Add initial commit for model downloader.

* Update comfy-kitchen

* Support requantizing with same settings as orig quant.

.ci/windows_amd_base_files/README_VERY_IMPORTANT.txt

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

.github/workflows/backport_release.yaml

@@ -0,0 +1,519 @@
+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"

.github/workflows/check-line-endings.yml

@@ -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 }})
+          CHANGED_FILES=$(git diff --name-only ${{ github.event.pull_request.base.sha }}..${{ github.event.pull_request.head.sha }} -- ':!.ci')
 
           # Flag to track if CRLF is found
           CRLF_FOUND=false

.github/workflows/detect-unreviewed-merge.yml

@@ -0,0 +1,24 @@
+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 }}

README.md

@@ -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://www.comfy.org/discord
+[discord-url]: https://discord.com/invite/comfyorg
 [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. **[ComfyUI Desktop](https://github.com/Comfy-Org/desktop)**
+2. **[Comfy Desktop](https://github.com/Comfy-Org/Comfy-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 or M2) with any recent macOS version.
+You can install ComfyUI in Apple Mac silicon (M1, M2, M3 or M4) 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 (requires `--enable-manager`) |
+| `--enable-manager-legacy-ui` | Use the legacy manager UI instead of the new UI (implies `--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`) |
 
 
@@ -382,11 +382,7 @@ For AMD 7600 and maybe other RDNA3 cards: ```HSA_OVERRIDE_GFX_VERSION=11.0.0 pyt
 
 ### AMD ROCm Tips
 
-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.
+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.
 
 # Notes
 
@@ -433,7 +429,7 @@ 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). This repository now hosts the compiled JS (from TS/Vue) under the `web/` directory.
+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.
 
 ### Reporting Issues and Requesting Features
 
@@ -462,16 +458,6 @@ 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?

alembic_db/versions/0004_drop_tag_type.py

@@ -0,0 +1,39 @@
+"""
+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"])

alembic_db/versions/0005_download_manager.py

@@ -0,0 +1,118 @@
+"""
+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")

app/assets/api/routes.py

@@ -39,6 +39,7 @@ 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()
@@ -160,10 +161,12 @@ 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,
-        asset_hash=result.asset.hash if result.asset else None,
+        hash=asset_content_hash,
+        asset_hash=asset_content_hash,
         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,
@@ -172,7 +175,7 @@ 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: mirrors job_id for cloud compat
+        prompt_id=result.ref.job_id,  # deprecated alias of job_id, kept for compatibility
         created_at=result.ref.created_at,
         updated_at=result.ref.updated_at,
         last_access_time=result.ref.last_access_time,
@@ -209,24 +212,37 @@ 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"
 
-    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,
-    )
+    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))
 
     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=(q.offset + len(summaries)) < result.total,
+        has_more=has_more,
+        next_cursor=result.next_cursor,
     )
     return web.json_response(payload.model_dump(mode="json", exclude_none=True))
 
@@ -517,18 +533,14 @@ 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=delete_content,
+            delete_content_if_orphan=False,
         )
     except Exception:
         logging.exception(
@@ -573,8 +585,8 @@ async def get_tags(request: web.Request) -> web.Response:
     )
 
     tags = [
-        schemas_out.TagUsage(name=name, count=count, type=tag_type)
-        for (name, tag_type, count) in rows
+        schemas_out.TagUsage(name=name, count=count)
+        for (name, count) in rows
     ]
     payload = schemas_out.TagsList(
         tags=tags, total=total, has_more=(query.offset + len(tags)) < total

app/assets/api/schemas_in.py

@@ -59,6 +59,11 @@ 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"

app/assets/api/schemas_out.py

@@ -10,6 +10,7 @@ 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
@@ -40,12 +41,13 @@ 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):

app/assets/database/models.py

@@ -227,7 +227,6 @@ 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",
@@ -240,7 +239,5 @@ 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}>"

app/assets/database/queries/asset_reference.py

@@ -266,9 +266,18 @@ 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 = (
@@ -297,9 +306,31 @@ def list_references_page(
         "size": Asset.size_bytes,
     }
     sort_col = sort_map.get(sort, AssetReference.created_at)
-    sort_exp = sort_col.desc() if order == "desc" else sort_col.asc()
+    descending = order == "desc"
 
-    base = base.order_by(sort_exp).limit(limit).offset(offset)
+    # 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)
 
     count_stmt = (
         select(sa.func.count())

app/assets/database/queries/tags.py

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

app/assets/scanner.py

@@ -33,6 +33,7 @@ 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,
@@ -354,7 +355,7 @@ 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, tag_type="user")
+            ensure_tags_exist(sess, tag_pool)
         result = batch_insert_seed_assets(sess, specs=specs, owner_id="")
         sess.commit()
         return result.inserted_refs
@@ -506,6 +507,10 @@ 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:

app/assets/services/asset_management.py

@@ -1,8 +1,19 @@
 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 (
@@ -149,6 +160,16 @@ 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
@@ -242,6 +263,11 @@ 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,
@@ -252,7 +278,39 @@ 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,
@@ -261,12 +319,22 @@ def list_assets_page(
             exclude_tags=exclude_tags,
             name_contains=name_contains,
             metadata_filter=metadata_filter,
-            limit=limit,
+            limit=fetch_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(
@@ -277,7 +345,39 @@ def list_assets_page(
                 )
             )
 
-        return ListAssetsResult(items=items, total=total)
+        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)
 
 
 def resolve_hash_to_path(

app/assets/services/cursor.py

@@ -0,0 +1,213 @@
+"""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)

app/assets/services/image_dimensions.py

@@ -0,0 +1,63 @@
+"""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}

app/assets/services/ingest.py

@@ -17,9 +17,11 @@ 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,
@@ -29,6 +31,7 @@ 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,
@@ -118,6 +121,14 @@ 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:
@@ -288,6 +299,13 @@ 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,
@@ -334,6 +352,87 @@ 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

app/assets/services/metadata_extract.py

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

app/assets/services/schemas.py

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

app/assets/services/tagging.py

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

app/custom_node_manager.py

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

app/database/db.py

@@ -21,6 +21,7 @@ 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:

app/frontend_management.py

@@ -1,4 +1,3 @@
-from __future__ import annotations
 import argparse
 import logging
 import os
@@ -62,6 +61,8 @@ 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"]
@@ -73,19 +74,26 @@ def check_comfy_packages_versions():
             logging.error(f"Failed to check {pkg['name']} version: {e}")
             continue
         if outdated:
-            app.logger.log_startup_warning(
-                f"""
+            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"""
 ________________________________________________________________________
 WARNING WARNING WARNING WARNING WARNING
 
-Installed {pkg["name"]} version {installed_str} is lower than the recommended version {required_str}.
+{package_warnings}
 
 {get_missing_requirements_message()}
 ________________________________________________________________________
 """.strip()
-            )
-        else:
-            logging.info("{} version: {}".format(pkg["name"], installed_str))
+        )
 
 
 REQUEST_TIMEOUT = 10  # seconds

app/logger.py

@@ -5,6 +5,40 @@ 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
@@ -68,8 +102,10 @@ 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(logging.Formatter("%(message)s"))
+    stream_handler.setFormatter(formatter)
 
     if use_stdout:
         # Only errors and critical to stderr
@@ -77,7 +113,7 @@ 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(logging.Formatter("%(message)s"))
+        stdout_handler.setFormatter(formatter)
         stdout_handler.addFilter(lambda record: record.levelno < logging.ERROR)
         logger.addHandler(stdout_handler)
 

app/model_downloader/api/routes.py

@@ -0,0 +1,203 @@
+"""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})

app/model_downloader/api/schemas_in.py

@@ -0,0 +1,51 @@
+"""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",
+]

app/model_downloader/api/schemas_out.py

@@ -0,0 +1,26 @@
+"""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,
+    }

app/model_downloader/constants.py

@@ -0,0 +1,38 @@
+"""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"

app/model_downloader/credentials/resolver.py

@@ -0,0 +1,99 @@
+"""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
+    )

app/model_downloader/credentials/store.py

@@ -0,0 +1,137 @@
+"""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()

app/model_downloader/database/models.py

@@ -0,0 +1,162 @@
+"""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}>"

app/model_downloader/database/queries.py

@@ -0,0 +1,235 @@
+"""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

app/model_downloader/engine/job.py

@@ -0,0 +1,443 @@
+"""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)

app/model_downloader/engine/planner.py

@@ -0,0 +1,51 @@
+"""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

app/model_downloader/engine/writer.py

@@ -0,0 +1,61 @@
+"""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)

app/model_downloader/manager.py

@@ -0,0 +1,294 @@
+"""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()

app/model_downloader/net/http.py

@@ -0,0 +1,110 @@
+"""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)

app/model_downloader/net/probe.py

@@ -0,0 +1,90 @@
+"""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}")

app/model_downloader/net/session.py

@@ -0,0 +1,72 @@
+"""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

app/model_downloader/scheduler.py

@@ -0,0 +1,160 @@
+"""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()

app/model_downloader/security/allowlist.py

@@ -0,0 +1,84 @@
+"""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)

app/model_downloader/security/paths.py

@@ -0,0 +1,110 @@
+"""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

app/model_downloader/security/ssrf.py

@@ -0,0 +1,111 @@
+"""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

app/model_downloader/verify/checksum.py

@@ -0,0 +1,49 @@
+"""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()}"
+        )

app/model_downloader/verify/dedup.py

@@ -0,0 +1,53 @@
+"""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)

app/model_downloader/verify/structural.py

@@ -0,0 +1,65 @@
+"""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)"
+        )

app/model_manager.py

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

app/user_manager.py

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

blueprints/Canny to Image (Z-Image-Turbo).json

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

blueprints/Canny to Video (LTX 2.0).json

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

blueprints/ControlNet (Z-Image-Turbo).json

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

blueprints/Depth to Image (Z-Image-Turbo).json

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

blueprints/Depth to Video (ltx 2.0).json

@@ -4233,7 +4233,7 @@
         "extra": {
           "workflowRendererVersion": "LG"
         },
-        "category": "Video generation and editing/Depth to video",
+        "category": "Video generation and editing/Conditioned",
         "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."
       },
       {

blueprints/First-Last-Frame to Video (LTX-2.3).json

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

blueprints/First-Last-Frame to Video.json

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

blueprints/Image Captioning (gemini).json

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

blueprints/Image Depth Estimation (Depth Anything 3).json

@@ -0,0 +1,569 @@
+{
+  "revision": 0,
+  "last_node_id": 89,
+  "last_link_id": 0,
+  "nodes": [
+    {
+      "id": 89,
+      "type": "85e595bd-af9e-40ee-85c5-b98bb15da47a",
+      "pos": [
+        320,
+        520
+      ],
+      "size": [
+        400,
+        360
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "localized_name": "image",
+          "name": "image",
+          "type": "IMAGE",
+          "link": null
+        },
+        {
+          "name": "resolution",
+          "type": "INT",
+          "widget": {
+            "name": "resolution"
+          },
+          "link": null
+        },
+        {
+          "name": "resize_method",
+          "type": "COMBO",
+          "widget": {
+            "name": "resize_method"
+          },
+          "link": null
+        },
+        {
+          "label": "output_type",
+          "name": "output",
+          "type": "COMFY_DYNAMICCOMBO_V3",
+          "widget": {
+            "name": "output"
+          },
+          "link": null
+        },
+        {
+          "label": "output_normalization",
+          "name": "output.normalization",
+          "type": "COMBO",
+          "widget": {
+            "name": "output.normalization"
+          },
+          "link": null
+        },
+        {
+          "label": "apply_sky_clip",
+          "name": "output.apply_sky_clip",
+          "type": "BOOLEAN",
+          "widget": {
+            "name": "output.apply_sky_clip"
+          },
+          "link": null
+        },
+        {
+          "name": "model_name",
+          "type": "COMBO",
+          "widget": {
+            "name": "model_name"
+          },
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "localized_name": "IMAGE",
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": []
+        }
+      ],
+      "properties": {
+        "proxyWidgets": [
+          [
+            "87",
+            "resolution"
+          ],
+          [
+            "87",
+            "resize_method"
+          ],
+          [
+            "86",
+            "output"
+          ],
+          [
+            "86",
+            "output.normalization"
+          ],
+          [
+            "86",
+            "output.apply_sky_clip"
+          ],
+          [
+            "88",
+            "model_name"
+          ]
+        ],
+        "cnr_id": "comfy-core",
+        "ver": "0.24.0"
+      },
+      "widgets_values": [],
+      "title": "Image Depth Estimation (Depth Anything 3)"
+    }
+  ],
+  "links": [],
+  "version": 0.4,
+  "definitions": {
+    "subgraphs": [
+      {
+        "id": "85e595bd-af9e-40ee-85c5-b98bb15da47a",
+        "version": 1,
+        "state": {
+          "lastGroupId": 4,
+          "lastNodeId": 89,
+          "lastLinkId": 109,
+          "lastRerouteId": 0
+        },
+        "revision": 2,
+        "config": {},
+        "name": "Image Depth Estimation (Depth Anything 3)",
+        "inputNode": {
+          "id": -10,
+          "bounding": [
+            400,
+            90,
+            166.998046875,
+            188
+          ]
+        },
+        "outputNode": {
+          "id": -20,
+          "bounding": [
+            1250,
+            146,
+            128,
+            68
+          ]
+        },
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+            "linkIds": [
+              19
+            ],
+            "localized_name": "image",
+            "pos": [
+              542.998046875,
+              114
+            ]
+          },
+          {
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+            "name": "resolution",
+            "type": "INT",
+            "linkIds": [
+              22
+            ],
+            "pos": [
+              542.998046875,
+              134
+            ]
+          },
+          {
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+            "name": "resize_method",
+            "type": "COMBO",
+            "linkIds": [
+              23
+            ],
+            "pos": [
+              542.998046875,
+              154
+            ]
+          },
+          {
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+            "name": "output",
+            "type": "COMFY_DYNAMICCOMBO_V3",
+            "linkIds": [
+              24
+            ],
+            "label": "output_type",
+            "pos": [
+              542.998046875,
+              174
+            ]
+          },
+          {
+            "id": "1da5009b-4648-43e8-a257-16426630cf22",
+            "name": "output.normalization",
+            "type": "COMBO",
+            "linkIds": [
+              25
+            ],
+            "label": "output_normalization",
+            "pos": [
+              542.998046875,
+              194
+            ]
+          },
+          {
+            "id": "fd7edb33-5fb1-4538-a411-26e5039a9321",
+            "name": "output.apply_sky_clip",
+            "type": "BOOLEAN",
+            "linkIds": [
+              26
+            ],
+            "label": "apply_sky_clip",
+            "pos": [
+              542.998046875,
+              214
+            ]
+          },
+          {
+            "id": "b5be4c8a-b833-4f1e-8c94-3ed1dd722190",
+            "name": "model_name",
+            "type": "COMBO",
+            "linkIds": [
+              106
+            ],
+            "pos": [
+              542.998046875,
+              234
+            ]
+          }
+        ],
+        "outputs": [
+          {
+            "id": "478ab537-63bc-4d74-a9f0-c975f550880f",
+            "name": "IMAGE",
+            "type": "IMAGE",
+            "linkIds": [
+              7
+            ],
+            "localized_name": "IMAGE",
+            "pos": [
+              1274,
+              170
+            ]
+          }
+        ],
+        "widgets": [],
+        "nodes": [
+          {
+            "id": 86,
+            "type": "DA3Render",
+            "pos": [
+              800,
+              310
+            ],
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+              380,
+              130
+            ],
+            "flags": {},
+            "order": 0,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "da3_geometry",
+                "name": "da3_geometry",
+                "type": "DA3_GEOMETRY",
+                "link": 12
+              },
+              {
+                "localized_name": "output",
+                "name": "output",
+                "type": "COMFY_DYNAMICCOMBO_V3",
+                "widget": {
+                  "name": "output"
+                },
+                "link": 24
+              },
+              {
+                "localized_name": "output.normalization",
+                "name": "output.normalization",
+                "type": "COMBO",
+                "widget": {
+                  "name": "output.normalization"
+                },
+                "link": 25
+              },
+              {
+                "localized_name": "output.apply_sky_clip",
+                "name": "output.apply_sky_clip",
+                "type": "BOOLEAN",
+                "widget": {
+                  "name": "output.apply_sky_clip"
+                },
+                "link": 26
+              },
+              {
+                "name": "geometry",
+                "type": "DA3_GEOMETRY",
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "IMAGE",
+                "name": "IMAGE",
+                "type": "IMAGE",
+                "slot_index": 0,
+                "links": [
+                  7
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "DA3Render",
+              "cnr_id": "comfy-core",
+              "ver": "0.19.0"
+            },
+            "widgets_values": [
+              "depth",
+              "v2_style",
+              false
+            ]
+          },
+          {
+            "id": 87,
+            "type": "DA3Inference",
+            "pos": [
+              800,
+              50
+            ],
+            "size": [
+              390,
+              130
+            ],
+            "flags": {},
+            "order": 1,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "da3_model",
+                "name": "da3_model",
+                "type": "DA3_MODEL",
+                "link": 107
+              },
+              {
+                "localized_name": "image",
+                "name": "image",
+                "type": "IMAGE",
+                "link": 19
+              },
+              {
+                "localized_name": "resolution",
+                "name": "resolution",
+                "type": "INT",
+                "widget": {
+                  "name": "resolution"
+                },
+                "link": 22
+              },
+              {
+                "localized_name": "resize_method",
+                "name": "resize_method",
+                "type": "COMBO",
+                "widget": {
+                  "name": "resize_method"
+                },
+                "link": 23
+              },
+              {
+                "localized_name": "mode",
+                "name": "mode",
+                "type": "COMFY_DYNAMICCOMBO_V3",
+                "widget": {
+                  "name": "mode"
+                },
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "da3_geometry",
+                "name": "da3_geometry",
+                "type": "DA3_GEOMETRY",
+                "slot_index": 0,
+                "links": [
+                  12
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "DA3Inference",
+              "cnr_id": "comfy-core",
+              "ver": "0.19.0"
+            },
+            "widgets_values": [
+              504,
+              "upper_bound_resize",
+              "mono"
+            ]
+          },
+          {
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+            "type": "LoadDA3Model",
+            "pos": [
+              810,
+              -160
+            ],
+            "size": [
+              400,
+              140
+            ],
+            "flags": {},
+            "order": 2,
+            "mode": 0,
+            "inputs": [
+              {
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+                "name": "model_name",
+                "type": "COMBO",
+                "widget": {
+                  "name": "model_name"
+                },
+                "link": 106
+              },
+              {
+                "localized_name": "weight_dtype",
+                "name": "weight_dtype",
+                "type": "COMBO",
+                "widget": {
+                  "name": "weight_dtype"
+                },
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "DA3_MODEL",
+                "name": "DA3_MODEL",
+                "type": "DA3_MODEL",
+                "links": [
+                  107
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "LoadDA3Model",
+              "cnr_id": "comfy-core",
+              "ver": "0.24.0",
+              "models": [
+                {
+                  "name": "depth_anything_3_mono_large.safetensors",
+                  "url": "https://huggingface.co/Comfy-Org/Depth-Anything-3/resolve/main/geometry_estimation/depth_anything_3_mono_large.safetensors",
+                  "directory": "geometry_estimation"
+                }
+              ]
+            },
+            "widgets_values": [
+              "depth_anything_3_mono_large.safetensors",
+              "default"
+            ]
+          }
+        ],
+        "groups": [],
+        "links": [
+          {
+            "id": 12,
+            "origin_id": 87,
+            "origin_slot": 0,
+            "target_id": 86,
+            "target_slot": 0,
+            "type": "DA3_GEOMETRY"
+          },
+          {
+            "id": 19,
+            "origin_id": -10,
+            "origin_slot": 0,
+            "target_id": 87,
+            "target_slot": 1,
+            "type": "IMAGE"
+          },
+          {
+            "id": 7,
+            "origin_id": 86,
+            "origin_slot": 0,
+            "target_id": -20,
+            "target_slot": 0,
+            "type": "IMAGE"
+          },
+          {
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+            "origin_id": -10,
+            "origin_slot": 1,
+            "target_id": 87,
+            "target_slot": 2,
+            "type": "INT"
+          },
+          {
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+            "origin_id": -10,
+            "origin_slot": 2,
+            "target_id": 87,
+            "target_slot": 3,
+            "type": "COMBO"
+          },
+          {
+            "id": 24,
+            "origin_id": -10,
+            "origin_slot": 3,
+            "target_id": 86,
+            "target_slot": 1,
+            "type": "COMFY_DYNAMICCOMBO_V3"
+          },
+          {
+            "id": 25,
+            "origin_id": -10,
+            "origin_slot": 4,
+            "target_id": 86,
+            "target_slot": 2,
+            "type": "COMBO"
+          },
+          {
+            "id": 26,
+            "origin_id": -10,
+            "origin_slot": 5,
+            "target_id": 86,
+            "target_slot": 3,
+            "type": "BOOLEAN"
+          },
+          {
+            "id": 106,
+            "origin_id": -10,
+            "origin_slot": 6,
+            "target_id": 88,
+            "target_slot": 0,
+            "type": "COMBO"
+          },
+          {
+            "id": 107,
+            "origin_id": 88,
+            "origin_slot": 0,
+            "target_id": 87,
+            "target_slot": 0,
+            "type": "DA3_MODEL"
+          }
+        ],
+        "extra": {},
+        "category": "Conditioning & Preprocessors/Depth",
+        "description": "This subgraph takes an input image and produces a depth map using the Depth Anything 3 model, which recovers spatially consistent geometry from any number of views. It is ideal for single or multi-view images, videos, and 3D scenes where accurate depth estimation is needed for tasks like SLAM, novel view synthesis, or spatial perception. The model uses a plain transformer backbone and supports both monocular and multi-view inputs without."
+      }
+    ]
+  },
+  "extra": {
+    "BlueprintDescription": "This subgraph takes an input image and produces a depth map using the Depth Anything 3 model, which recovers spatially consistent geometry from any number of views. It is ideal for single or multi-view images, videos, and 3D scenes where accurate depth estimation is needed for tasks like SLAM, novel view synthesis, or spatial perception. The model uses a plain transformer backbone and supports both monocular and multi-view inputs without."
+  }
+}

blueprints/Image Depth Estimation (Lotus Depth).json

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 }

blueprints/Image Face Detection (Mediapipe).json

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+              },
+              {
+                "name": "face_landmarker",
+                "type": "FACE_LANDMARKER",
+                "link": 74
+              }
+            ],
+            "outputs": [
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+                "localized_name": "face_landmarks",
+                "name": "face_landmarks",
+                "type": "FACE_LANDMARKS",
+                "links": [
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+                  46
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+                "type": "COMBO",
+                "widget": {
+                  "name": "model_name"
+                },
+                "link": 86
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "FACE_DETECTION_MODEL",
+                "name": "FACE_DETECTION_MODEL",
+                "type": "FACE_DETECTION_MODEL",
+                "links": [
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+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "LoadMediaPipeFaceLandmarker",
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+              "ver": "0.22.0",
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+              "secondTabWidth": 65
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+                "widget": {
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+                "link": null
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+            "type": "BOOLEAN"
+          },
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+          {
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+            "target_slot": 0,
+            "type": "COMBO"
+          }
+        ],
+        "extra": {},
+        "category": "Conditioning & Preprocessors/Face Detection"
+      }
+    ]
+  },
+  "extra": {}
+}

blueprints/Image Segmentation (SAM3).json

@@ -703,7 +703,7 @@
           }
         ],
         "extra": {},
-        "category": "Image Tools/Image Segmentation",
+        "category": "Conditioning & Preprocessors/Segmentation & Mask",
         "description": "Segments images into masks using Meta SAM3 from text prompts, points, or boxes."
       }
     ]

blueprints/Image Upscale(Z-image-Turbo).json

@@ -1302,7 +1302,7 @@
         "extra": {
           "workflowRendererVersion": "LG"
         },
-        "category": "Image generation and editing/Enhance",
+        "category": "Image generation and editing/Upscale",
         "description": "Upscales images to higher resolution using Z-Image-Turbo."
       }
     ]
@@ -1312,4 +1312,4 @@
     "workflowRendererVersion": "LG"
   },
   "version": 0.4
-}
+}

blueprints/Image to Pose Map (SDPose-OOD).json

@@ -0,0 +1,888 @@
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+                "type": "COMBO",
+                "widget": {
+                  "name": "scale_method"
+                },
+                "link": 1705
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "resized",
+                "name": "resized",
+                "type": "*",
+                "links": [
+                  1698
+                ]
+              }
+            ],
+            "properties": {
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+              "cnr_id": "comfy-core",
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+              "ue_properties": {
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+                "version": "7.7",
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+              "area"
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+                "type": "POSE_KEYPOINT",
+                "link": 1699
+              },
+              {
+                "localized_name": "draw_body",
+                "name": "draw_body",
+                "type": "BOOLEAN",
+                "widget": {
+                  "name": "draw_body"
+                },
+                "link": 1706
+              },
+              {
+                "localized_name": "draw_hands",
+                "name": "draw_hands",
+                "type": "BOOLEAN",
+                "widget": {
+                  "name": "draw_hands"
+                },
+                "link": 1707
+              },
+              {
+                "localized_name": "draw_face",
+                "name": "draw_face",
+                "type": "BOOLEAN",
+                "widget": {
+                  "name": "draw_face"
+                },
+                "link": 1708
+              },
+              {
+                "localized_name": "draw_feet",
+                "name": "draw_feet",
+                "type": "BOOLEAN",
+                "widget": {
+                  "name": "draw_feet"
+                },
+                "link": 1709
+              },
+              {
+                "localized_name": "stick_width",
+                "name": "stick_width",
+                "type": "INT",
+                "widget": {
+                  "name": "stick_width"
+                },
+                "link": 1710
+              },
+              {
+                "localized_name": "face_point_size",
+                "name": "face_point_size",
+                "type": "INT",
+                "widget": {
+                  "name": "face_point_size"
+                },
+                "link": 1711
+              },
+              {
+                "localized_name": "score_threshold",
+                "name": "score_threshold",
+                "type": "FLOAT",
+                "widget": {
+                  "name": "score_threshold"
+                },
+                "link": 1712
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "IMAGE",
+                "name": "IMAGE",
+                "type": "IMAGE",
+                "links": [
+                  1701
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "SDPoseDrawKeypoints",
+              "cnr_id": "comfy-core",
+              "ver": "0.15.0",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "version": "7.7",
+                "input_ue_unconnectable": {}
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+            },
+            "widgets_values": [
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+            "type": "CheckpointLoaderSimple",
+            "pos": [
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+              3250
+            ],
+            "size": [
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+              190
+            ],
+            "flags": {},
+            "order": 2,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "ckpt_name",
+                "name": "ckpt_name",
+                "type": "COMBO",
+                "widget": {
+                  "name": "ckpt_name"
+                },
+                "link": 1713
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "MODEL",
+                "name": "MODEL",
+                "type": "MODEL",
+                "links": [
+                  1696
+                ]
+              },
+              {
+                "localized_name": "CLIP",
+                "name": "CLIP",
+                "type": "CLIP",
+                "links": []
+              },
+              {
+                "localized_name": "VAE",
+                "name": "VAE",
+                "type": "VAE",
+                "links": [
+                  1697
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "CheckpointLoaderSimple",
+              "cnr_id": "comfy-core",
+              "ver": "0.15.0",
+              "models": [
+                {
+                  "name": "sdpose_wholebody_fp16.safetensors",
+                  "url": "https://huggingface.co/Comfy-Org/SDPose/resolve/main/checkpoints/sdpose_wholebody_fp16.safetensors",
+                  "directory": "checkpoints"
+                }
+              ],
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "version": "7.7",
+                "input_ue_unconnectable": {}
+              }
+            },
+            "widgets_values": [
+              "sdpose_wholebody_fp16.safetensors"
+            ]
+          }
+        ],
+        "groups": [],
+        "links": [
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+            "origin_id": 673,
+            "origin_slot": 0,
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+            "target_slot": 0,
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+          },
+          {
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+            "origin_id": 673,
+            "origin_slot": 2,
+            "target_id": 671,
+            "target_slot": 1,
+            "type": "VAE"
+          },
+          {
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+            "origin_id": 674,
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+            "target_slot": 2,
+            "type": "IMAGE"
+          },
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+            "target_slot": 0,
+            "type": "IMAGE,MASK"
+          },
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+            "origin_slot": 0,
+            "target_id": -20,
+            "target_slot": 0,
+            "type": "IMAGE"
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+            "origin_id": -10,
+            "origin_slot": 1,
+            "target_id": 674,
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+            "type": "INT"
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+            "origin_id": -10,
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+          },
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+            "target_id": 672,
+            "target_slot": 1,
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+            "target_slot": 2,
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+          {
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+            "target_id": 672,
+            "target_slot": 3,
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+            "target_id": 672,
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+            "origin_id": -10,
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+            "target_slot": 0,
+            "type": "COMBO"
+          },
+          {
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+            "origin_id": -10,
+            "origin_slot": 11,
+            "target_id": 671,
+            "target_slot": 3,
+            "type": "BOUNDING_BOX"
+          },
+          {
+            "id": 1715,
+            "origin_id": 671,
+            "origin_slot": 0,
+            "target_id": -20,
+            "target_slot": 1,
+            "type": "POSE_KEYPOINT"
+          }
+        ],
+        "extra": {
+          "workflowRendererVersion": "LG"
+        },
+        "category": "Conditioning & Preprocessors/Pose",
+        "description": "Extracts human pose keypoints and stick-figure visuals from an image using SDPose-OOD, with optional bounding-box input per subject."
+      }
+    ]
+  },
+  "extra": {
+    "ue_links": []
+  }
+}

blueprints/Pose to Image (Z-Image-Turbo).json

@@ -1298,7 +1298,7 @@
           "VHS_MetadataImage": true,
           "VHS_KeepIntermediate": true
         },
-        "category": "Image generation and editing/Pose to image",
+        "category": "Image generation and editing/Conditioned",
         "description": "Generates an image from pose keypoints using Z-Image-Turbo with text conditioning."
       }
     ]

blueprints/Pose to Video (LTX 2.0).json

@@ -3870,7 +3870,7 @@
         "extra": {
           "workflowRendererVersion": "LG"
         },
-        "category": "Video generation and editing/Pose to video",
+        "category": "Video generation and editing/Conditioned",
         "description": "Generates video from pose reference frames using LTX-2, with optional synchronized audio."
       }
     ]

blueprints/Prompt Enhance.json

@@ -270,7 +270,7 @@
         "extra": {
           "workflowRendererVersion": "LG"
         },
-        "category": "Text generation/Prompt enhance",
+        "category": "Text Tools",
         "description": "Expands short text prompts into detailed descriptions using a text generation model for better generation quality."
       }
     ]

blueprints/Remove Background (BiRefNet).json

@@ -389,7 +389,7 @@
           }
         ],
         "extra": {},
-        "category": "Image generation and editing/Background Removal"
+        "category": "Image Tools/Background Removal"
       }
     ]
   },

blueprints/Select Per-Line Text by Index.json

@@ -0,0 +1,485 @@
+{
+  "revision": 0,
+  "last_node_id": 10,
+  "last_link_id": 0,
+  "nodes": [
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+        8590
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+        360
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+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [
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+          "name": "text_per_line",
+          "type": "STRING",
+          "widget": {
+            "name": "text_per_line"
+          },
+          "link": null
+        },
+        {
+          "localized_name": "index",
+          "name": "index",
+          "type": "INT",
+          "widget": {
+            "name": "index"
+          },
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "localized_name": "selected_line",
+          "name": "selected_line",
+          "type": "STRING",
+          "links": []
+        }
+      ],
+      "properties": {
+        "proxyWidgets": [
+          [
+            "2",
+            "string"
+          ],
+          [
+            "3",
+            "value"
+          ]
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+        "cnr_id": "comfy-core",
+        "ver": "0.19.0",
+        "ue_properties": {
+          "widget_ue_connectable": {},
+          "input_ue_unconnectable": {}
+        }
+      },
+      "widgets_values": [],
+      "title": "Select Per-Line Text by Index"
+    }
+  ],
+  "links": [],
+  "version": 0.4,
+  "definitions": {
+    "subgraphs": [
+      {
+        "id": "3fb7557a-470d-4983-9d8c-6d5caa9788f0",
+        "version": 1,
+        "state": {
+          "lastGroupId": 0,
+          "lastNodeId": 10,
+          "lastLinkId": 14,
+          "lastRerouteId": 0
+        },
+        "revision": 0,
+        "config": {},
+        "name": "Select Per-Line Text by Index",
+        "inputNode": {
+          "id": -10,
+          "bounding": [
+            -990,
+            8595,
+            128,
+            88
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+        },
+        "outputNode": {
+          "id": -20,
+          "bounding": [
+            710,
+            8585,
+            128,
+            68
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+        },
+        "inputs": [
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+            "id": "75417d82-a934-4ac9-b667-d8dcd5a3bfb3",
+            "name": "text_per_line",
+            "type": "STRING",
+            "linkIds": [
+              13
+            ],
+            "localized_name": "text_per_line",
+            "pos": [
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+              8619
+            ]
+          },
+          {
+            "id": "46e69a73-1804-4ca6-9175-31445bf0be96",
+            "name": "index",
+            "type": "INT",
+            "linkIds": [
+              14
+            ],
+            "localized_name": "index",
+            "pos": [
+              -886,
+              8639
+            ]
+          }
+        ],
+        "outputs": [
+          {
+            "id": "e34e8ad1-84d2-4bd2-a460-eb7de6067c10",
+            "name": "selected_line",
+            "type": "STRING",
+            "linkIds": [
+              10
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+            "localized_name": "selected_line",
+            "pos": [
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+              8609
+            ]
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+        ],
+        "widgets": [],
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+          {
+            "id": 1,
+            "type": "PreviewAny",
+            "pos": [
+              -500,
+              8400
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+            "size": [
+              230,
+              180
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+            "flags": {},
+            "order": 0,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "source",
+                "name": "source",
+                "type": "*",
+                "link": 1
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "STRING",
+                "name": "STRING",
+                "type": "STRING",
+                "links": [
+                  6
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "PreviewAny",
+              "cnr_id": "comfy-core",
+              "ver": "0.19.0",
+              "ue_properties": {
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+                "input_ue_unconnectable": {}
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+            },
+            "widgets_values": [
+              null,
+              null,
+              null
+            ]
+          },
+          {
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+            "type": "RegexExtract",
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+              8740
+            ],
+            "size": [
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+              460
+            ],
+            "flags": {},
+            "order": 1,
+            "mode": 0,
+            "showAdvanced": false,
+            "inputs": [
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+                "name": "string",
+                "type": "STRING",
+                "widget": {
+                  "name": "string"
+                },
+                "link": 13
+              },
+              {
+                "localized_name": "regex_pattern",
+                "name": "regex_pattern",
+                "type": "STRING",
+                "widget": {
+                  "name": "regex_pattern"
+                },
+                "link": 9
+              },
+              {
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+                "name": "mode",
+                "type": "COMBO",
+                "widget": {
+                  "name": "mode"
+                },
+                "link": null
+              },
+              {
+                "localized_name": "case_insensitive",
+                "name": "case_insensitive",
+                "type": "BOOLEAN",
+                "widget": {
+                  "name": "case_insensitive"
+                },
+                "link": null
+              },
+              {
+                "localized_name": "multiline",
+                "name": "multiline",
+                "type": "BOOLEAN",
+                "widget": {
+                  "name": "multiline"
+                },
+                "link": null
+              },
+              {
+                "localized_name": "dotall",
+                "name": "dotall",
+                "type": "BOOLEAN",
+                "widget": {
+                  "name": "dotall"
+                },
+                "link": null
+              },
+              {
+                "localized_name": "group_index",
+                "name": "group_index",
+                "type": "INT",
+                "widget": {
+                  "name": "group_index"
+                },
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "STRING",
+                "name": "STRING",
+                "type": "STRING",
+                "links": [
+                  10
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "RegexExtract",
+              "cnr_id": "comfy-core",
+              "ver": "0.19.0",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {}
+              }
+            },
+            "widgets_values": [
+              "",
+              "",
+              "First Group",
+              false,
+              false,
+              false,
+              1
+            ]
+          },
+          {
+            "id": 3,
+            "type": "PrimitiveInt",
+            "pos": [
+              -810,
+              8400
+            ],
+            "size": [
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+              110
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+            "flags": {},
+            "order": 2,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "value",
+                "name": "value",
+                "type": "INT",
+                "widget": {
+                  "name": "value"
+                },
+                "link": 14
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "INT",
+                "name": "INT",
+                "type": "INT",
+                "links": [
+                  1
+                ]
+              }
+            ],
+            "title": "Int (line index)",
+            "properties": {
+              "Node name for S&R": "Int (line index)",
+              "cnr_id": "comfy-core",
+              "ver": "0.19.0",
+              "ue_properties": {
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+                "input_ue_unconnectable": {}
+              }
+            },
+            "widgets_values": [
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+              "fixed"
+            ]
+          },
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+            "id": 8,
+            "type": "StringReplace",
+            "pos": [
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+              8400
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+            "size": [
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+              280
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+            "flags": {},
+            "order": 3,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "string",
+                "name": "string",
+                "type": "STRING",
+                "widget": {
+                  "name": "string"
+                },
+                "link": null
+              },
+              {
+                "localized_name": "find",
+                "name": "find",
+                "type": "STRING",
+                "widget": {
+                  "name": "find"
+                },
+                "link": null
+              },
+              {
+                "localized_name": "replace",
+                "name": "replace",
+                "type": "STRING",
+                "widget": {
+                  "name": "replace"
+                },
+                "link": 6
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "STRING",
+                "name": "STRING",
+                "type": "STRING",
+                "links": [
+                  9
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "StringReplace",
+              "cnr_id": "comfy-core",
+              "ver": "0.19.0",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {}
+              }
+            },
+            "widgets_values": [
+              "^(?:[^\\n]*\\n){index}([^\\n]*)(?:\\n|$)",
+              "index",
+              ""
+            ]
+          }
+        ],
+        "groups": [],
+        "links": [
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+            "origin_id": 2,
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+            "origin_id": -10,
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+            "origin_slot": 1,
+            "target_id": 3,
+            "target_slot": 0,
+            "type": "INT"
+          }
+        ],
+        "extra": {},
+        "category": "Text Tools",
+        "description": "Selects one line from multiline text by zero-based index for batch or list-driven prompt workflows."
+      }
+    ]
+  },
+  "extra": {
+    "ue_links": [],
+    "links_added_by_ue": []
+  }
+}

blueprints/Split Image Grid to Tiles.json

@@ -0,0 +1,714 @@
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+  "last_link_id": 0,
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+          "widget": {
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+          "name": "rows",
+          "type": "INT",
+          "widget": {
+            "name": "rows"
+          },
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "localized_name": "tiles",
+          "name": "tiles",
+          "type": "IMAGE",
+          "links": []
+        }
+      ],
+      "properties": {
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+            "value"
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+        "secondTabText": "Send Back",
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+      "widgets_values": [],
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+        "outputs": [
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+            "name": "tiles",
+            "type": "IMAGE",
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+            "size": [
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+              170
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+            "order": 0,
+            "mode": 0,
+            "inputs": [
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+                "localized_name": "image",
+                "name": "image",
+                "type": "IMAGE",
+                "link": 386
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+              {
+                "localized_name": "tile_width",
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+                "widget": {
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+              },
+              {
+                "localized_name": "tile_height",
+                "name": "tile_height",
+                "type": "INT",
+                "widget": {
+                  "name": "tile_height"
+                },
+                "link": 404
+              },
+              {
+                "localized_name": "overlap",
+                "name": "overlap",
+                "type": "INT",
+                "widget": {
+                  "name": "overlap"
+                },
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "IMAGE",
+                "name": "IMAGE",
+                "shape": 6,
+                "type": "IMAGE",
+                "links": [
+                  394
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "SplitImageToTileList",
+              "cnr_id": "comfy-core",
+              "ver": "0.20.1",
+              "enableTabs": false,
+              "tabWidth": 65,
+              "tabXOffset": 10,
+              "hasSecondTab": false,
+              "secondTabText": "Send Back",
+              "secondTabOffset": 80,
+              "secondTabWidth": 65
+            },
+            "widgets_values": [
+              1024,
+              1024,
+              0
+            ]
+          },
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+            "id": 231,
+            "type": "ComfyMathExpression",
+            "pos": [
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+              330
+            ],
+            "size": [
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+              190
+            ],
+            "flags": {},
+            "order": 4,
+            "mode": 0,
+            "inputs": [
+              {
+                "label": "a",
+                "localized_name": "values.a",
+                "name": "values.a",
+                "type": "FLOAT,INT,BOOLEAN",
+                "link": 390
+              },
+              {
+                "label": "b",
+                "localized_name": "values.b",
+                "name": "values.b",
+                "shape": 7,
+                "type": "FLOAT,INT,BOOLEAN",
+                "link": 429
+              },
+              {
+                "label": "c",
+                "localized_name": "values.c",
+                "name": "values.c",
+                "shape": 7,
+                "type": "FLOAT,INT,BOOLEAN",
+                "link": null
+              },
+              {
+                "localized_name": "expression",
+                "name": "expression",
+                "type": "STRING",
+                "widget": {
+                  "name": "expression"
+                },
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "FLOAT",
+                "name": "FLOAT",
+                "type": "FLOAT",
+                "links": null
+              },
+              {
+                "localized_name": "INT",
+                "name": "INT",
+                "type": "INT",
+                "links": [
+                  404
+                ]
+              },
+              {
+                "localized_name": "BOOL",
+                "name": "BOOL",
+                "type": "BOOLEAN",
+                "links": null
+              }
+            ],
+            "title": "Math Expression （Height）",
+            "properties": {
+              "Node name for S&R": "ComfyMathExpression",
+              "cnr_id": "comfy-core",
+              "ver": "0.18.1",
+              "enableTabs": false,
+              "tabWidth": 65,
+              "tabXOffset": 10,
+              "hasSecondTab": false,
+              "secondTabText": "Send Back",
+              "secondTabOffset": 80,
+              "secondTabWidth": 65,
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "version": "7.7",
+                "input_ue_unconnectable": {}
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+            },
+            "widgets_values": [
+              "max(1, (int(a) + int(b) - 1) // int(b))"
+            ]
+          },
+          {
+            "id": 229,
+            "type": "ComfyMathExpression",
+            "pos": [
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+              -30
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+            "size": [
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+            "flags": {},
+            "order": 2,
+            "mode": 0,
+            "inputs": [
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+                "label": "a",
+                "localized_name": "values.a",
+                "name": "values.a",
+                "type": "FLOAT,INT,BOOLEAN",
+                "link": 387
+              },
+              {
+                "label": "b",
+                "localized_name": "values.b",
+                "name": "values.b",
+                "shape": 7,
+                "type": "FLOAT,INT,BOOLEAN",
+                "link": 388
+              },
+              {
+                "label": "c",
+                "localized_name": "values.c",
+                "name": "values.c",
+                "shape": 7,
+                "type": "FLOAT,INT,BOOLEAN",
+                "link": null
+              },
+              {
+                "localized_name": "expression",
+                "name": "expression",
+                "type": "STRING",
+                "widget": {
+                  "name": "expression"
+                },
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "FLOAT",
+                "name": "FLOAT",
+                "type": "FLOAT",
+                "links": null
+              },
+              {
+                "localized_name": "INT",
+                "name": "INT",
+                "type": "INT",
+                "links": [
+                  403
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+              },
+              {
+                "localized_name": "BOOL",
+                "name": "BOOL",
+                "type": "BOOLEAN",
+                "links": null
+              }
+            ],
+            "title": "Math Expression （Width）",
+            "properties": {
+              "Node name for S&R": "ComfyMathExpression",
+              "cnr_id": "comfy-core",
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+              "tabXOffset": 10,
+              "hasSecondTab": false,
+              "secondTabText": "Send Back",
+              "secondTabOffset": 80,
+              "secondTabWidth": 65,
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "version": "7.7",
+                "input_ue_unconnectable": {}
+              }
+            },
+            "widgets_values": [
+              "max(1, (int(a) + int(b) - 1) // int(b))"
+            ]
+          },
+          {
+            "id": 228,
+            "type": "PrimitiveInt",
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+              90
+            ],
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+            "flags": {},
+            "order": 1,
+            "mode": 0,
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+              {
+                "localized_name": "value",
+                "name": "value",
+                "type": "INT",
+                "widget": {
+                  "name": "value"
+                },
+                "link": 427
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "INT",
+                "name": "INT",
+                "type": "INT",
+                "links": [
+                  388
+                ]
+              }
+            ],
+            "title": "Int (grid columns)",
+            "properties": {
+              "Node name for S&R": "Int (grid columns)",
+              "cnr_id": "comfy-core",
+              "ver": "0.18.1",
+              "enableTabs": false,
+              "tabWidth": 65,
+              "tabXOffset": 10,
+              "hasSecondTab": false,
+              "secondTabText": "Send Back",
+              "secondTabOffset": 80,
+              "secondTabWidth": 65,
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "version": "7.7",
+                "input_ue_unconnectable": {}
+              }
+            },
+            "widgets_values": [
+              2,
+              "fixed"
+            ]
+          },
+          {
+            "id": 230,
+            "type": "GetImageSize",
+            "pos": [
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+              290
+            ],
+            "size": [
+              230,
+              100
+            ],
+            "flags": {},
+            "order": 3,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "image",
+                "name": "image",
+                "type": "IMAGE",
+                "link": 389
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "width",
+                "name": "width",
+                "type": "INT",
+                "links": [
+                  387
+                ]
+              },
+              {
+                "localized_name": "height",
+                "name": "height",
+                "type": "INT",
+                "links": [
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+              },
+              {
+                "localized_name": "batch_size",
+                "name": "batch_size",
+                "type": "INT",
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+            ],
+            "properties": {
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+              "cnr_id": "comfy-core",
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+              "enableTabs": false,
+              "tabWidth": 65,
+              "tabXOffset": 10,
+              "hasSecondTab": false,
+              "secondTabText": "Send Back",
+              "secondTabOffset": 80,
+              "secondTabWidth": 65,
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "version": "7.7",
+                "input_ue_unconnectable": {}
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+            "order": 5,
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+                "name": "value",
+                "type": "INT",
+                "widget": {
+                  "name": "value"
+                },
+                "link": 428
+              }
+            ],
+            "outputs": [
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+                "localized_name": "INT",
+                "name": "INT",
+                "type": "INT",
+                "links": [
+                  429
+                ]
+              }
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+            "properties": {
+              "Node name for S&R": "Int (grid rows)",
+              "cnr_id": "comfy-core",
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+              "enableTabs": false,
+              "tabWidth": 65,
+              "tabXOffset": 10,
+              "hasSecondTab": false,
+              "secondTabText": "Send Back",
+              "secondTabOffset": 80,
+              "secondTabWidth": 65,
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "version": "7.7",
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+        "groups": [],
+        "links": [
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+            "origin_id": 229,
+            "origin_slot": 1,
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+            "origin_id": 231,
+            "origin_slot": 1,
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+            "target_slot": 2,
+            "type": "INT"
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+            "origin_id": 230,
+            "origin_slot": 1,
+            "target_id": 231,
+            "target_slot": 0,
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+            "origin_id": 230,
+            "origin_slot": 0,
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+            "origin_slot": 0,
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+            "origin_id": -10,
+            "origin_slot": 0,
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+            "target_slot": 0,
+            "type": "IMAGE"
+          },
+          {
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+            "origin_id": -10,
+            "origin_slot": 0,
+            "target_id": 230,
+            "target_slot": 0,
+            "type": "IMAGE"
+          },
+          {
+            "id": 394,
+            "origin_id": 225,
+            "origin_slot": 0,
+            "target_id": -20,
+            "target_slot": 0,
+            "type": "IMAGE"
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+          {
+            "id": 427,
+            "origin_id": -10,
+            "origin_slot": 1,
+            "target_id": 228,
+            "target_slot": 0,
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+            "origin_id": -10,
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+            "target_slot": 0,
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+            "target_id": 231,
+            "target_slot": 1,
+            "type": "INT"
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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": {}
+}

blueprints/Video Captioning (Gemini).json

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

blueprints/Video Depth Estimation (Depth Anything 3).json

@@ -0,0 +1,825 @@
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+      "mode": 0,
+      "inputs": [
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+          "name": "video",
+          "type": "VIDEO",
+          "link": null
+        },
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+          "widget": {
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+          "link": null
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+          "name": "duration",
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+          "widget": {
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+          "link": null
+        },
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+          "name": "resolution",
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+          "widget": {
+            "name": "resolution"
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+        {
+          "name": "resize_method",
+          "type": "COMBO",
+          "widget": {
+            "name": "resize_method"
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+          "label": "normalization",
+          "name": "output.normalization",
+          "type": "COMBO",
+          "widget": {
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+          "link": null
+        },
+        {
+          "name": "output.apply_sky_clip",
+          "type": "BOOLEAN",
+          "widget": {
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+          "link": null
+        },
+        {
+          "name": "model_name",
+          "type": "COMBO",
+          "widget": {
+            "name": "model_name"
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+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "localized_name": "IMAGE",
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": []
+        },
+        {
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+          "type": "AUDIO",
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+        {
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+        "cnr_id": "comfy-core",
+        "ver": "0.24.0"
+      },
+      "widgets_values": [],
+      "title": "Video Depth Estimation (Depth Anything 3)"
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+  ],
+  "links": [],
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+  "definitions": {
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+          },
+          {
+            "id": "97a1f63e-1585-4a40-9dec-e2700120d84a",
+            "name": "start_time",
+            "type": "FLOAT",
+            "linkIds": [
+              121
+            ],
+            "pos": [
+              -86.087890625,
+              174
+            ]
+          },
+          {
+            "id": "4dbbd3b3-c5ee-4a56-a0d3-3268d3b2fd64",
+            "name": "duration",
+            "type": "FLOAT",
+            "linkIds": [
+              122
+            ],
+            "pos": [
+              -86.087890625,
+              194
+            ]
+          },
+          {
+            "id": "16f55101-f99d-4c0c-bebf-c3b31c54f13e",
+            "name": "resolution",
+            "type": "INT",
+            "linkIds": [
+              124
+            ],
+            "pos": [
+              -86.087890625,
+              214
+            ]
+          },
+          {
+            "id": "d9cd7693-4bb3-4ed7-9a75-276b997abcd9",
+            "name": "resize_method",
+            "type": "COMBO",
+            "linkIds": [
+              125
+            ],
+            "pos": [
+              -86.087890625,
+              234
+            ]
+          },
+          {
+            "id": "a6e90532-323b-462e-ba9c-1672384d5b31",
+            "name": "output",
+            "type": "COMFY_DYNAMICCOMBO_V3",
+            "linkIds": [
+              126
+            ],
+            "label": "output_type",
+            "pos": [
+              -86.087890625,
+              254
+            ]
+          },
+          {
+            "id": "69e6aeef-437d-4fde-b2fc-d5ab9369238d",
+            "name": "output.normalization",
+            "type": "COMBO",
+            "linkIds": [
+              127
+            ],
+            "label": "normalization",
+            "pos": [
+              -86.087890625,
+              274
+            ]
+          },
+          {
+            "id": "73206f72-f89a-4698-885e-5d9277df2998",
+            "name": "output.apply_sky_clip",
+            "type": "BOOLEAN",
+            "linkIds": [
+              128
+            ],
+            "pos": [
+              -86.087890625,
+              294
+            ]
+          },
+          {
+            "id": "dddbc7fc-9431-448a-9ed3-9aa62404288b",
+            "name": "model_name",
+            "type": "COMBO",
+            "linkIds": [
+              129
+            ],
+            "pos": [
+              -86.087890625,
+              314
+            ]
+          }
+        ],
+        "outputs": [
+          {
+            "id": "478ab537-63bc-4d74-a9f0-c975f550880f",
+            "name": "IMAGE",
+            "type": "IMAGE",
+            "linkIds": [
+              7
+            ],
+            "localized_name": "IMAGE",
+            "pos": [
+              1544,
+              164
+            ]
+          },
+          {
+            "id": "cdaf037e-79bc-4a94-b06c-0fd32e76f615",
+            "name": "audio",
+            "type": "AUDIO",
+            "linkIds": [
+              112
+            ],
+            "pos": [
+              1544,
+              184
+            ]
+          },
+          {
+            "id": "4c0e5484-d193-49c7-b107-92619628880a",
+            "name": "fps",
+            "type": "FLOAT",
+            "linkIds": [
+              113
+            ],
+            "pos": [
+              1544,
+              204
+            ]
+          }
+        ],
+        "widgets": [],
+        "nodes": [
+          {
+            "id": 92,
+            "type": "DA3Render",
+            "pos": [
+              740,
+              230
+            ],
+            "size": [
+              380,
+              130
+            ],
+            "flags": {},
+            "order": 0,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "da3_geometry",
+                "name": "da3_geometry",
+                "type": "DA3_GEOMETRY",
+                "link": 12
+              },
+              {
+                "localized_name": "output",
+                "name": "output",
+                "type": "COMFY_DYNAMICCOMBO_V3",
+                "widget": {
+                  "name": "output"
+                },
+                "link": 126
+              },
+              {
+                "localized_name": "output.normalization",
+                "name": "output.normalization",
+                "type": "COMBO",
+                "widget": {
+                  "name": "output.normalization"
+                },
+                "link": 127
+              },
+              {
+                "localized_name": "output.apply_sky_clip",
+                "name": "output.apply_sky_clip",
+                "type": "BOOLEAN",
+                "widget": {
+                  "name": "output.apply_sky_clip"
+                },
+                "link": 128
+              },
+              {
+                "name": "geometry",
+                "type": "DA3_GEOMETRY",
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "IMAGE",
+                "name": "IMAGE",
+                "type": "IMAGE",
+                "slot_index": 0,
+                "links": [
+                  7
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "DA3Render",
+              "cnr_id": "comfy-core",
+              "ver": "0.19.0"
+            },
+            "widgets_values": [
+              "depth",
+              "v2_style",
+              false
+            ]
+          },
+          {
+            "id": 93,
+            "type": "DA3Inference",
+            "pos": [
+              740,
+              -30
+            ],
+            "size": [
+              390,
+              130
+            ],
+            "flags": {},
+            "order": 1,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "da3_model",
+                "name": "da3_model",
+                "type": "DA3_MODEL",
+                "link": 107
+              },
+              {
+                "localized_name": "image",
+                "name": "image",
+                "type": "IMAGE",
+                "link": 111
+              },
+              {
+                "localized_name": "resolution",
+                "name": "resolution",
+                "type": "INT",
+                "widget": {
+                  "name": "resolution"
+                },
+                "link": 124
+              },
+              {
+                "localized_name": "resize_method",
+                "name": "resize_method",
+                "type": "COMBO",
+                "widget": {
+                  "name": "resize_method"
+                },
+                "link": 125
+              },
+              {
+                "localized_name": "mode",
+                "name": "mode",
+                "type": "COMFY_DYNAMICCOMBO_V3",
+                "widget": {
+                  "name": "mode"
+                },
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "da3_geometry",
+                "name": "da3_geometry",
+                "type": "DA3_GEOMETRY",
+                "slot_index": 0,
+                "links": [
+                  12
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "DA3Inference",
+              "cnr_id": "comfy-core",
+              "ver": "0.19.0"
+            },
+            "widgets_values": [
+              504,
+              "lower_bound_resize",
+              "mono"
+            ]
+          },
+          {
+            "id": 94,
+            "type": "LoadDA3Model",
+            "pos": [
+              50,
+              410
+            ],
+            "size": [
+              400,
+              140
+            ],
+            "flags": {},
+            "order": 2,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "model_name",
+                "name": "model_name",
+                "type": "COMBO",
+                "widget": {
+                  "name": "model_name"
+                },
+                "link": 129
+              },
+              {
+                "localized_name": "weight_dtype",
+                "name": "weight_dtype",
+                "type": "COMBO",
+                "widget": {
+                  "name": "weight_dtype"
+                },
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "DA3_MODEL",
+                "name": "DA3_MODEL",
+                "type": "DA3_MODEL",
+                "links": [
+                  107
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "LoadDA3Model",
+              "cnr_id": "comfy-core",
+              "ver": "0.24.0",
+              "models": [
+                {
+                  "name": "depth_anything_3_mono_large.safetensors",
+                  "url": "https://huggingface.co/Comfy-Org/Depth-Anything-3/resolve/main/geometry_estimation/depth_anything_3_mono_large.safetensors",
+                  "directory": "geometry_estimation"
+                }
+              ]
+            },
+            "widgets_values": [
+              "depth_anything_3_mono_large.safetensors",
+              "default"
+            ]
+          },
+          {
+            "id": 95,
+            "type": "GetVideoComponents",
+            "pos": [
+              70,
+              -140
+            ],
+            "size": [
+              260,
+              120
+            ],
+            "flags": {},
+            "order": 3,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "video",
+                "name": "video",
+                "type": "VIDEO",
+                "link": 120
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "images",
+                "name": "images",
+                "type": "IMAGE",
+                "links": [
+                  111
+                ]
+              },
+              {
+                "localized_name": "audio",
+                "name": "audio",
+                "type": "AUDIO",
+                "links": [
+                  112
+                ]
+              },
+              {
+                "localized_name": "fps",
+                "name": "fps",
+                "type": "FLOAT",
+                "links": [
+                  113
+                ]
+              },
+              {
+                "localized_name": "bit_depth",
+                "name": "bit_depth",
+                "type": "INT",
+                "links": null
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "GetVideoComponents",
+              "cnr_id": "comfy-core",
+              "ver": "0.24.0"
+            }
+          },
+          {
+            "id": 96,
+            "type": "Video Slice",
+            "pos": [
+              70,
+              -360
+            ],
+            "size": [
+              270,
+              170
+            ],
+            "flags": {},
+            "order": 4,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "video",
+                "name": "video",
+                "type": "VIDEO",
+                "link": 119
+              },
+              {
+                "localized_name": "start_time",
+                "name": "start_time",
+                "type": "FLOAT",
+                "widget": {
+                  "name": "start_time"
+                },
+                "link": 121
+              },
+              {
+                "localized_name": "duration",
+                "name": "duration",
+                "type": "FLOAT",
+                "widget": {
+                  "name": "duration"
+                },
+                "link": 122
+              },
+              {
+                "localized_name": "strict_duration",
+                "name": "strict_duration",
+                "type": "BOOLEAN",
+                "widget": {
+                  "name": "strict_duration"
+                },
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "VIDEO",
+                "name": "VIDEO",
+                "type": "VIDEO",
+                "links": [
+                  120
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "Video Slice",
+              "cnr_id": "comfy-core",
+              "ver": "0.24.0"
+            },
+            "widgets_values": [
+              0,
+              5,
+              false
+            ]
+          }
+        ],
+        "groups": [],
+        "links": [
+          {
+            "id": 12,
+            "origin_id": 93,
+            "origin_slot": 0,
+            "target_id": 92,
+            "target_slot": 0,
+            "type": "DA3_GEOMETRY"
+          },
+          {
+            "id": 7,
+            "origin_id": 92,
+            "origin_slot": 0,
+            "target_id": -20,
+            "target_slot": 0,
+            "type": "IMAGE"
+          },
+          {
+            "id": 107,
+            "origin_id": 94,
+            "origin_slot": 0,
+            "target_id": 93,
+            "target_slot": 0,
+            "type": "DA3_MODEL"
+          },
+          {
+            "id": 111,
+            "origin_id": 95,
+            "origin_slot": 0,
+            "target_id": 93,
+            "target_slot": 1,
+            "type": "IMAGE"
+          },
+          {
+            "id": 112,
+            "origin_id": 95,
+            "origin_slot": 1,
+            "target_id": -20,
+            "target_slot": 1,
+            "type": "AUDIO"
+          },
+          {
+            "id": 113,
+            "origin_id": 95,
+            "origin_slot": 2,
+            "target_id": -20,
+            "target_slot": 2,
+            "type": "FLOAT"
+          },
+          {
+            "id": 119,
+            "origin_id": -10,
+            "origin_slot": 0,
+            "target_id": 96,
+            "target_slot": 0,
+            "type": "VIDEO"
+          },
+          {
+            "id": 120,
+            "origin_id": 96,
+            "origin_slot": 0,
+            "target_id": 95,
+            "target_slot": 0,
+            "type": "VIDEO"
+          },
+          {
+            "id": 121,
+            "origin_id": -10,
+            "origin_slot": 1,
+            "target_id": 96,
+            "target_slot": 1,
+            "type": "FLOAT"
+          },
+          {
+            "id": 122,
+            "origin_id": -10,
+            "origin_slot": 2,
+            "target_id": 96,
+            "target_slot": 2,
+            "type": "FLOAT"
+          },
+          {
+            "id": 124,
+            "origin_id": -10,
+            "origin_slot": 3,
+            "target_id": 93,
+            "target_slot": 2,
+            "type": "INT"
+          },
+          {
+            "id": 125,
+            "origin_id": -10,
+            "origin_slot": 4,
+            "target_id": 93,
+            "target_slot": 3,
+            "type": "COMBO"
+          },
+          {
+            "id": 126,
+            "origin_id": -10,
+            "origin_slot": 5,
+            "target_id": 92,
+            "target_slot": 1,
+            "type": "COMFY_DYNAMICCOMBO_V3"
+          },
+          {
+            "id": 127,
+            "origin_id": -10,
+            "origin_slot": 6,
+            "target_id": 92,
+            "target_slot": 2,
+            "type": "COMBO"
+          },
+          {
+            "id": 128,
+            "origin_id": -10,
+            "origin_slot": 7,
+            "target_id": 92,
+            "target_slot": 3,
+            "type": "BOOLEAN"
+          },
+          {
+            "id": 129,
+            "origin_id": -10,
+            "origin_slot": 8,
+            "target_id": 94,
+            "target_slot": 0,
+            "type": "COMBO"
+          }
+        ],
+        "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."
+  }
+}

blueprints/Video Segmentation (SAM3).json

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

blueprints/Video Upscale(GAN x4).json

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

comfy/background_removal/birefnet.py

@@ -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 = relative_position_bias.permute(2, 0, 1).contiguous()  # nH, Wh*Ww, Wh*Ww
+        relative_position_bias = comfy.ops.cast_to_input(relative_position_bias.permute(2, 0, 1).contiguous(), attn)  # nH, Wh*Ww, Wh*Ww
         attn = attn + relative_position_bias.unsqueeze(0)
 
         if mask is not None:

comfy/bg_removal_model.py

@@ -55,12 +55,7 @@ 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())
-        if mask.ndim == 3:
-            mask = mask.unsqueeze(0)
-        if mask.shape[1] != 1:
-            mask = mask.movedim(-1, 1)
-
-        return mask
+        return mask.squeeze(1)  # (B, 1, H, W) -> (B, H, W)
 
 
 def load_background_removal_model(sd):

comfy/cli_args.py

@@ -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=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("--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("--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).")
@@ -111,10 +111,11 @@ 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 25%% of system RAM (min 4GB, max 32GB), inactive 75%% of system RAM (min 12GB, 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 10%% of system RAM (min 2GB, max 10GB), inactive 100%% of system RAM (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.")
@@ -133,7 +134,7 @@ 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")
+manager_group.add_argument("--enable-manager-legacy-ui", action="store_true", help="Enables the legacy UI of ComfyUI-Manager. Implies --enable-manager.")
 
 
 vram_group = parser.add_mutually_exclusive_group()
@@ -144,11 +145,13 @@ 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.")
 
@@ -165,6 +168,8 @@ 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.")
@@ -238,6 +243,14 @@ 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:
@@ -246,6 +259,9 @@ 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
 
@@ -255,6 +271,10 @@ 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:

comfy/clip_vision.py

@@ -9,6 +9,7 @@ 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):
@@ -23,12 +24,16 @@ 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):
-        with open(json_config) as f:
-            config = json.load(f)
+        if isinstance(json_config, dict):
+            config = json_config
+        else:
+            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])
@@ -134,6 +139,8 @@ 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
 

comfy/comfy_types/node_typing.py

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

comfy/context_windows.py

@@ -8,6 +8,8 @@ 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
@@ -51,12 +53,18 @@ class ContextHandlerABC(ABC):
 
 
 class IndexListContextWindow(ContextWindowABC):
-    def __init__(self, index_list: list[int], dim: int=0, total_frames: int=0):
+    def __init__(self, index_list: list[int], dim: int=0, total_frames: int=0, modality_windows: dict=None, context_overlap: 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:
@@ -85,6 +93,11 @@ 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"
@@ -148,6 +161,172 @@ 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
@@ -162,7 +341,7 @@ 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,
-                 causal_window_fix: bool=True):
+                 latent_retain_index_list: list[int]=[], causal_window_fix: bool=True):
         self.context_schedule = context_schedule
         self.fuse_method = fuse_method
         self.context_length = context_length
@@ -174,17 +353,118 @@ 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:
-        # 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.")
+        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.")
             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:
@@ -275,7 +555,9 @@ class IndexListContextHandler(ContextHandlerABC):
         return resized_cond
 
     def set_step(self, timestep: torch.Tensor, model_options: dict[str]):
-        mask = torch.isclose(model_options["transformer_options"]["sample_sigmas"], timestep[0], rtol=0.0001)
+        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)
         matches = torch.nonzero(mask)
         if torch.numel(matches) == 0:
             return  # substep from multi-step sampler: keep self._step from the last full step
@@ -284,54 +566,98 @@ 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) for window in context_windows]
+        context_windows = [IndexListContextWindow(window, dim=self.dim, total_frames=full_length, context_overlap=self.context_overlap) 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)
-        context_windows = self.get_context_windows(model, x_in, model_options)
-        enumerated_context_windows = list(enumerate(context_windows))
 
-        conds_final = [torch.zeros_like(x_in) for _ in conds]
+        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)
+        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]
         if self.fuse_method.name == ContextFuseMethods.RELATIVE:
-            counts_final = [torch.ones(get_shape_for_dim(x_in, self.dim), device=x_in.device) for _ in conds]
+            counts = [[torch.ones(get_shape_for_dim(m, self.dim), device=m.device) for _ in conds] for m in window_state.latents]
         else:
-            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]
+            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]
 
         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)
+            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)
             for result in results:
-                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)
+                # 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
         try:
-            # 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
+            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
         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, device=None, first_device=None):
+    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]
+
         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()
 
-            # causal_window_fix: prepend a pre-window frame that will be stripped post-forward
+            # 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.
             anchor_applied = False
             if self.causal_window_fix:
                 anchor_idx = window.index_list[0] - 1
@@ -339,27 +665,46 @@ 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)
 
-            # update exposed params
+            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
             model_options["transformer_options"]["context_window"] = window
-            # 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]
+            sub_timestep = window.get_tensor(timestep, dim=0)
+            sub_conds = [self.get_resized_cond(cond, x, window) 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)
 
-            # strip causal_window_fix anchor if applied
+            # 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
             if anchor_applied:
-                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)
+                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)
 
-            results.append(ContextResults(window_idx, sub_conds_out, sub_conds, window))
+            # 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))
         return results
 
 
@@ -383,7 +728,7 @@ 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)
+            weights = get_context_weights(window.context_length, x_in.shape[self.dim], window.index_list, self, sigma=timestep, context_overlap=window.context_overlap)
             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)
@@ -393,16 +738,22 @@ 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, *args, **kwargs):
-    # limit noise_shape length to context_length for more accurate vram use estimation
+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.
     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)
-        noise_shape[handler.dim] = min(noise_shape[handler.dim], handler.context_length)
-    return executor(model, noise_shape, *args, **kwargs)
+        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)
 
 
 def create_prepare_sampling_wrapper(model: ModelPatcher):
@@ -422,11 +773,12 @@ 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)
-    noise = apply_freenoise(noise, handler.dim, handler.context_length, handler.context_overlap, extra_args["seed"])
+
+    conds = [guider.conds.get('positive', guider.conds.get('negative', []))]
+    noise = handler._apply_freenoise(noise, conds, 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,
@@ -434,7 +786,6 @@ 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)
@@ -580,8 +931,9 @@ 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):
-    return handler.fuse_method.func(length, sigma=sigma, handler=handler, full_length=full_length, idxs=idxs)
+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 create_weights_flat(length: int, **kwargs) -> list[float]:
@@ -599,18 +951,18 @@ 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], handler: IndexListContextHandler, **kwargs):
+def create_weights_overlap_linear(length: int, full_length: int, idxs: list[int], context_overlap: int, **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, handler.context_overlap)
-        weights_torch[:handler.context_overlap] = ramp_up
+        ramp_up = torch.linspace(1e-37, 1, context_overlap)
+        weights_torch[: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, handler.context_overlap)
-        weights_torch[-handler.context_overlap:] = ramp_down
+        ramp_down = torch.linspace(1, 1e-37, context_overlap)
+        weights_torch[-context_overlap:] = ramp_down
     return weights_torch
 
 class ContextFuseMethods:

comfy/controlnet.py

@@ -15,13 +15,14 @@
     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
@@ -38,7 +39,7 @@ 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
+from typing import TYPE_CHECKING, Union
 if TYPE_CHECKING:
     from comfy.hooks import HookGroup
 
@@ -64,6 +65,18 @@ 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
@@ -77,7 +90,7 @@ class ControlBase:
         self.compression_ratio = 8
         self.upscale_algorithm = 'nearest-exact'
         self.extra_args = {}
-        self.previous_controlnet = None
+        self.previous_controlnet: Union[ControlBase, None] = None
         self.extra_conds = []
         self.strength_type = StrengthType.CONSTANT
         self.concat_mask = False
@@ -85,6 +98,7 @@ 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
@@ -111,17 +125,38 @@ 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:
@@ -130,7 +165,7 @@ class ControlBase:
             out += self.previous_controlnet.get_extra_hooks()
         return out
 
-    def copy_to(self, c):
+    def copy_to(self, c: ControlBase):
         c.cond_hint_original = self.cond_hint_original
         c.strength = self.strength
         c.timestep_percent_range = self.timestep_percent_range
@@ -284,6 +319,14 @@ 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)
@@ -314,6 +357,10 @@ 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
@@ -906,6 +953,14 @@ 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'

comfy/float.py

@@ -1,5 +1,20 @@
+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,
@@ -57,6 +72,10 @@ 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))