init__(self) -> None:
self._scheduler = SCHEDULER
self._notify_cb: Optional[Callable[[str], None]] = None
def set_notify(self, cb: Optional[Callable[[str], None]]) -> None:
self._notify_cb = cb
self._scheduler.set_notify(cb)
async def start(self) -> None:
await self._scheduler.start()
# ----- enqueue -----
async def enqueue(
self,
url: str,
model_id: str,
*,
priority: int = 0,
expected_sha256: Optional[str] = None,
allow_any_extension: bool = False,
credential_id: Optional[str] = None,
) -> str:
if not is_url_allowed(url, allow_any_extension):
raise DownloadError(
"URL_NOT_ALLOWED",
"URL is not on the download allowlist (host/scheme/extension).",
)
try:
paths.parse_model_id(model_id, allow_any_extension)
dest_path, temp_path = paths.resolve_destination(model_id, allow_any_extension)
except InvalidModelId as e:
raise DownloadError("INVALID_MODEL_ID", str(e))
if await asyncio.to_thread(
paths.resolve_existing, model_id, allow_any_extension
):
raise DownloadError(
"ALREADY_AVAILABLE",
f"Model already exists on disk: {model_id}",
status=409,
)
if await self._has_live_download(model_id):
raise DownloadError(
"ALREADY_DOWNLOADING",
f"A download for {model_id} is already in progress.",
status=409,
)
download_id = str(uuid.uuid4())
await asyncio.to_thread(
queries.insert_download,
{
"id": download_id,
"url": url,
"model_id": model_id,
"dest_path": dest_path,
"temp_path": temp_path,
"status": DownloadStatus.QUEUED,
"priority": priority,
"expected_sha256": expected_sha256,
"credential_id": credential_id,
"allow_any_extension": allow_any_extension,
},
)
logging.info("[model_downloader] enqueued %s -> %s", url, model_id)
await self._scheduler.pump()
return download_id
async def _has_live_download(self, model_id: str) -> bool:
rows = await asyncio.to_thread(queries.list_downloads)
return any(
r.model_id == model_id and r.status in _LIVE_STATUSES for r in rows
)
# ----- control -----
async def pause(self, download_id: str) -> None:
job = self._scheduler.get_job(download_id)
if job is not None:
job.request_pause()
return
row = await asyncio.to_thread(queries.get_download, download_id)
if row is None:
raise DownloadError("NOT_FOUND", "No such download.", status=404)
if row.status == DownloadStatus.QUEUED:
await asyncio.to_thread(
queries.update_download, download_id, status=DownloadStatus.PAUSED
)
async def resume(self, download_id: str) -> None:
row = await asyncio.to_thread(queries.get_download, download_id)
if row is None:
raise DownloadError("NOT_FOUND", "No such download.", status=404)
if row.status in (DownloadStatus.PAUSED, DownloadStatus.FAILED):
await asyncio.to_thread(
queries.update_download,
download_id,
status=DownloadStatus.QUEUED,
error=None,
)
await self._scheduler.pump()
async def cancel(self, download_id: str) -> None:
job = self._scheduler.get_job(download_id)
if job is not None:
job.request_cancel()
return
row = await asyncio.to_thread(queries.get_download, download_id)
if row is None:
raise DownloadError("NOT_FOUND", "No such download.", status=404)
if row.status in _LIVE_STATUSES:
import os
try:
os.remove(row.temp_path)
except OSError:
pass
await asyncio.to_thread(
queries.update_download, download_id, status=DownloadStatus.CANCELLED
)
async def set_priority(self, download_id: str, priority: int) -> None:
row = await asyncio.to_thread(queries.get_download, download_id)
if row is None:
raise DownloadError("NOT_FOUND", "No such download.", status=404)
await asyncio.to_thread(
queries.update_download, download_id, priority=priority
)
# Admission-order only (PRD section 13 default); a higher priority is
# picked up the next time a slot frees. Pump in case a slot is free now.
await self._scheduler.pump()
# ----- read models -----
def _view(self, row) -> dict:
"""Combine the persisted row with live in-memory progress, if running."""
job = self._scheduler.get_job(row.id)
bytes_done = row.bytes_done
total = row.total_bytes
speed = None
eta = None
segments = None
if job is not None:
st = job.state
bytes_done = st.bytes_done
total = st.total_bytes if st.total_bytes is not None else total
speed = st.speed_bps
eta = st.eta_seconds
segments = [
{"idx": s.idx, "bytes_done": s.bytes_done, "length": s.length}
for s in st.segments
if s.end >= s.start
]
progress = (bytes_done / total) if total else None
return {
"download_id": row.id,
"model_id": row.model_id,
"url": row.url,
"status": row.status,
"priority": row.priority,
"total_bytes": total,
"bytes_done": bytes_done,
"progress": progress,
"speed_bps": speed,
"eta_seconds": eta,
"segments": segments,
"error": row.error,
"created_at": row.created_at,
"updated_at": row.updated_at,
}
def _view_from_state(self, job) -> dict:
"""Build a view purely from the live in-memory job state (no DB)."""
st = job.state
return {
"download_id": st.download_id,
"model_id": st.model_id,
"url": st.url,
"status": st.status,
"priority": st.priority,
"total_bytes": st.total_bytes,
"bytes_done": st.bytes_done,
"progress": st.progress,
"speed_bps": st.speed_bps,
"eta_seconds": st.eta_seconds,
"segments": [
{"idx": s.idx, "bytes_done": s.bytes_done, "length": s.length}
for s in st.segments
if s.end >= s.start
],
"error": st.error,
}
def status_sync(self, download_id: str) -> Optional[dict]:
"""Synchronous status read for the websocket notify path.
Uses live in-memory state when the job is running (no DB round-trip on
the hot path); falls back to a quick DB read otherwise.
"""
job = self._scheduler.get_job(download_id)
if job is not None:
return self._view_from_state(job)
row = queries.get_download(download_id)
return self._view(row) if row is not None else None
async def status(self, download_id: str) -> Optional[dict]:
row = await asyncio.to_thread(queries.get_download, download_id)
return self._view(row) if row is not None else None
async def list(self) -> list[dict]:
rows = await asyncio.to_thread(queries.list_downloads)
return [self._view(r) for r in rows]
async def availability(self, models: dict[str, str]) -> dict[str, dict]:
"""Bulk per-id ``{state, progress, ...}`` for the frontend poll.
``state`` is ``available`` (on disk), ``downloading`` (live row), or
``missing``. Cheap: a path lookup plus an in-memory/DB status check.
"""
rows = await asyncio.to_thread(queries.list_downloads)
by_model: dict[str, object] = {}
for r in rows:
if r.status in _LIVE_STATUSES or r.model_id not in by_model:
by_model[r.model_id] = r
out: dict[str, dict] = {}
for model_id, url in models.items():
try:
exists = await asyncio.to_thread(paths.resolve_existing, model_id)
except InvalidModelId:
out[model_id] = {"state": "missing", "url_allowed": is_url_allowed(url)}
continue
if exists:
out[model_id] = {"state": "available", "url_allowed": is_url_allowed(url)}
continue
row = by_model.get(model_id)
if row is not None and row.status in _LIVE_STATUSES:
view = self._view(row)
out[model_id] = {
"state": "downloading",
"url_allowed": is_url_allowed(url),
"download_id": view["download_id"],
"progress": view["progress"],
"bytes_done": view["bytes_done"],
"total_bytes": view["total_bytes"],
"speed_bps": view["speed_bps"],
}
else:
out[model_id] = {"state": "missing", "url_allowed": is_url_allowed(url)}
return out
DOWNLOAD_MANAGER = DownloadManager()

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@ -1,110 +0,0 @@
"""Manual, validated redirect-following request opener.
Automatic redirects are disabled (PRD section 9.2): we follow hops ourselves
so that on *every* hop we (a) re-validate scheme + reject credentials-in-URL,
(b) recompute which stored credential — if any — applies to that hop's host,
and (c) let the connector's resolver screen the IP. This is the single place
that attaches credentials, so a token can never ride a redirect to a CDN host.
"""
from __future__ import annotations
import logging
from contextlib import asynccontextmanager
from typing import AsyncIterator, Optional
from urllib.parse import urljoin, urlsplit, urlunsplit
import aiohttp
from app.model_downloader.credentials.resolver import resolve_auth_for_hop
from app.model_downloader.net.session import get_session
from app.model_downloader.security.ssrf import (
MAX_REDIRECTS,
SSRFError,
check_redirect_hop,
)
_REDIRECT_CODES = {301, 302, 303, 307, 308}
DEFAULT_TIMEOUT = aiohttp.ClientTimeout(total=None, sock_connect=30, sock_read=120)
def redact_url(url: str) -> str:
"""Drop the query string so a query-scheme secret is never logged/stored."""
try:
parts = urlsplit(url)
except ValueError:
return "<unparseable-url>"
return urlunsplit(parts._replace(query=""))
async def _resolve_final_response(
method: str,
url: str,
credential_id: Optional[str],
base_headers: dict[str, str],
timeout: aiohttp.ClientTimeout,
) -> tuple[aiohttp.ClientResponse, str]:
"""Follow redirects manually until a non-redirect response.
Each intermediate redirect response is released before the next hop.
Returns the final ``(response, final_url)``; the caller owns releasing it.
"""
session = await get_session()
current = url
hops = 0
while True:
check_redirect_hop(current)
parts = urlsplit(current)
auth = await resolve_auth_for_hop(
parts.hostname or "", parts.scheme, explicit_credential_id=credential_id
)
req_headers = dict(base_headers)
req_url = current
if auth is not None:
req_headers.update(auth.headers)
req_url = auth.apply_to_url(current)
resp = await session.request(
method,
req_url,
allow_redirects=False,
headers=req_headers,
timeout=timeout,
)
if resp.status in _REDIRECT_CODES and resp.headers.get("Location"):
next_url = urljoin(str(resp.url), resp.headers["Location"])
await resp.release()
hops += 1
if hops > MAX_REDIRECTS:
raise SSRFError(
f"too many redirects (> {MAX_REDIRECTS}) for {redact_url(url)}"
)
current = next_url
continue
return resp, redact_url(str(resp.url))
@asynccontextmanager
async def open_validated(
method: str,
url: str,
*,
credential_id: Optional[str] = None,
headers: Optional[dict[str, str]] = None,
timeout: aiohttp.ClientTimeout = DEFAULT_TIMEOUT,
) -> AsyncIterator[tuple[aiohttp.ClientResponse, str]]:
"""Open ``method url`` following redirects manually and validated.
Yields ``(response, final_url)`` where ``final_url`` is redacted of any
query string. The response is released automatically on exit.
"""
resp, final_url = await _resolve_final_response(
method, url, credential_id, dict(headers or {}), timeout
)
try:
yield resp, final_url
finally:
try:
await resp.release()
except Exception: # pragma: no cover - best-effort cleanup
logging.debug("[model_downloader] response release error", exc_info=True)

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@ -1,90 +0,0 @@
"""Pre-download probe (PRD section 5.1).
Issues a tiny ranged GET (``Range: bytes=0-0``) — which doubles as a
range-support test — to discover ``Content-Length``, ``Accept-Ranges``,
``ETag``/``Last-Modified``, and the final post-redirect URL. For HuggingFace
LFS files the true size also appears in the non-standard ``X-Linked-Size``
header, which we read as a fallback.
"""
from __future__ import annotations
import logging
from dataclasses import dataclass
from typing import Optional
import aiohttp
from app.model_downloader.net.http import open_validated
from app.model_downloader.net.session import parse_int_header
_PROBE_TIMEOUT = aiohttp.ClientTimeout(total=60, sock_connect=30, sock_read=30)
@dataclass
class ProbeResult:
ok: bool
status: int
final_url: Optional[str] = None
total_bytes: Optional[int] = None
accept_ranges: bool = False
etag: Optional[str] = None
last_modified: Optional[str] = None
gated: bool = False # 401/403 — needs (or has wrong) credentials
error: Optional[str] = None
def _total_from_content_range(value: Optional[str]) -> Optional[int]:
# "bytes 0-0/12345" -> 12345 ; "bytes 0-0/*" -> None
if not value or "/" not in value:
return None
total = value.rsplit("/", 1)[1].strip()
return parse_int_header(total)
async def probe(url: str, *, credential_id: Optional[str] = None) -> ProbeResult:
"""Probe ``url`` and return discovered metadata, failing soft."""
try:
async with open_validated(
"GET",
url,
credential_id=credential_id,
headers={"Range": "bytes=0-0", "Accept-Encoding": "identity"},
timeout=_PROBE_TIMEOUT,
) as (resp, final_url):
if resp.status in (401, 403):
return ProbeResult(
ok=False, status=resp.status, final_url=final_url, gated=True,
error=f"host returned {resp.status} (authentication required)",
)
if resp.status not in (200, 206):
return ProbeResult(
ok=False, status=resp.status, final_url=final_url,
error=f"probe returned HTTP {resp.status}",
)
headers = resp.headers
accept_ranges = False
total: Optional[int] = None
if resp.status == 206:
accept_ranges = True
total = _total_from_content_range(headers.get("Content-Range"))
else: # 200: server ignored the range
accept_ranges = headers.get("Accept-Ranges", "").lower() == "bytes"
total = parse_int_header(headers.get("Content-Length"))
if total is None:
total = parse_int_header(headers.get("X-Linked-Size"))
return ProbeResult(
ok=True,
status=resp.status,
final_url=final_url,
total_bytes=total,
accept_ranges=accept_ranges,
etag=headers.get("ETag"),
last_modified=headers.get("Last-Modified"),
)
except Exception as e: # network / SSRF / timeout
logging.debug("[model_downloader] probe failed for %s: %s", url, e)
return ProbeResult(ok=False, status=0, error=f"{type(e).__name__}: {e}")

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@ -1,72 +0,0 @@
"""Lazily-created shared :class:`aiohttp.ClientSession`.
A single session reuses TLS handshakes and TCP connections across the probe
and the many segment GETs to the same host (HuggingFace is the dominant
case), which is a large speedup on cold connections and exactly the
connection-reuse strategy that lets us match aria2c (PRD section 5.2).
The connector uses :class:`ValidatingResolver` so every connection — initial
or post-redirect — is screened for private/special-use IPs at connect time.
TLS is pinned to certifi's CA bundle because the OS trust store is not wired
up on some Python installs (python.org macOS, slim containers).
"""
from __future__ import annotations
import asyncio
import ssl
from typing import Optional
import aiohttp
try:
import certifi
_CA_FILE = certifi.where()
except Exception: # pragma: no cover - certifi is a transitive dep of aiohttp
_CA_FILE = None
from comfy.cli_args import args
from app.model_downloader.security.ssrf import ValidatingResolver
_session: Optional[aiohttp.ClientSession] = None
_lock = asyncio.Lock()
def ssl_context() -> ssl.SSLContext:
if _CA_FILE is not None:
return ssl.create_default_context(cafile=_CA_FILE)
return ssl.create_default_context()
async def get_session() -> aiohttp.ClientSession:
"""Return the shared session, creating it on first use."""
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=max(1, getattr(args, "download_max_connections_per_host", 16)),
ssl=ssl_context(),
resolver=ValidatingResolver(),
)
_session = aiohttp.ClientSession(connector=connector)
return _session
async def close_session() -> None:
global _session
if _session is not None and not _session.closed:
await _session.close()
_session = None
def parse_int_header(value: Optional[str]) -> Optional[int]:
"""Parse a non-negative integer header value, or None if bad/absent."""
if not value:
return None
try:
n = int(value)
except (TypeError, ValueError):
return None
return n if n >= 0 else None

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@ -1,160 +0,0 @@
"""Priority scheduler + lifecycle (PRD sections 4, 6, 12).
Owns the set of running jobs and admits queued downloads up to a global
concurrency limit (K), highest priority first, FIFO within a priority. Runs
entirely on the existing ComfyUI asyncio loop; blocking work (disk, hashing,
DB) is offloaded by the job/writer layers.
On startup it reconciles DB vs. disk: ``active``/``verifying`` rows left by a
previous run are reset to ``queued`` and resumed from persisted offsets, and
orphaned ``.part`` files with no live download row are swept.
"""
from __future__ import annotations
import asyncio
import logging
import os
import random
import time
from typing import Callable, Optional
from comfy.cli_args import args
from app.model_downloader.constants import DownloadStatus
from app.model_downloader.database import queries
from app.model_downloader.engine.job import DownloadJob, JobSpec
from app.model_downloader.security import paths
# Backoff for retryable failures (PRD section 12).
_BACKOFF_BASE = 2.0
_BACKOFF_CAP = 300.0
_MAX_ATTEMPTS = 6
class Scheduler:
def __init__(self) -> None:
self._jobs: dict[str, DownloadJob] = {}
self._tasks: dict[str, asyncio.Task] = {}
self._backoff_until: dict[str, float] = {}
self._pump_lock = asyncio.Lock()
self._notify_cb: Optional[Callable[[str], None]] = None
self._started = False
@property
def max_active(self) -> int:
return max(1, getattr(args, "download_max_active", 3))
def set_notify(self, cb: Optional[Callable[[str], None]]) -> None:
self._notify_cb = cb
def get_job(self, download_id: str) -> Optional[DownloadJob]:
return self._jobs.get(download_id)
def is_active(self, download_id: str) -> bool:
return download_id in self._tasks
# ----- startup -----
async def start(self) -> None:
if self._started:
return
self._started = True
try:
await asyncio.to_thread(queries.reconcile_live_downloads)
await asyncio.to_thread(self._sweep_orphan_temp_files)
except Exception as e:
logging.warning("[model_downloader] startup reconcile failed: %s", e)
await self.pump()
@staticmethod
def _sweep_orphan_temp_files() -> None:
"""Remove ``.part`` files not referenced by a resumable download row.
Resumable partials (queued/paused rows) are preserved; only truly
orphaned temp files from crashed runs are deleted.
"""
live = {
row.temp_path
for row in queries.list_downloads()
if row.status in (DownloadStatus.QUEUED, DownloadStatus.PAUSED)
}
for path in paths.iter_all_tmp_paths():
if path in live:
continue
try:
os.remove(path)
logging.info("[model_downloader] removed orphan temp file: %s", path)
except OSError as e:
logging.warning("[model_downloader] could not remove %s: %s", path, e)
# ----- admission -----
async def pump(self) -> None:
async with self._pump_lock:
slots = self.max_active - len(self._tasks)
if slots <= 0:
return
now = time.monotonic()
candidates = await asyncio.to_thread(queries.list_queued_downloads)
for row in candidates:
if slots <= 0:
break
if row.id in self._tasks:
continue
if self._backoff_until.get(row.id, 0.0) > now:
continue
self._admit(row)
slots -= 1
def _admit(self, row) -> None:
spec = JobSpec(
download_id=row.id,
url=row.url,
model_id=row.model_id,
dest_path=row.dest_path,
temp_path=row.temp_path,
priority=row.priority,
credential_id=row.credential_id,
expected_sha256=row.expected_sha256,
allow_any_extension=row.allow_any_extension,
etag=row.etag,
attempts=row.attempts,
)
job = DownloadJob(spec, notify_cb=self._notify_cb)
self._jobs[row.id] = job
self._tasks[row.id] = asyncio.ensure_future(self._run_job(job))
async def _run_job(self, job: DownloadJob) -> None:
download_id = job.spec.download_id
status = DownloadStatus.FAILED
try:
status = await job.run()
except Exception as e: # run() is defensive, but never let a task die silently
logging.error("[model_downloader] job %s crashed: %s", download_id, e)
finally:
self._tasks.pop(download_id, None)
self._jobs.pop(download_id, None)
if status == DownloadStatus.QUEUED:
if job.spec.attempts >= _MAX_ATTEMPTS:
queries.update_download(
download_id,
status=DownloadStatus.FAILED,
error=f"giving up after {job.spec.attempts} attempts",
)
if self._notify_cb:
self._notify_cb(download_id)
else:
delay = min(
_BACKOFF_CAP, _BACKOFF_BASE ** job.spec.attempts
) + random.uniform(0, 1.0)
self._backoff_until[download_id] = time.monotonic() + delay
asyncio.ensure_future(self._delayed_pump(delay))
await self.pump()
async def _delayed_pump(self, delay: float) -> None:
await asyncio.sleep(delay)
await self.pump()
SCHEDULER = Scheduler()

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@ -1,84 +0,0 @@
"""URL allowlist for server-side model fetches (PRD section 9.1).
Default-deny. A URL is downloadable only when its parsed host + scheme are
allowlisted AND (unless explicitly relaxed) its final filename ends in a
known model extension.
The built-in host defaults mirror the frontend's ``isModelDownloadable``
allowlist so the two flows agree on what is eligible; ``--download-allowed-hosts``
extends it for self-hosted mirrors. Matching is done on ``urlparse().hostname``
(never a raw string prefix) so userinfo tricks like
``http://127.0.0.1@169.254.169.254/x.safetensors`` — whose real host is the
metadata IP — cannot slip past.
"""
from __future__ import annotations
from urllib.parse import urlparse
from comfy.cli_args import args
# host -> set of allowed schemes. Frontend parity (HuggingFace / Civitai /
# localhost). Extra hosts from --download-allowed-hosts are https-only.
_DEFAULT_ALLOWED_HOSTS: dict[str, set[str]] = {
"huggingface.co": {"https"},
"civitai.com": {"https"},
"localhost": {"http", "https"},
"127.0.0.1": {"http", "https"},
}
# Hosts for which loopback addresses are intentionally permitted (the localhost
# "download a local model" feature). Every other host's loopback resolution is
# rejected by the SSRF resolver.
LOOPBACK_HOSTS = frozenset({"localhost", "127.0.0.1", "::1"})
# Known model file extensions (frontend parity). Checked on the final filename.
ALLOWED_MODEL_EXTENSIONS = (
".safetensors",
".sft",
".ckpt",
".pth",
".pt",
".gguf",
".bin",
)
def _allowed_hosts() -> dict[str, set[str]]:
hosts = {h: set(s) for h, s in _DEFAULT_ALLOWED_HOSTS.items()}
for extra in getattr(args, "download_allowed_hosts", []) or []:
host = extra.strip().lower()
if host:
hosts.setdefault(host, set()).add("https")
return hosts
def is_host_allowed(host: str | None, scheme: str | None) -> bool:
"""True iff ``host`` is allowlisted for ``scheme``.
Used both for the initial URL and re-checked on every redirect hop
(PRD section 9.2), so a whitelisted URL cannot 30x into an off-list host.
"""
if not host or not scheme:
return False
allowed = _allowed_hosts().get(host.lower())
return allowed is not None and scheme.lower() in allowed
def has_allowed_extension(path: str, allow_any_extension: bool = False) -> bool:
if allow_any_extension:
return True
return path.lower().endswith(ALLOWED_MODEL_EXTENSIONS)
def is_url_allowed(url: str, allow_any_extension: bool = False) -> bool:
"""Check whether ``url`` is permitted as a server-side download source."""
if not isinstance(url, str) or not url:
return False
try:
parsed = urlparse(url)
except ValueError:
return False
if not is_host_allowed(parsed.hostname, parsed.scheme):
return False
return has_allowed_extension(parsed.path, allow_any_extension)

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@ -1,110 +0,0 @@
"""Path resolution + traversal safety for downloads (PRD section 9.3).
A ``model_id`` is a *relative destination path* of the form
``<directory>/<filename>`` (e.g. ``loras/my_lora.safetensors``). This module
turns one into an absolute on-disk path under one of ComfyUI's registered
model folders, rejecting unknown folders, path traversal, and symlink escape.
This is the only thing that composes destination paths, so the engine never
touches user-supplied path strings directly.
"""
from __future__ import annotations
import os
import re
from typing import Iterator, Optional
import folder_paths
from app.model_downloader.constants import TMP_SUFFIX
from app.model_downloader.security.allowlist import ALLOWED_MODEL_EXTENSIONS
# A model_id component is a single path segment of safe characters — no slashes,
# no "..", no leading dots that could escape the target directory.
_SEGMENT_RE = re.compile(r"^[A-Za-z0-9][A-Za-z0-9._-]*$")
class InvalidModelId(ValueError):
"""Raised when a model_id is malformed or names an unknown model folder."""
def parse_model_id(model_id: str, allow_any_extension: bool = False) -> tuple[str, str]:
"""Split ``<directory>/<filename>`` and validate both components.
Returns ``(directory, filename)``. 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 have 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 allow_any_extension and not filename.lower().endswith(
ALLOWED_MODEL_EXTENSIONS
):
raise InvalidModelId(
f"filename must end with a known model extension "
f"{ALLOWED_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, allow_any_extension: bool = False) -> Optional[str]:
"""Return the absolute path of an installed model, or None if missing.
Honours ``extra_model_paths.yaml`` transparently via ``get_full_path``.
"""
directory, filename = parse_model_id(model_id, allow_any_extension)
return folder_paths.get_full_path(directory, filename)
def resolve_destination(
model_id: str, allow_any_extension: bool = False
) -> tuple[str, str]:
"""Return ``(final_path, temp_path)`` for a download.
Downloads land at the first registered path for the model's directory
(the "primary" location). ``temp_path`` is a sibling ``.part`` file that
is atomically renamed onto ``final_path`` on success. The result is
asserted to stay within the registered root (defence in depth on top of
the segment regex).
"""
directory, filename = parse_model_id(model_id, allow_any_extension)
roots = folder_paths.get_folder_paths(directory)
if not roots:
raise InvalidModelId(f"no on-disk path registered for folder {directory!r}")
root = os.path.realpath(roots[0])
final_path = os.path.realpath(os.path.join(root, filename))
if final_path != root and not final_path.startswith(root + os.sep):
raise InvalidModelId(f"resolved path escapes model root: {model_id!r}")
temp_path = f"{final_path}{TMP_SUFFIX}"
return final_path, temp_path
def iter_all_tmp_paths() -> Iterator[str]:
"""Yield this subsystem's temp files under every registered model folder.
Matches only the distinctive ``TMP_SUFFIX`` so the startup orphan sweep
can never delete temp files created by other tools.
"""
seen_roots: set[str] = set()
for directory in list(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:
continue

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@ -1,111 +0,0 @@
"""SSRF / exfiltration defenses (PRD section 9.2).
Two cooperating layers:
1. :class:`ValidatingResolver` is installed on the shared connector. Every
connection — the initial probe and every segment GET, including ones made
after a redirect — resolves its host through this resolver, which rejects
any address that lands on a private / special-use IP range. Because the
resolve and the connect happen together inside the connector, there is no
check-then-connect window for DNS rebinding to exploit.
2. :func:`check_redirect_hop` re-validates every redirect hop. The host
allowlist gates only the *initial* user-supplied URL (anti-SSRF for
arbitrary input); legitimate downloads from allowlisted origins redirect
to presigned CDN hosts that are deliberately NOT on the allowlist (HF ->
``cdn-lfs*.huggingface.co``, Civitai -> signed Cloudflare/S3), so hops are
instead screened for scheme, embedded credentials, and — via the resolver
above — private IPs. Credentials are only ever attached when a hop's host
exactly matches a stored credential, so they are dropped on the CDN hop.
"""
from __future__ import annotations
import ipaddress
import socket
from urllib.parse import urlparse
from aiohttp.abc import AbstractResolver
from aiohttp.resolver import DefaultResolver
from app.model_downloader.security.allowlist import LOOPBACK_HOSTS
# Cap the redirect chain length and the schemes a hop may use.
MAX_REDIRECTS = 5
ALLOWED_SCHEMES = ("https", "http")
class SSRFError(Exception):
"""A hop failed an SSRF / allowlist check."""
def is_blocked_ip(ip_str: str) -> bool:
"""True for any address we refuse to connect to.
Covers loopback, link-local (incl. 169.254.169.254 cloud metadata),
RFC1918 private ranges, unique-local (ULA), unspecified (0.0.0.0/::),
multicast and other reserved ranges.
"""
try:
ip = ipaddress.ip_address(ip_str)
except ValueError:
return True # unparseable -> refuse
return (
ip.is_private
or ip.is_loopback
or ip.is_link_local
or ip.is_multicast
or ip.is_reserved
or ip.is_unspecified
)
class ValidatingResolver(AbstractResolver):
"""Delegating resolver that drops blocked IPs from every resolution.
If a hostname resolves only to blocked addresses, the connection fails
closed with an :class:`OSError`, which aiohttp surfaces as a connection
error to the caller.
"""
def __init__(self) -> None:
self._inner = DefaultResolver()
async def resolve(self, host, port=0, family=socket.AF_INET):
infos = await self._inner.resolve(host, port, family)
# localhost/127.0.0.1 are an explicit, opt-in allowlist feature.
if isinstance(host, str) and host.lower() in LOOPBACK_HOSTS:
return infos
safe = [info for info in infos if not is_blocked_ip(info["host"])]
if not safe:
raise OSError(
f"refusing to connect to {host!r}: resolves only to "
f"private/special-use addresses"
)
return safe
async def close(self) -> None:
await self._inner.close()
def check_redirect_hop(url: str) -> str:
"""Validate one redirect hop's URL.
Returns the URL unchanged on success; raises :class:`SSRFError` otherwise.
Enforces an allowed scheme and forbids credentials-in-URL. The host is NOT
re-checked against the allowlist (CDN redirect targets are off-list by
design); private-IP protection is provided by the connector's resolver,
and credential leakage is prevented by exact host matching at attach time.
The landing filename's extension is gated separately by the caller.
"""
try:
parsed = urlparse(url)
except ValueError as e:
raise SSRFError(f"unparseable redirect URL {url!r}: {e}") from e
if parsed.scheme.lower() not in ALLOWED_SCHEMES:
raise SSRFError(f"redirect to disallowed scheme {parsed.scheme!r}")
if parsed.username or parsed.password:
raise SSRFError("credentials-in-URL are not allowed")
if not parsed.hostname:
raise SSRFError(f"redirect URL has no host: {url!r}")
return url

View File

@ -1,49 +0,0 @@
"""Hub-checksum verification = SHA256 (PRD section 8.1).
Only used to confirm a download matches a *provided* ``expected_sha256``. It
is NOT the dedup key (that is blake3, owned by the assets system). The full
sequential read happens at most once, here, only when a checksum was supplied.
"""
from __future__ import annotations
import hashlib
from typing import Callable, Optional
_CHUNK = 8 * 1024 * 1024
InterruptCheck = Callable[[], bool]
class ChecksumError(Exception):
"""The computed SHA256 did not match the expected value."""
def sha256_file(path: str, interrupt_check: Optional[InterruptCheck] = None) -> Optional[str]:
"""Stream the file and return its lowercase hex SHA256.
Returns ``None`` if interrupted via ``interrupt_check``.
"""
h = hashlib.sha256()
with open(path, "rb") as f:
while True:
if interrupt_check is not None and interrupt_check():
return None
chunk = f.read(_CHUNK)
if not chunk:
break
h.update(chunk)
return h.hexdigest()
def verify_sha256(
path: str, expected: str, interrupt_check: Optional[InterruptCheck] = None
) -> None:
"""Raise :class:`ChecksumError` unless the file's SHA256 matches ``expected``."""
actual = sha256_file(path, interrupt_check)
if actual is None:
return # interrupted; caller will re-verify on resume
if actual.lower() != expected.lower():
raise ChecksumError(
f"sha256 mismatch: expected {expected.lower()}, got {actual.lower()}"
)

View File

@ -1,53 +0,0 @@
"""Dedup + catalog handoff — reuse the assets system (PRD section 8.5).
We do NOT build a parallel indexer. "Do I already have it?" is answered by
``resolve_existing`` (path) at enqueue time and, where a hash is known, by the
assets blake3 catalog. After a completed download we register the file
through the assets ingest path so it is cataloged and (eventually) hashed by
the existing enrichment worker.
"""
from __future__ import annotations
import asyncio
import logging
import os
from typing import Optional
def _register_sync(abs_path: str) -> Optional[str]:
"""Register a finished file into the assets catalog. Returns asset hash."""
try:
from app.assets.services.ingest import register_file_in_place
except Exception as e: # assets package import failure — non-fatal
logging.debug("[model_downloader] assets ingest unavailable: %s", e)
return None
try:
result = register_file_in_place(abs_path, name=os.path.basename(abs_path), tags=[])
return result.asset.hash if result and result.asset else None
except Exception as e:
# The file is already safely on disk; cataloging is best-effort.
logging.warning(
"[model_downloader] could not register %s into assets catalog: %s",
abs_path, e,
)
return None
async def register_completed(abs_path: str) -> Optional[str]:
"""Catalog a completed download via the assets system (off the event loop)."""
return await asyncio.to_thread(_register_sync, abs_path)
def _find_by_hash_sync(blake3_hex: str) -> Optional[str]:
try:
from app.assets.services.asset_management import get_asset_by_hash
except Exception:
return None
asset = get_asset_by_hash("blake3:" + blake3_hex)
return asset.hash if asset is not None else None
async def find_existing_by_hash(blake3_hex: str) -> Optional[str]:
"""Pure DB lookup — never triggers hashing on the hot path."""
return await asyncio.to_thread(_find_by_hash_sync, blake3_hex)

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@ -1,65 +0,0 @@
"""Cheap structural validation, no full read (PRD section 8.2).
For ``.safetensors``/``.sft`` we parse the header (first few KB): it carries
the tensor table and the byte length of the data region. We assert
``file_size == 8 + header_len + data_region_len``. This detects truncation
and most corruption for free, before any crypto hashing. Other extensions
have no cheap structural check and pass through.
"""
from __future__ import annotations
import json
import os
import struct
_SAFETENSORS_EXTS = (".safetensors", ".sft")
# A sane upper bound so a corrupt header length can't make us read gigabytes.
_MAX_HEADER_BYTES = 100 * 1024 * 1024
class StructuralError(Exception):
"""The file failed its structural integrity check."""
def validate(path: str) -> None:
"""Validate the file at ``path``. Raises :class:`StructuralError` on failure."""
lower = path.lower()
if lower.endswith(_SAFETENSORS_EXTS):
_validate_safetensors(path)
# No structural check for other formats; the size + (optional) checksum
# gates in the engine cover those.
def _validate_safetensors(path: str) -> None:
file_size = os.path.getsize(path)
if file_size < 8:
raise StructuralError(f"file too small to be safetensors ({file_size} bytes)")
with open(path, "rb") as f:
header_len = struct.unpack("<Q", f.read(8))[0]
if header_len <= 0 or header_len > _MAX_HEADER_BYTES:
raise StructuralError(f"implausible safetensors header length {header_len}")
if 8 + header_len > file_size:
raise StructuralError("safetensors header extends past end of file")
try:
header = json.loads(f.read(header_len).decode("utf-8"))
except (UnicodeDecodeError, json.JSONDecodeError) as e:
raise StructuralError(f"safetensors header is not valid JSON: {e}") from e
data_len = 0
for name, entry in header.items():
if name == "__metadata__":
continue
if not isinstance(entry, dict) or "data_offsets" not in entry:
raise StructuralError(f"tensor {name!r} missing data_offsets")
offsets = entry["data_offsets"]
if not (isinstance(offsets, list) and len(offsets) == 2):
raise StructuralError(f"tensor {name!r} has malformed data_offsets")
data_len = max(data_len, int(offsets[1]))
expected = 8 + header_len + data_len
if file_size != expected:
raise StructuralError(
f"size mismatch: file is {file_size} bytes, header implies {expected} "
f"(8 + {header_len} header + {data_len} data)"
)

View File

@ -1,3 +1,5 @@
from __future__ import annotations
import os
import base64
import json

View File

@ -1,3 +1,4 @@
from __future__ import annotations
import json
import os
import re

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View File

@ -1553,7 +1553,7 @@
"VHS_MetadataImage": true,
"VHS_KeepIntermediate": true
},
"category": "Image generation and editing/Conditioned",
"category": "Image generation and editing/Canny to image",
"description": "Generates an image from a Canny edge map using Z-Image-Turbo, with text conditioning."
}
]

View File

@ -3600,7 +3600,7 @@
"extra": {
"workflowRendererVersion": "LG"
},
"category": "Video generation and editing/Conditioned",
"category": "Video generation and editing/Canny to video",
"description": "Generates video from Canny edge maps using LTX-2, with optional synchronized audio."
}
]

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View File

@ -1401,7 +1401,7 @@
"extra": {
"workflowRendererVersion": "LG"
},
"category": "Image generation and editing/Conditioned",
"category": "Image generation and editing/ControlNet",
"description": "Generates images from a text prompt and ControlNet conditioning (e.g. depth, canny) using Z-Image-Turbo."
}
]

View File

@ -1579,7 +1579,7 @@
"VHS_MetadataImage": true,
"VHS_KeepIntermediate": true
},
"category": "Image generation and editing/Conditioned",
"category": "Image generation and editing/Depth to image",
"description": "Generates an image from a depth map using Z-Image-Turbo with text conditioning."
},
{

View File

@ -4233,7 +4233,7 @@
"extra": {
"workflowRendererVersion": "LG"
},
"category": "Video generation and editing/Conditioned",
"category": "Video generation and editing/Depth to video",
"description": "Generates depth-controlled video with LTX-2: motion and structure follow a depth-reference video alongside text prompting, optional first-frame image conditioning, with optional synchronized audio."
},
{

View File

@ -3350,7 +3350,7 @@
}
],
"extra": {},
"category": "Video generation and editing/Conditioned",
"category": "Video generation and editing/First-Last-Frame to Video",
"description": "Generates a video interpolating between first and last keyframes using LTX-2.3."
}
]

View File

@ -3350,7 +3350,7 @@
}
],
"extra": {},
"category": "Video generation and editing/FLF2V",
"category": "Video generation and editing/First-Last-Frame to Video",
"description": "Generates a video that interpolates between the first and last keyframes using LTX-2.3, including optional audio."
}
]

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View File

@ -310,9 +310,9 @@
"extra": {
"workflowRendererVersion": "LG"
},
"category": "Image Tools",
"category": "Text generation/Image Captioning",
"description": "Generates descriptive captions for images using Google's Gemini multimodal LLM."
}
]
}
}
}

View File

@ -1,569 +0,0 @@
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"revision": 0,
"last_node_id": 89,
"last_link_id": 0,
"nodes": [
{
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"type": "85e595bd-af9e-40ee-85c5-b98bb15da47a",
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},
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"name": "output"
},
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},
{
"label": "output_normalization",
"name": "output.normalization",
"type": "COMBO",
"widget": {
"name": "output.normalization"
},
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},
{
"label": "apply_sky_clip",
"name": "output.apply_sky_clip",
"type": "BOOLEAN",
"widget": {
"name": "output.apply_sky_clip"
},
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},
{
"name": "model_name",
"type": "COMBO",
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},
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View File

@ -3870,7 +3870,7 @@
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View File

@ -270,7 +270,7 @@
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View File

@ -389,7 +389,7 @@
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View File

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],
"extra": {},
"category": "Image Tools/Crop",
"description": "Splits an image into a configurable columns×rows grid of equal tiles for tiled generation or processing."
}
]
},
"extra": {}
}

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@ -307,9 +307,9 @@
"extra": {
"workflowRendererVersion": "LG"
},
"category": "Video Tools",
"category": "Text generation/Video Captioning",
"description": "Generates descriptive captions for video input using Google's Gemini multimodal LLM."
}
]
}
}
}

View File

@ -1,825 +0,0 @@
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},
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],
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},
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]
},
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],
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{
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"name": "VIDEO",
"type": "VIDEO",
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]
}
],
"properties": {
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}
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},
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},
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},
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"target_slot": 2,
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},
{
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"target_slot": 3,
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},
{
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"origin_slot": 5,
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"target_slot": 1,
"type": "COMFY_DYNAMICCOMBO_V3"
},
{
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},
{
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"target_id": 92,
"target_slot": 3,
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},
{
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],
"extra": {},
"category": "Conditioning & Preprocessors/Depth",
"description": "This subgraph processes a video input through Depth Anything 3 to produce temporally consistent depth maps for each frame, outputting a depth video. It is ideal for video content requiring spatial geometry estimation, such as 3D reconstruction, SLAM, or novel view synthesis from moving cameras. The model uses a plain transformer backbone trained with a depth-ray representation, supporting any number of views without requiring known camera poses."
}
]
},
"extra": {
"BlueprintDescription": "This subgraph processes a video input through Depth Anything 3 to produce temporally consistent depth maps for each frame, outputting a depth video. It is ideal for video content requiring spatial geometry estimation, such as 3D reconstruction, SLAM, or novel view synthesis from moving cameras. The model uses a plain transformer backbone trained with a depth-ray representation, supporting any number of views without requiring known camera poses."
}
}

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@ -818,7 +818,7 @@
}
],
"extra": {},
"category": "Conditioning & Preprocessors/Segmentation & Mask",
"category": "Video Tools",
"description": "Segments video into temporally consistent masks using Meta SAM3 from text or interactive prompts."
}
]

View File

@ -412,7 +412,7 @@
"extra": {
"workflowRendererVersion": "LG"
},
"category": "Video generation and editing/Upscale",
"category": "Video generation and editing/Enhance video",
"description": "Upscales video to 4× resolution using a GAN-based upscaling model."
}
]

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@ -105,7 +105,7 @@ class WindowAttention(nn.Module):
relative_position_bias = self.relative_position_bias_table[self.relative_position_index.long().view(-1)].view(
self.window_size[0] * self.window_size[1], self.window_size[0] * self.window_size[1], -1) # Wh*Ww,Wh*Ww,nH
relative_position_bias = comfy.ops.cast_to_input(relative_position_bias.permute(2, 0, 1).contiguous(), attn) # nH, Wh*Ww, Wh*Ww
relative_position_bias = relative_position_bias.permute(2, 0, 1).contiguous() # nH, Wh*Ww, Wh*Ww
attn = attn + relative_position_bias.unsqueeze(0)
if mask is not None:

View File

@ -55,7 +55,12 @@ class BackgroundRemovalModel():
out = torch.nn.functional.interpolate(out, size=(H, W), mode="bicubic", antialias=False)
mask = out.sigmoid().to(device=comfy.model_management.intermediate_device(), dtype=comfy.model_management.intermediate_dtype())
return mask.squeeze(1) # (B, 1, H, W) -> (B, H, W)
if mask.ndim == 3:
mask = mask.unsqueeze(0)
if mask.shape[1] != 1:
mask = mask.movedim(-1, 1)
return mask
def load_background_removal_model(sd):

View File

@ -49,7 +49,7 @@ parser.add_argument("--temp-directory", type=str, default=None, help="Set the Co
parser.add_argument("--input-directory", type=str, default=None, help="Set the ComfyUI input directory. Overrides --base-directory.")
parser.add_argument("--auto-launch", action="store_true", help="Automatically launch ComfyUI in the default browser.")
parser.add_argument("--disable-auto-launch", action="store_true", help="Disable auto launching the browser.")
parser.add_argument("--cuda-device", type=str, default=None, metavar="DEVICE_ID", help="Set the ids of cuda devices this instance will use, as a comma-separated list (e.g. '0' or '0,1'). All other devices will not be visible.")
parser.add_argument("--cuda-device", type=int, default=None, metavar="DEVICE_ID", help="Set the id of the cuda device this instance will use. All other devices will not be visible.")
parser.add_argument("--default-device", type=int, default=None, metavar="DEFAULT_DEVICE_ID", help="Set the id of the default device, all other devices will stay visible.")
cm_group = parser.add_mutually_exclusive_group()
cm_group.add_argument("--cuda-malloc", action="store_true", help="Enable cudaMallocAsync (enabled by default for torch 2.0 and up).")
@ -111,11 +111,10 @@ parser.add_argument("--preview-method", type=LatentPreviewMethod, default=Latent
parser.add_argument("--preview-size", type=int, default=512, help="Sets the maximum preview size for sampler nodes.")
cache_group = parser.add_mutually_exclusive_group()
cache_group.add_argument("--cache-ram", nargs='*', type=float, default=[], metavar="GB", help="Use RAM pressure caching with the specified headroom thresholds. This is the default caching mode. The first value sets the active-cache threshold; the optional second value sets the inactive-cache/pin threshold. Defaults when no values are provided: active 10%% of system RAM (min 2GB, max 10GB), inactive 100%% of system RAM (max 96GB).")
cache_group.add_argument("--cache-ram", nargs='*', type=float, default=[], metavar="GB", help="Use RAM pressure caching with the specified headroom thresholds. This is the default caching mode. The first value sets the active-cache threshold; the optional second value sets the inactive-cache/pin threshold. Defaults when no values are provided: active 25%% of system RAM (min 4GB, max 32GB), inactive 75%% of system RAM (min 12GB, max 96GB).")
cache_group.add_argument("--cache-classic", action="store_true", help="Use the old style (aggressive) caching.")
cache_group.add_argument("--cache-lru", type=int, default=0, help="Use LRU caching with a maximum of N node results cached. May use more RAM/VRAM.")
cache_group.add_argument("--cache-none", action="store_true", help="Reduced RAM/VRAM usage at the expense of executing every node for each run.")
cache_group.add_argument("--high-ram", action="store_true", help="Can improve performance slightly on high RAM or on systems where pagefile use is preferred over model loading.")
attn_group = parser.add_mutually_exclusive_group()
attn_group.add_argument("--use-split-cross-attention", action="store_true", help="Use the split cross attention optimization. Ignored when xformers is used.")
@ -134,7 +133,7 @@ upcast.add_argument("--dont-upcast-attention", action="store_true", help="Disabl
parser.add_argument("--enable-manager", action="store_true", help="Enable the ComfyUI-Manager feature.")
manager_group = parser.add_mutually_exclusive_group()
manager_group.add_argument("--disable-manager-ui", action="store_true", help="Disables only the ComfyUI-Manager UI and endpoints. Scheduled installations and similar background tasks will still operate.")
manager_group.add_argument("--enable-manager-legacy-ui", action="store_true", help="Enables the legacy UI of ComfyUI-Manager. Implies --enable-manager.")
manager_group.add_argument("--enable-manager-legacy-ui", action="store_true", help="Enables the legacy UI of ComfyUI-Manager")
vram_group = parser.add_mutually_exclusive_group()
@ -145,13 +144,11 @@ vram_group.add_argument("--novram", action="store_true", help="When lowvram isn'
vram_group.add_argument("--cpu", action="store_true", help="To use the CPU for everything (slow).")
parser.add_argument("--reserve-vram", type=float, default=None, help="Set the amount of vram in GB you want to reserve for use by your OS/other software. By default some amount is reserved depending on your OS.")
parser.add_argument("--vram-headroom", type=float, default=0, help="Set the amount of vram in GB for DynamicVRAM to maintain as extra headroom above default. ComfyUI will try and keep this much VRAM completely free and unused, even counting VRAM from other apps.")
parser.add_argument("--async-offload", nargs='?', const=2, type=int, default=None, metavar="NUM_STREAMS", help="Use async weight offloading. An optional argument controls the amount of offload streams. Default is 2. Enabled by default on Nvidia.")
parser.add_argument("--disable-async-offload", action="store_true", help="Disable async weight offloading.")
parser.add_argument("--disable-dynamic-vram", action="store_true", help="Disable dynamic VRAM and use estimate based model loading.")
parser.add_argument("--enable-dynamic-vram", action="store_true", help="Enable dynamic VRAM on systems where it's not enabled by default.")
parser.add_argument("--fast-disk", action="store_true", help="Prefer disk-backed dynamic loading and offload over unpinned RAM. Can be faster for users with fast NVME disks.")
parser.add_argument("--force-non-blocking", action="store_true", help="Force ComfyUI to use non-blocking operations for all applicable tensors. This may improve performance on some non-Nvidia systems but can cause issues with some workflows.")
@ -168,8 +165,6 @@ class PerformanceFeature(enum.Enum):
parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. This is used to test new features so using it might crash your comfyui. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: {}".format(" ".join(map(lambda c: c.value, PerformanceFeature))))
parser.add_argument("--debug-hang", action="store_true", help="Enable stack trace dumps on Ctrl-C for debugging hangs.")
parser.add_argument("--disable-pinned-memory", action="store_true", help="Disable pinned memory use.")
parser.add_argument("--mmap-torch-files", action="store_true", help="Use mmap when loading ckpt/pt files.")
@ -243,14 +238,6 @@ parser.add_argument("--enable-assets", action="store_true", help="Enable the ass
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.")
# ----- Model download manager (PRD: docs/prd-download-manager.md) -----
parser.add_argument("--download-segments", type=int, default=8, metavar="N", help="Number of parallel HTTP range segments per file for the model download manager (default: 8).")
parser.add_argument("--download-max-active", type=int, default=3, metavar="N", help="Maximum number of model downloads running concurrently (default: 3).")
parser.add_argument("--download-max-connections-per-host", type=int, default=16, metavar="N", help="Maximum simultaneous connections to a single host for the download manager (default: 16).")
parser.add_argument("--download-chunk-size", type=int, default=4 * 1024 * 1024, metavar="BYTES", help="Read chunk size in bytes for the download manager (default: 4 MiB).")
parser.add_argument("--download-allowed-hosts", type=str, nargs="*", default=[], metavar="HOST", help="Additional hostnames to add to the download manager allowlist (https only). The built-in defaults always include huggingface.co and civitai.com.")
parser.add_argument("--download-allow-any-extension", action="store_true", help="Allow the download manager to fetch files with any extension (default: only known model extensions like .safetensors).")
if comfy.options.args_parsing:
args = parser.parse_args()
else:
@ -259,9 +246,6 @@ else:
if args.cache_ram is not None and len(args.cache_ram) > 2:
parser.error("--cache-ram accepts at most two values: active GB and inactive GB")
if args.high_ram:
args.cache_classic = True
if args.windows_standalone_build:
args.auto_launch = True
@ -271,10 +255,6 @@ if args.disable_auto_launch:
if args.force_fp16:
args.fp16_unet = True
# '--enable-manager-legacy-ui' is meaningless unless the manager is enabled, so imply '--enable-manager'.
if args.enable_manager_legacy_ui:
args.enable_manager = True
# '--fast' is not provided, use an empty set
if args.fast is None:

View File

@ -9,7 +9,6 @@ import comfy.model_management
import comfy.utils
import comfy.clip_model
import comfy.image_encoders.dino2
import comfy.image_encoders.dino3
class Output:
def __getitem__(self, key):
@ -24,16 +23,12 @@ IMAGE_ENCODERS = {
"siglip_vision_model": comfy.clip_model.CLIPVisionModelProjection,
"siglip2_vision_model": comfy.clip_model.CLIPVisionModelProjection,
"dinov2": comfy.image_encoders.dino2.Dinov2Model,
"dinov3": comfy.image_encoders.dino3.DINOv3ViTModel,
}
class ClipVisionModel():
def __init__(self, json_config):
if isinstance(json_config, dict):
config = json_config
else:
with open(json_config) as f:
config = json.load(f)
with open(json_config) as f:
config = json.load(f)
self.image_size = config.get("image_size", 224)
self.image_mean = config.get("image_mean", [0.48145466, 0.4578275, 0.40821073])
@ -139,8 +134,6 @@ def load_clipvision_from_sd(sd, prefix="", convert_keys=False):
json_config = os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "image_encoders"), "dino2_giant.json")
elif 'encoder.layer.23.layer_scale2.lambda1' in sd:
json_config = os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "image_encoders"), "dino2_large.json")
elif 'layer.0.mlp.gate_proj.weight' in sd and 'layer.31.norm1.weight' in sd: # Dinov3 ViT-H/16+ (SwiGLU gated MLP, 32 layers)
json_config = comfy.image_encoders.dino3.DINOV3_VITH_CONFIG
else:
return None

View File

@ -1,5 +1,6 @@
"""Comfy-specific type hinting"""
from __future__ import annotations
from typing import Literal, TypedDict, Optional
from typing_extensions import NotRequired
from abc import ABC, abstractmethod

View File

@ -8,8 +8,6 @@ from abc import ABC, abstractmethod
import logging
import comfy.model_management
import comfy.patcher_extension
import comfy.utils
import comfy.conds
if TYPE_CHECKING:
from comfy.model_base import BaseModel
from comfy.model_patcher import ModelPatcher
@ -53,18 +51,12 @@ class ContextHandlerABC(ABC):
class IndexListContextWindow(ContextWindowABC):
def __init__(self, index_list: list[int], dim: int=0, total_frames: int=0, modality_windows: dict=None, context_overlap: int=0):
def __init__(self, index_list: list[int], dim: int=0, total_frames: int=0):
self.index_list = index_list
self.context_length = len(index_list)
self.context_overlap = context_overlap
self.dim = dim
self.total_frames = total_frames
self.center_ratio = (min(index_list) + max(index_list)) / (2 * total_frames)
self.modality_windows = modality_windows # dict of {mod_idx: IndexListContextWindow}
self.guide_frames_indices: list[int] = []
self.guide_overlap_info: list[tuple[int, int]] = []
self.guide_kf_local_positions: list[int] = []
self.guide_downscale_factors: list[int] = []
def get_tensor(self, full: torch.Tensor, device=None, dim=None, retain_index_list=[]) -> torch.Tensor:
if dim is None:
@ -93,11 +85,6 @@ class IndexListContextWindow(ContextWindowABC):
region_idx = int(self.center_ratio * num_regions)
return min(max(region_idx, 0), num_regions - 1)
def get_window_for_modality(self, modality_idx: int) -> 'IndexListContextWindow':
if modality_idx == 0:
return self
return self.modality_windows[modality_idx]
class IndexListCallbacks:
EVALUATE_CONTEXT_WINDOWS = "evaluate_context_windows"
@ -161,172 +148,6 @@ def slice_cond(cond_value, window: IndexListContextWindow, x_in: torch.Tensor, d
return cond_value._copy_with(sliced)
def compute_guide_overlap(guide_entries: list[dict], keyframe_idxs: torch.Tensor, temporal_downscale_ratio: int, window_index_list: list[int]):
"""Compute which concatenated guide frames overlap with a context window.
Each guide's latent-space start is derived from its first token's pixel-t-start
in keyframe_idxs (shape (B, [t,h,w], num_tokens, [start, end])), divided by the
model's temporal_downscale_ratio.
Args:
guide_entries: list of guide_attention_entry dicts
keyframe_idxs: per-token pixel coords cond tensor for the modality
temporal_downscale_ratio: model's pixel-to-latent temporal compression ratio
window_index_list: the window's frame indices into the video portion
Returns:
suffix_indices: indices into the guide_frames tensor for frame selection
overlap_info: list of (entry_idx, overlap_count) for guide_attention_entries adjustment
kf_local_positions: window-local frame positions for keyframe_idxs regeneration
total_overlap: total number of overlapping guide frames
"""
window_set = set(window_index_list)
window_list = list(window_index_list)
suffix_indices = []
overlap_info = []
kf_local_positions = []
suffix_base = 0
token_offset = 0
for entry_idx, entry in enumerate(guide_entries):
first_t_pixel = int(keyframe_idxs[0, 0, token_offset, 0].item())
latent_start = (first_t_pixel + temporal_downscale_ratio - 1) // temporal_downscale_ratio
guide_len = entry["latent_shape"][0]
entry_overlap = 0
for local_offset in range(guide_len):
video_pos = latent_start + local_offset
if video_pos in window_set:
suffix_indices.append(suffix_base + local_offset)
kf_local_positions.append(window_list.index(video_pos))
entry_overlap += 1
if entry_overlap > 0:
overlap_info.append((entry_idx, entry_overlap))
suffix_base += guide_len
token_offset += entry["pre_filter_count"]
return suffix_indices, overlap_info, kf_local_positions, len(suffix_indices)
@dataclass
class WindowingState:
"""Per-modality context windowing state for each step,
built using IndexListContextHandler._build_window_state().
For non-multimodal models the lists are length 1
"""
latents: list[torch.Tensor] # per-modality working latents (guide frames stripped)
guide_latents: list[torch.Tensor | None] # per-modality guide frames stripped from latents
guide_entries: list[list[dict] | None] # per-modality guide_attention_entry metadata
keyframe_idxs: list[torch.Tensor | None] # per-modality keyframe_idxs tensor for guide latent_start derivation
latent_shapes: list | None # original packed shapes for unpack/pack (None if not multimodal)
dim: int = 0 # primary modality temporal dim for context windowing
is_multimodal: bool = False
temporal_downscale_ratio: int = 1 # model's pixel-to-latent temporal compression ratio
def prepare_window(self, window: IndexListContextWindow, model) -> IndexListContextWindow:
"""Reformat window for multimodal contexts by deriving per-modality index lists.
Non-multimodal contexts return the input window unchanged.
"""
if not self.is_multimodal:
return window
x = self.latents[0]
primary_total = self.latent_shapes[0][self.dim]
primary_overlap = window.context_overlap
map_shapes = self.latent_shapes
if x.size(self.dim) != primary_total:
map_shapes = list(self.latent_shapes)
video_shape = list(self.latent_shapes[0])
video_shape[self.dim] = x.size(self.dim)
map_shapes[0] = torch.Size(video_shape)
try:
per_modality_indices = model.map_context_window_to_modalities(
window.index_list, map_shapes, self.dim)
except AttributeError:
raise NotImplementedError(
f"{type(model).__name__} must implement map_context_window_to_modalities for multimodal context windows.")
modality_windows = {}
for mod_idx in range(1, len(self.latents)):
modality_total_frames = self.latents[mod_idx].shape[self.dim]
ratio = modality_total_frames / primary_total if primary_total > 0 else 1
modality_overlap = max(round(primary_overlap * ratio), 0)
modality_windows[mod_idx] = IndexListContextWindow(
per_modality_indices[mod_idx], dim=self.dim,
total_frames=modality_total_frames,
context_overlap=modality_overlap)
return IndexListContextWindow(
window.index_list, dim=self.dim, total_frames=x.shape[self.dim],
modality_windows=modality_windows, context_overlap=primary_overlap)
def slice_for_window(self, window: IndexListContextWindow, retain_index_list: list[int], device=None) -> tuple[list[torch.Tensor], list[int]]:
"""Slice latents for a context window, injecting guide frames where applicable.
For multimodal contexts, uses the modality-specific windows derived in prepare_window().
"""
sliced = []
guide_frame_counts = []
for idx in range(len(self.latents)):
modality_window = window.get_window_for_modality(idx)
retain = retain_index_list if idx == 0 else []
s = modality_window.get_tensor(self.latents[idx], device, retain_index_list=retain)
if self.guide_entries[idx] is not None:
s, ng = self._inject_guide_frames(s, modality_window, modality_idx=idx)
else:
ng = 0
sliced.append(s)
guide_frame_counts.append(ng)
return sliced, guide_frame_counts
def strip_guide_frames(self, out_per_modality: list[list[torch.Tensor]], guide_frame_counts: list[int], window: IndexListContextWindow):
"""Strip injected guide frames from per-cond, per-modality outputs in place."""
for idx in range(len(self.latents)):
if guide_frame_counts[idx] > 0:
window_len = len(window.get_window_for_modality(idx).index_list)
for ci in range(len(out_per_modality)):
out_per_modality[ci][idx] = out_per_modality[ci][idx].narrow(self.dim, 0, window_len)
def _inject_guide_frames(self, latent_slice: torch.Tensor, window: IndexListContextWindow, modality_idx: int = 0) -> tuple[torch.Tensor, int]:
guide_entries = self.guide_entries[modality_idx]
guide_frames = self.guide_latents[modality_idx]
keyframe_idxs = self.keyframe_idxs[modality_idx]
suffix_idx, overlap_info, kf_local_pos, guide_frame_count = compute_guide_overlap(
guide_entries, keyframe_idxs, self.temporal_downscale_ratio, window.index_list)
# Shift keyframe positions to account for causal_window_fix anchor occupying sub-pos 0.
anchor_idx = getattr(window, 'causal_anchor_index', None)
if anchor_idx is not None and anchor_idx >= 0:
kf_local_pos = [p + 1 for p in kf_local_pos]
window.guide_frames_indices = suffix_idx
window.guide_overlap_info = overlap_info
window.guide_kf_local_positions = kf_local_pos
# Derive per-overlap-entry latent_downscale_factor from guide entry latent_shape vs guide frame spatial dims.
# guide_frames has full (post-dilation) spatial dims; entry["latent_shape"] has pre-dilation dims.
guide_downscale_factors = []
if guide_frame_count > 0:
full_H = guide_frames.shape[3]
for entry_idx, _ in overlap_info:
entry_H = guide_entries[entry_idx]["latent_shape"][1]
guide_downscale_factors.append(full_H // entry_H)
window.guide_downscale_factors = guide_downscale_factors
if guide_frame_count > 0:
idx = tuple([slice(None)] * self.dim + [suffix_idx])
return torch.cat([latent_slice, guide_frames[idx]], dim=self.dim), guide_frame_count
return latent_slice, 0
def patch_latent_shapes(self, sub_conds, new_shapes):
if not self.is_multimodal:
return
for cond_list in sub_conds:
if cond_list is None:
continue
for cond_dict in cond_list:
model_conds = cond_dict.get('model_conds', {})
if 'latent_shapes' in model_conds:
model_conds['latent_shapes'] = comfy.conds.CONDConstant(new_shapes)
@dataclass
class ContextSchedule:
name: str
@ -341,7 +162,7 @@ ContextResults = collections.namedtuple("ContextResults", ['window_idx', 'sub_co
class IndexListContextHandler(ContextHandlerABC):
def __init__(self, context_schedule: ContextSchedule, fuse_method: ContextFuseMethod, context_length: int=1, context_overlap: int=0, context_stride: int=1,
closed_loop: bool=False, dim:int=0, freenoise: bool=False, cond_retain_index_list: list[int]=[], split_conds_to_windows: bool=False,
latent_retain_index_list: list[int]=[], causal_window_fix: bool=True):
causal_window_fix: bool=True):
self.context_schedule = context_schedule
self.fuse_method = fuse_method
self.context_length = context_length
@ -353,118 +174,17 @@ class IndexListContextHandler(ContextHandlerABC):
self.freenoise = freenoise
self.cond_retain_index_list = [int(x.strip()) for x in cond_retain_index_list.split(",")] if cond_retain_index_list else []
self.split_conds_to_windows = split_conds_to_windows
self.latent_retain_index_list = [int(x.strip()) for x in latent_retain_index_list.split(",")] if latent_retain_index_list else []
self.causal_window_fix = causal_window_fix
self.callbacks = {}
@staticmethod
def _get_latent_shapes(conds):
for cond_list in conds:
if cond_list is None:
continue
for cond_dict in cond_list:
model_conds = cond_dict.get('model_conds', {})
if 'latent_shapes' in model_conds:
return model_conds['latent_shapes'].cond
return None
@staticmethod
def _get_guide_entries(conds):
for cond_list in conds:
if cond_list is None:
continue
for cond_dict in cond_list:
model_conds = cond_dict.get('model_conds', {})
entries = model_conds.get('guide_attention_entries')
if entries is not None and hasattr(entries, 'cond') and entries.cond:
return entries.cond
return None
@staticmethod
def _get_keyframe_idxs(conds):
for cond_list in conds:
if cond_list is None:
continue
for cond_dict in cond_list:
model_conds = cond_dict.get('model_conds', {})
kf = model_conds.get('keyframe_idxs')
if kf is not None and hasattr(kf, 'cond') and kf.cond is not None:
return kf.cond
return None
def _apply_freenoise(self, noise: torch.Tensor, conds: list[list[dict]], seed: int) -> torch.Tensor:
"""Apply FreeNoise shuffling, scaling context length/overlap per-modality by frame ratio.
If guide frames are present on the primary modality, only the video portion is shuffled.
"""
guide_entries = self._get_guide_entries(conds)
guide_count = sum(e["latent_shape"][0] for e in guide_entries) if guide_entries else 0
latent_shapes = self._get_latent_shapes(conds)
if latent_shapes is not None and len(latent_shapes) > 1:
modalities = comfy.utils.unpack_latents(noise, latent_shapes)
primary_total = latent_shapes[0][self.dim]
primary_video_count = modalities[0].size(self.dim) - guide_count
apply_freenoise(modalities[0].narrow(self.dim, 0, primary_video_count), self.dim, self.context_length, self.context_overlap, seed)
for i in range(1, len(modalities)):
mod_total = latent_shapes[i][self.dim]
ratio = mod_total / primary_total if primary_total > 0 else 1
mod_ctx_len = max(round(self.context_length * ratio), 1)
mod_ctx_overlap = max(round(self.context_overlap * ratio), 0)
modalities[i] = apply_freenoise(modalities[i], self.dim, mod_ctx_len, mod_ctx_overlap, seed)
noise, _ = comfy.utils.pack_latents(modalities)
return noise
video_count = noise.size(self.dim) - guide_count
apply_freenoise(noise.narrow(self.dim, 0, video_count), self.dim, self.context_length, self.context_overlap, seed)
return noise
def _build_window_state(self, x_in: torch.Tensor, conds: list[list[dict]], model: BaseModel) -> WindowingState:
"""Build windowing state for the current step, including unpacking latents and extracting guide frame info from conds."""
latent_shapes = self._get_latent_shapes(conds)
is_multimodal = latent_shapes is not None and len(latent_shapes) > 1
unpacked_latents = comfy.utils.unpack_latents(x_in, latent_shapes) if is_multimodal else [x_in]
unpacked_latents_list = list(unpacked_latents)
guide_latents_list = [None] * len(unpacked_latents)
guide_entries_list = [None] * len(unpacked_latents)
keyframe_idxs_list = [None] * len(unpacked_latents)
extracted_guide_entries = self._get_guide_entries(conds)
extracted_keyframe_idxs = self._get_keyframe_idxs(conds)
# Strip guide frames (only from first modality for now)
if extracted_guide_entries is not None:
guide_count = sum(e["latent_shape"][0] for e in extracted_guide_entries)
if guide_count > 0:
x = unpacked_latents[0]
latent_count = x.size(self.dim) - guide_count
unpacked_latents_list[0] = x.narrow(self.dim, 0, latent_count)
guide_latents_list[0] = x.narrow(self.dim, latent_count, guide_count)
guide_entries_list[0] = extracted_guide_entries
keyframe_idxs_list[0] = extracted_keyframe_idxs
return WindowingState(
latents=unpacked_latents_list,
guide_latents=guide_latents_list,
guide_entries=guide_entries_list,
keyframe_idxs=keyframe_idxs_list,
latent_shapes=latent_shapes,
dim=self.dim,
is_multimodal=is_multimodal,
temporal_downscale_ratio=model.latent_format.temporal_downscale_ratio)
def should_use_context(self, model: BaseModel, conds: list[list[dict]], x_in: torch.Tensor, timestep: torch.Tensor, model_options: dict[str]) -> bool:
window_state = self._build_window_state(x_in, conds, model) # build window_state to check frame counts, will be built again in execute
total_frame_count = window_state.latents[0].size(self.dim)
if total_frame_count > self.context_length:
logging.info(f"\nUsing context windows: Context length {self.context_length} with overlap {self.context_overlap} for {total_frame_count} frames.")
# for now, assume first dim is batch - should have stored on BaseModel in actual implementation
if x_in.size(self.dim) > self.context_length:
logging.info(f"Using context windows {self.context_length} with overlap {self.context_overlap} for {x_in.size(self.dim)} frames.")
if self.cond_retain_index_list:
logging.info(f"Retaining original cond for indexes: {self.cond_retain_index_list}")
if self.latent_retain_index_list:
logging.info(f"Retaining original latent for indexes: {self.latent_retain_index_list}")
return True
logging.info(f"\nNot using context windows since context length ({self.context_length}) exceeds input frames ({total_frame_count}).")
return False
def prepare_control_objects(self, control: ControlBase, device=None) -> ControlBase:
@ -555,9 +275,7 @@ class IndexListContextHandler(ContextHandlerABC):
return resized_cond
def set_step(self, timestep: torch.Tensor, model_options: dict[str]):
sample_sigmas = model_options["transformer_options"]["sample_sigmas"]
current_timestep = timestep[0].to(sample_sigmas.dtype)
mask = torch.isclose(sample_sigmas, current_timestep, rtol=0.0001)
mask = torch.isclose(model_options["transformer_options"]["sample_sigmas"], timestep[0], rtol=0.0001)
matches = torch.nonzero(mask)
if torch.numel(matches) == 0:
return # substep from multi-step sampler: keep self._step from the last full step
@ -566,98 +284,54 @@ class IndexListContextHandler(ContextHandlerABC):
def get_context_windows(self, model: BaseModel, x_in: torch.Tensor, model_options: dict[str]) -> list[IndexListContextWindow]:
full_length = x_in.size(self.dim) # TODO: choose dim based on model
context_windows = self.context_schedule.func(full_length, self, model_options)
context_windows = [IndexListContextWindow(window, dim=self.dim, total_frames=full_length, context_overlap=self.context_overlap) for window in context_windows]
context_windows = [IndexListContextWindow(window, dim=self.dim, total_frames=full_length) for window in context_windows]
return context_windows
def execute(self, calc_cond_batch: Callable, model: BaseModel, conds: list[list[dict]], x_in: torch.Tensor, timestep: torch.Tensor, model_options: dict[str]):
self._model = model
self.set_step(timestep, model_options)
window_state = self._build_window_state(x_in, conds, model)
num_modalities = len(window_state.latents)
context_windows = self.get_context_windows(model, window_state.latents[0], model_options)
context_windows = self.get_context_windows(model, x_in, model_options)
enumerated_context_windows = list(enumerate(context_windows))
total_windows = len(enumerated_context_windows)
# Initialize per-modality accumulators (length 1 for single-modality)
accum = [[torch.zeros_like(m) for _ in conds] for m in window_state.latents]
conds_final = [torch.zeros_like(x_in) for _ in conds]
if self.fuse_method.name == ContextFuseMethods.RELATIVE:
counts = [[torch.ones(get_shape_for_dim(m, self.dim), device=m.device) for _ in conds] for m in window_state.latents]
counts_final = [torch.ones(get_shape_for_dim(x_in, self.dim), device=x_in.device) for _ in conds]
else:
counts = [[torch.zeros(get_shape_for_dim(m, self.dim), device=m.device) for _ in conds] for m in window_state.latents]
biases = [[([0.0] * m.shape[self.dim]) for _ in conds] for m in window_state.latents]
counts_final = [torch.zeros(get_shape_for_dim(x_in, self.dim), device=x_in.device) for _ in conds]
biases_final = [([0.0] * x_in.shape[self.dim]) for _ in conds]
for callback in comfy.patcher_extension.get_all_callbacks(IndexListCallbacks.EXECUTE_START, self.callbacks):
callback(self, model, x_in, conds, timestep, model_options)
# accumulate results from each context window
for enum_window in enumerated_context_windows:
results = self.evaluate_context_windows(
calc_cond_batch, model, x_in, conds, timestep, [enum_window],
model_options, window_state=window_state, total_windows=total_windows)
results = self.evaluate_context_windows(calc_cond_batch, model, x_in, conds, timestep, [enum_window], model_options)
for result in results:
# result.sub_conds_out is per-cond, per-modality: list[list[Tensor]]
for mod_idx in range(num_modalities):
mod_out = [result.sub_conds_out[ci][mod_idx] for ci in range(len(conds))]
modality_window = result.window.get_window_for_modality(mod_idx)
self.combine_context_window_results(
window_state.latents[mod_idx], mod_out, result.sub_conds, modality_window,
result.window_idx, total_windows, timestep,
accum[mod_idx], counts[mod_idx], biases[mod_idx])
# fuse accumulated results into final conds
self.combine_context_window_results(x_in, result.sub_conds_out, result.sub_conds, result.window, result.window_idx, len(enumerated_context_windows), timestep,
conds_final, counts_final, biases_final)
try:
result_out = []
for ci in range(len(conds)):
finalized = []
for mod_idx in range(num_modalities):
if self.fuse_method.name != ContextFuseMethods.RELATIVE:
accum[mod_idx][ci] /= counts[mod_idx][ci]
f = accum[mod_idx][ci]
# if guide frames were injected, append them to the end of the fused latents for the next step
if window_state.guide_latents[mod_idx] is not None:
f = torch.cat([f, window_state.guide_latents[mod_idx]], dim=self.dim)
finalized.append(f)
# pack modalities together if needed
if window_state.is_multimodal and len(finalized) > 1:
packed, _ = comfy.utils.pack_latents(finalized)
else:
packed = finalized[0]
result_out.append(packed)
return result_out
# finalize conds
if self.fuse_method.name == ContextFuseMethods.RELATIVE:
# relative is already normalized, so return as is
del counts_final
return conds_final
else:
# normalize conds via division by context usage counts
for i in range(len(conds_final)):
conds_final[i] /= counts_final[i]
del counts_final
return conds_final
finally:
for callback in comfy.patcher_extension.get_all_callbacks(IndexListCallbacks.EXECUTE_CLEANUP, self.callbacks):
callback(self, model, x_in, conds, timestep, model_options)
def evaluate_context_windows(self, calc_cond_batch: Callable, model: BaseModel, x_in: torch.Tensor, conds,
timestep: torch.Tensor, enumerated_context_windows: list[tuple[int, IndexListContextWindow]],
model_options, window_state: WindowingState, total_windows: int = None,
device=None, first_device=None):
"""Evaluate context windows and return per-cond, per-modality outputs in ContextResults.sub_conds_out
For each window:
1. Builds windows (for each modality if multimodal)
2. Slices window for each modality
3. Injects concatenated latent guide frames where present
4. Packs together if needed and calls model
5. Unpacks and strips any guides from outputs
"""
x = window_state.latents[0]
def evaluate_context_windows(self, calc_cond_batch: Callable, model: BaseModel, x_in: torch.Tensor, conds, timestep: torch.Tensor, enumerated_context_windows: list[tuple[int, IndexListContextWindow]],
model_options, device=None, first_device=None):
results: list[ContextResults] = []
for window_idx, window in enumerated_context_windows:
# allow processing to end between context window executions for faster Cancel
comfy.model_management.throw_exception_if_processing_interrupted()
# prepare the window accounting for multimodal windows
window = window_state.prepare_window(window, model)
# causal_window_fix: prepend a pre-window frame that will be stripped post-forward.
# Set anchor before slice_for_window so the latent slice and downstream cond slices both pick it up.
# causal_window_fix: prepend a pre-window frame that will be stripped post-forward
anchor_applied = False
if self.causal_window_fix:
anchor_idx = window.index_list[0] - 1
@ -665,46 +339,27 @@ class IndexListContextHandler(ContextHandlerABC):
window.causal_anchor_index = anchor_idx
anchor_applied = True
# slice the window for each modality, injecting guide frames where applicable
sliced, guide_frame_counts_per_modality = window_state.slice_for_window(window, self.latent_retain_index_list, device)
for callback in comfy.patcher_extension.get_all_callbacks(IndexListCallbacks.EVALUATE_CONTEXT_WINDOWS, self.callbacks):
callback(self, model, x_in, conds, timestep, model_options, window_idx, window, model_options, device, first_device)
logging.info(f"Context window {window_idx + 1}/{total_windows or len(enumerated_context_windows)}: frames {window.index_list[0]}-{window.index_list[-1]} of {x.shape[self.dim]}"
+ (f" (+{guide_frame_counts_per_modality[0]} guide frames)" if guide_frame_counts_per_modality[0] > 0 else "")
)
# if multimodal, pack modalities together
if window_state.is_multimodal and len(sliced) > 1:
sub_x, sub_shapes = comfy.utils.pack_latents(sliced)
else:
sub_x, sub_shapes = sliced[0], [sliced[0].shape]
# get resized conds for window
# update exposed params
model_options["transformer_options"]["context_window"] = window
sub_timestep = window.get_tensor(timestep, dim=0)
sub_conds = [self.get_resized_cond(cond, x, window) for cond in conds]
# get subsections of x, timestep, conds
sub_x = window.get_tensor(x_in, device)
sub_timestep = window.get_tensor(timestep, device, dim=0)
sub_conds = [self.get_resized_cond(cond, x_in, window, device) for cond in conds]
# if multimodal, patch latent_shapes in conds for correct unpacking in model
window_state.patch_latent_shapes(sub_conds, sub_shapes)
# call model on window
sub_conds_out = calc_cond_batch(model, sub_conds, sub_x, sub_timestep, model_options)
if device is not None:
for i in range(len(sub_conds_out)):
sub_conds_out[i] = sub_conds_out[i].to(x_in.device)
# unpack outputs
out_per_modality = [comfy.utils.unpack_latents(sub_conds_out[i], sub_shapes) for i in range(len(sub_conds_out))]
# strip causal_window_fix anchor from primary modality before guide strip so window_len math stays correct
# strip causal_window_fix anchor if applied
if anchor_applied:
for ci in range(len(out_per_modality)):
t = out_per_modality[ci][0]
out_per_modality[ci][0] = t.narrow(self.dim, 1, t.shape[self.dim] - 1)
for i in range(len(sub_conds_out)):
sub_conds_out[i] = sub_conds_out[i].narrow(self.dim, 1, sub_conds_out[i].shape[self.dim] - 1)
# strip injected guide frames
window_state.strip_guide_frames(out_per_modality, guide_frame_counts_per_modality, window)
results.append(ContextResults(window_idx, out_per_modality, sub_conds, window))
results.append(ContextResults(window_idx, sub_conds_out, sub_conds, window))
return results
@ -728,7 +383,7 @@ class IndexListContextHandler(ContextHandlerABC):
biases_final[i][idx] = bias_total + bias
else:
# add conds and counts based on weights of fuse method
weights = get_context_weights(window.context_length, x_in.shape[self.dim], window.index_list, self, sigma=timestep, context_overlap=window.context_overlap)
weights = get_context_weights(window.context_length, x_in.shape[self.dim], window.index_list, self, sigma=timestep)
weights_tensor = match_weights_to_dim(weights, x_in, self.dim, device=x_in.device)
for i in range(len(sub_conds_out)):
window.add_window(conds_final[i], sub_conds_out[i] * weights_tensor)
@ -738,22 +393,16 @@ class IndexListContextHandler(ContextHandlerABC):
callback(self, x_in, sub_conds_out, sub_conds, window, window_idx, total_windows, timestep, conds_final, counts_final, biases_final)
def _prepare_sampling_wrapper(executor, model, noise_shape: torch.Tensor, conds, *args, **kwargs):
# Scale noise_shape to a single context window so VRAM estimation budgets per-window.
def _prepare_sampling_wrapper(executor, model, noise_shape: torch.Tensor, *args, **kwargs):
# limit noise_shape length to context_length for more accurate vram use estimation
model_options = kwargs.get("model_options", None)
if model_options is None:
raise Exception("model_options not found in prepare_sampling_wrapper; this should never happen, something went wrong.")
handler: IndexListContextHandler = model_options.get("context_handler", None)
if handler is not None:
noise_shape = list(noise_shape)
is_packed = len(noise_shape) == 3 and noise_shape[1] == 1
if is_packed:
# TODO: latent_shapes cond isn't attached yet at this point, so we can't compute a
# per-window flat latent here. Skipping the clamp over-estimates but prevents immediate OOM.
pass
elif handler.dim < len(noise_shape) and noise_shape[handler.dim] > handler.context_length:
noise_shape[handler.dim] = min(noise_shape[handler.dim], handler.context_length)
return executor(model, noise_shape, conds, *args, **kwargs)
noise_shape[handler.dim] = min(noise_shape[handler.dim], handler.context_length)
return executor(model, noise_shape, *args, **kwargs)
def create_prepare_sampling_wrapper(model: ModelPatcher):
@ -773,12 +422,11 @@ def _sampler_sample_wrapper(executor, guider, sigmas, extra_args, callback, nois
raise Exception("context_handler not found in sampler_sample_wrapper; this should never happen, something went wrong.")
if not handler.freenoise:
return executor(guider, sigmas, extra_args, callback, noise, *args, **kwargs)
conds = [guider.conds.get('positive', guider.conds.get('negative', []))]
noise = handler._apply_freenoise(noise, conds, extra_args["seed"])
noise = apply_freenoise(noise, handler.dim, handler.context_length, handler.context_overlap, extra_args["seed"])
return executor(guider, sigmas, extra_args, callback, noise, *args, **kwargs)
def create_sampler_sample_wrapper(model: ModelPatcher):
model.add_wrapper_with_key(
comfy.patcher_extension.WrappersMP.SAMPLER_SAMPLE,
@ -786,6 +434,7 @@ def create_sampler_sample_wrapper(model: ModelPatcher):
_sampler_sample_wrapper
)
def match_weights_to_dim(weights: list[float], x_in: torch.Tensor, dim: int, device=None) -> torch.Tensor:
total_dims = len(x_in.shape)
weights_tensor = torch.Tensor(weights).to(device=device)
@ -931,9 +580,8 @@ def get_matching_context_schedule(context_schedule: str) -> ContextSchedule:
return ContextSchedule(context_schedule, func)
def get_context_weights(length: int, full_length: int, idxs: list[int], handler: IndexListContextHandler, sigma: torch.Tensor=None, context_overlap: int=None):
context_overlap = handler.context_overlap if context_overlap is None else context_overlap
return handler.fuse_method.func(length, sigma=sigma, handler=handler, full_length=full_length, idxs=idxs, context_overlap=context_overlap)
def get_context_weights(length: int, full_length: int, idxs: list[int], handler: IndexListContextHandler, sigma: torch.Tensor=None):
return handler.fuse_method.func(length, sigma=sigma, handler=handler, full_length=full_length, idxs=idxs)
def create_weights_flat(length: int, **kwargs) -> list[float]:
@ -951,18 +599,18 @@ def create_weights_pyramid(length: int, **kwargs) -> list[float]:
weight_sequence = list(range(1, max_weight, 1)) + [max_weight] + list(range(max_weight - 1, 0, -1))
return weight_sequence
def create_weights_overlap_linear(length: int, full_length: int, idxs: list[int], context_overlap: int, **kwargs):
def create_weights_overlap_linear(length: int, full_length: int, idxs: list[int], handler: IndexListContextHandler, **kwargs):
# based on code in Kijai's WanVideoWrapper: https://github.com/kijai/ComfyUI-WanVideoWrapper/blob/dbb2523b37e4ccdf45127e5ae33e31362f755c8e/nodes.py#L1302
# only expected overlap is given different weights
weights_torch = torch.ones((length))
# blend left-side on all except first window
if min(idxs) > 0:
ramp_up = torch.linspace(1e-37, 1, context_overlap)
weights_torch[:context_overlap] = ramp_up
ramp_up = torch.linspace(1e-37, 1, handler.context_overlap)
weights_torch[:handler.context_overlap] = ramp_up
# blend right-side on all except last window
if max(idxs) < full_length-1:
ramp_down = torch.linspace(1, 1e-37, context_overlap)
weights_torch[-context_overlap:] = ramp_down
ramp_down = torch.linspace(1, 1e-37, handler.context_overlap)
weights_torch[-handler.context_overlap:] = ramp_down
return weights_torch
class ContextFuseMethods:

View File

@ -15,14 +15,13 @@
You should have received a copy of the GNU General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
"""
from __future__ import annotations
import torch
from enum import Enum
import math
import os
import logging
import copy
import comfy.utils
import comfy.model_management
import comfy.model_detection
@ -39,7 +38,7 @@ import comfy.ldm.hydit.controlnet
import comfy.ldm.flux.controlnet
import comfy.ldm.qwen_image.controlnet
import comfy.cldm.dit_embedder
from typing import TYPE_CHECKING, Union
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from comfy.hooks import HookGroup
@ -65,18 +64,6 @@ class StrengthType(Enum):
CONSTANT = 1
LINEAR_UP = 2
class ControlIsolation:
'''Temporarily set a ControlBase object's previous_controlnet to None to prevent cascading calls.'''
def __init__(self, control: ControlBase):
self.control = control
self.orig_previous_controlnet = control.previous_controlnet
def __enter__(self):
self.control.previous_controlnet = None
def __exit__(self, *args):
self.control.previous_controlnet = self.orig_previous_controlnet
class ControlBase:
def __init__(self):
self.cond_hint_original = None
@ -90,7 +77,7 @@ class ControlBase:
self.compression_ratio = 8
self.upscale_algorithm = 'nearest-exact'
self.extra_args = {}
self.previous_controlnet: Union[ControlBase, None] = None
self.previous_controlnet = None
self.extra_conds = []
self.strength_type = StrengthType.CONSTANT
self.concat_mask = False
@ -98,7 +85,6 @@ class ControlBase:
self.extra_concat = None
self.extra_hooks: HookGroup = None
self.preprocess_image = lambda a: a
self.multigpu_clones: dict[torch.device, ControlBase] = {}
def set_cond_hint(self, cond_hint, strength=1.0, timestep_percent_range=(0.0, 1.0), vae=None, extra_concat=[]):
self.cond_hint_original = cond_hint
@ -125,38 +111,17 @@ class ControlBase:
def cleanup(self):
if self.previous_controlnet is not None:
self.previous_controlnet.cleanup()
for device_cnet in self.multigpu_clones.values():
with ControlIsolation(device_cnet):
device_cnet.cleanup()
self.cond_hint = None
self.extra_concat = None
self.timestep_range = None
def get_models(self):
out = []
for device_cnet in self.multigpu_clones.values():
out += device_cnet.get_models_only_self()
if self.previous_controlnet is not None:
out += self.previous_controlnet.get_models()
return out
def get_models_only_self(self):
'Calls get_models, but temporarily sets previous_controlnet to None.'
with ControlIsolation(self):
return self.get_models()
def get_instance_for_device(self, device):
'Returns instance of this Control object intended for selected device.'
return self.multigpu_clones.get(device, self)
def deepclone_multigpu(self, load_device, autoregister=False):
'''
Create deep clone of Control object where model(s) is set to other devices.
When autoregister is set to True, the deep clone is also added to multigpu_clones dict.
'''
raise NotImplementedError("Classes inheriting from ControlBase should define their own deepclone_multigpu funtion.")
def get_extra_hooks(self):
out = []
if self.extra_hooks is not None:
@ -165,7 +130,7 @@ class ControlBase:
out += self.previous_controlnet.get_extra_hooks()
return out
def copy_to(self, c: ControlBase):
def copy_to(self, c):
c.cond_hint_original = self.cond_hint_original
c.strength = self.strength
c.timestep_percent_range = self.timestep_percent_range
@ -319,14 +284,6 @@ class ControlNet(ControlBase):
self.copy_to(c)
return c
def deepclone_multigpu(self, load_device, autoregister=False):
c = self.copy()
c.control_model = copy.deepcopy(c.control_model)
c.control_model_wrapped = comfy.model_patcher.ModelPatcher(c.control_model, load_device=load_device, offload_device=comfy.model_management.unet_offload_device())
if autoregister:
self.multigpu_clones[load_device] = c
return c
def get_models(self):
out = super().get_models()
out.append(self.control_model_wrapped)
@ -357,10 +314,6 @@ class QwenFunControlNet(ControlNet):
super().pre_run(model, percent_to_timestep_function)
self.set_extra_arg("base_model", model.diffusion_model)
def cleanup(self):
self.extra_args.pop("base_model", None)
super().cleanup()
def copy(self):
c = QwenFunControlNet(None, global_average_pooling=self.global_average_pooling, load_device=self.load_device, manual_cast_dtype=self.manual_cast_dtype)
c.control_model = self.control_model
@ -953,14 +906,6 @@ class T2IAdapter(ControlBase):
self.copy_to(c)
return c
def deepclone_multigpu(self, load_device, autoregister=False):
c = self.copy()
c.t2i_model = copy.deepcopy(c.t2i_model)
c.device = load_device
if autoregister:
self.multigpu_clones[load_device] = c
return c
def load_t2i_adapter(t2i_data, model_options={}): #TODO: model_options
compression_ratio = 8
upscale_algorithm = 'nearest-exact'

View File

@ -1,20 +1,5 @@
import logging
import torch
_CK_STOCHASTIC_ROUNDING_AVAILABLE = False
try:
import comfy_kitchen as ck
_ck_stochastic_rounding_fp8 = ck.stochastic_rounding_fp8
_CK_STOCHASTIC_ROUNDING_AVAILABLE = True
except (AttributeError, ImportError):
logging.warning("comfy_kitchen does not support stochastic FP8 rounding, please update comfy_kitchen.")
if not _CK_STOCHASTIC_ROUNDING_AVAILABLE:
def _ck_stochastic_rounding_fp8(value, rng, dtype):
raise NotImplementedError("comfy_kitchen does not support stochastic FP8 rounding")
def calc_mantissa(abs_x, exponent, normal_mask, MANTISSA_BITS, EXPONENT_BIAS, generator=None):
mantissa_scaled = torch.where(
normal_mask,
@ -72,10 +57,6 @@ def stochastic_rounding(value, dtype, seed=0):
if dtype == torch.float8_e4m3fn or dtype == torch.float8_e5m2:
generator = torch.Generator(device=value.device)
generator.manual_seed(seed)
if _CK_STOCHASTIC_ROUNDING_AVAILABLE:
rng = torch.randint(0, 256, value.size(), dtype=torch.uint8, layout=value.layout, device=value.device, generator=generator)
return _ck_stochastic_rounding_fp8(value, rng, dtype)
output = torch.empty_like(value, dtype=dtype)
num_slices = max(1, (value.numel() / (4096 * 4096)))
slice_size = max(1, round(value.shape[0] / num_slices))

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