Merge pull request #13646 from pollockjj/pre_master_all_squashed

pyisolate-support release refresh

.ci/windows_intel_base_files/run_intel_gpu.bat

@@ -0,0 +1,2 @@
+.\python_embeded\python.exe -s ComfyUI\main.py --windows-standalone-build
+pause

.github/workflows/release-stable-all.yml

@@ -20,29 +20,12 @@ jobs:
       git_tag: ${{ inputs.git_tag }}
       cache_tag: "cu130"
       python_minor: "13"
-      python_patch: "11"
+      python_patch: "12"
       rel_name: "nvidia"
       rel_extra_name: ""
       test_release: true
     secrets: inherit
 
-  release_nvidia_cu128:
-    permissions:
-      contents: "write"
-      packages: "write"
-      pull-requests: "read"
-    name: "Release NVIDIA cu128"
-    uses: ./.github/workflows/stable-release.yml
-    with:
-      git_tag: ${{ inputs.git_tag }}
-      cache_tag: "cu128"
-      python_minor: "12"
-      python_patch: "10"
-      rel_name: "nvidia"
-      rel_extra_name: "_cu128"
-      test_release: true
-    secrets: inherit
-
   release_nvidia_cu126:
     permissions:
       contents: "write"
@@ -76,3 +59,20 @@ jobs:
       rel_extra_name: ""
       test_release: false
     secrets: inherit
+
+  release_xpu:
+    permissions:
+      contents: "write"
+      packages: "write"
+      pull-requests: "read"
+    name: "Release Intel XPU"
+    uses: ./.github/workflows/stable-release.yml
+    with:
+      git_tag: ${{ inputs.git_tag }}
+      cache_tag: "xpu"
+      python_minor: "13"
+      python_patch: "12"
+      rel_name: "intel"
+      rel_extra_name: ""
+      test_release: true
+    secrets: inherit

.github/workflows/tag-dispatch-cloud.yml

@@ -0,0 +1,45 @@
+name: Tag Dispatch to Cloud
+
+on:
+  push:
+    tags:
+      - 'v*'
+
+jobs:
+  dispatch-cloud:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Send repository dispatch to cloud
+        env:
+          DISPATCH_TOKEN: ${{ secrets.CLOUD_REPO_DISPATCH_TOKEN }}
+          RELEASE_TAG: ${{ github.ref_name }}
+        run: |
+          set -euo pipefail
+
+          if [ -z "${DISPATCH_TOKEN:-}" ]; then
+            echo "::error::CLOUD_REPO_DISPATCH_TOKEN is required but not set."
+            exit 1
+          fi
+
+          RELEASE_URL="https://github.com/${{ github.repository }}/releases/tag/${RELEASE_TAG}"
+
+          PAYLOAD="$(jq -n \
+            --arg release_tag "$RELEASE_TAG" \
+            --arg release_url "$RELEASE_URL" \
+            '{
+              event_type: "comfyui_tag_pushed",
+              client_payload: {
+                release_tag: $release_tag,
+                release_url: $release_url
+              }
+            }')"
+
+          curl -fsSL \
+            -X POST \
+            -H "Accept: application/vnd.github+json" \
+            -H "Content-Type: application/json" \
+            -H "Authorization: Bearer ${DISPATCH_TOKEN}" \
+            https://api.github.com/repos/Comfy-Org/cloud/dispatches \
+            -d "$PAYLOAD"
+
+          echo "✅ Dispatched ComfyUI tag ${RELEASE_TAG} to Comfy-Org/cloud"

.gitignore

@@ -21,6 +21,6 @@ venv*/
 *.log
 web_custom_versions/
 .DS_Store
-openapi.yaml
 filtered-openapi.yaml
 uv.lock
+.pyisolate_venvs/

QUANTIZATION.md

@@ -139,9 +139,9 @@ Example:
   "_quantization_metadata": {
     "format_version": "1.0",
     "layers": {
-      "model.layers.0.mlp.up_proj": "float8_e4m3fn",
-      "model.layers.0.mlp.down_proj": "float8_e4m3fn",
-      "model.layers.1.mlp.up_proj": "float8_e4m3fn"
+      "model.layers.0.mlp.up_proj": {"format": "float8_e4m3fn"},
+      "model.layers.0.mlp.down_proj": {"format": "float8_e4m3fn"},
+      "model.layers.1.mlp.up_proj": {"format": "float8_e4m3fn"}
     }
   }
 }
@@ -165,4 +165,4 @@ Activation quantization (e.g., for FP8 Tensor Core operations) requires `input_s
 3. **Compute scales**: Derive `input_scale` from collected statistics
 4. **Store in checkpoint**: Save `input_scale` parameters alongside weights
 
-The calibration dataset should be representative of your target use case. For diffusion models, this typically means a diverse set of prompts and generation parameters.
+The calibration dataset should be representative of your target use case. For diffusion models, this typically means a diverse set of prompts and generation parameters.

README.md

@@ -61,6 +61,7 @@ See what ComfyUI can do with the [newer template workflows](https://comfy.org/wo
 
 ## Features
 - Nodes/graph/flowchart interface to experiment and create complex Stable Diffusion workflows without needing to code anything.
+- NOTE: There are many more models supported than the list below, if you want to see what is supported see our templates list inside ComfyUI.
 - Image Models
    - SD1.x, SD2.x ([unCLIP](https://comfyanonymous.github.io/ComfyUI_examples/unclip/))
    - [SDXL](https://comfyanonymous.github.io/ComfyUI_examples/sdxl/), [SDXL Turbo](https://comfyanonymous.github.io/ComfyUI_examples/sdturbo/)
@@ -136,7 +137,7 @@ ComfyUI follows a weekly release cycle targeting Monday but this regularly chang
    - Builds a new release using the latest stable core version
 
 3. **[ComfyUI Frontend](https://github.com/Comfy-Org/ComfyUI_frontend)**
-   - Weekly frontend updates are merged into the core repository
+   - Every 2+ weeks frontend updates are merged into the core repository
    - Features are frozen for the upcoming core release
    - Development continues for the next release cycle
 
@@ -194,7 +195,9 @@ The portable above currently comes with python 3.13 and pytorch cuda 13.0. Updat
 
 #### Alternative Downloads:
 
-[Experimental portable for AMD GPUs](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_amd.7z)
+[Portable for AMD GPUs](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_amd.7z)
+
+[Experimental portable for Intel GPUs](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_intel.7z)
 
 [Portable with pytorch cuda 12.6 and python 3.12](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_nvidia_cu126.7z) (Supports Nvidia 10 series and older GPUs).
 
@@ -232,7 +235,7 @@ Put your VAE in: models/vae
 
 AMD users can install rocm and pytorch with pip if you don't have it already installed, this is the command to install the stable version:
 
-```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.1```
+```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.2```
 
 This is the command to install the nightly with ROCm 7.2 which might have some performance improvements:
 
@@ -275,7 +278,7 @@ Nvidia users should install stable pytorch using this command:
 
 This is the command to install pytorch nightly instead which might have performance improvements.
 
-```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu130```
+```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu132```
 
 #### Troubleshooting
 

api_server/routes/internal/internal_routes.py

@@ -67,7 +67,7 @@ class InternalRoutes:
                 (entry for entry in os.scandir(directory) if is_visible_file(entry)),
                 key=lambda entry: -entry.stat().st_mtime
             )
-            return web.json_response([entry.name for entry in sorted_files], status=200)
+            return web.json_response([f"{entry.name} [{directory_type}]" for entry in sorted_files], status=200)
 
 
     def get_app(self):

app/assets/database/queries/__init__.py

@@ -1,6 +1,7 @@
 from app.assets.database.queries.asset import (
     asset_exists_by_hash,
     bulk_insert_assets,
+    create_stub_asset,
     get_asset_by_hash,
     get_existing_asset_ids,
     reassign_asset_references,
@@ -12,6 +13,7 @@ from app.assets.database.queries.asset_reference import (
     UnenrichedReferenceRow,
     bulk_insert_references_ignore_conflicts,
     bulk_update_enrichment_level,
+    count_active_siblings,
     bulk_update_is_missing,
     bulk_update_needs_verify,
     convert_metadata_to_rows,
@@ -80,6 +82,8 @@ __all__ = [
     "bulk_insert_references_ignore_conflicts",
     "bulk_insert_tags_and_meta",
     "bulk_update_enrichment_level",
+    "count_active_siblings",
+    "create_stub_asset",
     "bulk_update_is_missing",
     "bulk_update_needs_verify",
     "convert_metadata_to_rows",

app/assets/database/queries/asset.py

@@ -78,6 +78,18 @@ def upsert_asset(
     return asset, created, updated
 
 
+def create_stub_asset(
+    session: Session,
+    size_bytes: int,
+    mime_type: str | None = None,
+) -> Asset:
+    """Create a new asset with no hash (stub for later enrichment)."""
+    asset = Asset(size_bytes=size_bytes, mime_type=mime_type, hash=None)
+    session.add(asset)
+    session.flush()
+    return asset
+
+
 def bulk_insert_assets(
     session: Session,
     rows: list[dict],

app/assets/database/queries/asset_reference.py

@@ -114,6 +114,23 @@ def get_reference_by_file_path(
     )
 
 
+def count_active_siblings(
+    session: Session,
+    asset_id: str,
+    exclude_reference_id: str,
+) -> int:
+    """Count active (non-deleted) references to an asset, excluding one reference."""
+    return (
+        session.query(AssetReference)
+        .filter(
+            AssetReference.asset_id == asset_id,
+            AssetReference.id != exclude_reference_id,
+            AssetReference.deleted_at.is_(None),
+        )
+        .count()
+    )
+
+
 def reference_exists_for_asset_id(
     session: Session,
     asset_id: str,

app/assets/scanner.py

@@ -13,6 +13,7 @@ from app.assets.database.queries import (
     delete_references_by_ids,
     ensure_tags_exist,
     get_asset_by_hash,
+    get_reference_by_id,
     get_references_for_prefixes,
     get_unenriched_references,
     mark_references_missing_outside_prefixes,
@@ -338,6 +339,7 @@ def build_asset_specs(
                 "metadata": metadata,
                 "hash": asset_hash,
                 "mime_type": mime_type,
+                "job_id": None,
             }
         )
         tag_pool.update(tags)
@@ -426,6 +428,7 @@ def enrich_asset(
     except OSError:
         return new_level
 
+    initial_mtime_ns = get_mtime_ns(stat_p)
     rel_fname = compute_relative_filename(file_path)
     mime_type: str | None = None
     metadata = None
@@ -489,6 +492,18 @@ def enrich_asset(
         except Exception as e:
             logging.warning("Failed to hash %s: %s", file_path, e)
 
+    # Optimistic guard: if the reference's mtime_ns changed since we
+    # started (e.g. ingest_existing_file updated it), our results are
+    # stale — discard them to avoid overwriting fresh registration data.
+    ref = get_reference_by_id(session, reference_id)
+    if ref is None or ref.mtime_ns != initial_mtime_ns:
+        session.rollback()
+        logging.info(
+            "Ref %s mtime changed during enrichment, discarding stale result",
+            reference_id,
+        )
+        return ENRICHMENT_STUB
+
     if extract_metadata and metadata:
         system_metadata = metadata.to_user_metadata()
         set_reference_system_metadata(session, reference_id, system_metadata)

app/assets/seeder.py

@@ -77,7 +77,9 @@ class _AssetSeeder:
     """
 
     def __init__(self) -> None:
-        self._lock = threading.Lock()
+        # RLock is required because _run_scan() drains pending work while
+        # holding _lock and re-enters start() which also acquires _lock.
+        self._lock = threading.RLock()
         self._state = State.IDLE
         self._progress: Progress | None = None
         self._last_progress: Progress | None = None
@@ -92,6 +94,7 @@ class _AssetSeeder:
         self._prune_first: bool = False
         self._progress_callback: ProgressCallback | None = None
         self._disabled: bool = False
+        self._pending_enrich: dict | None = None
 
     def disable(self) -> None:
         """Disable the asset seeder, preventing any scans from starting."""
@@ -196,6 +199,42 @@ class _AssetSeeder:
             compute_hashes=compute_hashes,
         )
 
+    def enqueue_enrich(
+        self,
+        roots: tuple[RootType, ...] = ("models", "input", "output"),
+        compute_hashes: bool = False,
+    ) -> bool:
+        """Start an enrichment scan now, or queue it for after the current scan.
+
+        If the seeder is idle, starts immediately. Otherwise, the enrich
+        request is stored and will run automatically when the current scan
+        finishes.
+
+        Args:
+            roots: Tuple of root types to scan
+            compute_hashes: If True, compute blake3 hashes
+
+        Returns:
+            True if started immediately, False if queued for later
+        """
+        with self._lock:
+            if self.start_enrich(roots=roots, compute_hashes=compute_hashes):
+                return True
+            if self._pending_enrich is not None:
+                existing_roots = set(self._pending_enrich["roots"])
+                existing_roots.update(roots)
+                self._pending_enrich["roots"] = tuple(existing_roots)
+                self._pending_enrich["compute_hashes"] = (
+                    self._pending_enrich["compute_hashes"] or compute_hashes
+                )
+            else:
+                self._pending_enrich = {
+                    "roots": roots,
+                    "compute_hashes": compute_hashes,
+                }
+            logging.info("Enrich scan queued (roots=%s)", self._pending_enrich["roots"])
+        return False
+
     def cancel(self) -> bool:
         """Request cancellation of the current scan.
 
@@ -381,9 +420,13 @@ class _AssetSeeder:
             return marked
         finally:
             with self._lock:
-                self._last_progress = self._progress
-                self._state = State.IDLE
-                self._progress = None
+                self._reset_to_idle()
+
+    def _reset_to_idle(self) -> None:
+        """Reset state to IDLE, preserving last progress. Caller must hold _lock."""
+        self._last_progress = self._progress
+        self._state = State.IDLE
+        self._progress = None
 
     def _is_cancelled(self) -> bool:
         """Check if cancellation has been requested."""
@@ -594,9 +637,18 @@ class _AssetSeeder:
                     },
                 )
             with self._lock:
-                self._last_progress = self._progress
-                self._state = State.IDLE
-                self._progress = None
+                self._reset_to_idle()
+                pending = self._pending_enrich
+                if pending is not None:
+                    self._pending_enrich = None
+                    if not self.start_enrich(
+                        roots=pending["roots"],
+                        compute_hashes=pending["compute_hashes"],
+                    ):
+                        logging.warning(
+                            "Pending enrich scan could not start (roots=%s)",
+                            pending["roots"],
+                        )
 
     def _run_fast_phase(self, roots: tuple[RootType, ...]) -> tuple[int, int, int]:
         """Run phase 1: fast scan to create stub records.

app/assets/services/__init__.py

@@ -23,6 +23,8 @@ from app.assets.services.ingest import (
     DependencyMissingError,
     HashMismatchError,
     create_from_hash,
+    ingest_existing_file,
+    register_output_files,
     upload_from_temp_path,
 )
 from app.assets.database.queries import (
@@ -72,6 +74,8 @@ __all__ = [
     "delete_asset_reference",
     "get_asset_by_hash",
     "get_asset_detail",
+    "ingest_existing_file",
+    "register_output_files",
     "get_mtime_ns",
     "get_size_and_mtime_ns",
     "list_assets_page",

app/assets/services/bulk_ingest.py

@@ -37,6 +37,7 @@ class SeedAssetSpec(TypedDict):
     metadata: ExtractedMetadata | None
     hash: str | None
     mime_type: str | None
+    job_id: str | None
 
 
 class AssetRow(TypedDict):
@@ -60,6 +61,7 @@ class ReferenceRow(TypedDict):
     name: str
     preview_id: str | None
     user_metadata: dict[str, Any] | None
+    job_id: str | None
     created_at: datetime
     updated_at: datetime
     last_access_time: datetime
@@ -167,6 +169,7 @@ def batch_insert_seed_assets(
                 "name": spec["info_name"],
                 "preview_id": None,
                 "user_metadata": user_metadata,
+                "job_id": spec.get("job_id"),
                 "created_at": current_time,
                 "updated_at": current_time,
                 "last_access_time": current_time,

app/assets/services/ingest.py

@@ -9,6 +9,9 @@ from sqlalchemy.orm import Session
 import app.assets.services.hashing as hashing
 from app.assets.database.queries import (
     add_tags_to_reference,
+    count_active_siblings,
+    create_stub_asset,
+    ensure_tags_exist,
     fetch_reference_and_asset,
     get_asset_by_hash,
     get_reference_by_file_path,
@@ -23,7 +26,8 @@ from app.assets.database.queries import (
     upsert_reference,
     validate_tags_exist,
 )
-from app.assets.helpers import normalize_tags
+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.path_utils import (
     compute_relative_filename,
@@ -130,6 +134,102 @@ def _ingest_file_from_path(
     )
 
 
+def register_output_files(
+    file_paths: Sequence[str],
+    user_metadata: UserMetadata = None,
+    job_id: str | None = None,
+) -> int:
+    """Register a batch of output file paths as assets.
+
+    Returns the number of files successfully registered.
+    """
+    registered = 0
+    for abs_path in file_paths:
+        if not os.path.isfile(abs_path):
+            continue
+        try:
+            if ingest_existing_file(
+                abs_path, user_metadata=user_metadata, job_id=job_id
+            ):
+                registered += 1
+        except Exception:
+            logging.exception("Failed to register output: %s", abs_path)
+    return registered
+
+
+def ingest_existing_file(
+    abs_path: str,
+    user_metadata: UserMetadata = None,
+    extra_tags: Sequence[str] = (),
+    owner_id: str = "",
+    job_id: str | None = None,
+) -> bool:
+    """Register an existing on-disk file as an asset stub.
+
+    If a reference already exists for this path, updates mtime_ns, job_id,
+    size_bytes, and resets enrichment so the enricher will re-hash it.
+
+    For brand-new paths, inserts a stub record (hash=NULL) for immediate
+    UX visibility.
+
+    Returns True if a row was inserted or updated, False otherwise.
+    """
+    locator = os.path.abspath(abs_path)
+    size_bytes, mtime_ns = get_size_and_mtime_ns(abs_path)
+    mime_type = mimetypes.guess_type(abs_path, strict=False)[0]
+    name, path_tags = get_name_and_tags_from_asset_path(abs_path)
+    tags = list(dict.fromkeys(path_tags + list(extra_tags)))
+
+    with create_session() as session:
+        existing_ref = get_reference_by_file_path(session, locator)
+        if existing_ref is not None:
+            now = get_utc_now()
+            existing_ref.mtime_ns = mtime_ns
+            existing_ref.job_id = job_id
+            existing_ref.is_missing = False
+            existing_ref.deleted_at = None
+            existing_ref.updated_at = now
+            existing_ref.enrichment_level = 0
+
+            asset = existing_ref.asset
+            if asset:
+                # If other refs share this asset, detach to a new stub
+                # instead of mutating the shared row.
+                siblings = count_active_siblings(session, asset.id, existing_ref.id)
+                if siblings > 0:
+                    new_asset = create_stub_asset(
+                        session,
+                        size_bytes=size_bytes,
+                        mime_type=mime_type or asset.mime_type,
+                    )
+                    existing_ref.asset_id = new_asset.id
+                else:
+                    asset.hash = None
+                    asset.size_bytes = size_bytes
+                    if mime_type:
+                        asset.mime_type = mime_type
+            session.commit()
+            return True
+
+        spec = {
+            "abs_path": abs_path,
+            "size_bytes": size_bytes,
+            "mtime_ns": mtime_ns,
+            "info_name": name,
+            "tags": tags,
+            "fname": os.path.basename(abs_path),
+            "metadata": None,
+            "hash": None,
+            "mime_type": mime_type,
+            "job_id": job_id,
+        }
+        if tags:
+            ensure_tags_exist(session, tags)
+        result = batch_insert_seed_assets(session, [spec], owner_id=owner_id)
+        session.commit()
+        return result.won_paths > 0
+
+
 def _register_existing_asset(
     asset_hash: str,
     name: str,

app/assets/services/path_utils.py

@@ -93,12 +93,13 @@ def compute_relative_filename(file_path: str) -> str | None:
 
 def get_asset_category_and_relative_path(
     file_path: str,
-) -> tuple[Literal["input", "output", "models"], str]:
+) -> tuple[Literal["input", "output", "temp", "models"], str]:
     """Determine which root category a file path belongs to.
 
     Categories:
       - 'input': under folder_paths.get_input_directory()
       - 'output': under folder_paths.get_output_directory()
+      - 'temp': under folder_paths.get_temp_directory()
       - 'models': under any base path from get_comfy_models_folders()
 
     Returns:
@@ -129,7 +130,12 @@ def get_asset_category_and_relative_path(
     if _check_is_within(fp_abs, output_base):
         return "output", _compute_relative(fp_abs, output_base)
 
-    # 3) models (check deepest matching base to avoid ambiguity)
+    # 3) temp
+    temp_base = os.path.abspath(folder_paths.get_temp_directory())
+    if _check_is_within(fp_abs, temp_base):
+        return "temp", _compute_relative(fp_abs, temp_base)
+
+    # 4) models (check deepest matching base to avoid ambiguity)
     best: tuple[int, str, str] | None = None  # (base_len, bucket, rel_inside_bucket)
     for bucket, bases in get_comfy_models_folders():
         for b in bases:
@@ -146,7 +152,7 @@ def get_asset_category_and_relative_path(
         return "models", os.path.relpath(os.path.join(os.sep, combined), os.sep)
 
     raise ValueError(
-        f"Path is not within input, output, or configured model bases: {file_path}"
+        f"Path is not within input, output, temp, or configured model bases: {file_path}"
     )
 
 

blueprints/.glsl/Color_Balance_15.frag

@@ -0,0 +1,90 @@
+#version 300 es
+precision highp float;
+
+uniform sampler2D u_image0;
+uniform float u_float0;
+uniform float u_float1;
+uniform float u_float2;
+uniform float u_float3;
+uniform float u_float4;
+uniform float u_float5;
+uniform float u_float6;
+uniform float u_float7;
+uniform float u_float8;
+uniform bool u_bool0;
+
+in vec2 v_texCoord;
+out vec4 fragColor;
+
+vec3 rgb2hsl(vec3 c) {
+    float maxC = max(c.r, max(c.g, c.b));
+    float minC = min(c.r, min(c.g, c.b));
+    float l = (maxC + minC) * 0.5;
+    if (maxC == minC) return vec3(0.0, 0.0, l);
+    float d = maxC - minC;
+    float s = l > 0.5 ? d / (2.0 - maxC - minC) : d / (maxC + minC);
+    float h;
+    if (maxC == c.r) {
+        h = (c.g - c.b) / d + (c.g < c.b ? 6.0 : 0.0);
+    } else if (maxC == c.g) {
+        h = (c.b - c.r) / d + 2.0;
+    } else {
+        h = (c.r - c.g) / d + 4.0;
+    }
+    h /= 6.0;
+    return vec3(h, s, l);
+}
+
+float hue2rgb(float p, float q, float t) {
+    if (t < 0.0) t += 1.0;
+    if (t > 1.0) t -= 1.0;
+    if (t < 1.0 / 6.0) return p + (q - p) * 6.0 * t;
+    if (t < 1.0 / 2.0) return q;
+    if (t < 2.0 / 3.0) return p + (q - p) * (2.0 / 3.0 - t) * 6.0;
+    return p;
+}
+
+vec3 hsl2rgb(vec3 hsl) {
+    float h = hsl.x, s = hsl.y, l = hsl.z;
+    if (s == 0.0) return vec3(l);
+    float q = l < 0.5 ? l * (1.0 + s) : l + s - l * s;
+    float p = 2.0 * l - q;
+    return vec3(
+        hue2rgb(p, q, h + 1.0 / 3.0),
+        hue2rgb(p, q, h),
+        hue2rgb(p, q, h - 1.0 / 3.0)
+    );
+}
+
+void main() {
+    vec4 tex = texture(u_image0, v_texCoord);
+    vec3 color = tex.rgb;
+
+    vec3 shadows = vec3(u_float0, u_float1, u_float2) * 0.01;
+    vec3 midtones = vec3(u_float3, u_float4, u_float5) * 0.01;
+    vec3 highlights = vec3(u_float6, u_float7, u_float8) * 0.01;
+
+    float maxC = max(color.r, max(color.g, color.b));
+    float minC = min(color.r, min(color.g, color.b));
+    float lightness = (maxC + minC) * 0.5;
+
+    // GIMP weight curves: linear ramps with constants a=0.25, b=0.333, scale=0.7
+    const float a = 0.25;
+    const float b = 0.333;
+    const float scale = 0.7;
+
+    float sw = clamp((lightness - b) / -a + 0.5, 0.0, 1.0) * scale;
+    float mw = clamp((lightness - b) / a + 0.5, 0.0, 1.0) *
+               clamp((lightness + b - 1.0) / -a + 0.5, 0.0, 1.0) * scale;
+    float hw = clamp((lightness + b - 1.0) / a + 0.5, 0.0, 1.0) * scale;
+
+    color += sw * shadows + mw * midtones + hw * highlights;
+
+    if (u_bool0) {
+        vec3 hsl = rgb2hsl(clamp(color, 0.0, 1.0));
+        hsl.z = lightness;
+        color = hsl2rgb(hsl);
+    }
+
+    fragColor = vec4(clamp(color, 0.0, 1.0), tex.a);
+}

blueprints/.glsl/Color_Curves_8.frag

@@ -0,0 +1,49 @@
+#version 300 es
+precision highp float;
+
+uniform sampler2D u_image0;
+uniform sampler2D u_curve0;  // RGB master curve (256x1 LUT)
+uniform sampler2D u_curve1;  // Red channel curve
+uniform sampler2D u_curve2;  // Green channel curve
+uniform sampler2D u_curve3;  // Blue channel curve
+
+in vec2 v_texCoord;
+layout(location = 0) out vec4 fragColor0;
+
+// GIMP-compatible curve lookup with manual linear interpolation.
+// Matches gimp_curve_map_value_inline() from gimpcurve-map.c:
+//   index = value * (n_samples - 1)
+//   f = fract(index)
+//   result = (1-f) * samples[floor] + f * samples[ceil]
+//
+// Uses texelFetch (NEAREST) to avoid GPU half-texel offset issues
+// that occur with texture() + GL_LINEAR on small 256x1 LUTs.
+float applyCurve(sampler2D curve, float value) {
+    value = clamp(value, 0.0, 1.0);
+
+    float pos = value * 255.0;
+    int lo = int(floor(pos));
+    int hi = min(lo + 1, 255);
+    float f = pos - float(lo);
+
+    float a = texelFetch(curve, ivec2(lo, 0), 0).r;
+    float b = texelFetch(curve, ivec2(hi, 0), 0).r;
+
+    return a + f * (b - a);
+}
+
+void main() {
+    vec4 color = texture(u_image0, v_texCoord);
+
+    // GIMP order: per-channel curves first, then RGB master curve.
+    // See gimp_curve_map_pixels() default case in gimpcurve-map.c:
+    //   dest = colors_curve( channel_curve( src ) )
+    float tmp_r = applyCurve(u_curve1, color.r);
+    float tmp_g = applyCurve(u_curve2, color.g);
+    float tmp_b = applyCurve(u_curve3, color.b);
+    color.r = applyCurve(u_curve0, tmp_r);
+    color.g = applyCurve(u_curve0, tmp_g);
+    color.b = applyCurve(u_curve0, tmp_b);
+
+    fragColor0 = vec4(color.rgb, color.a);
+}

blueprints/.glsl/Glow_30.frag

@@ -2,7 +2,6 @@
 precision mediump float;
 
 uniform sampler2D u_image0;
-uniform vec2 u_resolution;
 uniform int u_int0;      // Blend mode
 uniform int u_int1;      // Color tint
 uniform float u_float0;  // Intensity
@@ -75,7 +74,7 @@ void main() {
     float t0 = threshold - 0.15;
     float t1 = threshold + 0.15;
     
-    vec2 texelSize = 1.0 / u_resolution;
+    vec2 texelSize = 1.0 / vec2(textureSize(u_image0, 0));
     float radius2 = radius * radius;
     
     float sampleScale = clamp(radius * 0.75, 0.35, 1.0);

blueprints/.glsl/Image_Blur_1.frag

@@ -12,7 +12,6 @@ const int RADIAL_SAMPLES = 12;
 const float RADIAL_STRENGTH = 0.0003;
 
 uniform sampler2D u_image0;
-uniform vec2 u_resolution;
 uniform int u_int0;      // Blur type (BLUR_GAUSSIAN, BLUR_BOX, BLUR_RADIAL)
 uniform float u_float0;  // Blur radius/amount
 uniform int u_pass;      // Pass index (0 = horizontal, 1 = vertical)
@@ -25,7 +24,7 @@ float gaussian(float x, float sigma) {
 }
 
 void main() {
-    vec2 texelSize = 1.0 / u_resolution;
+    vec2 texelSize = 1.0 / vec2(textureSize(u_image0, 0));
     float radius = max(u_float0, 0.0);
 
     // Radial (angular) blur - single pass, doesn't use separable

blueprints/.glsl/Sharpen_23.frag

@@ -2,14 +2,13 @@
 precision highp float;
 
 uniform sampler2D u_image0;
-uniform vec2 u_resolution;
 uniform float u_float0;  // strength [0.0 – 2.0] typical: 0.3–1.0
 
 in vec2 v_texCoord;
 layout(location = 0) out vec4 fragColor0;
 
 void main() {
-    vec2 texel = 1.0 / u_resolution;
+    vec2 texel = 1.0 / vec2(textureSize(u_image0, 0));
     
     // Sample center and neighbors
     vec4 center = texture(u_image0, v_texCoord);

blueprints/.glsl/Unsharp_Mask_26.frag

@@ -2,7 +2,6 @@
 precision highp float;
 
 uniform sampler2D u_image0;
-uniform vec2 u_resolution;
 uniform float u_float0;  // amount    [0.0 - 3.0]  typical: 0.5-1.5
 uniform float u_float1;  // radius    [0.5 - 10.0] blur radius in pixels
 uniform float u_float2;  // threshold [0.0 - 0.1]  min difference to sharpen
@@ -19,7 +18,7 @@ float getLuminance(vec3 color) {
 }
 
 void main() {
-    vec2 texel = 1.0 / u_resolution;
+    vec2 texel = 1.0 / vec2(textureSize(u_image0, 0));
     float radius = max(u_float1, 0.5);
     float amount = u_float0;
     float threshold = u_float2;

blueprints/Color Curves.json

@@ -0,0 +1,615 @@
+{
+  "revision": 0,
+  "last_node_id": 10,
+  "last_link_id": 0,
+  "nodes": [
+    {
+      "id": 10,
+      "type": "d5c462c8-1372-4af8-84f2-547c83470d04",
+      "pos": [
+        3610,
+        -2630
+      ],
+      "size": [
+        270,
+        420
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [
+        {
+          "label": "image",
+          "localized_name": "images.image0",
+          "name": "images.image0",
+          "type": "IMAGE",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "label": "IMAGE",
+          "localized_name": "IMAGE0",
+          "name": "IMAGE0",
+          "type": "IMAGE",
+          "links": []
+        }
+      ],
+      "properties": {
+        "proxyWidgets": [
+          [
+            "4",
+            "curve"
+          ],
+          [
+            "5",
+            "curve"
+          ],
+          [
+            "6",
+            "curve"
+          ],
+          [
+            "7",
+            "curve"
+          ]
+        ]
+      },
+      "widgets_values": [],
+      "title": "Color Curves"
+    }
+  ],
+  "links": [],
+  "version": 0.4,
+  "definitions": {
+    "subgraphs": [
+      {
+        "id": "d5c462c8-1372-4af8-84f2-547c83470d04",
+        "version": 1,
+        "state": {
+          "lastGroupId": 0,
+          "lastNodeId": 9,
+          "lastLinkId": 38,
+          "lastRerouteId": 0
+        },
+        "revision": 0,
+        "config": {},
+        "name": "Color Curves",
+        "inputNode": {
+          "id": -10,
+          "bounding": [
+            2660,
+            -4500,
+            120,
+            60
+          ]
+        },
+        "outputNode": {
+          "id": -20,
+          "bounding": [
+            4270,
+            -4500,
+            120,
+            60
+          ]
+        },
+        "inputs": [
+          {
+            "id": "abc345b7-f55e-4f32-a11d-3aa4c2b0936b",
+            "name": "images.image0",
+            "type": "IMAGE",
+            "linkIds": [
+              29,
+              34
+            ],
+            "localized_name": "images.image0",
+            "label": "image",
+            "pos": [
+              2760,
+              -4480
+            ]
+          }
+        ],
+        "outputs": [
+          {
+            "id": "eb0ec079-46da-4408-8263-9ef85569d33d",
+            "name": "IMAGE0",
+            "type": "IMAGE",
+            "linkIds": [
+              28
+            ],
+            "localized_name": "IMAGE0",
+            "label": "IMAGE",
+            "pos": [
+              4290,
+              -4480
+            ]
+          }
+        ],
+        "widgets": [],
+        "nodes": [
+          {
+            "id": 4,
+            "type": "CurveEditor",
+            "pos": [
+              3060,
+              -4500
+            ],
+            "size": [
+              270,
+              200
+            ],
+            "flags": {},
+            "order": 0,
+            "mode": 0,
+            "inputs": [
+              {
+                "label": "curve",
+                "localized_name": "curve",
+                "name": "curve",
+                "type": "CURVE",
+                "widget": {
+                  "name": "curve"
+                },
+                "link": null
+              },
+              {
+                "label": "histogram",
+                "localized_name": "histogram",
+                "name": "histogram",
+                "type": "HISTOGRAM",
+                "shape": 7,
+                "link": 35
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "CURVE",
+                "name": "CURVE",
+                "type": "CURVE",
+                "links": [
+                  30
+                ]
+              }
+            ],
+            "title": "RGB Master",
+            "properties": {
+              "Node name for S&R": "CurveEditor"
+            },
+            "widgets_values": []
+          },
+          {
+            "id": 5,
+            "type": "CurveEditor",
+            "pos": [
+              3060,
+              -4250
+            ],
+            "size": [
+              270,
+              200
+            ],
+            "flags": {},
+            "order": 1,
+            "mode": 0,
+            "inputs": [
+              {
+                "label": "curve",
+                "localized_name": "curve",
+                "name": "curve",
+                "type": "CURVE",
+                "widget": {
+                  "name": "curve"
+                },
+                "link": null
+              },
+              {
+                "label": "histogram",
+                "localized_name": "histogram",
+                "name": "histogram",
+                "type": "HISTOGRAM",
+                "shape": 7,
+                "link": 36
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "CURVE",
+                "name": "CURVE",
+                "type": "CURVE",
+                "links": [
+                  31
+                ]
+              }
+            ],
+            "title": "Red",
+            "properties": {
+              "Node name for S&R": "CurveEditor"
+            },
+            "widgets_values": []
+          },
+          {
+            "id": 6,
+            "type": "CurveEditor",
+            "pos": [
+              3060,
+              -4000
+            ],
+            "size": [
+              270,
+              200
+            ],
+            "flags": {},
+            "order": 2,
+            "mode": 0,
+            "inputs": [
+              {
+                "label": "curve",
+                "localized_name": "curve",
+                "name": "curve",
+                "type": "CURVE",
+                "widget": {
+                  "name": "curve"
+                },
+                "link": null
+              },
+              {
+                "label": "histogram",
+                "localized_name": "histogram",
+                "name": "histogram",
+                "type": "HISTOGRAM",
+                "shape": 7,
+                "link": 37
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "CURVE",
+                "name": "CURVE",
+                "type": "CURVE",
+                "links": [
+                  32
+                ]
+              }
+            ],
+            "title": "Green",
+            "properties": {
+              "Node name for S&R": "CurveEditor"
+            },
+            "widgets_values": []
+          },
+          {
+            "id": 7,
+            "type": "CurveEditor",
+            "pos": [
+              3060,
+              -3750
+            ],
+            "size": [
+              270,
+              200
+            ],
+            "flags": {},
+            "order": 3,
+            "mode": 0,
+            "inputs": [
+              {
+                "label": "curve",
+                "localized_name": "curve",
+                "name": "curve",
+                "type": "CURVE",
+                "widget": {
+                  "name": "curve"
+                },
+                "link": null
+              },
+              {
+                "label": "histogram",
+                "localized_name": "histogram",
+                "name": "histogram",
+                "type": "HISTOGRAM",
+                "shape": 7,
+                "link": 38
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "CURVE",
+                "name": "CURVE",
+                "type": "CURVE",
+                "links": [
+                  33
+                ]
+              }
+            ],
+            "title": "Blue",
+            "properties": {
+              "Node name for S&R": "CurveEditor"
+            },
+            "widgets_values": []
+          },
+          {
+            "id": 8,
+            "type": "GLSLShader",
+            "pos": [
+              3590,
+              -4500
+            ],
+            "size": [
+              420,
+              500
+            ],
+            "flags": {},
+            "order": 4,
+            "mode": 0,
+            "inputs": [
+              {
+                "label": "image0",
+                "localized_name": "images.image0",
+                "name": "images.image0",
+                "type": "IMAGE",
+                "link": 29
+              },
+              {
+                "label": "image1",
+                "localized_name": "images.image1",
+                "name": "images.image1",
+                "shape": 7,
+                "type": "IMAGE",
+                "link": null
+              },
+              {
+                "label": "u_curve0",
+                "localized_name": "curves.u_curve0",
+                "name": "curves.u_curve0",
+                "shape": 7,
+                "type": "CURVE",
+                "link": 30
+              },
+              {
+                "label": "u_curve1",
+                "localized_name": "curves.u_curve1",
+                "name": "curves.u_curve1",
+                "shape": 7,
+                "type": "CURVE",
+                "link": 31
+              },
+              {
+                "label": "u_curve2",
+                "localized_name": "curves.u_curve2",
+                "name": "curves.u_curve2",
+                "shape": 7,
+                "type": "CURVE",
+                "link": 32
+              },
+              {
+                "label": "u_curve3",
+                "localized_name": "curves.u_curve3",
+                "name": "curves.u_curve3",
+                "shape": 7,
+                "type": "CURVE",
+                "link": 33
+              },
+              {
+                "localized_name": "fragment_shader",
+                "name": "fragment_shader",
+                "type": "STRING",
+                "widget": {
+                  "name": "fragment_shader"
+                },
+                "link": null
+              },
+              {
+                "localized_name": "size_mode",
+                "name": "size_mode",
+                "type": "COMFY_DYNAMICCOMBO_V3",
+                "widget": {
+                  "name": "size_mode"
+                },
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "IMAGE0",
+                "name": "IMAGE0",
+                "type": "IMAGE",
+                "links": [
+                  28
+                ]
+              },
+              {
+                "localized_name": "IMAGE1",
+                "name": "IMAGE1",
+                "type": "IMAGE",
+                "links": null
+              },
+              {
+                "localized_name": "IMAGE2",
+                "name": "IMAGE2",
+                "type": "IMAGE",
+                "links": null
+              },
+              {
+                "localized_name": "IMAGE3",
+                "name": "IMAGE3",
+                "type": "IMAGE",
+                "links": null
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "GLSLShader"
+            },
+            "widgets_values": [
+              "#version 300 es\nprecision highp float;\n\nuniform sampler2D u_image0;\nuniform sampler2D u_curve0;  // RGB master curve (256x1 LUT)\nuniform sampler2D u_curve1;  // Red channel curve\nuniform sampler2D u_curve2;  // Green channel curve\nuniform sampler2D u_curve3;  // Blue channel curve\n\nin vec2 v_texCoord;\nlayout(location = 0) out vec4 fragColor0;\n\n// GIMP-compatible curve lookup with manual linear interpolation.\n// Matches gimp_curve_map_value_inline() from gimpcurve-map.c:\n//   index = value * (n_samples - 1)\n//   f = fract(index)\n//   result = (1-f) * samples[floor] + f * samples[ceil]\n//\n// Uses texelFetch (NEAREST) to avoid GPU half-texel offset issues\n// that occur with texture() + GL_LINEAR on small 256x1 LUTs.\nfloat applyCurve(sampler2D curve, float value) {\n    value = clamp(value, 0.0, 1.0);\n\n    float pos = value * 255.0;\n    int lo = int(floor(pos));\n    int hi = min(lo + 1, 255);\n    float f = pos - float(lo);\n\n    float a = texelFetch(curve, ivec2(lo, 0), 0).r;\n    float b = texelFetch(curve, ivec2(hi, 0), 0).r;\n\n    return a + f * (b - a);\n}\n\nvoid main() {\n    vec4 color = texture(u_image0, v_texCoord);\n\n    // GIMP order: per-channel curves first, then RGB master curve.\n    // See gimp_curve_map_pixels() default case in gimpcurve-map.c:\n    //   dest = colors_curve( channel_curve( src ) )\n    float tmp_r = applyCurve(u_curve1, color.r);\n    float tmp_g = applyCurve(u_curve2, color.g);\n    float tmp_b = applyCurve(u_curve3, color.b);\n    color.r = applyCurve(u_curve0, tmp_r);\n    color.g = applyCurve(u_curve0, tmp_g);\n    color.b = applyCurve(u_curve0, tmp_b);\n\n    fragColor0 = vec4(color.rgb, color.a);\n}\n",
+              "from_input"
+            ]
+          },
+          {
+            "id": 9,
+            "type": "ImageHistogram",
+            "pos": [
+              2800,
+              -4300
+            ],
+            "size": [
+              210,
+              150
+            ],
+            "flags": {},
+            "order": 5,
+            "mode": 0,
+            "inputs": [
+              {
+                "label": "image",
+                "localized_name": "image",
+                "name": "image",
+                "type": "IMAGE",
+                "link": 34
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "HISTOGRAM",
+                "name": "rgb",
+                "type": "HISTOGRAM",
+                "links": [
+                  35
+                ]
+              },
+              {
+                "localized_name": "HISTOGRAM",
+                "name": "luminance",
+                "type": "HISTOGRAM",
+                "links": []
+              },
+              {
+                "localized_name": "HISTOGRAM",
+                "name": "red",
+                "type": "HISTOGRAM",
+                "links": [
+                  36
+                ]
+              },
+              {
+                "localized_name": "HISTOGRAM",
+                "name": "green",
+                "type": "HISTOGRAM",
+                "links": [
+                  37
+                ]
+              },
+              {
+                "localized_name": "HISTOGRAM",
+                "name": "blue",
+                "type": "HISTOGRAM",
+                "links": [
+                  38
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "ImageHistogram"
+            },
+            "widgets_values": []
+          }
+        ],
+        "groups": [],
+        "links": [
+          {
+            "id": 29,
+            "origin_id": -10,
+            "origin_slot": 0,
+            "target_id": 8,
+            "target_slot": 0,
+            "type": "IMAGE"
+          },
+          {
+            "id": 28,
+            "origin_id": 8,
+            "origin_slot": 0,
+            "target_id": -20,
+            "target_slot": 0,
+            "type": "IMAGE"
+          },
+          {
+            "id": 30,
+            "origin_id": 4,
+            "origin_slot": 0,
+            "target_id": 8,
+            "target_slot": 2,
+            "type": "CURVE"
+          },
+          {
+            "id": 31,
+            "origin_id": 5,
+            "origin_slot": 0,
+            "target_id": 8,
+            "target_slot": 3,
+            "type": "CURVE"
+          },
+          {
+            "id": 32,
+            "origin_id": 6,
+            "origin_slot": 0,
+            "target_id": 8,
+            "target_slot": 4,
+            "type": "CURVE"
+          },
+          {
+            "id": 33,
+            "origin_id": 7,
+            "origin_slot": 0,
+            "target_id": 8,
+            "target_slot": 5,
+            "type": "CURVE"
+          },
+          {
+            "id": 34,
+            "origin_id": -10,
+            "origin_slot": 0,
+            "target_id": 9,
+            "target_slot": 0,
+            "type": "IMAGE"
+          },
+          {
+            "id": 35,
+            "origin_id": 9,
+            "origin_slot": 0,
+            "target_id": 4,
+            "target_slot": 1,
+            "type": "HISTOGRAM"
+          },
+          {
+            "id": 36,
+            "origin_id": 9,
+            "origin_slot": 2,
+            "target_id": 5,
+            "target_slot": 1,
+            "type": "HISTOGRAM"
+          },
+          {
+            "id": 37,
+            "origin_id": 9,
+            "origin_slot": 3,
+            "target_id": 6,
+            "target_slot": 1,
+            "type": "HISTOGRAM"
+          },
+          {
+            "id": 38,
+            "origin_id": 9,
+            "origin_slot": 4,
+            "target_id": 7,
+            "target_slot": 1,
+            "type": "HISTOGRAM"
+          }
+        ],
+        "extra": {
+          "workflowRendererVersion": "LG"
+        },
+        "category": "Image Tools/Color adjust"
+      }
+    ]
+  }
+}

blueprints/Image Channels.json

@@ -1 +1,322 @@
-{"revision": 0, "last_node_id": 29, "last_link_id": 0, "nodes": [{"id": 29, "type": "4c9d6ea4-b912-40e5-8766-6793a9758c53", "pos": [1970, -230], "size": [180, 86], "flags": {}, "order": 5, "mode": 0, "inputs": [{"label": "image", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": null}], "outputs": [{"label": "R", "localized_name": "IMAGE0", "name": "IMAGE0", "type": "IMAGE", "links": []}, {"label": "G", "localized_name": "IMAGE1", "name": "IMAGE1", "type": "IMAGE", "links": []}, {"label": "B", "localized_name": "IMAGE2", "name": "IMAGE2", "type": "IMAGE", "links": []}, {"label": "A", "localized_name": "IMAGE3", "name": "IMAGE3", "type": "IMAGE", "links": []}], "title": "Image Channels", "properties": {"proxyWidgets": []}, "widgets_values": []}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "4c9d6ea4-b912-40e5-8766-6793a9758c53", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 28, "lastLinkId": 39, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Image Channels", "inputNode": {"id": -10, "bounding": [1820, -185, 120, 60]}, "outputNode": {"id": -20, "bounding": [2460, -215, 120, 120]}, "inputs": [{"id": "3522932b-2d86-4a1f-a02a-cb29f3a9d7fe", "name": "images.image0", "type": "IMAGE", "linkIds": [39], "localized_name": "images.image0", "label": "image", "pos": [1920, -165]}], "outputs": [{"id": "605cb9c3-b065-4d9b-81d2-3ec331889b2b", "name": "IMAGE0", "type": "IMAGE", "linkIds": [26], "localized_name": "IMAGE0", "label": "R", "pos": [2480, -195]}, {"id": "fb44a77e-0522-43e9-9527-82e7465b3596", "name": "IMAGE1", "type": "IMAGE", "linkIds": [27], "localized_name": "IMAGE1", "label": "G", "pos": [2480, -175]}, {"id": "81460ee6-0131-402a-874f-6bf3001fc4ff", "name": "IMAGE2", "type": "IMAGE", "linkIds": [28], "localized_name": "IMAGE2", "label": "B", "pos": [2480, -155]}, {"id": "ae690246-80d4-4951-b1d9-9306d8a77417", "name": "IMAGE3", "type": "IMAGE", "linkIds": [29], "localized_name": "IMAGE3", "label": "A", "pos": [2480, -135]}], "widgets": [], "nodes": [{"id": 23, "type": "GLSLShader", "pos": [2000, -330], "size": [400, 172], "flags": {}, "order": 0, "mode": 0, "inputs": [{"label": "image", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": 39}, {"localized_name": "fragment_shader", "name": "fragment_shader", "type": "STRING", "widget": {"name": "fragment_shader"}, "link": null}, {"localized_name": "size_mode", "name": "size_mode", "type": "COMFY_DYNAMICCOMBO_V3", "widget": {"name": "size_mode"}, "link": null}, {"label": "image1", "localized_name": "images.image1", "name": "images.image1", "shape": 7, "type": "IMAGE", "link": null}], "outputs": [{"label": "R", "localized_name": "IMAGE0", "name": "IMAGE0", "type": "IMAGE", "links": [26]}, {"label": "G", "localized_name": "IMAGE1", "name": "IMAGE1", "type": "IMAGE", "links": [27]}, {"label": "B", "localized_name": "IMAGE2", "name": "IMAGE2", "type": "IMAGE", "links": [28]}, {"label": "A", "localized_name": "IMAGE3", "name": "IMAGE3", "type": "IMAGE", "links": [29]}], "properties": {"Node name for S&R": "GLSLShader"}, "widgets_values": ["#version 300 es\nprecision highp float;\n\nuniform sampler2D u_image0;\n\nin vec2 v_texCoord;\nlayout(location = 0) out vec4 fragColor0;\nlayout(location = 1) out vec4 fragColor1;\nlayout(location = 2) out vec4 fragColor2;\nlayout(location = 3) out vec4 fragColor3;\n\nvoid main() {\n  vec4 color = texture(u_image0, v_texCoord);\n  // Output each channel as grayscale to separate render targets\n  fragColor0 = vec4(vec3(color.r), 1.0);  // Red channel\n  fragColor1 = vec4(vec3(color.g), 1.0);  // Green channel\n  fragColor2 = vec4(vec3(color.b), 1.0);  // Blue channel\n  fragColor3 = vec4(vec3(color.a), 1.0);  // Alpha channel\n}\n", "from_input"]}], "groups": [], "links": [{"id": 39, "origin_id": -10, "origin_slot": 0, "target_id": 23, "target_slot": 0, "type": "IMAGE"}, {"id": 26, "origin_id": 23, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "IMAGE"}, {"id": 27, "origin_id": 23, "origin_slot": 1, "target_id": -20, "target_slot": 1, "type": "IMAGE"}, {"id": 28, "origin_id": 23, "origin_slot": 2, "target_id": -20, "target_slot": 2, "type": "IMAGE"}, {"id": 29, "origin_id": 23, "origin_slot": 3, "target_id": -20, "target_slot": 3, "type": "IMAGE"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Image Tools/Color adjust"}]}}
+{
+  "revision": 0,
+  "last_node_id": 29,
+  "last_link_id": 0,
+  "nodes": [
+    {
+      "id": 29,
+      "type": "4c9d6ea4-b912-40e5-8766-6793a9758c53",
+      "pos": [
+        1970,
+        -230
+      ],
+      "size": [
+        180,
+        86
+      ],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "label": "image",
+          "localized_name": "images.image0",
+          "name": "images.image0",
+          "type": "IMAGE",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "label": "R",
+          "localized_name": "IMAGE0",
+          "name": "IMAGE0",
+          "type": "IMAGE",
+          "links": []
+        },
+        {
+          "label": "G",
+          "localized_name": "IMAGE1",
+          "name": "IMAGE1",
+          "type": "IMAGE",
+          "links": []
+        },
+        {
+          "label": "B",
+          "localized_name": "IMAGE2",
+          "name": "IMAGE2",
+          "type": "IMAGE",
+          "links": []
+        },
+        {
+          "label": "A",
+          "localized_name": "IMAGE3",
+          "name": "IMAGE3",
+          "type": "IMAGE",
+          "links": []
+        }
+      ],
+      "title": "Image Channels",
+      "properties": {
+        "proxyWidgets": []
+      },
+      "widgets_values": []
+    }
+  ],
+  "links": [],
+  "version": 0.4,
+  "definitions": {
+    "subgraphs": [
+      {
+        "id": "4c9d6ea4-b912-40e5-8766-6793a9758c53",
+        "version": 1,
+        "state": {
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+          "lastNodeId": 28,
+          "lastLinkId": 39,
+          "lastRerouteId": 0
+        },
+        "revision": 0,
+        "config": {},
+        "name": "Image Channels",
+        "inputNode": {
+          "id": -10,
+          "bounding": [
+            1820,
+            -185,
+            120,
+            60
+          ]
+        },
+        "outputNode": {
+          "id": -20,
+          "bounding": [
+            2460,
+            -215,
+            120,
+            120
+          ]
+        },
+        "inputs": [
+          {
+            "id": "3522932b-2d86-4a1f-a02a-cb29f3a9d7fe",
+            "name": "images.image0",
+            "type": "IMAGE",
+            "linkIds": [
+              39
+            ],
+            "localized_name": "images.image0",
+            "label": "image",
+            "pos": [
+              1920,
+              -165
+            ]
+          }
+        ],
+        "outputs": [
+          {
+            "id": "605cb9c3-b065-4d9b-81d2-3ec331889b2b",
+            "name": "IMAGE0",
+            "type": "IMAGE",
+            "linkIds": [
+              26
+            ],
+            "localized_name": "IMAGE0",
+            "label": "R",
+            "pos": [
+              2480,
+              -195
+            ]
+          },
+          {
+            "id": "fb44a77e-0522-43e9-9527-82e7465b3596",
+            "name": "IMAGE1",
+            "type": "IMAGE",
+            "linkIds": [
+              27
+            ],
+            "localized_name": "IMAGE1",
+            "label": "G",
+            "pos": [
+              2480,
+              -175
+            ]
+          },
+          {
+            "id": "81460ee6-0131-402a-874f-6bf3001fc4ff",
+            "name": "IMAGE2",
+            "type": "IMAGE",
+            "linkIds": [
+              28
+            ],
+            "localized_name": "IMAGE2",
+            "label": "B",
+            "pos": [
+              2480,
+              -155
+            ]
+          },
+          {
+            "id": "ae690246-80d4-4951-b1d9-9306d8a77417",
+            "name": "IMAGE3",
+            "type": "IMAGE",
+            "linkIds": [
+              29
+            ],
+            "localized_name": "IMAGE3",
+            "label": "A",
+            "pos": [
+              2480,
+              -135
+            ]
+          }
+        ],
+        "widgets": [],
+        "nodes": [
+          {
+            "id": 23,
+            "type": "GLSLShader",
+            "pos": [
+              2000,
+              -330
+            ],
+            "size": [
+              400,
+              172
+            ],
+            "flags": {},
+            "order": 0,
+            "mode": 0,
+            "inputs": [
+              {
+                "label": "image",
+                "localized_name": "images.image0",
+                "name": "images.image0",
+                "type": "IMAGE",
+                "link": 39
+              },
+              {
+                "localized_name": "fragment_shader",
+                "name": "fragment_shader",
+                "type": "STRING",
+                "widget": {
+                  "name": "fragment_shader"
+                },
+                "link": null
+              },
+              {
+                "localized_name": "size_mode",
+                "name": "size_mode",
+                "type": "COMFY_DYNAMICCOMBO_V3",
+                "widget": {
+                  "name": "size_mode"
+                },
+                "link": null
+              },
+              {
+                "label": "image1",
+                "localized_name": "images.image1",
+                "name": "images.image1",
+                "shape": 7,
+                "type": "IMAGE",
+                "link": null
+              }
+            ],
+            "outputs": [
+              {
+                "label": "R",
+                "localized_name": "IMAGE0",
+                "name": "IMAGE0",
+                "type": "IMAGE",
+                "links": [
+                  26
+                ]
+              },
+              {
+                "label": "G",
+                "localized_name": "IMAGE1",
+                "name": "IMAGE1",
+                "type": "IMAGE",
+                "links": [
+                  27
+                ]
+              },
+              {
+                "label": "B",
+                "localized_name": "IMAGE2",
+                "name": "IMAGE2",
+                "type": "IMAGE",
+                "links": [
+                  28
+                ]
+              },
+              {
+                "label": "A",
+                "localized_name": "IMAGE3",
+                "name": "IMAGE3",
+                "type": "IMAGE",
+                "links": [
+                  29
+                ]
+              }
+            ],
+            "properties": {
+              "Node name for S&R": "GLSLShader"
+            },
+            "widgets_values": [
+              "#version 300 es\nprecision highp float;\n\nuniform sampler2D u_image0;\n\nin vec2 v_texCoord;\nlayout(location = 0) out vec4 fragColor0;\nlayout(location = 1) out vec4 fragColor1;\nlayout(location = 2) out vec4 fragColor2;\nlayout(location = 3) out vec4 fragColor3;\n\nvoid main() {\n  vec4 color = texture(u_image0, v_texCoord);\n  // Output each channel as grayscale to separate render targets\n  fragColor0 = vec4(vec3(color.r), 1.0);  // Red channel\n  fragColor1 = vec4(vec3(color.g), 1.0);  // Green channel\n  fragColor2 = vec4(vec3(color.b), 1.0);  // Blue channel\n  fragColor3 = vec4(vec3(color.a), 1.0);  // Alpha channel\n}\n",
+              "from_input"
+            ]
+          }
+        ],
+        "groups": [],
+        "links": [
+          {
+            "id": 39,
+            "origin_id": -10,
+            "origin_slot": 0,
+            "target_id": 23,
+            "target_slot": 0,
+            "type": "IMAGE"
+          },
+          {
+            "id": 26,
+            "origin_id": 23,
+            "origin_slot": 0,
+            "target_id": -20,
+            "target_slot": 0,
+            "type": "IMAGE"
+          },
+          {
+            "id": 27,
+            "origin_id": 23,
+            "origin_slot": 1,
+            "target_id": -20,
+            "target_slot": 1,
+            "type": "IMAGE"
+          },
+          {
+            "id": 28,
+            "origin_id": 23,
+            "origin_slot": 2,
+            "target_id": -20,
+            "target_slot": 2,
+            "type": "IMAGE"
+          },
+          {
+            "id": 29,
+            "origin_id": 23,
+            "origin_slot": 3,
+            "target_id": -20,
+            "target_slot": 3,
+            "type": "IMAGE"
+          }
+        ],
+        "extra": {
+          "workflowRendererVersion": "LG"
+        },
+        "category": "Image Tools/Color adjust"
+      }
+    ]
+  }
+}

blueprints/Prompt Enhance.json

@@ -1 +1,278 @@
-{"revision": 0, "last_node_id": 15, "last_link_id": 0, "nodes": [{"id": 15, "type": "24d8bbfd-39d4-4774-bff0-3de40cc7a471", "pos": [-1490, 2040], "size": [400, 260], "flags": {}, "order": 0, "mode": 0, "inputs": [{"name": "prompt", "type": "STRING", "widget": {"name": "prompt"}, "link": null}, {"label": "reference images", "name": "images", "type": "IMAGE", "link": null}], "outputs": [{"name": "STRING", "type": "STRING", "links": null}], "title": "Prompt Enhance", "properties": {"proxyWidgets": [["-1", "prompt"]], "cnr_id": "comfy-core", "ver": "0.14.1"}, "widgets_values": [""]}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "24d8bbfd-39d4-4774-bff0-3de40cc7a471", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 15, "lastLinkId": 14, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Prompt Enhance", "inputNode": {"id": -10, "bounding": [-2170, 2110, 138.876953125, 80]}, "outputNode": {"id": -20, "bounding": [-640, 2110, 120, 60]}, "inputs": [{"id": "aeab7216-00e0-4528-a09b-bba50845c5a6", "name": "prompt", "type": "STRING", "linkIds": [11], "pos": [-2051.123046875, 2130]}, {"id": "7b73fd36-aa31-4771-9066-f6c83879994b", "name": "images", "type": "IMAGE", "linkIds": [14], "label": "reference images", "pos": [-2051.123046875, 2150]}], "outputs": [{"id": "c7b0d930-68a1-48d1-b496-0519e5837064", "name": "STRING", "type": "STRING", "linkIds": [13], "pos": [-620, 2130]}], "widgets": [], "nodes": [{"id": 11, "type": "GeminiNode", "pos": [-1560, 1990], "size": [470, 470], "flags": {}, "order": 0, "mode": 0, "inputs": [{"localized_name": "images", "name": "images", "shape": 7, "type": "IMAGE", "link": 14}, {"localized_name": "audio", "name": "audio", "shape": 7, "type": "AUDIO", "link": null}, {"localized_name": "video", "name": "video", "shape": 7, "type": "VIDEO", "link": null}, {"localized_name": "files", "name": "files", "shape": 7, "type": "GEMINI_INPUT_FILES", "link": null}, {"localized_name": "prompt", "name": "prompt", "type": "STRING", "widget": {"name": "prompt"}, "link": 11}, {"localized_name": "model", "name": "model", "type": "COMBO", "widget": {"name": "model"}, "link": null}, {"localized_name": "seed", "name": "seed", "type": "INT", "widget": {"name": "seed"}, "link": null}, {"localized_name": "system_prompt", "name": "system_prompt", "shape": 7, "type": "STRING", "widget": {"name": "system_prompt"}, "link": null}], "outputs": [{"localized_name": "STRING", "name": "STRING", "type": "STRING", "links": [13]}], "properties": {"cnr_id": "comfy-core", "ver": "0.14.1", "Node name for S&R": "GeminiNode"}, "widgets_values": ["", "gemini-3-pro-preview", 42, "randomize", "You are an expert in prompt writing.\nBased on the input, rewrite the user's input into a detailed prompt.\nincluding camera settings, lighting, composition, and style.\nReturn the prompt only"], "color": "#432", "bgcolor": "#653"}], "groups": [], "links": [{"id": 11, "origin_id": -10, "origin_slot": 0, "target_id": 11, "target_slot": 4, "type": "STRING"}, {"id": 13, "origin_id": 11, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "STRING"}, {"id": 14, "origin_id": -10, "origin_slot": 1, "target_id": 11, "target_slot": 0, "type": "IMAGE"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Text generation/Prompt enhance"}]}, "extra": {}}
+{
+  "revision": 0,
+  "last_node_id": 15,
+  "last_link_id": 0,
+  "nodes": [
+    {
+      "id": 15,
+      "type": "24d8bbfd-39d4-4774-bff0-3de40cc7a471",
+      "pos": [
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+      ],
+      "size": [
+        400,
+        260
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "prompt",
+          "type": "STRING",
+          "widget": {
+            "name": "prompt"
+          },
+          "link": null
+        },
+        {
+          "label": "reference images",
+          "name": "images",
+          "type": "IMAGE",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "STRING",
+          "type": "STRING",
+          "links": null
+        }
+      ],
+      "title": "Prompt Enhance",
+      "properties": {
+        "proxyWidgets": [
+          [
+            "-1",
+            "prompt"
+          ]
+        ],
+        "cnr_id": "comfy-core",
+        "ver": "0.14.1"
+      },
+      "widgets_values": [
+        ""
+      ]
+    }
+  ],
+  "links": [],
+  "version": 0.4,
+  "definitions": {
+    "subgraphs": [
+      {
+        "id": "24d8bbfd-39d4-4774-bff0-3de40cc7a471",
+        "version": 1,
+        "state": {
+          "lastGroupId": 0,
+          "lastNodeId": 15,
+          "lastLinkId": 14,
+          "lastRerouteId": 0
+        },
+        "revision": 0,
+        "config": {},
+        "name": "Prompt Enhance",
+        "inputNode": {
+          "id": -10,
+          "bounding": [
+            -2170,
+            2110,
+            138.876953125,
+            80
+          ]
+        },
+        "outputNode": {
+          "id": -20,
+          "bounding": [
+            -640,
+            2110,
+            120,
+            60
+          ]
+        },
+        "inputs": [
+          {
+            "id": "aeab7216-00e0-4528-a09b-bba50845c5a6",
+            "name": "prompt",
+            "type": "STRING",
+            "linkIds": [
+              11
+            ],
+            "pos": [
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+              2130
+            ]
+          },
+          {
+            "id": "7b73fd36-aa31-4771-9066-f6c83879994b",
+            "name": "images",
+            "type": "IMAGE",
+            "linkIds": [
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+            ],
+            "label": "reference images",
+            "pos": [
+              -2051.123046875,
+              2150
+            ]
+          }
+        ],
+        "outputs": [
+          {
+            "id": "c7b0d930-68a1-48d1-b496-0519e5837064",
+            "name": "STRING",
+            "type": "STRING",
+            "linkIds": [
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+            "pos": [
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+              2130
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+            "type": "GeminiNode",
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+            "size": [
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+              470
+            ],
+            "flags": {},
+            "order": 0,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "images",
+                "name": "images",
+                "shape": 7,
+                "type": "IMAGE",
+                "link": 14
+              },
+              {
+                "localized_name": "audio",
+                "name": "audio",
+                "shape": 7,
+                "type": "AUDIO",
+                "link": null
+              },
+              {
+                "localized_name": "video",
+                "name": "video",
+                "shape": 7,
+                "type": "VIDEO",
+                "link": null
+              },
+              {
+                "localized_name": "files",
+                "name": "files",
+                "shape": 7,
+                "type": "GEMINI_INPUT_FILES",
+                "link": null
+              },
+              {
+                "localized_name": "prompt",
+                "name": "prompt",
+                "type": "STRING",
+                "widget": {
+                  "name": "prompt"
+                },
+                "link": 11
+              },
+              {
+                "localized_name": "model",
+                "name": "model",
+                "type": "COMBO",
+                "widget": {
+                  "name": "model"
+                },
+                "link": null
+              },
+              {
+                "localized_name": "seed",
+                "name": "seed",
+                "type": "INT",
+                "widget": {
+                  "name": "seed"
+                },
+                "link": null
+              },
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+}

blueprints/Sharpen.json

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+}

blueprints/Video Upscale(GAN x4).json

@@ -1 +1,420 @@
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+            120,
+            80
+          ]
+        },
+        "outputNode": {
+          "id": -20,
+          "bounding": [
+            1490,
+            460,
+            120,
+            60
+          ]
+        },
+        "inputs": [
+          {
+            "id": "666d633e-93e7-42dc-8d11-2b7b99b0f2a6",
+            "name": "video",
+            "type": "VIDEO",
+            "linkIds": [
+              10
+            ],
+            "localized_name": "video",
+            "pos": [
+              650,
+              480
+            ]
+          },
+          {
+            "id": "2e23a087-caa8-4d65-99e6-662761aa905a",
+            "name": "model_name",
+            "type": "COMBO",
+            "linkIds": [
+              19
+            ],
+            "pos": [
+              650,
+              500
+            ]
+          }
+        ],
+        "outputs": [
+          {
+            "id": "0c1768ea-3ec2-412f-9af6-8e0fa36dae70",
+            "name": "VIDEO",
+            "type": "VIDEO",
+            "linkIds": [
+              15
+            ],
+            "localized_name": "VIDEO",
+            "pos": [
+              1510,
+              480
+            ]
+          }
+        ],
+        "widgets": [],
+        "nodes": [
+          {
+            "id": 2,
+            "type": "ImageUpscaleWithModel",
+            "pos": [
+              1110,
+              450
+            ],
+            "size": [
+              320,
+              46
+            ],
+            "flags": {},
+            "order": 1,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "upscale_model",
+                "name": "upscale_model",
+                "type": "UPSCALE_MODEL",
+                "link": 1
+              },
+              {
+                "localized_name": "image",
+                "name": "image",
+                "type": "IMAGE",
+                "link": 14
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "IMAGE",
+                "name": "IMAGE",
+                "type": "IMAGE",
+                "links": [
+                  13
+                ]
+              }
+            ],
+            "properties": {
+              "cnr_id": "comfy-core",
+              "ver": "0.10.0",
+              "Node name for S&R": "ImageUpscaleWithModel"
+            }
+          },
+          {
+            "id": 11,
+            "type": "CreateVideo",
+            "pos": [
+              1110,
+              550
+            ],
+            "size": [
+              320,
+              78
+            ],
+            "flags": {},
+            "order": 3,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "images",
+                "name": "images",
+                "type": "IMAGE",
+                "link": 13
+              },
+              {
+                "localized_name": "audio",
+                "name": "audio",
+                "shape": 7,
+                "type": "AUDIO",
+                "link": 16
+              },
+              {
+                "localized_name": "fps",
+                "name": "fps",
+                "type": "FLOAT",
+                "widget": {
+                  "name": "fps"
+                },
+                "link": 12
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "VIDEO",
+                "name": "VIDEO",
+                "type": "VIDEO",
+                "links": [
+                  15
+                ]
+              }
+            ],
+            "properties": {
+              "cnr_id": "comfy-core",
+              "ver": "0.10.0",
+              "Node name for S&R": "CreateVideo"
+            },
+            "widgets_values": [
+              30
+            ]
+          },
+          {
+            "id": 10,
+            "type": "GetVideoComponents",
+            "pos": [
+              1110,
+              330
+            ],
+            "size": [
+              320,
+              70
+            ],
+            "flags": {},
+            "order": 2,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "video",
+                "name": "video",
+                "type": "VIDEO",
+                "link": 10
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "images",
+                "name": "images",
+                "type": "IMAGE",
+                "links": [
+                  14
+                ]
+              },
+              {
+                "localized_name": "audio",
+                "name": "audio",
+                "type": "AUDIO",
+                "links": [
+                  16
+                ]
+              },
+              {
+                "localized_name": "fps",
+                "name": "fps",
+                "type": "FLOAT",
+                "links": [
+                  12
+                ]
+              }
+            ],
+            "properties": {
+              "cnr_id": "comfy-core",
+              "ver": "0.10.0",
+              "Node name for S&R": "GetVideoComponents"
+            }
+          },
+          {
+            "id": 1,
+            "type": "UpscaleModelLoader",
+            "pos": [
+              750,
+              450
+            ],
+            "size": [
+              280,
+              60
+            ],
+            "flags": {},
+            "order": 0,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "model_name",
+                "name": "model_name",
+                "type": "COMBO",
+                "widget": {
+                  "name": "model_name"
+                },
+                "link": 19
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "UPSCALE_MODEL",
+                "name": "UPSCALE_MODEL",
+                "type": "UPSCALE_MODEL",
+                "links": [
+                  1
+                ]
+              }
+            ],
+            "properties": {
+              "cnr_id": "comfy-core",
+              "ver": "0.10.0",
+              "Node name for S&R": "UpscaleModelLoader",
+              "models": [
+                {
+                  "name": "RealESRGAN_x4plus.safetensors",
+                  "url": "https://huggingface.co/Comfy-Org/Real-ESRGAN_repackaged/resolve/main/RealESRGAN_x4plus.safetensors",
+                  "directory": "upscale_models"
+                }
+              ]
+            },
+            "widgets_values": [
+              "RealESRGAN_x4plus.safetensors"
+            ]
+          }
+        ],
+        "groups": [],
+        "links": [
+          {
+            "id": 1,
+            "origin_id": 1,
+            "origin_slot": 0,
+            "target_id": 2,
+            "target_slot": 0,
+            "type": "UPSCALE_MODEL"
+          },
+          {
+            "id": 14,
+            "origin_id": 10,
+            "origin_slot": 0,
+            "target_id": 2,
+            "target_slot": 1,
+            "type": "IMAGE"
+          },
+          {
+            "id": 13,
+            "origin_id": 2,
+            "origin_slot": 0,
+            "target_id": 11,
+            "target_slot": 0,
+            "type": "IMAGE"
+          },
+          {
+            "id": 16,
+            "origin_id": 10,
+            "origin_slot": 1,
+            "target_id": 11,
+            "target_slot": 1,
+            "type": "AUDIO"
+          },
+          {
+            "id": 12,
+            "origin_id": 10,
+            "origin_slot": 2,
+            "target_id": 11,
+            "target_slot": 2,
+            "type": "FLOAT"
+          },
+          {
+            "id": 10,
+            "origin_id": -10,
+            "origin_slot": 0,
+            "target_id": 10,
+            "target_slot": 0,
+            "type": "VIDEO"
+          },
+          {
+            "id": 15,
+            "origin_id": 11,
+            "origin_slot": 0,
+            "target_id": -20,
+            "target_slot": 0,
+            "type": "VIDEO"
+          },
+          {
+            "id": 19,
+            "origin_id": -10,
+            "origin_slot": 1,
+            "target_id": 1,
+            "target_slot": 0,
+            "type": "COMBO"
+          }
+        ],
+        "extra": {
+          "workflowRendererVersion": "LG"
+        },
+        "category": "Video generation and editing/Enhance video"
+      }
+    ]
+  },
+  "extra": {}
+}

comfy/cli_args.py

@@ -110,11 +110,13 @@ 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_RAM_AUTO_GB = -1.0
+
 cache_group = parser.add_mutually_exclusive_group()
 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("--cache-ram", nargs='?', const=4.0, type=float, default=0, help="Use RAM pressure caching with the specified headroom threshold. If available RAM drops below the threhold the cache remove large items to free RAM. Default 4GB")
+cache_group.add_argument("--cache-ram", nargs='?', const=CACHE_RAM_AUTO_GB, type=float, default=0, help="Use RAM pressure caching with the specified headroom threshold. If available RAM drops below the threshold the cache removes large items to free RAM. Default (when no value is provided): 25%% of system RAM (min 4GB, max 32GB).")
 
 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.")
@@ -182,6 +184,8 @@ parser.add_argument("--disable-api-nodes", action="store_true", help="Disable lo
 
 parser.add_argument("--multi-user", action="store_true", help="Enables per-user storage.")
 
+parser.add_argument("--use-process-isolation", action="store_true", help="Enable process isolation for custom nodes with pyproject.toml manifests containing a [tool.comfy.isolation] section.")
+
 parser.add_argument("--verbose", default='INFO', const='DEBUG', nargs="?", choices=['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'], help='Set the logging level')
 parser.add_argument("--log-stdout", action="store_true", help="Send normal process output to stdout instead of stderr (default).")
 

comfy/hooks.py

@@ -14,6 +14,9 @@ if TYPE_CHECKING:
 import comfy.lora
 import comfy.model_management
 import comfy.patcher_extension
+from comfy.cli_args import args
+import uuid
+import os
 from node_helpers import conditioning_set_values
 
 # #######################################################################################################
@@ -61,8 +64,37 @@ class EnumHookScope(enum.Enum):
     HookedOnly = "hooked_only"
 
 
+_ISOLATION_HOOKREF_MODE = args.use_process_isolation or os.environ.get("PYISOLATE_CHILD") == "1"
+
+
 class _HookRef:
-    pass
+    def __init__(self):
+        if _ISOLATION_HOOKREF_MODE:
+            self._pyisolate_id = str(uuid.uuid4())
+
+    def _ensure_pyisolate_id(self):
+        pyisolate_id = getattr(self, "_pyisolate_id", None)
+        if pyisolate_id is None:
+            pyisolate_id = str(uuid.uuid4())
+            self._pyisolate_id = pyisolate_id
+        return pyisolate_id
+
+    def __eq__(self, other):
+        if not _ISOLATION_HOOKREF_MODE:
+            return self is other
+        if not isinstance(other, _HookRef):
+            return False
+        return self._ensure_pyisolate_id() == other._ensure_pyisolate_id()
+
+    def __hash__(self):
+        if not _ISOLATION_HOOKREF_MODE:
+            return id(self)
+        return hash(self._ensure_pyisolate_id())
+
+    def __str__(self):
+        if not _ISOLATION_HOOKREF_MODE:
+            return super().__str__()
+        return f"PYISOLATE_HOOKREF:{self._ensure_pyisolate_id()}"
 
 
 def default_should_register(hook: Hook, model: ModelPatcher, model_options: dict, target_dict: dict[str], registered: HookGroup):
@@ -168,6 +200,8 @@ class WeightHook(Hook):
                 key_map = comfy.lora.model_lora_keys_clip(model.model, key_map)
             else:
                 key_map = comfy.lora.model_lora_keys_unet(model.model, key_map)
+            if self.weights is None:
+                self.weights = {}
             weights = comfy.lora.load_lora(self.weights, key_map, log_missing=False)
         else:
             if target == EnumWeightTarget.Clip:

comfy/isolation/__init__.py

@@ -0,0 +1,436 @@
+# pylint: disable=consider-using-from-import,cyclic-import,global-statement,global-variable-not-assigned,import-outside-toplevel,logging-fstring-interpolation
+from __future__ import annotations
+import asyncio
+import inspect
+import logging
+import os
+import time
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Dict, List, Optional, Set, TYPE_CHECKING
+_IMPORT_TORCH = os.environ.get("PYISOLATE_IMPORT_TORCH", "1") == "1"
+
+load_isolated_node = None
+find_manifest_directories = None
+build_stub_class = None
+get_class_types_for_extension = None
+scan_shm_forensics = None
+start_shm_forensics = None
+
+if _IMPORT_TORCH:
+    import folder_paths
+    from .extension_loader import load_isolated_node
+    from .manifest_loader import find_manifest_directories
+    from .runtime_helpers import build_stub_class, get_class_types_for_extension
+    from .shm_forensics import scan_shm_forensics, start_shm_forensics
+
+if TYPE_CHECKING:
+    from pyisolate import ExtensionManager
+    from .extension_wrapper import ComfyNodeExtension
+
+LOG_PREFIX = "]["
+isolated_node_timings: List[tuple[float, Path, int]] = []
+
+if _IMPORT_TORCH:
+    PYISOLATE_VENV_ROOT = Path(folder_paths.base_path) / ".pyisolate_venvs"
+    PYISOLATE_VENV_ROOT.mkdir(parents=True, exist_ok=True)
+
+logger = logging.getLogger(__name__)
+_WORKFLOW_BOUNDARY_MIN_FREE_VRAM_BYTES = 2 * 1024 * 1024 * 1024
+_MODEL_PATCHER_IDLE_TIMEOUT_MS = 120000
+
+
+def initialize_proxies() -> None:
+    from .child_hooks import is_child_process
+
+    is_child = is_child_process()
+
+    if is_child:
+        from .child_hooks import initialize_child_process
+
+        initialize_child_process()
+    else:
+        from .host_hooks import initialize_host_process
+
+        initialize_host_process()
+        if start_shm_forensics is not None:
+            start_shm_forensics()
+
+
+@dataclass(frozen=True)
+class IsolatedNodeSpec:
+    node_name: str
+    display_name: str
+    stub_class: type
+    module_path: Path
+
+
+_ISOLATED_NODE_SPECS: List[IsolatedNodeSpec] = []
+_CLAIMED_PATHS: Set[Path] = set()
+_ISOLATION_SCAN_ATTEMPTED = False
+_EXTENSION_MANAGERS: List["ExtensionManager"] = []
+_RUNNING_EXTENSIONS: Dict[str, "ComfyNodeExtension"] = {}
+_ISOLATION_BACKGROUND_TASK: Optional["asyncio.Task[List[IsolatedNodeSpec]]"] = None
+_EARLY_START_TIME: Optional[float] = None
+
+
+def start_isolation_loading_early(loop: "asyncio.AbstractEventLoop") -> None:
+    global _ISOLATION_BACKGROUND_TASK, _EARLY_START_TIME
+    if _ISOLATION_BACKGROUND_TASK is not None:
+        return
+    _EARLY_START_TIME = time.perf_counter()
+    _ISOLATION_BACKGROUND_TASK = loop.create_task(initialize_isolation_nodes())
+
+
+async def await_isolation_loading() -> List[IsolatedNodeSpec]:
+    global _ISOLATION_BACKGROUND_TASK, _EARLY_START_TIME
+    if _ISOLATION_BACKGROUND_TASK is not None:
+        specs = await _ISOLATION_BACKGROUND_TASK
+        return specs
+    return await initialize_isolation_nodes()
+
+
+async def initialize_isolation_nodes() -> List[IsolatedNodeSpec]:
+    global _ISOLATED_NODE_SPECS, _ISOLATION_SCAN_ATTEMPTED, _CLAIMED_PATHS
+
+    if _ISOLATED_NODE_SPECS:
+        return _ISOLATED_NODE_SPECS
+
+    if _ISOLATION_SCAN_ATTEMPTED:
+        return []
+
+    _ISOLATION_SCAN_ATTEMPTED = True
+    if find_manifest_directories is None or load_isolated_node is None or build_stub_class is None:
+        return []
+    manifest_entries = find_manifest_directories()
+    _CLAIMED_PATHS = {entry[0].resolve() for entry in manifest_entries}
+
+    if not manifest_entries:
+        return []
+
+    os.environ["PYISOLATE_ISOLATION_ACTIVE"] = "1"
+    concurrency_limit = max(1, (os.cpu_count() or 4) // 2)
+    semaphore = asyncio.Semaphore(concurrency_limit)
+
+    async def load_with_semaphore(
+        node_dir: Path, manifest: Path
+    ) -> List[IsolatedNodeSpec]:
+        async with semaphore:
+            load_start = time.perf_counter()
+            spec_list = await load_isolated_node(
+                node_dir,
+                manifest,
+                logger,
+                lambda name, info, extension: build_stub_class(
+                    name,
+                    info,
+                    extension,
+                    _RUNNING_EXTENSIONS,
+                    logger,
+                ),
+                PYISOLATE_VENV_ROOT,
+                _EXTENSION_MANAGERS,
+            )
+            spec_list = [
+                IsolatedNodeSpec(
+                    node_name=node_name,
+                    display_name=display_name,
+                    stub_class=stub_cls,
+                    module_path=node_dir,
+                )
+                for node_name, display_name, stub_cls in spec_list
+            ]
+            isolated_node_timings.append(
+                (time.perf_counter() - load_start, node_dir, len(spec_list))
+            )
+            return spec_list
+
+    tasks = [
+        load_with_semaphore(node_dir, manifest)
+        for node_dir, manifest in manifest_entries
+    ]
+    results = await asyncio.gather(*tasks, return_exceptions=True)
+
+    specs: List[IsolatedNodeSpec] = []
+    for result in results:
+        if isinstance(result, Exception):
+            logger.error(
+                "%s Isolated node failed during startup; continuing: %s",
+                LOG_PREFIX,
+                result,
+            )
+            continue
+        specs.extend(result)
+
+    _ISOLATED_NODE_SPECS = specs
+    return list(_ISOLATED_NODE_SPECS)
+
+
+def _get_class_types_for_extension(extension_name: str) -> Set[str]:
+    """Get all node class types (node names) belonging to an extension."""
+    extension = _RUNNING_EXTENSIONS.get(extension_name)
+    if not extension:
+        return set()
+
+    ext_path = Path(extension.module_path)
+    class_types = set()
+    for spec in _ISOLATED_NODE_SPECS:
+        if spec.module_path.resolve() == ext_path.resolve():
+            class_types.add(spec.node_name)
+
+    return class_types
+
+
+async def notify_execution_graph(needed_class_types: Set[str], caches: list | None = None) -> None:
+    """Evict running extensions not needed for current execution.
+
+    When *caches* is provided, cache entries for evicted extensions' node
+    class_types are invalidated to prevent stale ``RemoteObjectHandle``
+    references from surviving in the output cache.
+    """
+    await wait_for_model_patcher_quiescence(
+        timeout_ms=_MODEL_PATCHER_IDLE_TIMEOUT_MS,
+        fail_loud=True,
+        marker="ISO:notify_graph_wait_idle",
+    )
+
+    evicted_class_types: Set[str] = set()
+
+    async def _stop_extension(
+        ext_name: str, extension: "ComfyNodeExtension", reason: str
+    ) -> None:
+        # Collect class_types BEFORE stopping so we can invalidate cache entries.
+        ext_class_types = _get_class_types_for_extension(ext_name)
+        evicted_class_types.update(ext_class_types)
+        logger.info("%s ISO:eject_start ext=%s reason=%s", LOG_PREFIX, ext_name, reason)
+        logger.debug("%s ISO:stop_start ext=%s", LOG_PREFIX, ext_name)
+        stop_result = extension.stop()
+        if inspect.isawaitable(stop_result):
+            await stop_result
+        _RUNNING_EXTENSIONS.pop(ext_name, None)
+        logger.debug("%s ISO:stop_done ext=%s", LOG_PREFIX, ext_name)
+        if scan_shm_forensics is not None:
+            scan_shm_forensics("ISO:stop_extension", refresh_model_context=True)
+
+    if scan_shm_forensics is not None:
+        scan_shm_forensics("ISO:notify_graph_start", refresh_model_context=True)
+    isolated_class_types_in_graph = needed_class_types.intersection(
+        {spec.node_name for spec in _ISOLATED_NODE_SPECS}
+    )
+    graph_uses_isolation = bool(isolated_class_types_in_graph)
+    logger.debug(
+        "%s ISO:notify_graph_start running=%d needed=%d",
+        LOG_PREFIX,
+        len(_RUNNING_EXTENSIONS),
+        len(needed_class_types),
+    )
+    if graph_uses_isolation:
+        for ext_name, extension in list(_RUNNING_EXTENSIONS.items()):
+            ext_class_types = _get_class_types_for_extension(ext_name)
+
+            # If NONE of this extension's nodes are in the execution graph -> evict.
+            if not ext_class_types.intersection(needed_class_types):
+                await _stop_extension(
+                    ext_name,
+                    extension,
+                    "isolated custom_node not in execution graph, evicting",
+                )
+    else:
+        logger.debug(
+            "%s ISO:notify_graph_skip_evict running=%d reason=no isolated nodes in graph",
+            LOG_PREFIX,
+            len(_RUNNING_EXTENSIONS),
+        )
+
+    # Isolated child processes add steady VRAM pressure; reclaim host-side models
+    # at workflow boundaries so subsequent host nodes (e.g. CLIP encode) keep headroom.
+    try:
+        import comfy.model_management as model_management
+
+        device = model_management.get_torch_device()
+        if getattr(device, "type", None) == "cuda":
+            required = max(
+                model_management.minimum_inference_memory(),
+                _WORKFLOW_BOUNDARY_MIN_FREE_VRAM_BYTES,
+            )
+            free_before = model_management.get_free_memory(device)
+            if free_before < required and _RUNNING_EXTENSIONS and graph_uses_isolation:
+                for ext_name, extension in list(_RUNNING_EXTENSIONS.items()):
+                    await _stop_extension(
+                        ext_name,
+                        extension,
+                        f"boundary low-vram restart (free={int(free_before)} target={int(required)})",
+                    )
+            if model_management.get_free_memory(device) < required:
+                model_management.unload_all_models()
+            model_management.cleanup_models_gc()
+            model_management.cleanup_models()
+            if model_management.get_free_memory(device) < required:
+                model_management.free_memory(required, device, for_dynamic=False)
+                model_management.soft_empty_cache()
+    except Exception:
+        logger.debug(
+            "%s workflow-boundary host VRAM relief failed", LOG_PREFIX, exc_info=True
+        )
+    finally:
+        # Invalidate cached outputs for evicted extensions so stale
+        # RemoteObjectHandle references are not served from cache.
+        if evicted_class_types and caches:
+            total_invalidated = 0
+            for cache in caches:
+                if hasattr(cache, "invalidate_by_class_types"):
+                    total_invalidated += cache.invalidate_by_class_types(
+                        evicted_class_types
+                    )
+            if total_invalidated > 0:
+                logger.info(
+                    "%s ISO:cache_invalidated count=%d class_types=%s",
+                    LOG_PREFIX,
+                    total_invalidated,
+                    evicted_class_types,
+                )
+        scan_shm_forensics("ISO:notify_graph_done", refresh_model_context=True)
+        logger.debug(
+            "%s ISO:notify_graph_done running=%d", LOG_PREFIX, len(_RUNNING_EXTENSIONS)
+        )
+
+
+async def flush_running_extensions_transport_state() -> int:
+    await wait_for_model_patcher_quiescence(
+        timeout_ms=_MODEL_PATCHER_IDLE_TIMEOUT_MS,
+        fail_loud=True,
+        marker="ISO:flush_transport_wait_idle",
+    )
+    total_flushed = 0
+    for ext_name, extension in list(_RUNNING_EXTENSIONS.items()):
+        flush_fn = getattr(extension, "flush_transport_state", None)
+        if not callable(flush_fn):
+            continue
+        try:
+            flushed = await flush_fn()
+            if isinstance(flushed, int):
+                total_flushed += flushed
+                if flushed > 0:
+                    logger.debug(
+                        "%s %s workflow-end flush released=%d",
+                        LOG_PREFIX,
+                        ext_name,
+                        flushed,
+                    )
+        except Exception:
+            logger.debug(
+                "%s %s workflow-end flush failed", LOG_PREFIX, ext_name, exc_info=True
+            )
+    scan_shm_forensics(
+        "ISO:flush_running_extensions_transport_state", refresh_model_context=True
+    )
+    return total_flushed
+
+
+async def wait_for_model_patcher_quiescence(
+    timeout_ms: int = _MODEL_PATCHER_IDLE_TIMEOUT_MS,
+    *,
+    fail_loud: bool = False,
+    marker: str = "ISO:wait_model_patcher_idle",
+) -> bool:
+    try:
+        from comfy.isolation.model_patcher_proxy_registry import ModelPatcherRegistry
+
+        registry = ModelPatcherRegistry()
+        start = time.perf_counter()
+        idle = await registry.wait_all_idle(timeout_ms)
+        elapsed_ms = (time.perf_counter() - start) * 1000.0
+        if idle:
+            logger.debug(
+                "%s %s idle=1 timeout_ms=%d elapsed_ms=%.3f",
+                LOG_PREFIX,
+                marker,
+                timeout_ms,
+                elapsed_ms,
+            )
+            return True
+
+        states = await registry.get_all_operation_states()
+        logger.error(
+            "%s %s idle_timeout timeout_ms=%d elapsed_ms=%.3f states=%s",
+            LOG_PREFIX,
+            marker,
+            timeout_ms,
+            elapsed_ms,
+            states,
+        )
+        if fail_loud:
+            raise TimeoutError(
+                f"ModelPatcherRegistry did not quiesce within {timeout_ms} ms"
+            )
+        return False
+    except Exception:
+        if fail_loud:
+            raise
+        logger.debug("%s %s failed", LOG_PREFIX, marker, exc_info=True)
+        return False
+
+
+def get_claimed_paths() -> Set[Path]:
+    return _CLAIMED_PATHS
+
+
+def update_rpc_event_loops(loop: "asyncio.AbstractEventLoop | None" = None) -> None:
+    """Update all active RPC instances with the current event loop.
+
+    This MUST be called at the start of each workflow execution to ensure
+    RPC calls are scheduled on the correct event loop. This handles the case
+    where asyncio.run() creates a new event loop for each workflow.
+
+    Args:
+        loop: The event loop to use. If None, uses asyncio.get_running_loop().
+    """
+    if loop is None:
+        try:
+            loop = asyncio.get_running_loop()
+        except RuntimeError:
+            loop = asyncio.get_event_loop()
+
+    update_count = 0
+
+    # Update RPCs from ExtensionManagers
+    for manager in _EXTENSION_MANAGERS:
+        if not hasattr(manager, "extensions"):
+            continue
+        for name, extension in manager.extensions.items():
+            if hasattr(extension, "rpc") and extension.rpc is not None:
+                if hasattr(extension.rpc, "update_event_loop"):
+                    extension.rpc.update_event_loop(loop)
+                    update_count += 1
+                    logger.debug(f"{LOG_PREFIX}Updated loop on extension '{name}'")
+
+    # Also update RPCs from running extensions (they may have direct RPC refs)
+    for name, extension in _RUNNING_EXTENSIONS.items():
+        if hasattr(extension, "rpc") and extension.rpc is not None:
+            if hasattr(extension.rpc, "update_event_loop"):
+                extension.rpc.update_event_loop(loop)
+                update_count += 1
+                logger.debug(f"{LOG_PREFIX}Updated loop on running extension '{name}'")
+
+    if update_count > 0:
+        logger.debug(f"{LOG_PREFIX}Updated event loop on {update_count} RPC instances")
+    else:
+        logger.debug(
+            f"{LOG_PREFIX}No RPC instances found to update (managers={len(_EXTENSION_MANAGERS)}, running={len(_RUNNING_EXTENSIONS)})"
+        )
+
+
+__all__ = [
+    "LOG_PREFIX",
+    "initialize_proxies",
+    "initialize_isolation_nodes",
+    "start_isolation_loading_early",
+    "await_isolation_loading",
+    "notify_execution_graph",
+    "flush_running_extensions_transport_state",
+    "wait_for_model_patcher_quiescence",
+    "get_claimed_paths",
+    "update_rpc_event_loops",
+    "IsolatedNodeSpec",
+    "get_class_types_for_extension",
+]

comfy/isolation/adapter.py

@@ -0,0 +1,864 @@
+# pylint: disable=import-outside-toplevel,logging-fstring-interpolation,protected-access,raise-missing-from,useless-return,wrong-import-position
+from __future__ import annotations
+
+import logging
+import os
+import inspect
+from pathlib import Path
+from typing import Any, Dict, List, Optional, cast
+
+from pyisolate.interfaces import IsolationAdapter, SerializerRegistryProtocol  # type: ignore[import-untyped]
+from pyisolate._internal.rpc_protocol import AsyncRPC, ProxiedSingleton  # type: ignore[import-untyped]
+
+_IMPORT_TORCH = os.environ.get("PYISOLATE_IMPORT_TORCH", "1") == "1"
+
+# Singleton proxies that do NOT transitively import torch/PIL/psutil/aiohttp.
+# Safe to import in sealed workers without host framework modules.
+from comfy.isolation.proxies.folder_paths_proxy import FolderPathsProxy
+from comfy.isolation.proxies.helper_proxies import HelperProxiesService
+from comfy.isolation.proxies.web_directory_proxy import WebDirectoryProxy
+
+# Singleton proxies that transitively import torch, PIL, or heavy host modules.
+# Only available when torch/host framework is present.
+CLIPProxy = None
+CLIPRegistry = None
+ModelPatcherProxy = None
+ModelPatcherRegistry = None
+ModelSamplingProxy = None
+ModelSamplingRegistry = None
+VAEProxy = None
+VAERegistry = None
+FirstStageModelRegistry = None
+ModelManagementProxy = None
+PromptServerService = None
+ProgressProxy = None
+UtilsProxy = None
+_HAS_TORCH_PROXIES = False
+if _IMPORT_TORCH:
+    from comfy.isolation.clip_proxy import CLIPProxy, CLIPRegistry
+    from comfy.isolation.model_patcher_proxy import (
+        ModelPatcherProxy,
+        ModelPatcherRegistry,
+    )
+    from comfy.isolation.model_sampling_proxy import (
+        ModelSamplingProxy,
+        ModelSamplingRegistry,
+    )
+    from comfy.isolation.vae_proxy import VAEProxy, VAERegistry, FirstStageModelRegistry
+    from comfy.isolation.proxies.model_management_proxy import ModelManagementProxy
+    from comfy.isolation.proxies.prompt_server_impl import PromptServerService
+    from comfy.isolation.proxies.progress_proxy import ProgressProxy
+    from comfy.isolation.proxies.utils_proxy import UtilsProxy
+    _HAS_TORCH_PROXIES = True
+
+logger = logging.getLogger(__name__)
+
+# Force /dev/shm for shared memory (bwrap makes /tmp private)
+import tempfile
+
+if os.path.exists("/dev/shm"):
+    # Only override if not already set or if default is not /dev/shm
+    current_tmp = tempfile.gettempdir()
+    if not current_tmp.startswith("/dev/shm"):
+        logger.debug(
+            f"Configuring shared memory: Changing TMPDIR from {current_tmp} to /dev/shm"
+        )
+        os.environ["TMPDIR"] = "/dev/shm"
+        tempfile.tempdir = None  # Clear cache to force re-evaluation
+
+
+class ComfyUIAdapter(IsolationAdapter):
+    # ComfyUI-specific IsolationAdapter implementation
+
+    @property
+    def identifier(self) -> str:
+        return "comfyui"
+
+    def get_path_config(self, module_path: str) -> Optional[Dict[str, Any]]:
+        if "ComfyUI" in module_path and "custom_nodes" in module_path:
+            parts = module_path.split("ComfyUI")
+            if len(parts) > 1:
+                comfy_root = parts[0] + "ComfyUI"
+                return {
+                    "preferred_root": comfy_root,
+                    "additional_paths": [
+                        os.path.join(comfy_root, "custom_nodes"),
+                        os.path.join(comfy_root, "comfy"),
+                    ],
+                    "filtered_subdirs": ["comfy", "app", "comfy_execution", "utils"],
+                }
+        return None
+
+    def get_sandbox_system_paths(self) -> Optional[List[str]]:
+        """Returns required application paths to mount in the sandbox."""
+        # By inspecting where our adapter is loaded from, we can determine the comfy root
+        adapter_file = inspect.getfile(self.__class__)
+        # adapter_file = /home/johnj/ComfyUI/comfy/isolation/adapter.py
+        comfy_root = os.path.dirname(os.path.dirname(os.path.dirname(adapter_file)))
+        if os.path.exists(comfy_root):
+            return [comfy_root]
+        return None
+
+    def setup_child_environment(self, snapshot: Dict[str, Any]) -> None:
+        comfy_root = snapshot.get("preferred_root")
+        if not comfy_root:
+            return
+
+        requirements_path = Path(comfy_root) / "requirements.txt"
+        if requirements_path.exists():
+            import re
+
+            for line in requirements_path.read_text().splitlines():
+                line = line.strip()
+                if not line or line.startswith("#"):
+                    continue
+                pkg_name = re.split(r"[<>=!~\[]", line)[0].strip()
+                if pkg_name:
+                    logging.getLogger(pkg_name).setLevel(logging.ERROR)
+
+    def register_serializers(self, registry: SerializerRegistryProtocol) -> None:
+        if not _IMPORT_TORCH:
+            # Sealed worker without torch — register torch-free TensorValue handler
+            # so IMAGE/MASK/LATENT tensors arrive as numpy arrays, not raw dicts.
+            import numpy as np
+
+            _TORCH_DTYPE_TO_NUMPY = {
+                "torch.float32": np.float32,
+                "torch.float64": np.float64,
+                "torch.float16": np.float16,
+                "torch.bfloat16": np.float32,  # numpy has no bfloat16; upcast
+                "torch.int32": np.int32,
+                "torch.int64": np.int64,
+                "torch.int16": np.int16,
+                "torch.int8": np.int8,
+                "torch.uint8": np.uint8,
+                "torch.bool": np.bool_,
+            }
+
+            def _deserialize_tensor_value(data: Dict[str, Any]) -> Any:
+                dtype_str = data["dtype"]
+                np_dtype = _TORCH_DTYPE_TO_NUMPY.get(dtype_str, np.float32)
+                shape = tuple(data["tensor_size"])
+                arr = np.array(data["data"], dtype=np_dtype).reshape(shape)
+                return arr
+
+            _NUMPY_TO_TORCH_DTYPE = {
+                np.float32: "torch.float32",
+                np.float64: "torch.float64",
+                np.float16: "torch.float16",
+                np.int32: "torch.int32",
+                np.int64: "torch.int64",
+                np.int16: "torch.int16",
+                np.int8: "torch.int8",
+                np.uint8: "torch.uint8",
+                np.bool_: "torch.bool",
+            }
+
+            def _serialize_tensor_value(obj: Any) -> Dict[str, Any]:
+                arr = np.asarray(obj, dtype=np.float32) if obj.dtype not in _NUMPY_TO_TORCH_DTYPE else np.asarray(obj)
+                dtype_str = _NUMPY_TO_TORCH_DTYPE.get(arr.dtype.type, "torch.float32")
+                return {
+                    "__type__": "TensorValue",
+                    "dtype": dtype_str,
+                    "tensor_size": list(arr.shape),
+                    "requires_grad": False,
+                    "data": arr.tolist(),
+                }
+
+            registry.register("TensorValue", _serialize_tensor_value, _deserialize_tensor_value, data_type=True)
+            # ndarray output from sealed workers serializes as TensorValue for host torch reconstruction
+            registry.register("ndarray", _serialize_tensor_value, _deserialize_tensor_value, data_type=True)
+            return
+
+        import torch
+
+        def serialize_device(obj: Any) -> Dict[str, Any]:
+            return {"__type__": "device", "device_str": str(obj)}
+
+        def deserialize_device(data: Dict[str, Any]) -> Any:
+            return torch.device(data["device_str"])
+
+        registry.register("device", serialize_device, deserialize_device)
+
+        _VALID_DTYPES = {
+            "float16", "float32", "float64", "bfloat16",
+            "int8", "int16", "int32", "int64",
+            "uint8", "bool",
+        }
+
+        def serialize_dtype(obj: Any) -> Dict[str, Any]:
+            return {"__type__": "dtype", "dtype_str": str(obj)}
+
+        def deserialize_dtype(data: Dict[str, Any]) -> Any:
+            dtype_name = data["dtype_str"].replace("torch.", "")
+            if dtype_name not in _VALID_DTYPES:
+                raise ValueError(f"Invalid dtype: {data['dtype_str']}")
+            return getattr(torch, dtype_name)
+
+        registry.register("dtype", serialize_dtype, deserialize_dtype)
+
+        from comfy_api.latest._io import FolderType
+        from comfy_api.latest._ui import SavedImages, SavedResult
+
+        def serialize_saved_result(obj: Any) -> Dict[str, Any]:
+            return {
+                "__type__": "SavedResult",
+                "filename": obj.filename,
+                "subfolder": obj.subfolder,
+                "folder_type": obj.type.value,
+            }
+
+        def deserialize_saved_result(data: Dict[str, Any]) -> Any:
+            if isinstance(data, SavedResult):
+                return data
+            folder_type = data["folder_type"] if "folder_type" in data else data["type"]
+            return SavedResult(
+                filename=data["filename"],
+                subfolder=data["subfolder"],
+                type=FolderType(folder_type),
+            )
+
+        registry.register(
+            "SavedResult",
+            serialize_saved_result,
+            deserialize_saved_result,
+            data_type=True,
+        )
+
+        def serialize_saved_images(obj: Any) -> Dict[str, Any]:
+            return {
+                "__type__": "SavedImages",
+                "results": [serialize_saved_result(result) for result in obj.results],
+                "is_animated": obj.is_animated,
+            }
+
+        def deserialize_saved_images(data: Dict[str, Any]) -> Any:
+            return SavedImages(
+                results=[deserialize_saved_result(result) for result in data["results"]],
+                is_animated=data.get("is_animated", False),
+            )
+
+        registry.register(
+            "SavedImages",
+            serialize_saved_images,
+            deserialize_saved_images,
+            data_type=True,
+        )
+
+        def serialize_model_patcher(obj: Any) -> Dict[str, Any]:
+            # Child-side: must already have _instance_id (proxy)
+            if os.environ.get("PYISOLATE_CHILD") == "1":
+                if hasattr(obj, "_instance_id"):
+                    return {"__type__": "ModelPatcherRef", "model_id": obj._instance_id}
+                raise RuntimeError(
+                    f"ModelPatcher in child lacks _instance_id: "
+                    f"{type(obj).__module__}.{type(obj).__name__}"
+                )
+            # Host-side: register with registry
+            if hasattr(obj, "_instance_id"):
+                return {"__type__": "ModelPatcherRef", "model_id": obj._instance_id}
+            model_id = ModelPatcherRegistry().register(obj)
+            return {"__type__": "ModelPatcherRef", "model_id": model_id}
+
+        def deserialize_model_patcher(data: Any) -> Any:
+            """Deserialize ModelPatcher refs; pass through already-materialized objects."""
+            if isinstance(data, dict):
+                return ModelPatcherProxy(
+                    data["model_id"], registry=None, manage_lifecycle=False
+                )
+            return data
+
+        def deserialize_model_patcher_ref(data: Dict[str, Any]) -> Any:
+            """Context-aware ModelPatcherRef deserializer for both host and child."""
+            is_child = os.environ.get("PYISOLATE_CHILD") == "1"
+            if is_child:
+                return ModelPatcherProxy(
+                    data["model_id"], registry=None, manage_lifecycle=False
+                )
+            else:
+                return ModelPatcherRegistry()._get_instance(data["model_id"])
+
+        # Register ModelPatcher type for serialization
+        registry.register(
+            "ModelPatcher", serialize_model_patcher, deserialize_model_patcher
+        )
+        # Register ModelPatcherProxy type (already a proxy, just return ref)
+        registry.register(
+            "ModelPatcherProxy", serialize_model_patcher, deserialize_model_patcher
+        )
+        # Register ModelPatcherRef for deserialization (context-aware: host or child)
+        registry.register("ModelPatcherRef", None, deserialize_model_patcher_ref)
+
+        def serialize_clip(obj: Any) -> Dict[str, Any]:
+            if hasattr(obj, "_instance_id"):
+                return {"__type__": "CLIPRef", "clip_id": obj._instance_id}
+            clip_id = CLIPRegistry().register(obj)
+            return {"__type__": "CLIPRef", "clip_id": clip_id}
+
+        def deserialize_clip(data: Any) -> Any:
+            if isinstance(data, dict):
+                return CLIPProxy(data["clip_id"], registry=None, manage_lifecycle=False)
+            return data
+
+        def deserialize_clip_ref(data: Dict[str, Any]) -> Any:
+            """Context-aware CLIPRef deserializer for both host and child."""
+            is_child = os.environ.get("PYISOLATE_CHILD") == "1"
+            if is_child:
+                return CLIPProxy(data["clip_id"], registry=None, manage_lifecycle=False)
+            else:
+                return CLIPRegistry()._get_instance(data["clip_id"])
+
+        # Register CLIP type for serialization
+        registry.register("CLIP", serialize_clip, deserialize_clip)
+        # Register CLIPProxy type (already a proxy, just return ref)
+        registry.register("CLIPProxy", serialize_clip, deserialize_clip)
+        # Register CLIPRef for deserialization (context-aware: host or child)
+        registry.register("CLIPRef", None, deserialize_clip_ref)
+
+        def serialize_vae(obj: Any) -> Dict[str, Any]:
+            if hasattr(obj, "_instance_id"):
+                return {"__type__": "VAERef", "vae_id": obj._instance_id}
+            vae_id = VAERegistry().register(obj)
+            return {"__type__": "VAERef", "vae_id": vae_id}
+
+        def deserialize_vae(data: Any) -> Any:
+            if isinstance(data, dict):
+                return VAEProxy(data["vae_id"])
+            return data
+
+        def deserialize_vae_ref(data: Dict[str, Any]) -> Any:
+            """Context-aware VAERef deserializer for both host and child."""
+            is_child = os.environ.get("PYISOLATE_CHILD") == "1"
+            if is_child:
+                # Child: create a proxy
+                return VAEProxy(data["vae_id"])
+            else:
+                # Host: lookup real VAE from registry
+                return VAERegistry()._get_instance(data["vae_id"])
+
+        # Register VAE type for serialization
+        registry.register("VAE", serialize_vae, deserialize_vae)
+        # Register VAEProxy type (already a proxy, just return ref)
+        registry.register("VAEProxy", serialize_vae, deserialize_vae)
+        # Register VAERef for deserialization (context-aware: host or child)
+        registry.register("VAERef", None, deserialize_vae_ref)
+
+        # ModelSampling serialization - handles ModelSampling* types
+        # copyreg removed - no pickle fallback allowed
+
+        def serialize_model_sampling(obj: Any) -> Dict[str, Any]:
+            # Proxy with _instance_id — return ref (works from both host and child)
+            if hasattr(obj, "_instance_id"):
+                return {"__type__": "ModelSamplingRef", "ms_id": obj._instance_id}
+            # Child-side: object created locally in child (e.g. ModelSamplingAdvanced
+            # in nodes_z_image_turbo.py). Serialize as inline data so the host can
+            # reconstruct the real torch.nn.Module.
+            if os.environ.get("PYISOLATE_CHILD") == "1":
+                import base64
+                import io as _io
+
+                # Identify base classes from comfy.model_sampling
+                bases = []
+                for base in type(obj).__mro__:
+                    if base.__module__ == "comfy.model_sampling" and base.__name__ != "object":
+                        bases.append(base.__name__)
+                # Serialize state_dict as base64 safetensors-like
+                sd = obj.state_dict()
+                sd_serialized = {}
+                for k, v in sd.items():
+                    buf = _io.BytesIO()
+                    torch.save(v, buf)
+                    sd_serialized[k] = base64.b64encode(buf.getvalue()).decode("ascii")
+                # Capture plain attrs (shift, multiplier, sigma_data, etc.)
+                plain_attrs = {}
+                for k, v in obj.__dict__.items():
+                    if k.startswith("_"):
+                        continue
+                    if isinstance(v, (bool, int, float, str)):
+                        plain_attrs[k] = v
+                return {
+                    "__type__": "ModelSamplingInline",
+                    "bases": bases,
+                    "state_dict": sd_serialized,
+                    "attrs": plain_attrs,
+                }
+            # Host-side: register with ModelSamplingRegistry and return JSON-safe dict
+            ms_id = ModelSamplingRegistry().register(obj)
+            return {"__type__": "ModelSamplingRef", "ms_id": ms_id}
+
+        def deserialize_model_sampling(data: Any) -> Any:
+            """Deserialize ModelSampling refs or inline data."""
+            if isinstance(data, dict):
+                if data.get("__type__") == "ModelSamplingInline":
+                    return _reconstruct_model_sampling_inline(data)
+                return ModelSamplingProxy(data["ms_id"])
+            return data
+
+        def _reconstruct_model_sampling_inline(data: Dict[str, Any]) -> Any:
+            """Reconstruct a ModelSampling object on the host from inline child data."""
+            import comfy.model_sampling as _ms
+            import base64
+            import io as _io
+
+            # Resolve base classes
+            base_classes = []
+            for name in data["bases"]:
+                cls = getattr(_ms, name, None)
+                if cls is not None:
+                    base_classes.append(cls)
+            if not base_classes:
+                raise RuntimeError(
+                    f"Cannot reconstruct ModelSampling: no known bases in {data['bases']}"
+                )
+            # Create dynamic class matching the child's class hierarchy
+            ReconstructedSampling = type("ReconstructedSampling", tuple(base_classes), {})
+            obj = ReconstructedSampling.__new__(ReconstructedSampling)
+            torch.nn.Module.__init__(obj)
+            # Restore plain attributes first
+            for k, v in data.get("attrs", {}).items():
+                setattr(obj, k, v)
+            # Restore state_dict (buffers like sigmas)
+            for k, v_b64 in data.get("state_dict", {}).items():
+                buf = _io.BytesIO(base64.b64decode(v_b64))
+                tensor = torch.load(buf, weights_only=True)
+                # Register as buffer so it's part of state_dict
+                parts = k.split(".")
+                if len(parts) == 1:
+                    cast(Any, obj).register_buffer(parts[0], tensor)  # pylint: disable=no-member
+                else:
+                    setattr(obj, parts[0], tensor)
+            # Register on host so future references use proxy pattern.
+            # Skip in child process — register() is async RPC and cannot be
+            # called synchronously during deserialization.
+            if os.environ.get("PYISOLATE_CHILD") != "1":
+                ModelSamplingRegistry().register(obj)
+            return obj
+
+        def deserialize_model_sampling_ref(data: Dict[str, Any]) -> Any:
+            """Context-aware ModelSamplingRef deserializer for both host and child."""
+            is_child = os.environ.get("PYISOLATE_CHILD") == "1"
+            if is_child:
+                return ModelSamplingProxy(data["ms_id"])
+            else:
+                return ModelSamplingRegistry()._get_instance(data["ms_id"])
+
+        # Register all ModelSampling* and StableCascadeSampling classes dynamically
+        import comfy.model_sampling
+
+        for ms_cls in vars(comfy.model_sampling).values():
+            if not isinstance(ms_cls, type):
+                continue
+            if not issubclass(ms_cls, torch.nn.Module):
+                continue
+            if not (ms_cls.__name__.startswith("ModelSampling") or ms_cls.__name__ == "StableCascadeSampling"):
+                continue
+            registry.register(
+                ms_cls.__name__,
+                serialize_model_sampling,
+                deserialize_model_sampling,
+            )
+        registry.register(
+            "ModelSamplingProxy", serialize_model_sampling, deserialize_model_sampling
+        )
+        # Register ModelSamplingRef for deserialization (context-aware: host or child)
+        registry.register("ModelSamplingRef", None, deserialize_model_sampling_ref)
+        # Register ModelSamplingInline for deserialization (child→host inline transfer)
+        registry.register(
+            "ModelSamplingInline", None, lambda data: _reconstruct_model_sampling_inline(data)
+        )
+
+        def serialize_cond(obj: Any) -> Dict[str, Any]:
+            type_key = f"{type(obj).__module__}.{type(obj).__name__}"
+            return {
+                "__type__": type_key,
+                "cond": obj.cond,
+            }
+
+        def deserialize_cond(data: Dict[str, Any]) -> Any:
+            import importlib
+
+            type_key = data["__type__"]
+            module_name, class_name = type_key.rsplit(".", 1)
+            module = importlib.import_module(module_name)
+            cls = getattr(module, class_name)
+            return cls(data["cond"])
+
+        def _serialize_public_state(obj: Any) -> Dict[str, Any]:
+            state: Dict[str, Any] = {}
+            for key, value in obj.__dict__.items():
+                if key.startswith("_"):
+                    continue
+                if callable(value):
+                    continue
+                state[key] = value
+            return state
+
+        def serialize_latent_format(obj: Any) -> Dict[str, Any]:
+            type_key = f"{type(obj).__module__}.{type(obj).__name__}"
+            return {
+                "__type__": type_key,
+                "state": _serialize_public_state(obj),
+            }
+
+        def deserialize_latent_format(data: Dict[str, Any]) -> Any:
+            import importlib
+
+            type_key = data["__type__"]
+            module_name, class_name = type_key.rsplit(".", 1)
+            module = importlib.import_module(module_name)
+            cls = getattr(module, class_name)
+            obj = cls()
+            for key, value in data.get("state", {}).items():
+                prop = getattr(type(obj), key, None)
+                if isinstance(prop, property) and prop.fset is None:
+                    continue
+                setattr(obj, key, value)
+            return obj
+
+        import comfy.conds
+
+        for cond_cls in vars(comfy.conds).values():
+            if not isinstance(cond_cls, type):
+                continue
+            if not issubclass(cond_cls, comfy.conds.CONDRegular):
+                continue
+            type_key = f"{cond_cls.__module__}.{cond_cls.__name__}"
+            registry.register(type_key, serialize_cond, deserialize_cond)
+            registry.register(cond_cls.__name__, serialize_cond, deserialize_cond)
+
+        import comfy.latent_formats
+
+        for latent_cls in vars(comfy.latent_formats).values():
+            if not isinstance(latent_cls, type):
+                continue
+            if not issubclass(latent_cls, comfy.latent_formats.LatentFormat):
+                continue
+            type_key = f"{latent_cls.__module__}.{latent_cls.__name__}"
+            registry.register(
+                type_key, serialize_latent_format, deserialize_latent_format
+            )
+            registry.register(
+                latent_cls.__name__, serialize_latent_format, deserialize_latent_format
+            )
+
+        # V3 API: unwrap NodeOutput.args
+        def deserialize_node_output(data: Any) -> Any:
+            return getattr(data, "args", data)
+
+        registry.register("NodeOutput", None, deserialize_node_output)
+
+        # KSAMPLER serializer: stores sampler name instead of function object
+        # sampler_function is a callable which gets filtered out by JSONSocketTransport
+        def serialize_ksampler(obj: Any) -> Dict[str, Any]:
+            func_name = obj.sampler_function.__name__
+            # Map function name back to sampler name
+            if func_name == "sample_unipc":
+                sampler_name = "uni_pc"
+            elif func_name == "sample_unipc_bh2":
+                sampler_name = "uni_pc_bh2"
+            elif func_name == "dpm_fast_function":
+                sampler_name = "dpm_fast"
+            elif func_name == "dpm_adaptive_function":
+                sampler_name = "dpm_adaptive"
+            elif func_name.startswith("sample_"):
+                sampler_name = func_name[7:]  # Remove "sample_" prefix
+            else:
+                sampler_name = func_name
+            return {
+                "__type__": "KSAMPLER",
+                "sampler_name": sampler_name,
+                "extra_options": obj.extra_options,
+                "inpaint_options": obj.inpaint_options,
+            }
+
+        def deserialize_ksampler(data: Dict[str, Any]) -> Any:
+            import comfy.samplers
+
+            return comfy.samplers.ksampler(
+                data["sampler_name"],
+                data.get("extra_options", {}),
+                data.get("inpaint_options", {}),
+            )
+
+        registry.register("KSAMPLER", serialize_ksampler, deserialize_ksampler)
+
+        from comfy.isolation.model_patcher_proxy_utils import register_hooks_serializers
+
+        register_hooks_serializers(registry)
+
+        # -- File3D (comfy_api.latest._util.geometry_types) ---------------------
+        # Origin: comfy_api by ComfyOrg (Alexander Piskun), PR #12129
+
+        def serialize_file3d(obj: Any) -> Dict[str, Any]:
+            import base64
+            return {
+                "__type__": "File3D",
+                "format": obj.format,
+                "data": base64.b64encode(obj.get_bytes()).decode("ascii"),
+            }
+
+        def deserialize_file3d(data: Any) -> Any:
+            import base64
+            from io import BytesIO
+            from comfy_api.latest._util.geometry_types import File3D
+            return File3D(BytesIO(base64.b64decode(data["data"])), file_format=data["format"])
+
+        registry.register("File3D", serialize_file3d, deserialize_file3d, data_type=True)
+
+        # -- VIDEO (comfy_api.latest._input_impl.video_types) -------------------
+        # Origin: ComfyAPI Core v0.0.2 by ComfyOrg (guill), PR #8962
+
+        def serialize_video(obj: Any) -> Dict[str, Any]:
+            components = obj.get_components()
+            images = components.images.detach() if components.images.requires_grad else components.images
+            result: Dict[str, Any] = {
+                "__type__": "VIDEO",
+                "images": images,
+                "frame_rate_num": components.frame_rate.numerator,
+                "frame_rate_den": components.frame_rate.denominator,
+            }
+            if components.audio is not None:
+                waveform = components.audio["waveform"]
+                if waveform.requires_grad:
+                    waveform = waveform.detach()
+                result["audio_waveform"] = waveform
+                result["audio_sample_rate"] = components.audio["sample_rate"]
+            if components.metadata is not None:
+                result["metadata"] = components.metadata
+            return result
+
+        def deserialize_video(data: Any) -> Any:
+            from fractions import Fraction
+            from comfy_api.latest._input_impl.video_types import VideoFromComponents
+            from comfy_api.latest._util.video_types import VideoComponents
+            audio = None
+            if "audio_waveform" in data:
+                audio = {"waveform": data["audio_waveform"], "sample_rate": data["audio_sample_rate"]}
+            components = VideoComponents(
+                images=data["images"],
+                frame_rate=Fraction(data["frame_rate_num"], data["frame_rate_den"]),
+                audio=audio,
+                metadata=data.get("metadata"),
+            )
+            return VideoFromComponents(components)
+
+        registry.register("VIDEO", serialize_video, deserialize_video, data_type=True)
+        registry.register("VideoFromFile", serialize_video, deserialize_video, data_type=True)
+        registry.register("VideoFromComponents", serialize_video, deserialize_video, data_type=True)
+
+    def setup_web_directory(self, module: Any) -> None:
+        """Detect WEB_DIRECTORY on a module and populate/register it.
+
+        Called by the sealed worker after loading the node module.
+        Mirrors extension_wrapper.py:216-227 for host-coupled nodes.
+        Does NOT import extension_wrapper.py (it has `import torch` at module level).
+        """
+        import shutil
+
+        web_dir_attr = getattr(module, "WEB_DIRECTORY", None)
+        if web_dir_attr is None:
+            return
+
+        module_dir = os.path.dirname(os.path.abspath(module.__file__))
+        web_dir_path = os.path.abspath(os.path.join(module_dir, web_dir_attr))
+
+        # Read extension name from pyproject.toml
+        ext_name = os.path.basename(module_dir)
+        pyproject = os.path.join(module_dir, "pyproject.toml")
+        if os.path.exists(pyproject):
+            try:
+                import tomllib
+            except ImportError:
+                import tomli as tomllib  # type: ignore[no-redef]
+            try:
+                with open(pyproject, "rb") as f:
+                    data = tomllib.load(f)
+                name = data.get("project", {}).get("name")
+                if name:
+                    ext_name = name
+            except Exception:
+                pass
+
+        # Populate web dir if empty (mirrors _run_prestartup_web_copy)
+        if not (os.path.isdir(web_dir_path) and any(os.scandir(web_dir_path))):
+            os.makedirs(web_dir_path, exist_ok=True)
+
+            # Module-defined copy spec
+            copy_spec = getattr(module, "_PRESTARTUP_WEB_COPY", None)
+            if copy_spec is not None and callable(copy_spec):
+                try:
+                    copy_spec(web_dir_path)
+                except Exception as e:
+                    logger.warning("][ _PRESTARTUP_WEB_COPY failed: %s", e)
+
+            # Fallback: comfy_3d_viewers
+            try:
+                from comfy_3d_viewers import copy_viewer, VIEWER_FILES
+                for viewer in VIEWER_FILES:
+                    try:
+                        copy_viewer(viewer, web_dir_path)
+                    except Exception:
+                        pass
+            except ImportError:
+                pass
+
+            # Fallback: comfy_dynamic_widgets
+            try:
+                from comfy_dynamic_widgets import get_js_path
+                src = os.path.realpath(get_js_path())
+                if os.path.exists(src):
+                    dst_dir = os.path.join(web_dir_path, "js")
+                    os.makedirs(dst_dir, exist_ok=True)
+                    shutil.copy2(src, os.path.join(dst_dir, "dynamic_widgets.js"))
+            except ImportError:
+                pass
+
+        if os.path.isdir(web_dir_path) and any(os.scandir(web_dir_path)):
+            WebDirectoryProxy.register_web_dir(ext_name, web_dir_path)
+            logger.info(
+                "][ Adapter: registered web dir for %s (%d files)",
+                ext_name,
+                sum(1 for _ in Path(web_dir_path).rglob("*") if _.is_file()),
+            )
+
+    @staticmethod
+    def register_host_event_handlers(extension: Any) -> None:
+        """Register host-side event handlers for an isolated extension.
+
+        Wires ``"progress"`` events from the child to ``comfy.utils.PROGRESS_BAR_HOOK``
+        so the ComfyUI frontend receives progress bar updates.
+        """
+        register_event_handler = inspect.getattr_static(
+            extension, "register_event_handler", None
+        )
+        if not callable(register_event_handler):
+            return
+
+        def _host_progress_handler(payload: dict) -> None:
+            import comfy.utils
+
+            hook = comfy.utils.PROGRESS_BAR_HOOK
+            if hook is not None:
+                hook(
+                    payload.get("value", 0),
+                    payload.get("total", 0),
+                    payload.get("preview"),
+                    payload.get("node_id"),
+                )
+
+        extension.register_event_handler("progress", _host_progress_handler)
+
+    def setup_child_event_hooks(self, extension: Any) -> None:
+        """Wire PROGRESS_BAR_HOOK in the child to emit_event on the extension.
+
+        Host-coupled only — sealed workers do not have comfy.utils (torch).
+        """
+        is_child = os.environ.get("PYISOLATE_CHILD") == "1"
+        logger.info("][ ISO:setup_child_event_hooks called, PYISOLATE_CHILD=%s", is_child)
+        if not is_child:
+            return
+
+        if not _IMPORT_TORCH:
+            logger.info("][ ISO:setup_child_event_hooks skipped — sealed worker (no torch)")
+            return
+
+        import comfy.utils
+
+        def _event_progress_hook(value, total, preview=None, node_id=None):
+            logger.debug("][ ISO:event_progress value=%s/%s node_id=%s", value, total, node_id)
+            extension.emit_event("progress", {
+                "value": value,
+                "total": total,
+                "node_id": node_id,
+            })
+
+        comfy.utils.PROGRESS_BAR_HOOK = _event_progress_hook
+        logger.info("][ ISO:PROGRESS_BAR_HOOK wired to event channel")
+
+    def provide_rpc_services(self) -> List[type[ProxiedSingleton]]:
+        # Always available — no torch/PIL dependency
+        services: List[type[ProxiedSingleton]] = [
+            FolderPathsProxy,
+            HelperProxiesService,
+            WebDirectoryProxy,
+        ]
+        # Torch/PIL-dependent proxies
+        if _HAS_TORCH_PROXIES:
+            services.extend([
+                PromptServerService,
+                ModelManagementProxy,
+                UtilsProxy,
+                ProgressProxy,
+                VAERegistry,
+                CLIPRegistry,
+                ModelPatcherRegistry,
+                ModelSamplingRegistry,
+                FirstStageModelRegistry,
+            ])
+        return services
+
+    def handle_api_registration(self, api: ProxiedSingleton, rpc: AsyncRPC) -> None:
+        # Resolve the real name whether it's an instance or the Singleton class itself
+        api_name = api.__name__ if isinstance(api, type) else api.__class__.__name__
+
+        if api_name == "FolderPathsProxy":
+            import folder_paths
+
+            # Replace module-level functions with proxy methods
+            # This is aggressive but necessary for transparent proxying
+            # Handle both instance and class cases
+            instance = api() if isinstance(api, type) else api
+            for name in dir(instance):
+                if not name.startswith("_"):
+                    setattr(folder_paths, name, getattr(instance, name))
+
+            # Fence: isolated children get writable temp inside sandbox
+            if os.environ.get("PYISOLATE_CHILD") == "1":
+                import tempfile
+                _child_temp = os.path.join(tempfile.gettempdir(), "comfyui_temp")
+                os.makedirs(_child_temp, exist_ok=True)
+                folder_paths.temp_directory = _child_temp
+
+            return
+
+        if api_name == "ModelManagementProxy":
+            if _IMPORT_TORCH:
+                import comfy.model_management
+
+                instance = api() if isinstance(api, type) else api
+                # Replace module-level functions with proxy methods
+                for name in dir(instance):
+                    if not name.startswith("_"):
+                        setattr(comfy.model_management, name, getattr(instance, name))
+            return
+
+        if api_name == "UtilsProxy":
+            if not _IMPORT_TORCH:
+                logger.info("][ ISO:UtilsProxy handle_api_registration skipped — sealed worker (no torch)")
+                return
+
+            import comfy.utils
+
+            # Static Injection of RPC mechanism to ensure Child can access it
+            # independent of instance lifecycle.
+            api.set_rpc(rpc)
+
+            is_child = os.environ.get("PYISOLATE_CHILD") == "1"
+            logger.info("][ ISO:UtilsProxy handle_api_registration PYISOLATE_CHILD=%s", is_child)
+
+            # Progress hook wiring moved to setup_child_event_hooks via event channel
+
+            return
+
+        if api_name == "PromptServerService":
+            if not _IMPORT_TORCH:
+                return
+            import server
+            from comfy.isolation.proxies.prompt_server_impl import PromptServerStub
+
+            stub = PromptServerStub()
+            if (
+                hasattr(server, "PromptServer")
+                and getattr(server.PromptServer, "instance", None) is not stub
+            ):
+                server.PromptServer.instance = stub

comfy/isolation/child_hooks.py

@@ -0,0 +1,122 @@
+# pylint: disable=import-outside-toplevel,logging-fstring-interpolation
+# Child process initialization for PyIsolate
+import logging
+import os
+
+logger = logging.getLogger(__name__)
+
+
+def is_child_process() -> bool:
+    return os.environ.get("PYISOLATE_CHILD") == "1"
+
+
+def _load_extra_model_paths() -> None:
+    """Load extra_model_paths.yaml so the child's folder_paths has the same search paths as the host.
+
+    The host loads this in main.py:143-145. The child is spawned by
+    pyisolate's uds_client.py and never runs main.py, so folder_paths
+    only has the base model directories. Any isolated node calling
+    folder_paths.get_filename_list() in define_schema() would get empty
+    results for folders whose files live in extra_model_paths locations.
+    """
+    import folder_paths  # noqa: F401 — side-effect import; load_extra_path_config writes to folder_paths internals
+    from utils.extra_config import load_extra_path_config
+
+    extra_config_path = os.path.join(
+        os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))),
+        "extra_model_paths.yaml",
+    )
+    if os.path.isfile(extra_config_path):
+        load_extra_path_config(extra_config_path)
+
+
+def initialize_child_process() -> None:
+    if os.environ.get("PYISOLATE_IMPORT_TORCH", "1") != "0":
+        _load_extra_model_paths()
+    _setup_child_loop_bridge()
+
+    # Manual RPC injection
+    try:
+        from pyisolate._internal.rpc_protocol import get_child_rpc_instance
+
+        rpc = get_child_rpc_instance()
+        if rpc:
+            _setup_proxy_callers(rpc)
+        else:
+            _setup_proxy_callers()
+    except Exception as e:
+        logger.error(f"][ child_hooks Manual RPC Injection failed: {e}")
+        _setup_proxy_callers()
+
+    _setup_logging()
+
+
+def _setup_child_loop_bridge() -> None:
+    import asyncio
+
+    main_loop = None
+    try:
+        main_loop = asyncio.get_running_loop()
+    except RuntimeError:
+        try:
+            main_loop = asyncio.get_event_loop()
+        except RuntimeError:
+            pass
+
+    if main_loop is None:
+        return
+
+    try:
+        from .proxies.base import set_global_loop
+
+        set_global_loop(main_loop)
+    except ImportError:
+        pass
+
+
+def _setup_prompt_server_stub(rpc=None) -> None:
+    try:
+        from .proxies.prompt_server_impl import PromptServerStub
+
+        if rpc:
+            PromptServerStub.set_rpc(rpc)
+        elif hasattr(PromptServerStub, "clear_rpc"):
+            PromptServerStub.clear_rpc()
+        else:
+            PromptServerStub._rpc = None  # type: ignore[attr-defined]
+
+    except Exception as e:
+        logger.error(f"Failed to setup PromptServerStub: {e}")
+
+
+def _setup_proxy_callers(rpc=None) -> None:
+    try:
+        from .proxies.folder_paths_proxy import FolderPathsProxy
+        from .proxies.helper_proxies import HelperProxiesService
+        from .proxies.model_management_proxy import ModelManagementProxy
+        from .proxies.progress_proxy import ProgressProxy
+        from .proxies.prompt_server_impl import PromptServerStub
+        from .proxies.utils_proxy import UtilsProxy
+
+        if rpc is None:
+            FolderPathsProxy.clear_rpc()
+            HelperProxiesService.clear_rpc()
+            ModelManagementProxy.clear_rpc()
+            ProgressProxy.clear_rpc()
+            PromptServerStub.clear_rpc()
+            UtilsProxy.clear_rpc()
+            return
+
+        FolderPathsProxy.set_rpc(rpc)
+        HelperProxiesService.set_rpc(rpc)
+        ModelManagementProxy.set_rpc(rpc)
+        ProgressProxy.set_rpc(rpc)
+        PromptServerStub.set_rpc(rpc)
+        UtilsProxy.set_rpc(rpc)
+
+    except Exception as e:
+        logger.error(f"Failed to setup child singleton proxy callers: {e}")
+
+
+def _setup_logging() -> None:
+    logging.getLogger().setLevel(logging.INFO)

comfy/isolation/clip_proxy.py

@@ -0,0 +1,327 @@
+# pylint: disable=attribute-defined-outside-init,import-outside-toplevel,logging-fstring-interpolation
+# CLIP Proxy implementation
+from __future__ import annotations
+
+import logging
+from typing import TYPE_CHECKING, Any, Optional
+
+from comfy.isolation.proxies.base import (
+    IS_CHILD_PROCESS,
+    BaseProxy,
+    BaseRegistry,
+    detach_if_grad,
+)
+
+if TYPE_CHECKING:
+    from comfy.isolation.model_patcher_proxy import ModelPatcherProxy
+
+
+class CondStageModelRegistry(BaseRegistry[Any]):
+    _type_prefix = "cond_stage_model"
+
+    async def get_property(self, instance_id: str, name: str) -> Any:
+        obj = self._get_instance(instance_id)
+        return getattr(obj, name)
+
+
+class CondStageModelProxy(BaseProxy[CondStageModelRegistry]):
+    _registry_class = CondStageModelRegistry
+    __module__ = "comfy.sd"
+
+    def __getattr__(self, name: str) -> Any:
+        try:
+            return self._call_rpc("get_property", name)
+        except Exception as e:
+            raise AttributeError(
+                f"'{self.__class__.__name__}' object has no attribute '{name}'"
+            ) from e
+
+    def __repr__(self) -> str:
+        return f"<CondStageModelProxy {self._instance_id}>"
+
+
+class TokenizerRegistry(BaseRegistry[Any]):
+    _type_prefix = "tokenizer"
+
+    async def get_property(self, instance_id: str, name: str) -> Any:
+        obj = self._get_instance(instance_id)
+        return getattr(obj, name)
+
+
+class TokenizerProxy(BaseProxy[TokenizerRegistry]):
+    _registry_class = TokenizerRegistry
+    __module__ = "comfy.sd"
+
+    def __getattr__(self, name: str) -> Any:
+        try:
+            return self._call_rpc("get_property", name)
+        except Exception as e:
+            raise AttributeError(
+                f"'{self.__class__.__name__}' object has no attribute '{name}'"
+            ) from e
+
+    def __repr__(self) -> str:
+        return f"<TokenizerProxy {self._instance_id}>"
+
+
+logger = logging.getLogger(__name__)
+
+
+class CLIPRegistry(BaseRegistry[Any]):
+    _type_prefix = "clip"
+    _allowed_setters = {
+        "layer_idx",
+        "tokenizer_options",
+        "use_clip_schedule",
+        "apply_hooks_to_conds",
+    }
+
+    async def get_ram_usage(self, instance_id: str) -> int:
+        return self._get_instance(instance_id).get_ram_usage()
+
+    async def get_patcher_id(self, instance_id: str) -> str:
+        from comfy.isolation.model_patcher_proxy import ModelPatcherRegistry
+
+        return ModelPatcherRegistry().register(self._get_instance(instance_id).patcher)
+
+    async def get_cond_stage_model_id(self, instance_id: str) -> str:
+        return CondStageModelRegistry().register(
+            self._get_instance(instance_id).cond_stage_model
+        )
+
+    async def get_tokenizer_id(self, instance_id: str) -> str:
+        return TokenizerRegistry().register(self._get_instance(instance_id).tokenizer)
+
+    async def load_model(self, instance_id: str) -> None:
+        self._get_instance(instance_id).load_model()
+
+    async def clip_layer(self, instance_id: str, layer_idx: int) -> None:
+        self._get_instance(instance_id).clip_layer(layer_idx)
+
+    async def set_tokenizer_option(
+        self, instance_id: str, option_name: str, value: Any
+    ) -> None:
+        self._get_instance(instance_id).set_tokenizer_option(option_name, value)
+
+    async def get_property(self, instance_id: str, name: str) -> Any:
+        return getattr(self._get_instance(instance_id), name)
+
+    async def set_property(self, instance_id: str, name: str, value: Any) -> None:
+        if name not in self._allowed_setters:
+            raise PermissionError(f"Setting '{name}' is not allowed via RPC")
+        setattr(self._get_instance(instance_id), name, value)
+
+    async def tokenize(
+        self, instance_id: str, text: str, return_word_ids: bool = False, **kwargs: Any
+    ) -> Any:
+        return self._get_instance(instance_id).tokenize(
+            text, return_word_ids=return_word_ids, **kwargs
+        )
+
+    async def encode(self, instance_id: str, text: str) -> Any:
+        return detach_if_grad(self._get_instance(instance_id).encode(text))
+
+    async def encode_from_tokens(
+        self,
+        instance_id: str,
+        tokens: Any,
+        return_pooled: bool = False,
+        return_dict: bool = False,
+    ) -> Any:
+        return detach_if_grad(
+            self._get_instance(instance_id).encode_from_tokens(
+                tokens, return_pooled=return_pooled, return_dict=return_dict
+            )
+        )
+
+    async def encode_from_tokens_scheduled(
+        self,
+        instance_id: str,
+        tokens: Any,
+        unprojected: bool = False,
+        add_dict: Optional[dict] = None,
+        show_pbar: bool = True,
+    ) -> Any:
+        add_dict = add_dict or {}
+        return detach_if_grad(
+            self._get_instance(instance_id).encode_from_tokens_scheduled(
+                tokens, unprojected=unprojected, add_dict=add_dict, show_pbar=show_pbar
+            )
+        )
+
+    async def add_patches(
+        self,
+        instance_id: str,
+        patches: Any,
+        strength_patch: float = 1.0,
+        strength_model: float = 1.0,
+    ) -> Any:
+        return self._get_instance(instance_id).add_patches(
+            patches, strength_patch=strength_patch, strength_model=strength_model
+        )
+
+    async def get_key_patches(self, instance_id: str) -> Any:
+        return self._get_instance(instance_id).get_key_patches()
+
+    async def load_sd(
+        self, instance_id: str, sd: dict, full_model: bool = False
+    ) -> Any:
+        return self._get_instance(instance_id).load_sd(sd, full_model=full_model)
+
+    async def get_sd(self, instance_id: str) -> Any:
+        return self._get_instance(instance_id).get_sd()
+
+    async def clone(self, instance_id: str) -> str:
+        return self.register(self._get_instance(instance_id).clone())
+
+
+class CLIPProxy(BaseProxy[CLIPRegistry]):
+    _registry_class = CLIPRegistry
+    __module__ = "comfy.sd"
+
+    def get_ram_usage(self) -> int:
+        return self._call_rpc("get_ram_usage")
+
+    @property
+    def patcher(self) -> "ModelPatcherProxy":
+        from comfy.isolation.model_patcher_proxy import ModelPatcherProxy
+
+        if not hasattr(self, "_patcher_proxy"):
+            patcher_id = self._call_rpc("get_patcher_id")
+            self._patcher_proxy = ModelPatcherProxy(patcher_id, manage_lifecycle=False)
+        return self._patcher_proxy
+
+    @patcher.setter
+    def patcher(self, value: Any) -> None:
+        from comfy.isolation.model_patcher_proxy import ModelPatcherProxy
+
+        if isinstance(value, ModelPatcherProxy):
+            self._patcher_proxy = value
+        else:
+            logger.warning(
+                f"Attempted to set CLIPProxy.patcher to non-proxy object: {value}"
+            )
+
+    @property
+    def cond_stage_model(self) -> CondStageModelProxy:
+        if not hasattr(self, "_cond_stage_model_proxy"):
+            csm_id = self._call_rpc("get_cond_stage_model_id")
+            self._cond_stage_model_proxy = CondStageModelProxy(
+                csm_id, manage_lifecycle=False
+            )
+        return self._cond_stage_model_proxy
+
+    @property
+    def tokenizer(self) -> TokenizerProxy:
+        if not hasattr(self, "_tokenizer_proxy"):
+            tok_id = self._call_rpc("get_tokenizer_id")
+            self._tokenizer_proxy = TokenizerProxy(tok_id, manage_lifecycle=False)
+        return self._tokenizer_proxy
+
+    def load_model(self) -> ModelPatcherProxy:
+        self._call_rpc("load_model")
+        return self.patcher
+
+    @property
+    def layer_idx(self) -> Optional[int]:
+        return self._call_rpc("get_property", "layer_idx")
+
+    @layer_idx.setter
+    def layer_idx(self, value: Optional[int]) -> None:
+        self._call_rpc("set_property", "layer_idx", value)
+
+    @property
+    def tokenizer_options(self) -> dict:
+        return self._call_rpc("get_property", "tokenizer_options")
+
+    @tokenizer_options.setter
+    def tokenizer_options(self, value: dict) -> None:
+        self._call_rpc("set_property", "tokenizer_options", value)
+
+    @property
+    def use_clip_schedule(self) -> bool:
+        return self._call_rpc("get_property", "use_clip_schedule")
+
+    @use_clip_schedule.setter
+    def use_clip_schedule(self, value: bool) -> None:
+        self._call_rpc("set_property", "use_clip_schedule", value)
+
+    @property
+    def apply_hooks_to_conds(self) -> Any:
+        return self._call_rpc("get_property", "apply_hooks_to_conds")
+
+    @apply_hooks_to_conds.setter
+    def apply_hooks_to_conds(self, value: Any) -> None:
+        self._call_rpc("set_property", "apply_hooks_to_conds", value)
+
+    def clip_layer(self, layer_idx: int) -> None:
+        return self._call_rpc("clip_layer", layer_idx)
+
+    def set_tokenizer_option(self, option_name: str, value: Any) -> None:
+        return self._call_rpc("set_tokenizer_option", option_name, value)
+
+    def tokenize(self, text: str, return_word_ids: bool = False, **kwargs: Any) -> Any:
+        return self._call_rpc(
+            "tokenize", text, return_word_ids=return_word_ids, **kwargs
+        )
+
+    def encode(self, text: str) -> Any:
+        return self._call_rpc("encode", text)
+
+    def encode_from_tokens(
+        self, tokens: Any, return_pooled: bool = False, return_dict: bool = False
+    ) -> Any:
+        res = self._call_rpc(
+            "encode_from_tokens",
+            tokens,
+            return_pooled=return_pooled,
+            return_dict=return_dict,
+        )
+        if return_pooled and isinstance(res, list) and not return_dict:
+            return tuple(res)
+        return res
+
+    def encode_from_tokens_scheduled(
+        self,
+        tokens: Any,
+        unprojected: bool = False,
+        add_dict: Optional[dict] = None,
+        show_pbar: bool = True,
+    ) -> Any:
+        add_dict = add_dict or {}
+        return self._call_rpc(
+            "encode_from_tokens_scheduled",
+            tokens,
+            unprojected=unprojected,
+            add_dict=add_dict,
+            show_pbar=show_pbar,
+        )
+
+    def add_patches(
+        self, patches: Any, strength_patch: float = 1.0, strength_model: float = 1.0
+    ) -> Any:
+        return self._call_rpc(
+            "add_patches",
+            patches,
+            strength_patch=strength_patch,
+            strength_model=strength_model,
+        )
+
+    def get_key_patches(self) -> Any:
+        return self._call_rpc("get_key_patches")
+
+    def load_sd(self, sd: dict, full_model: bool = False) -> Any:
+        return self._call_rpc("load_sd", sd, full_model=full_model)
+
+    def get_sd(self) -> Any:
+        return self._call_rpc("get_sd")
+
+    def clone(self) -> CLIPProxy:
+        new_id = self._call_rpc("clone")
+        return CLIPProxy(new_id, self._registry, manage_lifecycle=not IS_CHILD_PROCESS)
+
+
+if not IS_CHILD_PROCESS:
+    _CLIP_REGISTRY_SINGLETON = CLIPRegistry()
+    _COND_STAGE_MODEL_REGISTRY_SINGLETON = CondStageModelRegistry()
+    _TOKENIZER_REGISTRY_SINGLETON = TokenizerRegistry()

comfy/isolation/custom_node_serializers.py

@@ -0,0 +1,16 @@
+"""Compatibility shim for the indexed serializer path."""
+
+from __future__ import annotations
+
+from typing import Any
+
+
+def register_custom_node_serializers(_registry: Any) -> None:
+    """Legacy no-op shim.
+
+    Serializer registration now lives directly in the active isolation adapter.
+    This module remains importable because the isolation index still references it.
+    """
+    return None
+
+__all__ = ["register_custom_node_serializers"]

comfy/isolation/extension_loader.py

@@ -0,0 +1,540 @@
+# pylint: disable=cyclic-import,import-outside-toplevel,redefined-outer-name
+from __future__ import annotations
+
+import logging
+import os
+import inspect
+import sys
+import types
+import platform
+from pathlib import Path
+from typing import Any, Callable, Dict, List, Tuple
+
+import pyisolate
+from pyisolate import ExtensionManager, ExtensionManagerConfig
+from packaging.requirements import InvalidRequirement, Requirement
+from packaging.utils import canonicalize_name
+
+from .manifest_loader import is_cache_valid, load_from_cache, save_to_cache
+from .host_policy import load_host_policy
+
+try:
+    import tomllib
+except ImportError:
+    import tomli as tomllib  # type: ignore[no-redef]
+
+logger = logging.getLogger(__name__)
+
+
+def _register_web_directory(extension_name: str, node_dir: Path) -> None:
+    """Register an isolated extension's web directory on the host side."""
+    import nodes
+
+    # Method 1: pyproject.toml [tool.comfy] web field
+    pyproject = node_dir / "pyproject.toml"
+    if pyproject.exists():
+        try:
+            with pyproject.open("rb") as f:
+                data = tomllib.load(f)
+            web_dir_name = data.get("tool", {}).get("comfy", {}).get("web")
+            if web_dir_name:
+                web_dir_path = str(node_dir / web_dir_name)
+                if os.path.isdir(web_dir_path):
+                    nodes.EXTENSION_WEB_DIRS[extension_name] = web_dir_path
+                    logger.debug(
+                        "][ Registered web dir for isolated %s: %s",
+                        extension_name,
+                        web_dir_path,
+                    )
+                    return
+        except Exception:
+            pass
+
+    # Method 2: __init__.py WEB_DIRECTORY constant (parse without importing)
+    init_file = node_dir / "__init__.py"
+    if init_file.exists():
+        try:
+            source = init_file.read_text()
+            for line in source.splitlines():
+                stripped = line.strip()
+                if stripped.startswith("WEB_DIRECTORY"):
+                    # Parse: WEB_DIRECTORY = "./web" or WEB_DIRECTORY = "web"
+                    _, _, value = stripped.partition("=")
+                    value = value.strip().strip("\"'")
+                    if value:
+                        web_dir_path = str((node_dir / value).resolve())
+                        if os.path.isdir(web_dir_path):
+                            nodes.EXTENSION_WEB_DIRS[extension_name] = web_dir_path
+                            logger.debug(
+                                "][ Registered web dir for isolated %s: %s",
+                                extension_name,
+                                web_dir_path,
+                            )
+                            return
+        except Exception:
+            pass
+
+
+def _get_extension_type(execution_model: str) -> type[Any]:
+    if execution_model == "sealed_worker":
+        return pyisolate.SealedNodeExtension
+
+    from .extension_wrapper import ComfyNodeExtension
+
+    return ComfyNodeExtension
+
+
+async def _stop_extension_safe(extension: Any, extension_name: str) -> None:
+    try:
+        stop_result = extension.stop()
+        if inspect.isawaitable(stop_result):
+            await stop_result
+    except Exception:
+        logger.debug("][ %s stop failed", extension_name, exc_info=True)
+
+
+def _normalize_dependency_spec(dep: str, base_paths: list[Path]) -> str:
+    req, sep, marker = dep.partition(";")
+    req = req.strip()
+    marker_suffix = f";{marker}" if sep else ""
+
+    def _resolve_local_path(local_path: str) -> Path | None:
+        for base in base_paths:
+            candidate = (base / local_path).resolve()
+            if candidate.exists():
+                return candidate
+        return None
+
+    if req.startswith("./") or req.startswith("../"):
+        resolved = _resolve_local_path(req)
+        if resolved is not None:
+            return f"{resolved}{marker_suffix}"
+
+    if req.startswith("file://"):
+        raw = req[len("file://") :]
+        if raw.startswith("./") or raw.startswith("../"):
+            resolved = _resolve_local_path(raw)
+            if resolved is not None:
+                return f"file://{resolved}{marker_suffix}"
+
+    return dep
+
+
+def _dependency_name_from_spec(dep: str) -> str | None:
+    stripped = dep.strip()
+    if not stripped or stripped == "-e" or stripped.startswith("-e "):
+        return None
+    if stripped.startswith(("/", "./", "../", "file://")):
+        return None
+
+    try:
+        return canonicalize_name(Requirement(stripped).name)
+    except InvalidRequirement:
+        return None
+
+
+def _parse_cuda_wheels_config(
+    tool_config: dict[str, object], dependencies: list[str]
+) -> dict[str, object] | None:
+    raw_config = tool_config.get("cuda_wheels")
+    if raw_config is None:
+        return None
+    if not isinstance(raw_config, dict):
+        raise ExtensionLoadError("[tool.comfy.isolation.cuda_wheels] must be a table")
+
+    index_url = raw_config.get("index_url")
+    index_urls = raw_config.get("index_urls")
+    if index_urls is not None:
+        if not isinstance(index_urls, list) or not all(
+            isinstance(u, str) and u.strip() for u in index_urls
+        ):
+            raise ExtensionLoadError(
+                "[tool.comfy.isolation.cuda_wheels.index_urls] must be a list of non-empty strings"
+            )
+    elif not isinstance(index_url, str) or not index_url.strip():
+        raise ExtensionLoadError(
+            "[tool.comfy.isolation.cuda_wheels.index_url] must be a non-empty string"
+        )
+
+    packages = raw_config.get("packages")
+    if not isinstance(packages, list) or not all(
+        isinstance(package_name, str) and package_name.strip()
+        for package_name in packages
+    ):
+        raise ExtensionLoadError(
+            "[tool.comfy.isolation.cuda_wheels.packages] must be a list of non-empty strings"
+        )
+
+    declared_dependencies = {
+        dependency_name
+        for dep in dependencies
+        if (dependency_name := _dependency_name_from_spec(dep)) is not None
+    }
+    normalized_packages = [canonicalize_name(package_name) for package_name in packages]
+    missing = [
+        package_name
+        for package_name in normalized_packages
+        if package_name not in declared_dependencies
+    ]
+    if missing:
+        missing_joined = ", ".join(sorted(missing))
+        raise ExtensionLoadError(
+            "[tool.comfy.isolation.cuda_wheels.packages] references undeclared dependencies: "
+            f"{missing_joined}"
+        )
+
+    package_map = raw_config.get("package_map", {})
+    if not isinstance(package_map, dict):
+        raise ExtensionLoadError(
+            "[tool.comfy.isolation.cuda_wheels.package_map] must be a table"
+        )
+
+    normalized_package_map: dict[str, str] = {}
+    for dependency_name, index_package_name in package_map.items():
+        if not isinstance(dependency_name, str) or not dependency_name.strip():
+            raise ExtensionLoadError(
+                "[tool.comfy.isolation.cuda_wheels.package_map] keys must be non-empty strings"
+            )
+        if not isinstance(index_package_name, str) or not index_package_name.strip():
+            raise ExtensionLoadError(
+                "[tool.comfy.isolation.cuda_wheels.package_map] values must be non-empty strings"
+            )
+        canonical_dependency_name = canonicalize_name(dependency_name)
+        if canonical_dependency_name not in normalized_packages:
+            raise ExtensionLoadError(
+                "[tool.comfy.isolation.cuda_wheels.package_map] can only override packages listed in "
+                "[tool.comfy.isolation.cuda_wheels.packages]"
+            )
+        normalized_package_map[canonical_dependency_name] = index_package_name.strip()
+
+    result: dict = {
+        "packages": normalized_packages,
+        "package_map": normalized_package_map,
+    }
+    if index_urls is not None:
+        result["index_urls"] = [u.rstrip("/") + "/" for u in index_urls]
+    else:
+        result["index_url"] = index_url.rstrip("/") + "/"
+    return result
+
+
+def get_enforcement_policy() -> Dict[str, bool]:
+    return {
+        "force_isolated": os.environ.get("PYISOLATE_ENFORCE_ISOLATED") == "1",
+        "force_sandbox": os.environ.get("PYISOLATE_ENFORCE_SANDBOX") == "1",
+    }
+
+
+class ExtensionLoadError(RuntimeError):
+    pass
+
+
+def register_dummy_module(extension_name: str, node_dir: Path) -> None:
+    normalized_name = extension_name.replace("-", "_").replace(".", "_")
+    if normalized_name not in sys.modules:
+        dummy_module = types.ModuleType(normalized_name)
+        dummy_module.__file__ = str(node_dir / "__init__.py")
+        dummy_module.__path__ = [str(node_dir)]
+        dummy_module.__package__ = normalized_name
+        sys.modules[normalized_name] = dummy_module
+
+
+def _is_stale_node_cache(cached_data: Dict[str, Dict]) -> bool:
+    for details in cached_data.values():
+        if not isinstance(details, dict):
+            return True
+        if details.get("is_v3") and "schema_v1" not in details:
+            return True
+    return False
+
+
+async def load_isolated_node(
+    node_dir: Path,
+    manifest_path: Path,
+    logger: logging.Logger,
+    build_stub_class: Callable[[str, Dict[str, object], Any], type],
+    venv_root: Path,
+    extension_managers: List[ExtensionManager],
+) -> List[Tuple[str, str, type]]:
+    try:
+        with manifest_path.open("rb") as handle:
+            manifest_data = tomllib.load(handle)
+    except Exception as e:
+        logger.warning(f"][ Failed to parse {manifest_path}: {e}")
+        return []
+
+    # Parse [tool.comfy.isolation]
+    tool_config = manifest_data.get("tool", {}).get("comfy", {}).get("isolation", {})
+    can_isolate = tool_config.get("can_isolate", False)
+    share_torch = tool_config.get("share_torch", False)
+    package_manager = tool_config.get("package_manager", "uv")
+    is_conda = package_manager == "conda"
+    execution_model = tool_config.get("execution_model")
+    if execution_model is None:
+        execution_model = "sealed_worker" if is_conda else "host-coupled"
+
+    if "sealed_host_ro_paths" in tool_config:
+        raise ValueError(
+            "Manifest field 'sealed_host_ro_paths' is not allowed. "
+            "Configure [tool.comfy.host].sealed_worker_ro_import_paths in host policy."
+        )
+
+    # Conda-specific manifest fields
+    conda_channels: list[str] = (
+        tool_config.get("conda_channels", []) if is_conda else []
+    )
+    conda_dependencies: list[str] = (
+        tool_config.get("conda_dependencies", []) if is_conda else []
+    )
+    conda_platforms: list[str] = (
+        tool_config.get("conda_platforms", []) if is_conda else []
+    )
+    conda_python: str = (
+        tool_config.get("conda_python", "*") if is_conda else "*"
+    )
+
+    # Parse [project] dependencies
+    project_config = manifest_data.get("project", {})
+    dependencies = project_config.get("dependencies", [])
+    if not isinstance(dependencies, list):
+        dependencies = []
+
+    # Get extension name (default to folder name if not in project.name)
+    extension_name = project_config.get("name", node_dir.name)
+
+    # LOGIC: Isolation Decision
+    policy = get_enforcement_policy()
+    isolated = can_isolate or policy["force_isolated"]
+
+    if not isolated:
+        return []
+
+    import folder_paths
+
+    base_paths = [Path(folder_paths.base_path), node_dir]
+    dependencies = [
+        _normalize_dependency_spec(dep, base_paths) if isinstance(dep, str) else dep
+        for dep in dependencies
+    ]
+    cuda_wheels = _parse_cuda_wheels_config(tool_config, dependencies)
+
+    manager_config = ExtensionManagerConfig(venv_root_path=str(venv_root))
+    extension_type = _get_extension_type(execution_model)
+    manager: ExtensionManager = pyisolate.ExtensionManager(
+        extension_type, manager_config
+    )
+    extension_managers.append(manager)
+
+    host_policy = load_host_policy(Path(folder_paths.base_path))
+
+    sandbox_config = {}
+    is_linux = platform.system() == "Linux"
+
+    if is_conda:
+        share_torch = False
+        share_cuda_ipc = False
+    else:
+        share_cuda_ipc = share_torch and is_linux
+
+    if is_linux and isolated:
+        sandbox_config = {
+            "network": host_policy["allow_network"],
+            "writable_paths": host_policy["writable_paths"],
+            "readonly_paths": host_policy["readonly_paths"],
+        }
+
+    extension_config: dict = {
+        "name": extension_name,
+        "module_path": str(node_dir),
+        "isolated": True,
+        "dependencies": dependencies,
+        "share_torch": share_torch,
+        "share_cuda_ipc": share_cuda_ipc,
+        "sandbox_mode": host_policy["sandbox_mode"],
+        "sandbox": sandbox_config,
+    }
+
+    share_torch_no_deps = tool_config.get("share_torch_no_deps", [])
+    if share_torch_no_deps:
+        if not isinstance(share_torch_no_deps, list) or not all(
+            isinstance(dep, str) and dep.strip() for dep in share_torch_no_deps
+        ):
+            raise ExtensionLoadError(
+                "[tool.comfy.isolation.share_torch_no_deps] must be a list of non-empty strings"
+            )
+        extension_config["share_torch_no_deps"] = share_torch_no_deps
+
+    _is_sealed = execution_model == "sealed_worker"
+    _is_sandboxed = host_policy["sandbox_mode"] != "disabled" and is_linux
+    logger.info(
+        "][ Loading isolated node: %s (torch_share [%s], sealed [%s], sandboxed [%s])",
+        extension_name,
+        "x" if share_torch else " ",
+        "x" if _is_sealed else " ",
+        "x" if _is_sandboxed else " ",
+    )
+
+    if cuda_wheels is not None:
+        extension_config["cuda_wheels"] = cuda_wheels
+
+    extra_index_urls = tool_config.get("extra_index_urls", [])
+    if extra_index_urls:
+        if not isinstance(extra_index_urls, list) or not all(
+            isinstance(u, str) and u.strip() for u in extra_index_urls
+        ):
+            raise ExtensionLoadError(
+                "[tool.comfy.isolation.extra_index_urls] must be a list of non-empty strings"
+            )
+        extension_config["extra_index_urls"] = extra_index_urls
+
+    # Conda-specific keys
+    if is_conda:
+        extension_config["package_manager"] = "conda"
+        extension_config["conda_channels"] = conda_channels
+        extension_config["conda_dependencies"] = conda_dependencies
+        extension_config["conda_python"] = conda_python
+        find_links = tool_config.get("find_links", [])
+        if find_links:
+            extension_config["find_links"] = find_links
+        if conda_platforms:
+            extension_config["conda_platforms"] = conda_platforms
+
+    if execution_model != "host-coupled":
+        extension_config["execution_model"] = execution_model
+    if execution_model == "sealed_worker":
+        policy_ro_paths = host_policy.get("sealed_worker_ro_import_paths", [])
+        if isinstance(policy_ro_paths, list) and policy_ro_paths:
+            extension_config["sealed_host_ro_paths"] = list(policy_ro_paths)
+        # Sealed workers keep the host RPC service inventory even when the
+        # child resolves no API classes locally.
+
+    extension = manager.load_extension(extension_config)
+    register_dummy_module(extension_name, node_dir)
+
+    # Register host-side event handlers via adapter
+    from .adapter import ComfyUIAdapter
+    ComfyUIAdapter.register_host_event_handlers(extension)
+
+    # Register web directory on the host — only when sandbox is disabled.
+    # In sandbox mode, serving untrusted JS to the browser is not safe.
+    if host_policy["sandbox_mode"] == "disabled":
+        _register_web_directory(extension_name, node_dir)
+
+    # Register for proxied web serving — the child's web dir may have
+    # content that doesn't exist on the host (e.g., pip-installed viewer
+    # bundles). The WebDirectoryCache will lazily fetch via RPC.
+    from .proxies.web_directory_proxy import WebDirectoryProxy, get_web_directory_cache
+
+    class ChildWebDirectoryProxy:
+        def __init__(self, host_extension):
+            self._host_extension = host_extension
+            self._caller = None
+
+        def _get_caller(self):
+            self._host_extension.proxy
+            rpc = self._host_extension._extension.rpc
+            caller = rpc.create_caller(WebDirectoryProxy, WebDirectoryProxy.get_remote_id())
+            if self._caller is not caller:
+                self._caller = caller
+            return self._caller
+
+        def list_web_files(self, extension_name: str):
+            from .proxies.base import run_sync_rpc_coro
+            return run_sync_rpc_coro(self._get_caller().list_web_files(extension_name))
+
+        def get_web_file(self, extension_name: str, relative_path: str):
+            from .proxies.base import run_sync_rpc_coro
+            return run_sync_rpc_coro(
+                self._get_caller().get_web_file(extension_name, relative_path)
+            )
+
+    cache = get_web_directory_cache()
+    cache.register_proxy(extension_name, ChildWebDirectoryProxy(extension))
+
+    # Try cache first (lazy spawn)
+    if is_cache_valid(node_dir, manifest_path, venv_root):
+        cached_data = load_from_cache(node_dir, venv_root)
+        if cached_data:
+            if _is_stale_node_cache(cached_data):
+                pass
+            else:
+                try:
+                    flushed = await extension.flush_pending_routes()
+                    logger.info("][ %s flushed %d routes", extension_name, flushed)
+                except Exception as exc:
+                    logger.warning("][ %s route flush failed: %s", extension_name, exc)
+                specs: List[Tuple[str, str, type]] = []
+                for node_name, details in cached_data.items():
+                    stub_cls = build_stub_class(node_name, details, extension)
+                    specs.append(
+                        (node_name, details.get("display_name", node_name), stub_cls)
+                    )
+                return specs
+    # Cache miss - spawn process and get metadata
+
+    try:
+        remote_nodes: Dict[str, str] = await extension.list_nodes()
+    except Exception as exc:
+        logger.warning(
+            "][ %s metadata discovery failed, skipping isolated load: %s",
+            extension_name,
+            exc,
+        )
+        await _stop_extension_safe(extension, extension_name)
+        return []
+
+    if not remote_nodes:
+        logger.debug("][ %s exposed no isolated nodes; skipping", extension_name)
+        await _stop_extension_safe(extension, extension_name)
+        return []
+
+    specs: List[Tuple[str, str, type]] = []
+    cache_data: Dict[str, Dict] = {}
+
+    for node_name, display_name in remote_nodes.items():
+        try:
+            details = await extension.get_node_details(node_name)
+        except Exception as exc:
+            logger.warning(
+                "][ %s failed to load metadata for %s, skipping node: %s",
+                extension_name,
+                node_name,
+                exc,
+            )
+            continue
+        details["display_name"] = display_name
+        cache_data[node_name] = details
+        stub_cls = build_stub_class(node_name, details, extension)
+        specs.append((node_name, display_name, stub_cls))
+
+    if not specs:
+        logger.warning(
+            "][ %s produced no usable nodes after metadata scan; skipping",
+            extension_name,
+        )
+        await _stop_extension_safe(extension, extension_name)
+        return []
+
+    # Save metadata to cache for future runs
+    save_to_cache(node_dir, venv_root, cache_data, manifest_path)
+    logger.debug(f"][ {extension_name} metadata cached")
+
+    # Re-check web directory AFTER child has populated it
+    if host_policy["sandbox_mode"] == "disabled":
+        _register_web_directory(extension_name, node_dir)
+
+    # Flush any routes the child buffered during module import — must happen
+    # before router freeze and before we kill the child process.
+    try:
+        flushed = await extension.flush_pending_routes()
+        logger.info("][ %s flushed %d routes", extension_name, flushed)
+    except Exception as exc:
+        logger.warning("][ %s route flush failed: %s", extension_name, exc)
+
+    # EJECT: Kill process after getting metadata (will respawn on first execution)
+    await _stop_extension_safe(extension, extension_name)
+
+    return specs
+
+
+__all__ = ["ExtensionLoadError", "register_dummy_module", "load_isolated_node"]

comfy/isolation/extension_wrapper.py

@@ -0,0 +1,942 @@
+# pylint: disable=consider-using-from-import,cyclic-import,import-outside-toplevel,logging-fstring-interpolation,protected-access,wrong-import-position
+from __future__ import annotations
+
+import asyncio
+import torch
+
+
+class AttrDict(dict):
+    def __getattr__(self, item):
+        try:
+            return self[item]
+        except KeyError as e:
+            raise AttributeError(item) from e
+
+    def copy(self):
+        return AttrDict(super().copy())
+
+
+import importlib
+import inspect
+import json
+import logging
+import os
+import sys
+import uuid
+from dataclasses import asdict
+from typing import Any, Dict, List, Tuple
+
+from pyisolate import ExtensionBase
+
+from comfy_api.internal import _ComfyNodeInternal
+
+LOG_PREFIX = "]["
+V3_DISCOVERY_TIMEOUT = 30
+_PRE_EXEC_MIN_FREE_VRAM_BYTES = 2 * 1024 * 1024 * 1024
+
+logger = logging.getLogger(__name__)
+
+
+def _run_prestartup_web_copy(module: Any, module_dir: str, web_dir_path: str) -> None:
+    """Run the web asset copy step that prestartup_script.py used to do.
+
+    If the module's web/ directory is empty and the module had a
+    prestartup_script.py that copied assets from pip packages, this
+    function replicates that work inside the child process.
+
+    Generic pattern: reads _PRESTARTUP_WEB_COPY from the module if
+    defined, otherwise falls back to detecting common asset packages.
+    """
+    import shutil
+
+    # Already populated — nothing to do
+    if os.path.isdir(web_dir_path) and any(os.scandir(web_dir_path)):
+        return
+
+    os.makedirs(web_dir_path, exist_ok=True)
+
+    # Try module-defined copy spec first (generic hook for any node pack)
+    copy_spec = getattr(module, "_PRESTARTUP_WEB_COPY", None)
+    if copy_spec is not None and callable(copy_spec):
+        try:
+            copy_spec(web_dir_path)
+            logger.info(
+                "%s Ran _PRESTARTUP_WEB_COPY for %s", LOG_PREFIX, module_dir
+            )
+            return
+        except Exception as e:
+            logger.warning(
+                "%s _PRESTARTUP_WEB_COPY failed for %s: %s",
+                LOG_PREFIX, module_dir, e,
+            )
+
+    # Fallback: detect comfy_3d_viewers and run copy_viewer()
+    try:
+        from comfy_3d_viewers import copy_viewer, VIEWER_FILES
+        viewers = list(VIEWER_FILES.keys())
+        for viewer in viewers:
+            try:
+                copy_viewer(viewer, web_dir_path)
+            except Exception:
+                pass
+        if any(os.scandir(web_dir_path)):
+            logger.info(
+                "%s Copied %d viewer types from comfy_3d_viewers to %s",
+                LOG_PREFIX, len(viewers), web_dir_path,
+            )
+    except ImportError:
+        pass
+
+    # Fallback: detect comfy_dynamic_widgets
+    try:
+        from comfy_dynamic_widgets import get_js_path
+        src = os.path.realpath(get_js_path())
+        if os.path.exists(src):
+            dst_dir = os.path.join(web_dir_path, "js")
+            os.makedirs(dst_dir, exist_ok=True)
+            dst = os.path.join(dst_dir, "dynamic_widgets.js")
+            shutil.copy2(src, dst)
+    except ImportError:
+        pass
+
+
+def _read_extension_name(module_dir: str) -> str:
+    """Read extension name from pyproject.toml, falling back to directory name."""
+    pyproject = os.path.join(module_dir, "pyproject.toml")
+    if os.path.exists(pyproject):
+        try:
+            import tomllib
+        except ImportError:
+            import tomli as tomllib  # type: ignore[no-redef]
+        try:
+            with open(pyproject, "rb") as f:
+                data = tomllib.load(f)
+            name = data.get("project", {}).get("name")
+            if name:
+                return name
+        except Exception:
+            pass
+    return os.path.basename(module_dir)
+
+
+def _flush_tensor_transport_state(marker: str) -> int:
+    try:
+        from pyisolate import flush_tensor_keeper  # type: ignore[attr-defined]
+    except Exception:
+        return 0
+    if not callable(flush_tensor_keeper):
+        return 0
+    flushed = flush_tensor_keeper()
+    if flushed > 0:
+        logger.debug(
+            "%s %s flush_tensor_keeper released=%d", LOG_PREFIX, marker, flushed
+        )
+    return flushed
+
+
+def _relieve_child_vram_pressure(marker: str) -> None:
+    import comfy.model_management as model_management
+
+    model_management.cleanup_models_gc()
+    model_management.cleanup_models()
+
+    device = model_management.get_torch_device()
+    if not hasattr(device, "type") or device.type == "cpu":
+        return
+
+    required = max(
+        model_management.minimum_inference_memory(),
+        _PRE_EXEC_MIN_FREE_VRAM_BYTES,
+    )
+    if model_management.get_free_memory(device) < required:
+        model_management.free_memory(required, device, for_dynamic=True)
+        if model_management.get_free_memory(device) < required:
+            model_management.free_memory(required, device, for_dynamic=False)
+        model_management.cleanup_models()
+        model_management.soft_empty_cache()
+        logger.debug("%s %s free_memory target=%d", LOG_PREFIX, marker, required)
+
+
+def _sanitize_for_transport(value):
+    primitives = (str, int, float, bool, type(None))
+    if isinstance(value, primitives):
+        return value
+
+    cls_name = value.__class__.__name__
+    if cls_name == "FlexibleOptionalInputType":
+        return {
+            "__pyisolate_flexible_optional__": True,
+            "type": _sanitize_for_transport(getattr(value, "type", "*")),
+        }
+    if cls_name == "AnyType":
+        return {"__pyisolate_any_type__": True, "value": str(value)}
+    if cls_name == "ByPassTypeTuple":
+        return {
+            "__pyisolate_bypass_tuple__": [
+                _sanitize_for_transport(v) for v in tuple(value)
+            ]
+        }
+
+    if isinstance(value, dict):
+        return {k: _sanitize_for_transport(v) for k, v in value.items()}
+    if isinstance(value, tuple):
+        return {"__pyisolate_tuple__": [_sanitize_for_transport(v) for v in value]}
+    if isinstance(value, list):
+        return [_sanitize_for_transport(v) for v in value]
+
+    return str(value)
+
+
+# Re-export RemoteObjectHandle from pyisolate for backward compatibility
+# The canonical definition is now in pyisolate._internal.remote_handle
+from pyisolate._internal.remote_handle import RemoteObjectHandle  # noqa: E402,F401
+
+
+class ComfyNodeExtension(ExtensionBase):
+    def __init__(self) -> None:
+        super().__init__()
+        self.node_classes: Dict[str, type] = {}
+        self.display_names: Dict[str, str] = {}
+        self.node_instances: Dict[str, Any] = {}
+        self.remote_objects: Dict[str, Any] = {}
+        self._route_handlers: Dict[str, Any] = {}
+        self._module: Any = None
+        self._metadata_ready = asyncio.Event()
+
+    async def on_module_loaded(self, module: Any) -> None:
+        try:
+            self._module = module
+
+            # Registries are initialized in host_hooks.py initialize_host_process()
+            # They auto-register via ProxiedSingleton when instantiated
+            # NO additional setup required here - if a registry is missing from host_hooks, it WILL fail
+
+            self.node_classes = getattr(module, "NODE_CLASS_MAPPINGS", {}) or {}
+            self.display_names = getattr(module, "NODE_DISPLAY_NAME_MAPPINGS", {}) or {}
+            self._register_module_routes(module)
+
+            # Register web directory with WebDirectoryProxy (child-side)
+            web_dir_attr = getattr(module, "WEB_DIRECTORY", None)
+            if web_dir_attr is not None:
+                module_dir = os.path.dirname(os.path.abspath(module.__file__))
+                web_dir_path = os.path.abspath(os.path.join(module_dir, web_dir_attr))
+                ext_name = _read_extension_name(module_dir)
+
+                # If web dir is empty, run the copy step that prestartup_script.py did
+                _run_prestartup_web_copy(module, module_dir, web_dir_path)
+
+                if os.path.isdir(web_dir_path) and any(os.scandir(web_dir_path)):
+                    from comfy.isolation.proxies.web_directory_proxy import WebDirectoryProxy
+                    WebDirectoryProxy.register_web_dir(ext_name, web_dir_path)
+
+            try:
+                from comfy_api.latest import ComfyExtension
+
+                for name, obj in inspect.getmembers(module):
+                    if not (
+                        inspect.isclass(obj)
+                        and issubclass(obj, ComfyExtension)
+                        and obj is not ComfyExtension
+                    ):
+                        continue
+                    if not obj.__module__.startswith(module.__name__):
+                        continue
+                    try:
+                        ext_instance = obj()
+                        try:
+                            await asyncio.wait_for(
+                                ext_instance.on_load(), timeout=V3_DISCOVERY_TIMEOUT
+                            )
+                        except asyncio.TimeoutError:
+                            logger.error(
+                                "%s V3 Extension %s timed out in on_load()",
+                                LOG_PREFIX,
+                                name,
+                            )
+                            continue
+                        try:
+                            v3_nodes = await asyncio.wait_for(
+                                ext_instance.get_node_list(), timeout=V3_DISCOVERY_TIMEOUT
+                            )
+                        except asyncio.TimeoutError:
+                            logger.error(
+                                "%s V3 Extension %s timed out in get_node_list()",
+                                LOG_PREFIX,
+                                name,
+                            )
+                            continue
+                        for node_cls in v3_nodes:
+                            if hasattr(node_cls, "GET_SCHEMA"):
+                                schema = node_cls.GET_SCHEMA()
+                                self.node_classes[schema.node_id] = node_cls
+                                if schema.display_name:
+                                    self.display_names[schema.node_id] = schema.display_name
+                    except Exception as e:
+                        logger.error("%s V3 Extension %s failed: %s", LOG_PREFIX, name, e)
+            except ImportError:
+                pass
+
+            module_name = getattr(module, "__name__", "isolated_nodes")
+            for node_cls in self.node_classes.values():
+                if hasattr(node_cls, "__module__") and "/" in str(node_cls.__module__):
+                    node_cls.__module__ = module_name
+
+            self.node_instances = {}
+        finally:
+            self._metadata_ready.set()
+
+    def _register_module_routes(self, module: Any) -> None:
+        """Bridge legacy module-level ROUTES declarations into isolated routing."""
+        routes = getattr(module, "ROUTES", None) or []
+        if not routes:
+            return
+
+        from comfy.isolation.proxies.prompt_server_impl import PromptServerStub
+
+        prompt_server = PromptServerStub()
+        route_table = getattr(prompt_server, "routes", None)
+        if route_table is None:
+            logger.warning("%s Route registration unavailable for %s", LOG_PREFIX, module)
+            return
+
+        for route_spec in routes:
+            if not isinstance(route_spec, dict):
+                logger.warning("%s Ignoring non-dict ROUTES entry: %r", LOG_PREFIX, route_spec)
+                continue
+
+            method = str(route_spec.get("method", "")).strip().upper()
+            path = str(route_spec.get("path", "")).strip()
+            handler_ref = route_spec.get("handler")
+            if not method or not path:
+                logger.warning("%s Ignoring incomplete route spec: %r", LOG_PREFIX, route_spec)
+                continue
+
+            if isinstance(handler_ref, str):
+                handler = getattr(module, handler_ref, None)
+            else:
+                handler = handler_ref
+            if not callable(handler):
+                logger.warning(
+                    "%s Ignoring route with missing handler %r for %s %s",
+                    LOG_PREFIX,
+                    handler_ref,
+                    method,
+                    path,
+                )
+                continue
+
+            decorator = getattr(route_table, method.lower(), None)
+            if not callable(decorator):
+                logger.warning("%s Unsupported route method %s for %s", LOG_PREFIX, method, path)
+                continue
+
+            decorator(path)(handler)
+            self._route_handlers[f"{method} {path}"] = handler
+            logger.info("%s buffered legacy route %s %s", LOG_PREFIX, method, path)
+
+    async def list_nodes(self) -> Dict[str, str]:
+        await asyncio.wait_for(
+            self._metadata_ready.wait(), timeout=V3_DISCOVERY_TIMEOUT
+        )
+        return {name: self.display_names.get(name, name) for name in self.node_classes}
+
+    async def get_node_info(self, node_name: str) -> Dict[str, Any]:
+        return await self.get_node_details(node_name)
+
+    async def get_node_details(self, node_name: str) -> Dict[str, Any]:
+        await asyncio.wait_for(
+            self._metadata_ready.wait(), timeout=V3_DISCOVERY_TIMEOUT
+        )
+        node_cls = self._get_node_class(node_name)
+        is_v3 = issubclass(node_cls, _ComfyNodeInternal)
+
+        input_types_raw = (
+            node_cls.INPUT_TYPES() if hasattr(node_cls, "INPUT_TYPES") else {}
+        )
+        output_is_list = getattr(node_cls, "OUTPUT_IS_LIST", None)
+        if output_is_list is not None:
+            output_is_list = tuple(bool(x) for x in output_is_list)
+
+        details: Dict[str, Any] = {
+            "input_types": _sanitize_for_transport(input_types_raw),
+            "return_types": tuple(
+                str(t) for t in getattr(node_cls, "RETURN_TYPES", ())
+            ),
+            "return_names": getattr(node_cls, "RETURN_NAMES", None),
+            "function": str(getattr(node_cls, "FUNCTION", "execute")),
+            "category": str(getattr(node_cls, "CATEGORY", "")),
+            "output_node": bool(getattr(node_cls, "OUTPUT_NODE", False)),
+            "output_is_list": output_is_list,
+            "is_v3": is_v3,
+        }
+
+        if is_v3:
+            try:
+                schema = node_cls.GET_SCHEMA()
+                schema_v1 = asdict(schema.get_v1_info(node_cls))
+                try:
+                    schema_v3 = asdict(schema.get_v3_info(node_cls))
+                except (AttributeError, TypeError):
+                    schema_v3 = self._build_schema_v3_fallback(schema)
+                details.update(
+                    {
+                        "schema_v1": schema_v1,
+                        "schema_v3": schema_v3,
+                        "hidden": [h.value for h in (schema.hidden or [])],
+                        "description": getattr(schema, "description", ""),
+                        "deprecated": bool(getattr(node_cls, "DEPRECATED", False)),
+                        "experimental": bool(getattr(node_cls, "EXPERIMENTAL", False)),
+                        "api_node": bool(getattr(node_cls, "API_NODE", False)),
+                        "input_is_list": bool(
+                            getattr(node_cls, "INPUT_IS_LIST", False)
+                        ),
+                        "not_idempotent": bool(
+                            getattr(node_cls, "NOT_IDEMPOTENT", False)
+                        ),
+                        "accept_all_inputs": bool(
+                            getattr(node_cls, "ACCEPT_ALL_INPUTS", False)
+                        ),
+                    }
+                )
+            except Exception as exc:
+                logger.warning(
+                    "%s V3 schema serialization failed for %s: %s",
+                    LOG_PREFIX,
+                    node_name,
+                    exc,
+                )
+        return details
+
+    def _build_schema_v3_fallback(self, schema) -> Dict[str, Any]:
+        input_dict: Dict[str, Any] = {}
+        output_dict: Dict[str, Any] = {}
+        hidden_list: List[str] = []
+
+        if getattr(schema, "inputs", None):
+            for inp in schema.inputs:
+                self._add_schema_io_v3(inp, input_dict)
+        if getattr(schema, "outputs", None):
+            for out in schema.outputs:
+                self._add_schema_io_v3(out, output_dict)
+        if getattr(schema, "hidden", None):
+            for h in schema.hidden:
+                hidden_list.append(getattr(h, "value", str(h)))
+
+        return {
+            "input": input_dict,
+            "output": output_dict,
+            "hidden": hidden_list,
+            "name": getattr(schema, "node_id", None),
+            "display_name": getattr(schema, "display_name", None),
+            "description": getattr(schema, "description", None),
+            "category": getattr(schema, "category", None),
+            "output_node": getattr(schema, "is_output_node", False),
+            "deprecated": getattr(schema, "is_deprecated", False),
+            "experimental": getattr(schema, "is_experimental", False),
+            "api_node": getattr(schema, "is_api_node", False),
+        }
+
+    def _add_schema_io_v3(self, io_obj: Any, target: Dict[str, Any]) -> None:
+        io_id = getattr(io_obj, "id", None)
+        if io_id is None:
+            return
+
+        io_type_fn = getattr(io_obj, "get_io_type", None)
+        io_type = (
+            io_type_fn() if callable(io_type_fn) else getattr(io_obj, "io_type", None)
+        )
+
+        as_dict_fn = getattr(io_obj, "as_dict", None)
+        payload = as_dict_fn() if callable(as_dict_fn) else {}
+
+        target[str(io_id)] = (io_type, payload)
+
+    async def get_input_types(self, node_name: str) -> Dict[str, Any]:
+        node_cls = self._get_node_class(node_name)
+        if hasattr(node_cls, "INPUT_TYPES"):
+            return node_cls.INPUT_TYPES()
+        return {}
+
+    async def execute_node(self, node_name: str, **inputs: Any) -> Tuple[Any, ...]:
+        logger.debug(
+            "%s ISO:child_execute_start ext=%s node=%s input_keys=%d",
+            LOG_PREFIX,
+            getattr(self, "name", "?"),
+            node_name,
+            len(inputs),
+        )
+        if os.environ.get("PYISOLATE_CHILD") == "1":
+            _relieve_child_vram_pressure("EXT:pre_execute")
+
+        resolved_inputs = self._resolve_remote_objects(inputs)
+
+        instance = self._get_node_instance(node_name)
+        node_cls = self._get_node_class(node_name)
+
+        # V3 API nodes expect hidden parameters in cls.hidden, not as kwargs
+        # Hidden params come through RPC as string keys like "Hidden.prompt"
+        from comfy_api.latest._io import Hidden, HiddenHolder
+
+        # Map string representations back to Hidden enum keys
+        hidden_string_map = {
+            "Hidden.unique_id": Hidden.unique_id,
+            "Hidden.prompt": Hidden.prompt,
+            "Hidden.extra_pnginfo": Hidden.extra_pnginfo,
+            "Hidden.dynprompt": Hidden.dynprompt,
+            "Hidden.auth_token_comfy_org": Hidden.auth_token_comfy_org,
+            "Hidden.api_key_comfy_org": Hidden.api_key_comfy_org,
+            # Uppercase enum VALUE forms — V3 execution engine passes these
+            "UNIQUE_ID": Hidden.unique_id,
+            "PROMPT": Hidden.prompt,
+            "EXTRA_PNGINFO": Hidden.extra_pnginfo,
+            "DYNPROMPT": Hidden.dynprompt,
+            "AUTH_TOKEN_COMFY_ORG": Hidden.auth_token_comfy_org,
+            "API_KEY_COMFY_ORG": Hidden.api_key_comfy_org,
+        }
+
+        # Find and extract hidden parameters (both enum and string form)
+        hidden_found = {}
+        keys_to_remove = []
+
+        for key in list(resolved_inputs.keys()):
+            # Check string form first (from RPC serialization)
+            if key in hidden_string_map:
+                hidden_found[hidden_string_map[key]] = resolved_inputs[key]
+                keys_to_remove.append(key)
+            # Also check enum form (direct calls)
+            elif isinstance(key, Hidden):
+                hidden_found[key] = resolved_inputs[key]
+                keys_to_remove.append(key)
+
+        # Remove hidden params from kwargs
+        for key in keys_to_remove:
+            resolved_inputs.pop(key)
+
+        # Set hidden on node class if any hidden params found
+        if hidden_found:
+            if not hasattr(node_cls, "hidden") or node_cls.hidden is None:
+                node_cls.hidden = HiddenHolder.from_dict(hidden_found)
+            else:
+                # Update existing hidden holder
+                for key, value in hidden_found.items():
+                    setattr(node_cls.hidden, key.value.lower(), value)
+
+        # INPUT_IS_LIST: ComfyUI's executor passes all inputs as lists when this
+        # flag is set.  The isolation RPC delivers unwrapped values, so we must
+        # wrap each input in a single-element list to match the contract.
+        if getattr(node_cls, "INPUT_IS_LIST", False):
+            resolved_inputs = {k: [v] for k, v in resolved_inputs.items()}
+
+        function_name = getattr(node_cls, "FUNCTION", "execute")
+        if not hasattr(instance, function_name):
+            raise AttributeError(f"Node {node_name} missing callable '{function_name}'")
+
+        handler = getattr(instance, function_name)
+
+        try:
+            import torch
+            if asyncio.iscoroutinefunction(handler):
+                with torch.inference_mode():
+                    result = await handler(**resolved_inputs)
+            else:
+                import functools
+
+                def _run_with_inference_mode(**kwargs):
+                    with torch.inference_mode():
+                        return handler(**kwargs)
+
+                loop = asyncio.get_running_loop()
+                result = await loop.run_in_executor(
+                    None, functools.partial(_run_with_inference_mode, **resolved_inputs)
+                )
+        except Exception:
+            logger.exception(
+                "%s ISO:child_execute_error ext=%s node=%s",
+                LOG_PREFIX,
+                getattr(self, "name", "?"),
+                node_name,
+            )
+            raise
+
+        if type(result).__name__ == "NodeOutput":
+            node_output_dict = {
+                "__node_output__": True,
+                "args": self._wrap_unpicklable_objects(result.args),
+            }
+            if result.ui is not None:
+                node_output_dict["ui"] = self._wrap_unpicklable_objects(result.ui)
+            if getattr(result, "expand", None) is not None:
+                node_output_dict["expand"] = result.expand
+            if getattr(result, "block_execution", None) is not None:
+                node_output_dict["block_execution"] = result.block_execution
+            return node_output_dict
+        if self._is_comfy_protocol_return(result):
+            wrapped = self._wrap_unpicklable_objects(result)
+            return wrapped
+
+        if not isinstance(result, tuple):
+            result = (result,)
+        wrapped = self._wrap_unpicklable_objects(result)
+        return wrapped
+
+    async def flush_pending_routes(self) -> int:
+        """Flush buffered route registrations to host via RPC. Called by host after node discovery."""
+        from comfy.isolation.proxies.prompt_server_impl import PromptServerStub
+        return await PromptServerStub.flush_child_routes()
+
+    async def flush_transport_state(self) -> int:
+        if os.environ.get("PYISOLATE_CHILD") != "1":
+            return 0
+        logger.debug(
+            "%s ISO:child_flush_start ext=%s", LOG_PREFIX, getattr(self, "name", "?")
+        )
+        flushed = _flush_tensor_transport_state("EXT:workflow_end")
+        try:
+            from comfy.isolation.model_patcher_proxy_registry import (
+                ModelPatcherRegistry,
+            )
+
+            registry = ModelPatcherRegistry()
+            removed = registry.sweep_pending_cleanup()
+            if removed > 0:
+                logger.debug(
+                    "%s EXT:workflow_end registry sweep removed=%d", LOG_PREFIX, removed
+                )
+        except Exception:
+            logger.debug(
+                "%s EXT:workflow_end registry sweep failed", LOG_PREFIX, exc_info=True
+            )
+        logger.debug(
+            "%s ISO:child_flush_done ext=%s flushed=%d",
+            LOG_PREFIX,
+            getattr(self, "name", "?"),
+            flushed,
+        )
+        return flushed
+
+    async def get_remote_object(self, object_id: str) -> Any:
+        """Retrieve a remote object by ID for host-side deserialization."""
+        if object_id not in self.remote_objects:
+            raise KeyError(f"Remote object {object_id} not found")
+
+        return self.remote_objects[object_id]
+
+    def _store_remote_object_handle(self, obj: Any) -> RemoteObjectHandle:
+        object_id = str(uuid.uuid4())
+        self.remote_objects[object_id] = obj
+        return RemoteObjectHandle(object_id, type(obj).__name__)
+
+    async def call_remote_object_method(
+        self,
+        object_id: str,
+        method_name: str,
+        *args: Any,
+        **kwargs: Any,
+    ) -> Any:
+        """Invoke a method or attribute-backed accessor on a child-owned object."""
+        obj = await self.get_remote_object(object_id)
+
+        if method_name == "get_patcher_attr":
+            return getattr(obj, args[0])
+        if method_name == "get_model_options":
+            return getattr(obj, "model_options")
+        if method_name == "set_model_options":
+            setattr(obj, "model_options", args[0])
+            return None
+        if method_name == "get_object_patches":
+            return getattr(obj, "object_patches")
+        if method_name == "get_patches":
+            return getattr(obj, "patches")
+        if method_name == "get_wrappers":
+            return getattr(obj, "wrappers")
+        if method_name == "get_callbacks":
+            return getattr(obj, "callbacks")
+        if method_name == "get_load_device":
+            return getattr(obj, "load_device")
+        if method_name == "get_offload_device":
+            return getattr(obj, "offload_device")
+        if method_name == "get_hook_mode":
+            return getattr(obj, "hook_mode")
+        if method_name == "get_parent":
+            parent = getattr(obj, "parent", None)
+            if parent is None:
+                return None
+            return self._store_remote_object_handle(parent)
+        if method_name == "get_inner_model_attr":
+            attr_name = args[0]
+            if hasattr(obj.model, attr_name):
+                return getattr(obj.model, attr_name)
+            if hasattr(obj, attr_name):
+                return getattr(obj, attr_name)
+            return None
+        if method_name == "inner_model_apply_model":
+            return obj.model.apply_model(*args[0], **args[1])
+        if method_name == "inner_model_extra_conds_shapes":
+            return obj.model.extra_conds_shapes(*args[0], **args[1])
+        if method_name == "inner_model_extra_conds":
+            return obj.model.extra_conds(*args[0], **args[1])
+        if method_name == "inner_model_memory_required":
+            return obj.model.memory_required(*args[0], **args[1])
+        if method_name == "process_latent_in":
+            return obj.model.process_latent_in(*args[0], **args[1])
+        if method_name == "process_latent_out":
+            return obj.model.process_latent_out(*args[0], **args[1])
+        if method_name == "scale_latent_inpaint":
+            return obj.model.scale_latent_inpaint(*args[0], **args[1])
+        if method_name.startswith("get_"):
+            attr_name = method_name[4:]
+            if hasattr(obj, attr_name):
+                return getattr(obj, attr_name)
+
+        target = getattr(obj, method_name)
+        if callable(target):
+            result = target(*args, **kwargs)
+            if inspect.isawaitable(result):
+                result = await result
+            if type(result).__name__ == "ModelPatcher":
+                return self._store_remote_object_handle(result)
+            return result
+        if args or kwargs:
+            raise TypeError(f"{method_name} is not callable on remote object {object_id}")
+        return target
+
+    def _wrap_unpicklable_objects(self, data: Any) -> Any:
+        if isinstance(data, (str, int, float, bool, type(None))):
+            return data
+        if isinstance(data, torch.Tensor):
+            tensor = data.detach() if data.requires_grad else data
+            if os.environ.get("PYISOLATE_CHILD") == "1" and tensor.device.type != "cpu":
+                return tensor.cpu()
+            return tensor
+
+        # Special-case clip vision outputs: preserve attribute access by packing fields
+        if hasattr(data, "penultimate_hidden_states") or hasattr(
+            data, "last_hidden_state"
+        ):
+            fields = {}
+            for attr in (
+                "penultimate_hidden_states",
+                "last_hidden_state",
+                "image_embeds",
+                "text_embeds",
+            ):
+                if hasattr(data, attr):
+                    try:
+                        fields[attr] = self._wrap_unpicklable_objects(
+                            getattr(data, attr)
+                        )
+                    except Exception:
+                        pass
+            if fields:
+                return {"__pyisolate_attribute_container__": True, "data": fields}
+
+        # Avoid converting arbitrary objects with stateful methods (models, etc.)
+        # They will be handled via RemoteObjectHandle below.
+
+        type_name = type(data).__name__
+        if type_name == "ModelPatcherProxy":
+            return {"__type__": "ModelPatcherRef", "model_id": data._instance_id}
+        if type_name == "CLIPProxy":
+            return {"__type__": "CLIPRef", "clip_id": data._instance_id}
+        if type_name == "VAEProxy":
+            return {"__type__": "VAERef", "vae_id": data._instance_id}
+        if type_name == "ModelSamplingProxy":
+            return {"__type__": "ModelSamplingRef", "ms_id": data._instance_id}
+
+        if isinstance(data, (list, tuple)):
+            wrapped = [self._wrap_unpicklable_objects(item) for item in data]
+            return tuple(wrapped) if isinstance(data, tuple) else wrapped
+        if isinstance(data, dict):
+            converted_dict = {
+                k: self._wrap_unpicklable_objects(v) for k, v in data.items()
+            }
+            return {"__pyisolate_attrdict__": True, "data": converted_dict}
+
+        from pyisolate._internal.serialization_registry import SerializerRegistry
+
+        registry = SerializerRegistry.get_instance()
+        if registry.is_data_type(type_name):
+            serializer = registry.get_serializer(type_name)
+            if serializer:
+                return serializer(data)
+
+        return self._store_remote_object_handle(data)
+
+    def _resolve_remote_objects(self, data: Any) -> Any:
+        if isinstance(data, RemoteObjectHandle):
+            if data.object_id not in self.remote_objects:
+                raise KeyError(f"Remote object {data.object_id} not found")
+            return self.remote_objects[data.object_id]
+
+        if isinstance(data, dict):
+            ref_type = data.get("__type__")
+            if ref_type in ("CLIPRef", "ModelPatcherRef", "VAERef"):
+                from pyisolate._internal.model_serialization import (
+                    deserialize_proxy_result,
+                )
+
+                return deserialize_proxy_result(data)
+            if ref_type == "ModelSamplingRef":
+                from pyisolate._internal.model_serialization import (
+                    deserialize_proxy_result,
+                )
+
+                return deserialize_proxy_result(data)
+            return {k: self._resolve_remote_objects(v) for k, v in data.items()}
+
+        if isinstance(data, (list, tuple)):
+            resolved = [self._resolve_remote_objects(item) for item in data]
+            return tuple(resolved) if isinstance(data, tuple) else resolved
+        return data
+
+    def _get_node_class(self, node_name: str) -> type:
+        if node_name not in self.node_classes:
+            raise KeyError(f"Unknown node: {node_name}")
+        return self.node_classes[node_name]
+
+    def _get_node_instance(self, node_name: str) -> Any:
+        if node_name not in self.node_instances:
+            if node_name not in self.node_classes:
+                raise KeyError(f"Unknown node: {node_name}")
+            self.node_instances[node_name] = self.node_classes[node_name]()
+        return self.node_instances[node_name]
+
+    async def before_module_loaded(self) -> None:
+        try:
+            from comfy.isolation import initialize_proxies
+
+            initialize_proxies()
+        except Exception as e:
+            logger.error(
+                "%s before_module_loaded initialize_proxies FAILED: %s", LOG_PREFIX, e
+            )
+
+        await super().before_module_loaded()
+        try:
+            from comfy_api.latest import ComfyAPI_latest
+            from .proxies.progress_proxy import ProgressProxy
+
+            ComfyAPI_latest.Execution = ProgressProxy
+            # ComfyAPI_latest.execution = ProgressProxy()  # Eliminated to avoid Singleton collision
+            # fp_proxy = FolderPathsProxy()                 # Eliminated to avoid Singleton collision
+            # latest_ui.folder_paths = fp_proxy
+            # latest_resources.folder_paths = fp_proxy
+        except Exception:
+            pass
+
+    async def call_route_handler(
+        self,
+        handler_module: str,
+        handler_func: str,
+        request_data: Dict[str, Any],
+    ) -> Any:
+        cache_key = f"{handler_module}.{handler_func}"
+        if cache_key not in self._route_handlers:
+            if self._module is not None and hasattr(self._module, "__file__"):
+                node_dir = os.path.dirname(self._module.__file__)
+                if node_dir not in sys.path:
+                    sys.path.insert(0, node_dir)
+            try:
+                module = importlib.import_module(handler_module)
+                self._route_handlers[cache_key] = getattr(module, handler_func)
+            except (ImportError, AttributeError) as e:
+                raise ValueError(f"Route handler not found: {cache_key}") from e
+
+        handler = self._route_handlers[cache_key]
+        mock_request = MockRequest(request_data)
+
+        if asyncio.iscoroutinefunction(handler):
+            result = await handler(mock_request)
+        else:
+            result = handler(mock_request)
+        return self._serialize_response(result)
+
+    def _is_comfy_protocol_return(self, result: Any) -> bool:
+        """
+        Check if the result matches the ComfyUI 'Protocol Return' schema.
+
+        A Protocol Return is a dictionary containing specific reserved keys that
+        ComfyUI's execution engine interprets as instructions (UI updates,
+        Workflow expansion, etc.) rather than purely data outputs.
+
+        Schema:
+           - Must be a dict
+           - Must contain at least one of: 'ui', 'result', 'expand'
+        """
+        if not isinstance(result, dict):
+            return False
+        return any(key in result for key in ("ui", "result", "expand"))
+
+    def _serialize_response(self, response: Any) -> Dict[str, Any]:
+        if response is None:
+            return {"type": "text", "body": "", "status": 204}
+        if isinstance(response, dict):
+            return {"type": "json", "body": response, "status": 200}
+        if isinstance(response, str):
+            return {"type": "text", "body": response, "status": 200}
+        if hasattr(response, "text") and hasattr(response, "status"):
+            return {
+                "type": "text",
+                "body": response.text
+                if hasattr(response, "text")
+                else str(response.body),
+                "status": response.status,
+                "headers": dict(response.headers)
+                if hasattr(response, "headers")
+                else {},
+            }
+        if hasattr(response, "body") and hasattr(response, "status"):
+            body = response.body
+            if isinstance(body, bytes):
+                try:
+                    return {
+                        "type": "text",
+                        "body": body.decode("utf-8"),
+                        "status": response.status,
+                    }
+                except UnicodeDecodeError:
+                    return {
+                        "type": "binary",
+                        "body": body.hex(),
+                        "status": response.status,
+                    }
+            return {"type": "json", "body": body, "status": response.status}
+        return {"type": "text", "body": str(response), "status": 200}
+
+
+class MockRequest:
+    def __init__(self, data: Dict[str, Any]):
+        self.method = data.get("method", "GET")
+        self.path = data.get("path", "/")
+        self.query = data.get("query", {})
+        self._body = data.get("body", {})
+        self._text = data.get("text", "")
+        self.headers = data.get("headers", {})
+        self.content_type = data.get(
+            "content_type", self.headers.get("Content-Type", "application/json")
+        )
+        self.match_info = data.get("match_info", {})
+
+    async def json(self) -> Any:
+        if isinstance(self._body, dict):
+            return self._body
+        if isinstance(self._body, str):
+            return json.loads(self._body)
+        return {}
+
+    async def post(self) -> Dict[str, Any]:
+        if isinstance(self._body, dict):
+            return self._body
+        return {}
+
+    async def text(self) -> str:
+        if self._text:
+            return self._text
+        if isinstance(self._body, str):
+            return self._body
+        if isinstance(self._body, dict):
+            return json.dumps(self._body)
+        return ""
+
+    async def read(self) -> bytes:
+        return (await self.text()).encode("utf-8")

comfy/isolation/host_hooks.py

@@ -0,0 +1,25 @@
+# pylint: disable=import-outside-toplevel
+# Host process initialization for PyIsolate
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+def initialize_host_process() -> None:
+    from .proxies.folder_paths_proxy import FolderPathsProxy
+    from .proxies.helper_proxies import HelperProxiesService
+    from .proxies.model_management_proxy import ModelManagementProxy
+    from .proxies.progress_proxy import ProgressProxy
+    from .proxies.prompt_server_impl import PromptServerService
+    from .proxies.utils_proxy import UtilsProxy
+    from .proxies.web_directory_proxy import WebDirectoryProxy
+    from .vae_proxy import VAERegistry
+
+    FolderPathsProxy()
+    HelperProxiesService()
+    ModelManagementProxy()
+    ProgressProxy()
+    PromptServerService()
+    UtilsProxy()
+    WebDirectoryProxy()
+    VAERegistry()

comfy/isolation/host_policy.py

@@ -0,0 +1,180 @@
+# pylint: disable=logging-fstring-interpolation
+from __future__ import annotations
+
+import logging
+import os
+from pathlib import Path
+from pathlib import PurePosixPath
+from typing import Dict, List, TypedDict
+
+try:
+    import tomllib
+except ImportError:
+    import tomli as tomllib  # type: ignore[no-redef]
+
+logger = logging.getLogger(__name__)
+
+HOST_POLICY_PATH_ENV = "COMFY_HOST_POLICY_PATH"
+VALID_SANDBOX_MODES = frozenset({"required", "disabled"})
+FORBIDDEN_WRITABLE_PATHS = frozenset({"/tmp"})
+
+
+class HostSecurityPolicy(TypedDict):
+    sandbox_mode: str
+    allow_network: bool
+    writable_paths: List[str]
+    readonly_paths: List[str]
+    sealed_worker_ro_import_paths: List[str]
+    whitelist: Dict[str, str]
+
+
+DEFAULT_POLICY: HostSecurityPolicy = {
+    "sandbox_mode": "required",
+    "allow_network": False,
+    "writable_paths": ["/dev/shm"],
+    "readonly_paths": [],
+    "sealed_worker_ro_import_paths": [],
+    "whitelist": {},
+}
+
+
+def _default_policy() -> HostSecurityPolicy:
+    return {
+        "sandbox_mode": DEFAULT_POLICY["sandbox_mode"],
+        "allow_network": DEFAULT_POLICY["allow_network"],
+        "writable_paths": list(DEFAULT_POLICY["writable_paths"]),
+        "readonly_paths": list(DEFAULT_POLICY["readonly_paths"]),
+        "sealed_worker_ro_import_paths": list(DEFAULT_POLICY["sealed_worker_ro_import_paths"]),
+        "whitelist": dict(DEFAULT_POLICY["whitelist"]),
+    }
+
+
+def _normalize_writable_paths(paths: list[object]) -> list[str]:
+    normalized_paths: list[str] = []
+    for raw_path in paths:
+        # Host-policy paths are contract-style POSIX paths; keep representation
+        # stable across Windows/Linux so tests and config behavior stay consistent.
+        normalized_path = str(PurePosixPath(str(raw_path).replace("\\", "/")))
+        if normalized_path in FORBIDDEN_WRITABLE_PATHS:
+            continue
+        normalized_paths.append(normalized_path)
+    return normalized_paths
+
+
+def _load_whitelist_file(file_path: Path, config_path: Path) -> Dict[str, str]:
+    if not file_path.is_absolute():
+        file_path = config_path.parent / file_path
+    if not file_path.exists():
+        logger.warning("whitelist_file %s not found, skipping.", file_path)
+        return {}
+    entries: Dict[str, str] = {}
+    for line in file_path.read_text().splitlines():
+        line = line.strip()
+        if not line or line.startswith("#"):
+            continue
+        entries[line] = "*"
+    logger.debug("Loaded %d whitelist entries from %s", len(entries), file_path)
+    return entries
+
+
+def _normalize_sealed_worker_ro_import_paths(raw_paths: object) -> list[str]:
+    if not isinstance(raw_paths, list):
+        raise ValueError(
+            "tool.comfy.host.sealed_worker_ro_import_paths must be a list of absolute paths."
+        )
+
+    normalized_paths: list[str] = []
+    seen: set[str] = set()
+    for raw_path in raw_paths:
+        if not isinstance(raw_path, str) or not raw_path.strip():
+            raise ValueError(
+                "tool.comfy.host.sealed_worker_ro_import_paths entries must be non-empty strings."
+            )
+        normalized_path = str(PurePosixPath(raw_path.replace("\\", "/")))
+        # Accept both POSIX absolute paths (/home/...) and Windows drive-letter paths (D:/...)
+        is_absolute = normalized_path.startswith("/") or (
+            len(normalized_path) >= 3 and normalized_path[1] == ":" and normalized_path[2] == "/"
+        )
+        if not is_absolute:
+            raise ValueError(
+                "tool.comfy.host.sealed_worker_ro_import_paths entries must be absolute paths."
+            )
+        if normalized_path not in seen:
+            seen.add(normalized_path)
+            normalized_paths.append(normalized_path)
+
+    return normalized_paths
+
+
+def load_host_policy(comfy_root: Path) -> HostSecurityPolicy:
+    config_override = os.environ.get(HOST_POLICY_PATH_ENV)
+    config_path = Path(config_override) if config_override else comfy_root / "pyproject.toml"
+    policy = _default_policy()
+
+    if not config_path.exists():
+        logger.debug("Host policy file missing at %s, using defaults.", config_path)
+        return policy
+
+    try:
+        with config_path.open("rb") as f:
+            data = tomllib.load(f)
+    except Exception:
+        logger.warning(
+            "Failed to parse host policy from %s, using defaults.",
+            config_path,
+            exc_info=True,
+        )
+        return policy
+
+    tool_config = data.get("tool", {}).get("comfy", {}).get("host", {})
+    if not isinstance(tool_config, dict):
+        logger.debug("No [tool.comfy.host] section found, using defaults.")
+        return policy
+
+    sandbox_mode = tool_config.get("sandbox_mode")
+    if isinstance(sandbox_mode, str):
+        normalized_sandbox_mode = sandbox_mode.strip().lower()
+        if normalized_sandbox_mode in VALID_SANDBOX_MODES:
+            policy["sandbox_mode"] = normalized_sandbox_mode
+        else:
+            logger.warning(
+                "Invalid host sandbox_mode %r in %s, using default %r.",
+                sandbox_mode,
+                config_path,
+                DEFAULT_POLICY["sandbox_mode"],
+            )
+
+    if "allow_network" in tool_config:
+        policy["allow_network"] = bool(tool_config["allow_network"])
+
+    if "writable_paths" in tool_config:
+        policy["writable_paths"] = _normalize_writable_paths(tool_config["writable_paths"])
+
+    if "readonly_paths" in tool_config:
+        policy["readonly_paths"] = [str(p) for p in tool_config["readonly_paths"]]
+
+    if "sealed_worker_ro_import_paths" in tool_config:
+        policy["sealed_worker_ro_import_paths"] = _normalize_sealed_worker_ro_import_paths(
+            tool_config["sealed_worker_ro_import_paths"]
+        )
+
+    whitelist_file = tool_config.get("whitelist_file")
+    if isinstance(whitelist_file, str):
+        policy["whitelist"].update(_load_whitelist_file(Path(whitelist_file), config_path))
+
+    whitelist_raw = tool_config.get("whitelist")
+    if isinstance(whitelist_raw, dict):
+        policy["whitelist"].update({str(k): str(v) for k, v in whitelist_raw.items()})
+
+    os.environ["PYISOLATE_SANDBOX_MODE"] = policy["sandbox_mode"]
+
+    logger.debug(
+        "Loaded Host Policy: %d whitelisted nodes, Sandbox=%s, Network=%s",
+        len(policy["whitelist"]),
+        policy["sandbox_mode"],
+        policy["allow_network"],
+    )
+    return policy
+
+
+__all__ = ["HostSecurityPolicy", "load_host_policy", "DEFAULT_POLICY"]

comfy/isolation/manifest_loader.py

@@ -0,0 +1,221 @@
+# pylint: disable=import-outside-toplevel
+from __future__ import annotations
+
+import hashlib
+import json
+import logging
+import os
+import sys
+import tempfile
+from pathlib import Path
+from typing import Any, Dict, List, Optional, Tuple
+
+import folder_paths
+
+try:
+    import tomllib
+except ImportError:
+    import tomli as tomllib  # type: ignore[no-redef]
+
+LOG_PREFIX = "]["
+logger = logging.getLogger(__name__)
+
+CACHE_SUBDIR = "cache"
+CACHE_KEY_FILE = "cache_key"
+CACHE_DATA_FILE = "node_info.json"
+CACHE_KEY_LENGTH = 16
+_NESTED_SCAN_ROOT = "packages"
+_IGNORED_MANIFEST_DIRS = {".git", ".venv", "__pycache__"}
+
+
+def _read_manifest(manifest_path: Path) -> dict[str, Any] | None:
+    try:
+        with manifest_path.open("rb") as f:
+            data = tomllib.load(f)
+        if isinstance(data, dict):
+            return data
+    except Exception:
+        return None
+    return None
+
+
+def _is_isolation_manifest(data: dict[str, Any]) -> bool:
+    return (
+        "tool" in data
+        and "comfy" in data["tool"]
+        and "isolation" in data["tool"]["comfy"]
+    )
+
+
+def _discover_nested_manifests(entry: Path) -> List[Tuple[Path, Path]]:
+    packages_root = entry / _NESTED_SCAN_ROOT
+    if not packages_root.exists() or not packages_root.is_dir():
+        return []
+
+    nested: List[Tuple[Path, Path]] = []
+    for manifest in sorted(packages_root.rglob("pyproject.toml")):
+        node_dir = manifest.parent
+        if any(part in _IGNORED_MANIFEST_DIRS for part in node_dir.parts):
+            continue
+
+        data = _read_manifest(manifest)
+        if not data or not _is_isolation_manifest(data):
+            continue
+
+        isolation = data["tool"]["comfy"]["isolation"]
+        if isolation.get("standalone") is True:
+            nested.append((node_dir, manifest))
+
+    return nested
+
+
+def find_manifest_directories() -> List[Tuple[Path, Path]]:
+    """Find custom node directories containing a valid pyproject.toml with [tool.comfy.isolation]."""
+    manifest_dirs: List[Tuple[Path, Path]] = []
+
+    # Standard custom_nodes paths
+    for base_path in folder_paths.get_folder_paths("custom_nodes"):
+        base = Path(base_path)
+        if not base.exists() or not base.is_dir():
+            continue
+
+        for entry in base.iterdir():
+            if not entry.is_dir():
+                continue
+
+            # Look for pyproject.toml
+            manifest = entry / "pyproject.toml"
+            if not manifest.exists():
+                continue
+
+            data = _read_manifest(manifest)
+            if not data or not _is_isolation_manifest(data):
+                continue
+
+            manifest_dirs.append((entry, manifest))
+            manifest_dirs.extend(_discover_nested_manifests(entry))
+
+    return manifest_dirs
+
+
+def compute_cache_key(node_dir: Path, manifest_path: Path) -> str:
+    """Hash manifest + .py mtimes + Python version + PyIsolate version."""
+    hasher = hashlib.sha256()
+
+    try:
+        # Hashing the manifest content ensures config changes invalidate cache
+        hasher.update(manifest_path.read_bytes())
+    except OSError:
+        hasher.update(b"__manifest_read_error__")
+
+    try:
+        py_files = sorted(node_dir.rglob("*.py"))
+        for py_file in py_files:
+            rel_path = py_file.relative_to(node_dir)
+            if "__pycache__" in str(rel_path) or ".venv" in str(rel_path):
+                continue
+            hasher.update(str(rel_path).encode("utf-8"))
+            try:
+                hasher.update(str(py_file.stat().st_mtime).encode("utf-8"))
+            except OSError:
+                hasher.update(b"__file_stat_error__")
+    except OSError:
+        hasher.update(b"__dir_scan_error__")
+
+    hasher.update(sys.version.encode("utf-8"))
+
+    try:
+        import pyisolate
+
+        hasher.update(pyisolate.__version__.encode("utf-8"))
+    except (ImportError, AttributeError):
+        hasher.update(b"__pyisolate_unknown__")
+
+    return hasher.hexdigest()[:CACHE_KEY_LENGTH]
+
+
+def get_cache_path(node_dir: Path, venv_root: Path) -> Tuple[Path, Path]:
+    """Return (cache_key_file, cache_data_file) in venv_root/{node}/cache/."""
+    cache_dir = venv_root / node_dir.name / CACHE_SUBDIR
+    return (cache_dir / CACHE_KEY_FILE, cache_dir / CACHE_DATA_FILE)
+
+
+def is_cache_valid(node_dir: Path, manifest_path: Path, venv_root: Path) -> bool:
+    """Return True only if stored cache key matches current computed key."""
+    try:
+        cache_key_file, cache_data_file = get_cache_path(node_dir, venv_root)
+        if not cache_key_file.exists() or not cache_data_file.exists():
+            return False
+        current_key = compute_cache_key(node_dir, manifest_path)
+        stored_key = cache_key_file.read_text(encoding="utf-8").strip()
+        return current_key == stored_key
+    except Exception as e:
+        logger.debug(
+            "%s Cache validation error for %s: %s", LOG_PREFIX, node_dir.name, e
+        )
+        return False
+
+
+def load_from_cache(node_dir: Path, venv_root: Path) -> Optional[Dict[str, Any]]:
+    """Load node metadata from cache, return None on any error."""
+    try:
+        _, cache_data_file = get_cache_path(node_dir, venv_root)
+        if not cache_data_file.exists():
+            return None
+        data = json.loads(cache_data_file.read_text(encoding="utf-8"))
+        if not isinstance(data, dict):
+            return None
+        return data
+    except Exception:
+        return None
+
+
+def save_to_cache(
+    node_dir: Path, venv_root: Path, node_data: Dict[str, Any], manifest_path: Path
+) -> None:
+    """Save node metadata and cache key atomically."""
+    try:
+        cache_key_file, cache_data_file = get_cache_path(node_dir, venv_root)
+        cache_dir = cache_key_file.parent
+        cache_dir.mkdir(parents=True, exist_ok=True)
+        cache_key = compute_cache_key(node_dir, manifest_path)
+
+        # Atomic write: data
+        tmp_data_fd, tmp_data_path = tempfile.mkstemp(dir=str(cache_dir), suffix=".tmp")
+        try:
+            with os.fdopen(tmp_data_fd, "w", encoding="utf-8") as f:
+                json.dump(node_data, f, indent=2)
+            os.replace(tmp_data_path, cache_data_file)
+        except Exception:
+            try:
+                os.unlink(tmp_data_path)
+            except OSError:
+                pass
+            raise
+
+        # Atomic write: key
+        tmp_key_fd, tmp_key_path = tempfile.mkstemp(dir=str(cache_dir), suffix=".tmp")
+        try:
+            with os.fdopen(tmp_key_fd, "w", encoding="utf-8") as f:
+                f.write(cache_key)
+            os.replace(tmp_key_path, cache_key_file)
+        except Exception:
+            try:
+                os.unlink(tmp_key_path)
+            except OSError:
+                pass
+            raise
+
+    except Exception as e:
+        logger.warning("%s Cache save failed for %s: %s", LOG_PREFIX, node_dir.name, e)
+
+
+__all__ = [
+    "LOG_PREFIX",
+    "find_manifest_directories",
+    "compute_cache_key",
+    "get_cache_path",
+    "is_cache_valid",
+    "load_from_cache",
+    "save_to_cache",
+]

comfy/isolation/model_patcher_proxy.py

@@ -0,0 +1,891 @@
+# pylint: disable=bare-except,consider-using-from-import,import-outside-toplevel,protected-access
+# RPC proxy for ModelPatcher (parent process)
+from __future__ import annotations
+
+import logging
+from typing import Any, Optional, List, Set, Dict, Callable
+
+from comfy.isolation.proxies.base import (
+    IS_CHILD_PROCESS,
+    BaseProxy,
+)
+from comfy.isolation.model_patcher_proxy_registry import (
+    ModelPatcherRegistry,
+    AutoPatcherEjector,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class ModelPatcherProxy(BaseProxy[ModelPatcherRegistry]):
+    _registry_class = ModelPatcherRegistry
+    __module__ = "comfy.model_patcher"
+    _APPLY_MODEL_GUARD_PADDING_BYTES = 32 * 1024 * 1024
+
+    def _spawn_related_proxy(self, instance_id: str) -> "ModelPatcherProxy":
+        proxy = ModelPatcherProxy(
+            instance_id,
+            self._registry,
+            manage_lifecycle=not IS_CHILD_PROCESS,
+        )
+        if getattr(self, "_rpc_caller", None) is not None:
+            proxy._rpc_caller = self._rpc_caller
+        return proxy
+
+    def _get_rpc(self) -> Any:
+        if self._rpc_caller is None:
+            from pyisolate._internal.rpc_protocol import get_child_rpc_instance
+
+            rpc = get_child_rpc_instance()
+            if rpc is not None:
+                self._rpc_caller = rpc.create_caller(
+                    self._registry_class, self._registry_class.get_remote_id()
+                )
+            else:
+                self._rpc_caller = self._registry
+        return self._rpc_caller
+
+    def get_all_callbacks(self, call_type: str = None) -> Any:
+        return self._call_rpc("get_all_callbacks", call_type)
+
+    def get_all_wrappers(self, wrapper_type: str = None) -> Any:
+        return self._call_rpc("get_all_wrappers", wrapper_type)
+
+    def _load_list(self, *args, **kwargs) -> Any:
+        return self._call_rpc("load_list_internal", *args, **kwargs)
+
+    def prepare_hook_patches_current_keyframe(
+        self, t: Any, hook_group: Any, model_options: Any
+    ) -> None:
+        self._call_rpc(
+            "prepare_hook_patches_current_keyframe", t, hook_group, model_options
+        )
+
+    def add_hook_patches(
+        self,
+        hook: Any,
+        patches: Any,
+        strength_patch: float = 1.0,
+        strength_model: float = 1.0,
+    ) -> None:
+        self._call_rpc(
+            "add_hook_patches", hook, patches, strength_patch, strength_model
+        )
+
+    def clear_cached_hook_weights(self) -> None:
+        self._call_rpc("clear_cached_hook_weights")
+
+    def get_combined_hook_patches(self, hooks: Any) -> Any:
+        return self._call_rpc("get_combined_hook_patches", hooks)
+
+    def get_additional_models_with_key(self, key: str) -> Any:
+        return self._call_rpc("get_additional_models_with_key", key)
+
+    @property
+    def object_patches(self) -> Any:
+        return self._call_rpc("get_object_patches")
+
+    @property
+    def patches(self) -> Any:
+        res = self._call_rpc("get_patches")
+        if isinstance(res, dict):
+            new_res = {}
+            for k, v in res.items():
+                new_list = []
+                for item in v:
+                    if isinstance(item, list):
+                        new_list.append(tuple(item))
+                    else:
+                        new_list.append(item)
+                new_res[k] = new_list
+            return new_res
+        return res
+
+    @property
+    def pinned(self) -> Set:
+        val = self._call_rpc("get_patcher_attr", "pinned")
+        return set(val) if val is not None else set()
+
+    @property
+    def hook_patches(self) -> Dict:
+        val = self._call_rpc("get_patcher_attr", "hook_patches")
+        if val is None:
+            return {}
+        try:
+            from comfy.hooks import _HookRef
+            import json
+
+            new_val = {}
+            for k, v in val.items():
+                if isinstance(k, str):
+                    if k.startswith("PYISOLATE_HOOKREF:"):
+                        ref_id = k.split(":", 1)[1]
+                        h = _HookRef()
+                        h._pyisolate_id = ref_id
+                        new_val[h] = v
+                    elif k.startswith("__pyisolate_key__"):
+                        try:
+                            json_str = k[len("__pyisolate_key__") :]
+                            data = json.loads(json_str)
+                            ref_id = None
+                            if isinstance(data, list):
+                                for item in data:
+                                    if (
+                                        isinstance(item, list)
+                                        and len(item) == 2
+                                        and item[0] == "id"
+                                    ):
+                                        ref_id = item[1]
+                                        break
+                            if ref_id:
+                                h = _HookRef()
+                                h._pyisolate_id = ref_id
+                                new_val[h] = v
+                            else:
+                                new_val[k] = v
+                        except Exception:
+                            new_val[k] = v
+                    else:
+                        new_val[k] = v
+                else:
+                    new_val[k] = v
+            return new_val
+        except ImportError:
+            return val
+
+    def set_hook_mode(self, hook_mode: Any) -> None:
+        self._call_rpc("set_hook_mode", hook_mode)
+
+    def register_all_hook_patches(
+        self,
+        hooks: Any,
+        target_dict: Any,
+        model_options: Any = None,
+        registered: Any = None,
+    ) -> None:
+        self._call_rpc(
+            "register_all_hook_patches", hooks, target_dict, model_options, registered
+        )
+
+    def is_clone(self, other: Any) -> bool:
+        if isinstance(other, ModelPatcherProxy):
+            return self._call_rpc("is_clone_by_id", other._instance_id)
+        return False
+
+    def clone(self) -> ModelPatcherProxy:
+        new_id = self._call_rpc("clone")
+        return self._spawn_related_proxy(new_id)
+
+    def clone_has_same_weights(self, clone: Any) -> bool:
+        if isinstance(clone, ModelPatcherProxy):
+            return self._call_rpc("clone_has_same_weights_by_id", clone._instance_id)
+        if not IS_CHILD_PROCESS:
+            return self._call_rpc("is_clone", clone)
+        return False
+
+    def get_model_object(self, name: str) -> Any:
+        return self._call_rpc("get_model_object", name)
+
+    @property
+    def model_options(self) -> dict:
+        data = self._call_rpc("get_model_options")
+        import json
+
+        def _decode_keys(obj):
+            if isinstance(obj, dict):
+                new_d = {}
+                for k, v in obj.items():
+                    if isinstance(k, str) and k.startswith("__pyisolate_key__"):
+                        try:
+                            json_str = k[17:]
+                            val = json.loads(json_str)
+                            if isinstance(val, list):
+                                val = tuple(val)
+                            new_d[val] = _decode_keys(v)
+                        except:
+                            new_d[k] = _decode_keys(v)
+                    else:
+                        new_d[k] = _decode_keys(v)
+                return new_d
+            if isinstance(obj, list):
+                return [_decode_keys(x) for x in obj]
+            return obj
+
+        return _decode_keys(data)
+
+    @model_options.setter
+    def model_options(self, value: dict) -> None:
+        self._call_rpc("set_model_options", value)
+
+    def apply_hooks(self, hooks: Any) -> Any:
+        return self._call_rpc("apply_hooks", hooks)
+
+    def prepare_state(self, timestep: Any) -> Any:
+        return self._call_rpc("prepare_state", timestep)
+
+    def restore_hook_patches(self) -> None:
+        self._call_rpc("restore_hook_patches")
+
+    def unpatch_hooks(self, whitelist_keys_set: Optional[Set[str]] = None) -> None:
+        self._call_rpc("unpatch_hooks", whitelist_keys_set)
+
+    def model_patches_to(self, device: Any) -> Any:
+        return self._call_rpc("model_patches_to", device)
+
+    def partially_load(
+        self, device: Any, extra_memory: Any, force_patch_weights: bool = False
+    ) -> Any:
+        return self._call_rpc(
+            "partially_load", device, extra_memory, force_patch_weights
+        )
+
+    def partially_unload(
+        self, device_to: Any, memory_to_free: int = 0, force_patch_weights: bool = False
+    ) -> int:
+        return self._call_rpc(
+            "partially_unload", device_to, memory_to_free, force_patch_weights
+        )
+
+    def load(
+        self,
+        device_to: Any = None,
+        lowvram_model_memory: int = 0,
+        force_patch_weights: bool = False,
+        full_load: bool = False,
+    ) -> None:
+        self._call_rpc(
+            "load", device_to, lowvram_model_memory, force_patch_weights, full_load
+        )
+
+    def patch_model(
+        self,
+        device_to: Any = None,
+        lowvram_model_memory: int = 0,
+        load_weights: bool = True,
+        force_patch_weights: bool = False,
+    ) -> Any:
+        self._call_rpc(
+            "patch_model",
+            device_to,
+            lowvram_model_memory,
+            load_weights,
+            force_patch_weights,
+        )
+        return self
+
+    def unpatch_model(
+        self, device_to: Any = None, unpatch_weights: bool = True
+    ) -> None:
+        self._call_rpc("unpatch_model", device_to, unpatch_weights)
+
+    def detach(self, unpatch_all: bool = True) -> Any:
+        self._call_rpc("detach", unpatch_all)
+        return self.model
+
+    def _cpu_tensor_bytes(self, obj: Any) -> int:
+        import torch
+
+        if isinstance(obj, torch.Tensor):
+            if obj.device.type == "cpu":
+                return obj.nbytes
+            return 0
+        if isinstance(obj, dict):
+            return sum(self._cpu_tensor_bytes(v) for v in obj.values())
+        if isinstance(obj, (list, tuple)):
+            return sum(self._cpu_tensor_bytes(v) for v in obj)
+        return 0
+
+    def _ensure_apply_model_headroom(self, required_bytes: int) -> bool:
+        if required_bytes <= 0:
+            return True
+
+        import torch
+        import comfy.model_management as model_management
+
+        target_raw = self.load_device
+        try:
+            if isinstance(target_raw, torch.device):
+                target = target_raw
+            elif isinstance(target_raw, str):
+                target = torch.device(target_raw)
+            elif isinstance(target_raw, int):
+                target = torch.device(f"cuda:{target_raw}")
+            else:
+                target = torch.device(target_raw)
+        except Exception:
+            return True
+
+        if target.type != "cuda":
+            return True
+
+        required = required_bytes + self._APPLY_MODEL_GUARD_PADDING_BYTES
+        if model_management.get_free_memory(target) >= required:
+            return True
+
+        model_management.cleanup_models_gc()
+        model_management.cleanup_models()
+        model_management.soft_empty_cache()
+
+        if model_management.get_free_memory(target) < required:
+            model_management.free_memory(required, target, for_dynamic=True)
+            model_management.soft_empty_cache()
+
+        if model_management.get_free_memory(target) < required:
+            # Escalate to non-dynamic unloading before dispatching CUDA transfer.
+            model_management.free_memory(required, target, for_dynamic=False)
+            model_management.soft_empty_cache()
+
+        if model_management.get_free_memory(target) < required:
+            model_management.load_models_gpu(
+                [self],
+                minimum_memory_required=required,
+            )
+
+        return model_management.get_free_memory(target) >= required
+
+    def apply_model(self, *args, **kwargs) -> Any:
+        import torch
+
+        def _preferred_device() -> Any:
+            for value in args:
+                if isinstance(value, torch.Tensor):
+                    return value.device
+            for value in kwargs.values():
+                if isinstance(value, torch.Tensor):
+                    return value.device
+            return None
+
+        def _move_result_to_device(obj: Any, device: Any) -> Any:
+            if device is None:
+                return obj
+            if isinstance(obj, torch.Tensor):
+                return obj.to(device) if obj.device != device else obj
+            if isinstance(obj, dict):
+                return {k: _move_result_to_device(v, device) for k, v in obj.items()}
+            if isinstance(obj, list):
+                return [_move_result_to_device(v, device) for v in obj]
+            if isinstance(obj, tuple):
+                return tuple(_move_result_to_device(v, device) for v in obj)
+            return obj
+
+        # DynamicVRAM models must keep load/offload decisions in host process.
+        # Child-side CUDA staging here can deadlock before first inference RPC.
+        if self.is_dynamic():
+            out = self._call_rpc("inner_model_apply_model", args, kwargs)
+            return _move_result_to_device(out, _preferred_device())
+
+        required_bytes = self._cpu_tensor_bytes(args) + self._cpu_tensor_bytes(kwargs)
+        self._ensure_apply_model_headroom(required_bytes)
+        target_device = self.load_device
+
+        def _to_cuda(obj: Any) -> Any:
+            if isinstance(obj, torch.Tensor) and obj.device.type == "cpu":
+                return obj.to(target_device)
+            if isinstance(obj, dict):
+                return {k: _to_cuda(v) for k, v in obj.items()}
+            if isinstance(obj, list):
+                return [_to_cuda(v) for v in obj]
+            if isinstance(obj, tuple):
+                return tuple(_to_cuda(v) for v in obj)
+            return obj
+
+        try:
+            args_cuda = _to_cuda(args)
+            kwargs_cuda = _to_cuda(kwargs)
+        except torch.OutOfMemoryError:
+            self._ensure_apply_model_headroom(required_bytes)
+            args_cuda = _to_cuda(args)
+            kwargs_cuda = _to_cuda(kwargs)
+
+        out = self._call_rpc("inner_model_apply_model", args_cuda, kwargs_cuda)
+        return _move_result_to_device(out, _preferred_device())
+
+    def model_state_dict(self, filter_prefix: Optional[str] = None) -> Any:
+        keys = self._call_rpc("model_state_dict", filter_prefix)
+        return dict.fromkeys(keys, None)
+
+    def add_patches(self, *args: Any, **kwargs: Any) -> Any:
+        res = self._call_rpc("add_patches", *args, **kwargs)
+        if isinstance(res, list):
+            return [tuple(x) if isinstance(x, list) else x for x in res]
+        return res
+
+    def get_key_patches(self, filter_prefix: Optional[str] = None) -> Any:
+        return self._call_rpc("get_key_patches", filter_prefix)
+
+    def patch_weight_to_device(self, key, device_to=None, inplace_update=False):
+        self._call_rpc("patch_weight_to_device", key, device_to, inplace_update)
+
+    def pin_weight_to_device(self, key):
+        self._call_rpc("pin_weight_to_device", key)
+
+    def unpin_weight(self, key):
+        self._call_rpc("unpin_weight", key)
+
+    def unpin_all_weights(self):
+        self._call_rpc("unpin_all_weights")
+
+    def calculate_weight(self, patches, weight, key, intermediate_dtype=None):
+        return self._call_rpc(
+            "calculate_weight", patches, weight, key, intermediate_dtype
+        )
+
+    def inject_model(self) -> None:
+        self._call_rpc("inject_model")
+
+    def eject_model(self) -> None:
+        self._call_rpc("eject_model")
+
+    def use_ejected(self, skip_and_inject_on_exit_only: bool = False) -> Any:
+        return AutoPatcherEjector(
+            self, skip_and_inject_on_exit_only=skip_and_inject_on_exit_only
+        )
+
+    @property
+    def is_injected(self) -> bool:
+        return self._call_rpc("get_is_injected")
+
+    @property
+    def skip_injection(self) -> bool:
+        return self._call_rpc("get_skip_injection")
+
+    @skip_injection.setter
+    def skip_injection(self, value: bool) -> None:
+        self._call_rpc("set_skip_injection", value)
+
+    def clean_hooks(self) -> None:
+        self._call_rpc("clean_hooks")
+
+    def pre_run(self) -> None:
+        self._call_rpc("pre_run")
+
+    def cleanup(self) -> None:
+        try:
+            self._call_rpc("cleanup")
+        except Exception:
+            logger.debug(
+                "ModelPatcherProxy cleanup RPC failed for %s",
+                self._instance_id,
+                exc_info=True,
+            )
+        finally:
+            super().cleanup()
+
+    @property
+    def model(self) -> _InnerModelProxy:
+        return _InnerModelProxy(self)
+
+    def __getattr__(self, name: str) -> Any:
+        _whitelisted_attrs = {
+            "hook_patches_backup",
+            "hook_backup",
+            "cached_hook_patches",
+            "current_hooks",
+            "forced_hooks",
+            "is_clip",
+            "patches_uuid",
+            "pinned",
+            "attachments",
+            "additional_models",
+            "injections",
+            "hook_patches",
+            "model_lowvram",
+            "model_loaded_weight_memory",
+            "backup",
+            "object_patches_backup",
+            "weight_wrapper_patches",
+            "weight_inplace_update",
+            "force_cast_weights",
+        }
+        if name in _whitelisted_attrs:
+            return self._call_rpc("get_patcher_attr", name)
+        raise AttributeError(
+            f"'{type(self).__name__}' object has no attribute '{name}'"
+        )
+
+    def load_lora(
+        self,
+        lora_path: str,
+        strength_model: float,
+        clip: Optional[Any] = None,
+        strength_clip: float = 1.0,
+    ) -> tuple:
+        clip_id = None
+        if clip is not None:
+            clip_id = getattr(clip, "_instance_id", getattr(clip, "_clip_id", None))
+        result = self._call_rpc(
+            "load_lora", lora_path, strength_model, clip_id, strength_clip
+        )
+        new_model = None
+        if result.get("model_id"):
+            new_model = self._spawn_related_proxy(result["model_id"])
+        new_clip = None
+        if result.get("clip_id"):
+            from comfy.isolation.clip_proxy import CLIPProxy
+
+            new_clip = CLIPProxy(result["clip_id"])
+        return (new_model, new_clip)
+
+    @property
+    def load_device(self) -> Any:
+        return self._call_rpc("get_load_device")
+
+    @property
+    def offload_device(self) -> Any:
+        return self._call_rpc("get_offload_device")
+
+    @property
+    def device(self) -> Any:
+        return self.load_device
+
+    def current_loaded_device(self) -> Any:
+        return self._call_rpc("current_loaded_device")
+
+    @property
+    def size(self) -> int:
+        return self._call_rpc("get_size")
+
+    def model_size(self) -> Any:
+        return self._call_rpc("model_size")
+
+    def loaded_size(self) -> Any:
+        return self._call_rpc("loaded_size")
+
+    def get_ram_usage(self) -> int:
+        return self._call_rpc("get_ram_usage")
+
+    def lowvram_patch_counter(self) -> int:
+        return self._call_rpc("lowvram_patch_counter")
+
+    def memory_required(self, input_shape: Any) -> Any:
+        return self._call_rpc("memory_required", input_shape)
+
+    def get_operation_state(self) -> Dict[str, Any]:
+        state = self._call_rpc("get_operation_state")
+        return state if isinstance(state, dict) else {}
+
+    def wait_for_idle(self, timeout_ms: int = 0) -> bool:
+        return bool(self._call_rpc("wait_for_idle", timeout_ms))
+
+    def is_dynamic(self) -> bool:
+        return bool(self._call_rpc("is_dynamic"))
+
+    def get_free_memory(self, device: Any) -> Any:
+        return self._call_rpc("get_free_memory", device)
+
+    def partially_unload_ram(self, ram_to_unload: int) -> Any:
+        return self._call_rpc("partially_unload_ram", ram_to_unload)
+
+    def model_dtype(self) -> Any:
+        res = self._call_rpc("model_dtype")
+        if isinstance(res, str) and res.startswith("torch."):
+            try:
+                import torch
+
+                attr = res.split(".")[-1]
+                if hasattr(torch, attr):
+                    return getattr(torch, attr)
+            except ImportError:
+                pass
+        return res
+
+    @property
+    def hook_mode(self) -> Any:
+        return self._call_rpc("get_hook_mode")
+
+    @hook_mode.setter
+    def hook_mode(self, value: Any) -> None:
+        self._call_rpc("set_hook_mode", value)
+
+    def set_model_sampler_cfg_function(
+        self, sampler_cfg_function: Any, disable_cfg1_optimization: bool = False
+    ) -> None:
+        self._call_rpc(
+            "set_model_sampler_cfg_function",
+            sampler_cfg_function,
+            disable_cfg1_optimization,
+        )
+
+    def set_model_sampler_post_cfg_function(
+        self, post_cfg_function: Any, disable_cfg1_optimization: bool = False
+    ) -> None:
+        self._call_rpc(
+            "set_model_sampler_post_cfg_function",
+            post_cfg_function,
+            disable_cfg1_optimization,
+        )
+
+    def set_model_sampler_pre_cfg_function(
+        self, pre_cfg_function: Any, disable_cfg1_optimization: bool = False
+    ) -> None:
+        self._call_rpc(
+            "set_model_sampler_pre_cfg_function",
+            pre_cfg_function,
+            disable_cfg1_optimization,
+        )
+
+    def set_model_sampler_calc_cond_batch_function(self, fn: Any) -> None:
+        self._call_rpc("set_model_sampler_calc_cond_batch_function", fn)
+
+    def set_model_unet_function_wrapper(self, unet_wrapper_function: Any) -> None:
+        self._call_rpc("set_model_unet_function_wrapper", unet_wrapper_function)
+
+    def set_model_denoise_mask_function(self, denoise_mask_function: Any) -> None:
+        self._call_rpc("set_model_denoise_mask_function", denoise_mask_function)
+
+    def set_model_patch(self, patch: Any, name: str) -> None:
+        self._call_rpc("set_model_patch", patch, name)
+
+    def set_model_patch_replace(
+        self,
+        patch: Any,
+        name: str,
+        block_name: str,
+        number: int,
+        transformer_index: Optional[int] = None,
+    ) -> None:
+        self._call_rpc(
+            "set_model_patch_replace",
+            patch,
+            name,
+            block_name,
+            number,
+            transformer_index,
+        )
+
+    def set_model_attn1_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "attn1_patch")
+
+    def set_model_attn2_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "attn2_patch")
+
+    def set_model_attn1_replace(
+        self,
+        patch: Any,
+        block_name: str,
+        number: int,
+        transformer_index: Optional[int] = None,
+    ) -> None:
+        self.set_model_patch_replace(
+            patch, "attn1", block_name, number, transformer_index
+        )
+
+    def set_model_attn2_replace(
+        self,
+        patch: Any,
+        block_name: str,
+        number: int,
+        transformer_index: Optional[int] = None,
+    ) -> None:
+        self.set_model_patch_replace(
+            patch, "attn2", block_name, number, transformer_index
+        )
+
+    def set_model_attn1_output_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "attn1_output_patch")
+
+    def set_model_attn2_output_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "attn2_output_patch")
+
+    def set_model_input_block_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "input_block_patch")
+
+    def set_model_input_block_patch_after_skip(self, patch: Any) -> None:
+        self.set_model_patch(patch, "input_block_patch_after_skip")
+
+    def set_model_output_block_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "output_block_patch")
+
+    def set_model_emb_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "emb_patch")
+
+    def set_model_forward_timestep_embed_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "forward_timestep_embed_patch")
+
+    def set_model_double_block_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "double_block")
+
+    def set_model_post_input_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "post_input")
+
+    def set_model_rope_options(
+        self,
+        scale_x=1.0,
+        shift_x=0.0,
+        scale_y=1.0,
+        shift_y=0.0,
+        scale_t=1.0,
+        shift_t=0.0,
+        **kwargs: Any,
+    ) -> None:
+        options = {
+            "scale_x": scale_x,
+            "shift_x": shift_x,
+            "scale_y": scale_y,
+            "shift_y": shift_y,
+            "scale_t": scale_t,
+            "shift_t": shift_t,
+        }
+        options.update(kwargs)
+        self._call_rpc("set_model_rope_options", options)
+
+    def set_model_compute_dtype(self, dtype: Any) -> None:
+        self._call_rpc("set_model_compute_dtype", dtype)
+
+    def add_object_patch(self, name: str, obj: Any) -> None:
+        self._call_rpc("add_object_patch", name, obj)
+
+    def add_weight_wrapper(self, name: str, function: Any) -> None:
+        self._call_rpc("add_weight_wrapper", name, function)
+
+    def add_wrapper_with_key(self, wrapper_type: Any, key: str, fn: Any) -> None:
+        self._call_rpc("add_wrapper_with_key", wrapper_type, key, fn)
+
+    def add_wrapper(self, wrapper_type: str, wrapper: Callable) -> None:
+        self.add_wrapper_with_key(wrapper_type, None, wrapper)
+
+    def remove_wrappers_with_key(self, wrapper_type: str, key: str) -> None:
+        self._call_rpc("remove_wrappers_with_key", wrapper_type, key)
+
+    @property
+    def wrappers(self) -> Any:
+        return self._call_rpc("get_wrappers")
+
+    def add_callback_with_key(self, call_type: str, key: str, callback: Any) -> None:
+        self._call_rpc("add_callback_with_key", call_type, key, callback)
+
+    def add_callback(self, call_type: str, callback: Any) -> None:
+        self.add_callback_with_key(call_type, None, callback)
+
+    def remove_callbacks_with_key(self, call_type: str, key: str) -> None:
+        self._call_rpc("remove_callbacks_with_key", call_type, key)
+
+    @property
+    def callbacks(self) -> Any:
+        return self._call_rpc("get_callbacks")
+
+    def set_attachments(self, key: str, attachment: Any) -> None:
+        self._call_rpc("set_attachments", key, attachment)
+
+    def get_attachment(self, key: str) -> Any:
+        return self._call_rpc("get_attachment", key)
+
+    def remove_attachments(self, key: str) -> None:
+        self._call_rpc("remove_attachments", key)
+
+    def set_injections(self, key: str, injections: Any) -> None:
+        self._call_rpc("set_injections", key, injections)
+
+    def get_injections(self, key: str) -> Any:
+        return self._call_rpc("get_injections", key)
+
+    def remove_injections(self, key: str) -> None:
+        self._call_rpc("remove_injections", key)
+
+    def set_additional_models(self, key: str, models: Any) -> None:
+        ids = [m._instance_id for m in models]
+        self._call_rpc("set_additional_models", key, ids)
+
+    def remove_additional_models(self, key: str) -> None:
+        self._call_rpc("remove_additional_models", key)
+
+    def get_nested_additional_models(self) -> Any:
+        return self._call_rpc("get_nested_additional_models")
+
+    def get_additional_models(self) -> List[ModelPatcherProxy]:
+        ids = self._call_rpc("get_additional_models")
+        return [self._spawn_related_proxy(mid) for mid in ids]
+
+    def model_patches_models(self) -> Any:
+        return self._call_rpc("model_patches_models")
+
+    @property
+    def parent(self) -> Any:
+        return self._call_rpc("get_parent")
+
+    def model_mmap_residency(self, free: bool = False) -> tuple:
+        result = self._call_rpc("model_mmap_residency", free)
+        if isinstance(result, list):
+            return tuple(result)
+        return result
+
+    def pinned_memory_size(self) -> int:
+        return self._call_rpc("pinned_memory_size")
+
+    def get_non_dynamic_delegate(self) -> ModelPatcherProxy:
+        new_id = self._call_rpc("get_non_dynamic_delegate")
+        return self._spawn_related_proxy(new_id)
+
+    def disable_model_cfg1_optimization(self) -> None:
+        self._call_rpc("disable_model_cfg1_optimization")
+
+    def set_model_noise_refiner_patch(self, patch: Any) -> None:
+        self.set_model_patch(patch, "noise_refiner")
+
+
+class _InnerModelProxy:
+    def __init__(self, parent: ModelPatcherProxy):
+        self._parent = parent
+        self._model_sampling = None
+
+    def __getattr__(self, name: str) -> Any:
+        if name.startswith("_"):
+            raise AttributeError(name)
+        if name == "model_config":
+            from types import SimpleNamespace
+
+            data = self._parent._call_rpc("get_inner_model_attr", name)
+            if isinstance(data, dict):
+                return SimpleNamespace(**data)
+            return data
+        if name in (
+            "latent_format",
+            "model_type",
+            "current_weight_patches_uuid",
+        ):
+            return self._parent._call_rpc("get_inner_model_attr", name)
+        if name == "load_device":
+            return self._parent._call_rpc("get_inner_model_attr", "load_device")
+        if name == "device":
+            return self._parent._call_rpc("get_inner_model_attr", "device")
+        if name == "current_patcher":
+            proxy = ModelPatcherProxy(
+                self._parent._instance_id,
+                self._parent._registry,
+                manage_lifecycle=False,
+            )
+            if getattr(self._parent, "_rpc_caller", None) is not None:
+                proxy._rpc_caller = self._parent._rpc_caller
+            return proxy
+        if name == "model_sampling":
+            if self._model_sampling is None:
+                self._model_sampling = self._parent._call_rpc(
+                    "get_model_object", "model_sampling"
+                )
+            return self._model_sampling
+        if name == "extra_conds_shapes":
+            return lambda *a, **k: self._parent._call_rpc(
+                "inner_model_extra_conds_shapes", a, k
+            )
+        if name == "extra_conds":
+            return lambda *a, **k: self._parent._call_rpc(
+                "inner_model_extra_conds", a, k
+            )
+        if name == "memory_required":
+            return lambda *a, **k: self._parent._call_rpc(
+                "inner_model_memory_required", a, k
+            )
+        if name == "apply_model":
+            # Delegate to parent's method to get the CPU->CUDA optimization
+            return self._parent.apply_model
+        if name == "process_latent_in":
+            return lambda *a, **k: self._parent._call_rpc("process_latent_in", a, k)
+        if name == "process_latent_out":
+            return lambda *a, **k: self._parent._call_rpc("process_latent_out", a, k)
+        if name == "scale_latent_inpaint":
+            return lambda *a, **k: self._parent._call_rpc("scale_latent_inpaint", a, k)
+        if name == "diffusion_model":
+            return self._parent._call_rpc("get_inner_model_attr", "diffusion_model")
+        if name == "state_dict":
+            return lambda: self._parent.model_state_dict()
+        raise AttributeError(f"'{name}' not supported on isolated InnerModel")

comfy/isolation/model_patcher_proxy_utils.py

@@ -0,0 +1,150 @@
+# pylint: disable=import-outside-toplevel,logging-fstring-interpolation,protected-access
+# Isolation utilities and serializers for ModelPatcherProxy
+from __future__ import annotations
+
+import logging
+import os
+from typing import Any
+
+from comfy.cli_args import args
+
+logger = logging.getLogger(__name__)
+
+
+def maybe_wrap_model_for_isolation(model_patcher: Any) -> Any:
+    from comfy.isolation.model_patcher_proxy_registry import ModelPatcherRegistry
+    from comfy.isolation.model_patcher_proxy import ModelPatcherProxy
+
+    is_child = os.environ.get("PYISOLATE_CHILD") == "1"
+    isolation_active = args.use_process_isolation or is_child
+
+    if not isolation_active:
+        return model_patcher
+    if is_child:
+        return model_patcher
+    if isinstance(model_patcher, ModelPatcherProxy):
+        return model_patcher
+
+    registry = ModelPatcherRegistry()
+    model_id = registry.register(model_patcher)
+    logger.debug(f"Isolated ModelPatcher: {model_id}")
+    return ModelPatcherProxy(model_id, registry, manage_lifecycle=True)
+
+
+def register_hooks_serializers(registry=None):
+    from pyisolate._internal.serialization_registry import SerializerRegistry
+    import comfy.hooks
+
+    if registry is None:
+        registry = SerializerRegistry.get_instance()
+
+    def serialize_enum(obj):
+        return {"__enum__": f"{type(obj).__name__}.{obj.name}"}
+
+    def deserialize_enum(data):
+        cls_name, val_name = data["__enum__"].split(".")
+        cls = getattr(comfy.hooks, cls_name)
+        return cls[val_name]
+
+    registry.register("EnumHookType", serialize_enum, deserialize_enum)
+    registry.register("EnumHookScope", serialize_enum, deserialize_enum)
+    registry.register("EnumHookMode", serialize_enum, deserialize_enum)
+    registry.register("EnumWeightTarget", serialize_enum, deserialize_enum)
+
+    def serialize_hook_group(obj):
+        return {"__type__": "HookGroup", "hooks": obj.hooks}
+
+    def deserialize_hook_group(data):
+        hg = comfy.hooks.HookGroup()
+        for h in data["hooks"]:
+            hg.add(h)
+        return hg
+
+    registry.register("HookGroup", serialize_hook_group, deserialize_hook_group)
+
+    def serialize_dict_state(obj):
+        d = obj.__dict__.copy()
+        d["__type__"] = type(obj).__name__
+        if "custom_should_register" in d:
+            del d["custom_should_register"]
+        return d
+
+    def deserialize_dict_state_generic(cls):
+        def _deserialize(data):
+            h = cls()
+            h.__dict__.update(data)
+            return h
+
+        return _deserialize
+
+    def deserialize_hook_keyframe(data):
+        h = comfy.hooks.HookKeyframe(strength=data.get("strength", 1.0))
+        h.__dict__.update(data)
+        return h
+
+    registry.register("HookKeyframe", serialize_dict_state, deserialize_hook_keyframe)
+
+    def deserialize_hook_keyframe_group(data):
+        h = comfy.hooks.HookKeyframeGroup()
+        h.__dict__.update(data)
+        return h
+
+    registry.register(
+        "HookKeyframeGroup", serialize_dict_state, deserialize_hook_keyframe_group
+    )
+
+    def deserialize_hook(data):
+        h = comfy.hooks.Hook()
+        h.__dict__.update(data)
+        return h
+
+    registry.register("Hook", serialize_dict_state, deserialize_hook)
+
+    def deserialize_weight_hook(data):
+        h = comfy.hooks.WeightHook()
+        h.__dict__.update(data)
+        return h
+
+    registry.register("WeightHook", serialize_dict_state, deserialize_weight_hook)
+
+    def serialize_set(obj):
+        return {"__set__": list(obj)}
+
+    def deserialize_set(data):
+        return set(data["__set__"])
+
+    registry.register("set", serialize_set, deserialize_set)
+
+    try:
+        from comfy.weight_adapter.lora import LoRAAdapter
+
+        def serialize_lora(obj):
+            return {"weights": {}, "loaded_keys": list(obj.loaded_keys)}
+
+        def deserialize_lora(data):
+            return LoRAAdapter(set(data["loaded_keys"]), data["weights"])
+
+        registry.register("LoRAAdapter", serialize_lora, deserialize_lora)
+    except Exception:
+        pass
+
+    try:
+        from comfy.hooks import _HookRef
+        import uuid
+
+        def serialize_hook_ref(obj):
+            return {
+                "__hook_ref__": True,
+                "id": getattr(obj, "_pyisolate_id", str(uuid.uuid4())),
+            }
+
+        def deserialize_hook_ref(data):
+            h = _HookRef()
+            h._pyisolate_id = data.get("id", str(uuid.uuid4()))
+            return h
+
+        registry.register("_HookRef", serialize_hook_ref, deserialize_hook_ref)
+    except ImportError:
+        pass
+    except Exception as e:
+        logger.warning(f"Failed to register _HookRef: {e}")

comfy/isolation/model_sampling_proxy.py

@@ -0,0 +1,360 @@
+# pylint: disable=import-outside-toplevel
+from __future__ import annotations
+
+import asyncio
+import logging
+import os
+import threading
+import time
+from typing import Any
+
+from comfy.isolation.proxies.base import (
+    BaseProxy,
+    BaseRegistry,
+    detach_if_grad,
+    get_thread_loop,
+    run_coro_in_new_loop,
+)
+
+logger = logging.getLogger(__name__)
+
+
+def _describe_value(obj: Any) -> str:
+    try:
+        import torch
+    except Exception:
+        torch = None
+    try:
+        if torch is not None and isinstance(obj, torch.Tensor):
+            return (
+                "Tensor(shape=%s,dtype=%s,device=%s,id=%s)"
+                % (tuple(obj.shape), obj.dtype, obj.device, id(obj))
+            )
+    except Exception:
+        pass
+    return "%s(id=%s)" % (type(obj).__name__, id(obj))
+
+
+def _prefer_device(*tensors: Any) -> Any:
+    try:
+        import torch
+    except Exception:
+        return None
+    for t in tensors:
+        if isinstance(t, torch.Tensor) and t.is_cuda:
+            return t.device
+    for t in tensors:
+        if isinstance(t, torch.Tensor):
+            return t.device
+    return None
+
+
+def _to_device(obj: Any, device: Any) -> Any:
+    try:
+        import torch
+    except Exception:
+        return obj
+    if device is None:
+        return obj
+    if isinstance(obj, torch.Tensor):
+        if obj.device != device:
+            return obj.to(device)
+        return obj
+    if isinstance(obj, (list, tuple)):
+        converted = [_to_device(x, device) for x in obj]
+        return type(obj)(converted) if isinstance(obj, tuple) else converted
+    if isinstance(obj, dict):
+        return {k: _to_device(v, device) for k, v in obj.items()}
+    return obj
+
+
+def _to_cpu_for_rpc(obj: Any) -> Any:
+    try:
+        import torch
+    except Exception:
+        return obj
+    if isinstance(obj, torch.Tensor):
+        t = obj.detach() if obj.requires_grad else obj
+        if t.is_cuda:
+            return t.to("cpu")
+        return t
+    if isinstance(obj, (list, tuple)):
+        converted = [_to_cpu_for_rpc(x) for x in obj]
+        return type(obj)(converted) if isinstance(obj, tuple) else converted
+    if isinstance(obj, dict):
+        return {k: _to_cpu_for_rpc(v) for k, v in obj.items()}
+    return obj
+
+
+class ModelSamplingRegistry(BaseRegistry[Any]):
+    _type_prefix = "modelsampling"
+
+    async def calculate_input(self, instance_id: str, sigma: Any, noise: Any) -> Any:
+        sampling = self._get_instance(instance_id)
+        return detach_if_grad(sampling.calculate_input(sigma, noise))
+
+    async def calculate_denoised(
+        self, instance_id: str, sigma: Any, model_output: Any, model_input: Any
+    ) -> Any:
+        sampling = self._get_instance(instance_id)
+        return detach_if_grad(
+            sampling.calculate_denoised(sigma, model_output, model_input)
+        )
+
+    async def noise_scaling(
+        self,
+        instance_id: str,
+        sigma: Any,
+        noise: Any,
+        latent_image: Any,
+        max_denoise: bool = False,
+    ) -> Any:
+        sampling = self._get_instance(instance_id)
+        return detach_if_grad(
+            sampling.noise_scaling(sigma, noise, latent_image, max_denoise=max_denoise)
+        )
+
+    async def inverse_noise_scaling(
+        self, instance_id: str, sigma: Any, latent: Any
+    ) -> Any:
+        sampling = self._get_instance(instance_id)
+        return detach_if_grad(sampling.inverse_noise_scaling(sigma, latent))
+
+    async def timestep(self, instance_id: str, sigma: Any) -> Any:
+        sampling = self._get_instance(instance_id)
+        return sampling.timestep(sigma)
+
+    async def sigma(self, instance_id: str, timestep: Any) -> Any:
+        sampling = self._get_instance(instance_id)
+        return sampling.sigma(timestep)
+
+    async def percent_to_sigma(self, instance_id: str, percent: float) -> Any:
+        sampling = self._get_instance(instance_id)
+        return sampling.percent_to_sigma(percent)
+
+    async def get_sigma_min(self, instance_id: str) -> Any:
+        sampling = self._get_instance(instance_id)
+        return detach_if_grad(sampling.sigma_min)
+
+    async def get_sigma_max(self, instance_id: str) -> Any:
+        sampling = self._get_instance(instance_id)
+        return detach_if_grad(sampling.sigma_max)
+
+    async def get_sigma_data(self, instance_id: str) -> Any:
+        sampling = self._get_instance(instance_id)
+        return detach_if_grad(sampling.sigma_data)
+
+    async def get_sigmas(self, instance_id: str) -> Any:
+        sampling = self._get_instance(instance_id)
+        return detach_if_grad(sampling.sigmas)
+
+    async def set_sigmas(self, instance_id: str, sigmas: Any) -> None:
+        sampling = self._get_instance(instance_id)
+        sampling.set_sigmas(sigmas)
+
+
+class ModelSamplingProxy(BaseProxy[ModelSamplingRegistry]):
+    _registry_class = ModelSamplingRegistry
+    __module__ = "comfy.isolation.model_sampling_proxy"
+
+    def _get_rpc(self) -> Any:
+        if self._rpc_caller is None:
+            from pyisolate._internal.rpc_protocol import get_child_rpc_instance
+
+            rpc = get_child_rpc_instance()
+            if rpc is not None:
+                self._rpc_caller = rpc.create_caller(
+                    ModelSamplingRegistry, ModelSamplingRegistry.get_remote_id()
+                )
+            else:
+                registry = ModelSamplingRegistry()
+
+                class _LocalCaller:
+                    def calculate_input(
+                        self, instance_id: str, sigma: Any, noise: Any
+                    ) -> Any:
+                        return registry.calculate_input(instance_id, sigma, noise)
+
+                    def calculate_denoised(
+                        self,
+                        instance_id: str,
+                        sigma: Any,
+                        model_output: Any,
+                        model_input: Any,
+                    ) -> Any:
+                        return registry.calculate_denoised(
+                            instance_id, sigma, model_output, model_input
+                        )
+
+                    def noise_scaling(
+                        self,
+                        instance_id: str,
+                        sigma: Any,
+                        noise: Any,
+                        latent_image: Any,
+                        max_denoise: bool = False,
+                    ) -> Any:
+                        return registry.noise_scaling(
+                            instance_id, sigma, noise, latent_image, max_denoise
+                        )
+
+                    def inverse_noise_scaling(
+                        self, instance_id: str, sigma: Any, latent: Any
+                    ) -> Any:
+                        return registry.inverse_noise_scaling(
+                            instance_id, sigma, latent
+                        )
+
+                    def timestep(self, instance_id: str, sigma: Any) -> Any:
+                        return registry.timestep(instance_id, sigma)
+
+                    def sigma(self, instance_id: str, timestep: Any) -> Any:
+                        return registry.sigma(instance_id, timestep)
+
+                    def percent_to_sigma(self, instance_id: str, percent: float) -> Any:
+                        return registry.percent_to_sigma(instance_id, percent)
+
+                    def get_sigma_min(self, instance_id: str) -> Any:
+                        return registry.get_sigma_min(instance_id)
+
+                    def get_sigma_max(self, instance_id: str) -> Any:
+                        return registry.get_sigma_max(instance_id)
+
+                    def get_sigma_data(self, instance_id: str) -> Any:
+                        return registry.get_sigma_data(instance_id)
+
+                    def get_sigmas(self, instance_id: str) -> Any:
+                        return registry.get_sigmas(instance_id)
+
+                    def set_sigmas(self, instance_id: str, sigmas: Any) -> None:
+                        return registry.set_sigmas(instance_id, sigmas)
+
+                self._rpc_caller = _LocalCaller()
+        return self._rpc_caller
+
+    def _call(self, method_name: str, *args: Any) -> Any:
+        rpc = self._get_rpc()
+        method = getattr(rpc, method_name)
+        result = method(self._instance_id, *args)
+        timeout_ms = self._rpc_timeout_ms()
+        start_epoch = time.time()
+        start_perf = time.perf_counter()
+        thread_id = threading.get_ident()
+        call_id = "%s:%s:%s:%.6f" % (
+            self._instance_id,
+            method_name,
+            thread_id,
+            start_perf,
+        )
+        logger.debug(
+            "ISO:modelsampling_rpc_start method=%s instance_id=%s call_id=%s start_ts=%.6f thread=%s timeout_ms=%s",
+            method_name,
+            self._instance_id,
+            call_id,
+            start_epoch,
+            thread_id,
+            timeout_ms,
+        )
+        if asyncio.iscoroutine(result):
+            result = asyncio.wait_for(result, timeout=timeout_ms / 1000.0)
+            try:
+                asyncio.get_running_loop()
+                out = run_coro_in_new_loop(result)
+            except RuntimeError:
+                loop = get_thread_loop()
+                out = loop.run_until_complete(result)
+        else:
+            out = result
+        logger.debug(
+            "ISO:modelsampling_rpc_after_await method=%s instance_id=%s call_id=%s out=%s",
+            method_name,
+            self._instance_id,
+            call_id,
+            _describe_value(out),
+        )
+        elapsed_ms = (time.perf_counter() - start_perf) * 1000.0
+        logger.debug(
+            "ISO:modelsampling_rpc_end method=%s instance_id=%s call_id=%s elapsed_ms=%.3f thread=%s",
+            method_name,
+            self._instance_id,
+            call_id,
+            elapsed_ms,
+            thread_id,
+        )
+        logger.debug(
+            "ISO:modelsampling_rpc_return method=%s instance_id=%s call_id=%s",
+            method_name,
+            self._instance_id,
+            call_id,
+        )
+        return out
+
+    @staticmethod
+    def _rpc_timeout_ms() -> int:
+        raw = os.environ.get(
+            "COMFY_ISOLATION_MODEL_SAMPLING_RPC_TIMEOUT_MS",
+            os.environ.get("COMFY_ISOLATION_LOAD_RPC_TIMEOUT_MS", "30000"),
+        )
+        try:
+            timeout_ms = int(raw)
+        except ValueError:
+            timeout_ms = 30000
+        return max(1, timeout_ms)
+
+    @property
+    def sigma_min(self) -> Any:
+        return self._call("get_sigma_min")
+
+    @property
+    def sigma_max(self) -> Any:
+        return self._call("get_sigma_max")
+
+    @property
+    def sigma_data(self) -> Any:
+        return self._call("get_sigma_data")
+
+    @property
+    def sigmas(self) -> Any:
+        return self._call("get_sigmas")
+
+    def calculate_input(self, sigma: Any, noise: Any) -> Any:
+        return self._call("calculate_input", sigma, noise)
+
+    def calculate_denoised(
+        self, sigma: Any, model_output: Any, model_input: Any
+    ) -> Any:
+        return self._call("calculate_denoised", sigma, model_output, model_input)
+
+    def noise_scaling(
+        self, sigma: Any, noise: Any, latent_image: Any, max_denoise: bool = False
+    ) -> Any:
+        preferred_device = _prefer_device(noise, latent_image)
+        out = self._call(
+            "noise_scaling",
+            _to_cpu_for_rpc(sigma),
+            _to_cpu_for_rpc(noise),
+            _to_cpu_for_rpc(latent_image),
+            max_denoise,
+        )
+        return _to_device(out, preferred_device)
+
+    def inverse_noise_scaling(self, sigma: Any, latent: Any) -> Any:
+        preferred_device = _prefer_device(latent)
+        out = self._call(
+            "inverse_noise_scaling",
+            _to_cpu_for_rpc(sigma),
+            _to_cpu_for_rpc(latent),
+        )
+        return _to_device(out, preferred_device)
+
+    def timestep(self, sigma: Any) -> Any:
+        return self._call("timestep", sigma)
+
+    def sigma(self, timestep: Any) -> Any:
+        return self._call("sigma", timestep)
+
+    def percent_to_sigma(self, percent: float) -> Any:
+        return self._call("percent_to_sigma", percent)
+
+    def set_sigmas(self, sigmas: Any) -> None:
+        return self._call("set_sigmas", sigmas)

comfy/isolation/proxies/__init__.py

@@ -0,0 +1,17 @@
+from .base import (
+    IS_CHILD_PROCESS,
+    BaseProxy,
+    BaseRegistry,
+    detach_if_grad,
+    get_thread_loop,
+    run_coro_in_new_loop,
+)
+
+__all__ = [
+    "IS_CHILD_PROCESS",
+    "BaseRegistry",
+    "BaseProxy",
+    "get_thread_loop",
+    "run_coro_in_new_loop",
+    "detach_if_grad",
+]

comfy/isolation/proxies/base.py

@@ -0,0 +1,301 @@
+# pylint: disable=global-statement,import-outside-toplevel,protected-access
+from __future__ import annotations
+
+import asyncio
+import concurrent.futures
+import logging
+import os
+import threading
+import time
+import weakref
+from typing import Any, Callable, Dict, Generic, Optional, TypeVar
+
+try:
+    from pyisolate import ProxiedSingleton
+except ImportError:
+
+    class ProxiedSingleton:  # type: ignore[no-redef]
+        pass
+
+
+logger = logging.getLogger(__name__)
+
+IS_CHILD_PROCESS = os.environ.get("PYISOLATE_CHILD") == "1"
+_thread_local = threading.local()
+T = TypeVar("T")
+
+
+def get_thread_loop() -> asyncio.AbstractEventLoop:
+    loop = getattr(_thread_local, "loop", None)
+    if loop is None or loop.is_closed():
+        loop = asyncio.new_event_loop()
+        _thread_local.loop = loop
+    return loop
+
+
+def run_coro_in_new_loop(coro: Any) -> Any:
+    result_box: Dict[str, Any] = {}
+    exc_box: Dict[str, BaseException] = {}
+
+    def runner() -> None:
+        loop = asyncio.new_event_loop()
+        asyncio.set_event_loop(loop)
+        try:
+            result_box["value"] = loop.run_until_complete(coro)
+        except Exception as exc:  # noqa: BLE001
+            exc_box["exc"] = exc
+        finally:
+            loop.close()
+
+    t = threading.Thread(target=runner, daemon=True)
+    t.start()
+    t.join()
+    if "exc" in exc_box:
+        raise exc_box["exc"]
+    return result_box.get("value")
+
+
+def detach_if_grad(obj: Any) -> Any:
+    try:
+        import torch
+    except Exception:
+        return obj
+
+    if isinstance(obj, torch.Tensor):
+        return obj.detach() if obj.requires_grad else obj
+    if isinstance(obj, (list, tuple)):
+        return type(obj)(detach_if_grad(x) for x in obj)
+    if isinstance(obj, dict):
+        return {k: detach_if_grad(v) for k, v in obj.items()}
+    return obj
+
+
+class BaseRegistry(ProxiedSingleton, Generic[T]):
+    _type_prefix: str = "base"
+
+    def __init__(self) -> None:
+        if hasattr(ProxiedSingleton, "__init__") and ProxiedSingleton is not object:
+            super().__init__()
+        self._registry: Dict[str, T] = {}
+        self._id_map: Dict[int, str] = {}
+        self._counter = 0
+        self._lock = threading.Lock()
+
+    def register(self, instance: T) -> str:
+        with self._lock:
+            obj_id = id(instance)
+            if obj_id in self._id_map:
+                return self._id_map[obj_id]
+            instance_id = f"{self._type_prefix}_{self._counter}"
+            self._counter += 1
+            self._registry[instance_id] = instance
+            self._id_map[obj_id] = instance_id
+        return instance_id
+
+    def unregister_sync(self, instance_id: str) -> None:
+        with self._lock:
+            instance = self._registry.pop(instance_id, None)
+            if instance:
+                self._id_map.pop(id(instance), None)
+
+    def _get_instance(self, instance_id: str) -> T:
+        if IS_CHILD_PROCESS:
+            raise RuntimeError(
+                f"[{self.__class__.__name__}] _get_instance called in child"
+            )
+        with self._lock:
+            instance = self._registry.get(instance_id)
+        if instance is None:
+            raise ValueError(f"{instance_id} not found")
+        return instance
+
+
+_GLOBAL_LOOP: Optional[asyncio.AbstractEventLoop] = None
+
+
+def set_global_loop(loop: asyncio.AbstractEventLoop) -> None:
+    global _GLOBAL_LOOP
+    _GLOBAL_LOOP = loop
+
+
+def run_sync_rpc_coro(coro: Any, timeout_ms: Optional[int] = None) -> Any:
+    if timeout_ms is not None:
+        coro = asyncio.wait_for(coro, timeout=timeout_ms / 1000.0)
+
+    try:
+        if _GLOBAL_LOOP is not None and _GLOBAL_LOOP.is_running():
+            try:
+                curr_loop = asyncio.get_running_loop()
+                if curr_loop is _GLOBAL_LOOP:
+                    pass
+            except RuntimeError:
+                future = asyncio.run_coroutine_threadsafe(coro, _GLOBAL_LOOP)
+                return future.result(
+                    timeout=(timeout_ms / 1000.0) if timeout_ms is not None else None
+                )
+
+        try:
+            asyncio.get_running_loop()
+            return run_coro_in_new_loop(coro)
+        except RuntimeError:
+            loop = get_thread_loop()
+            return loop.run_until_complete(coro)
+    except asyncio.TimeoutError as exc:
+        raise TimeoutError(f"Isolation RPC timeout (timeout_ms={timeout_ms})") from exc
+    except concurrent.futures.TimeoutError as exc:
+        raise TimeoutError(f"Isolation RPC timeout (timeout_ms={timeout_ms})") from exc
+
+
+def call_singleton_rpc(
+    caller: Any,
+    method_name: str,
+    *args: Any,
+    timeout_ms: Optional[int] = None,
+    **kwargs: Any,
+) -> Any:
+    if caller is None:
+        raise RuntimeError(f"No RPC caller available for {method_name}")
+    method = getattr(caller, method_name)
+    return run_sync_rpc_coro(method(*args, **kwargs), timeout_ms=timeout_ms)
+
+
+class BaseProxy(Generic[T]):
+    _registry_class: type = BaseRegistry  # type: ignore[type-arg]
+    __module__: str = "comfy.isolation.proxies.base"
+    _TIMEOUT_RPC_METHODS = frozenset(
+        {
+            "partially_load",
+            "partially_unload",
+            "load",
+            "patch_model",
+            "unpatch_model",
+            "inner_model_apply_model",
+            "memory_required",
+            "model_dtype",
+            "inner_model_memory_required",
+            "inner_model_extra_conds_shapes",
+            "inner_model_extra_conds",
+            "process_latent_in",
+            "process_latent_out",
+            "scale_latent_inpaint",
+        }
+    )
+
+    def __init__(
+        self,
+        instance_id: str,
+        registry: Optional[Any] = None,
+        manage_lifecycle: bool = False,
+    ) -> None:
+        self._instance_id = instance_id
+        self._rpc_caller: Optional[Any] = None
+        self._registry = registry if registry is not None else self._registry_class()
+        self._manage_lifecycle = manage_lifecycle
+        self._cleaned_up = False
+        if manage_lifecycle and not IS_CHILD_PROCESS:
+            self._finalizer = weakref.finalize(
+                self, self._registry.unregister_sync, instance_id
+            )
+
+    def _get_rpc(self) -> Any:
+        if self._rpc_caller is None:
+            from pyisolate._internal.rpc_protocol import get_child_rpc_instance
+
+            rpc = get_child_rpc_instance()
+            if rpc is None:
+                raise RuntimeError(f"[{self.__class__.__name__}] No RPC in child")
+            self._rpc_caller = rpc.create_caller(
+                self._registry_class, self._registry_class.get_remote_id()
+            )
+        return self._rpc_caller
+
+    def _rpc_timeout_ms_for_method(self, method_name: str) -> Optional[int]:
+        if method_name not in self._TIMEOUT_RPC_METHODS:
+            return None
+        try:
+            timeout_ms = int(
+                os.environ.get("COMFY_ISOLATION_LOAD_RPC_TIMEOUT_MS", "120000")
+            )
+        except ValueError:
+            timeout_ms = 120000
+        return max(1, timeout_ms)
+
+    def _call_rpc(self, method_name: str, *args: Any, **kwargs: Any) -> Any:
+        rpc = self._get_rpc()
+        method = getattr(rpc, method_name)
+        timeout_ms = self._rpc_timeout_ms_for_method(method_name)
+        coro = method(self._instance_id, *args, **kwargs)
+        if timeout_ms is not None:
+            coro = asyncio.wait_for(coro, timeout=timeout_ms / 1000.0)
+
+        start_epoch = time.time()
+        start_perf = time.perf_counter()
+        thread_id = threading.get_ident()
+        try:
+            running_loop = asyncio.get_running_loop()
+            loop_id: Optional[int] = id(running_loop)
+        except RuntimeError:
+            loop_id = None
+        logger.debug(
+            "ISO:rpc_start proxy=%s method=%s instance_id=%s start_ts=%.6f "
+            "thread=%s loop=%s timeout_ms=%s",
+            self.__class__.__name__,
+            method_name,
+            self._instance_id,
+            start_epoch,
+            thread_id,
+            loop_id,
+            timeout_ms,
+        )
+
+        try:
+            return run_sync_rpc_coro(coro, timeout_ms=timeout_ms)
+        except TimeoutError as exc:
+            raise TimeoutError(
+                f"Isolation RPC timeout in {self.__class__.__name__}.{method_name} "
+                f"(instance_id={self._instance_id}, timeout_ms={timeout_ms})"
+            ) from exc
+        finally:
+            end_epoch = time.time()
+            elapsed_ms = (time.perf_counter() - start_perf) * 1000.0
+            logger.debug(
+                "ISO:rpc_end proxy=%s method=%s instance_id=%s end_ts=%.6f "
+                "elapsed_ms=%.3f thread=%s loop=%s",
+                self.__class__.__name__,
+                method_name,
+                self._instance_id,
+                end_epoch,
+                elapsed_ms,
+                thread_id,
+                loop_id,
+            )
+
+    def __getstate__(self) -> Dict[str, Any]:
+        return {"_instance_id": self._instance_id}
+
+    def __setstate__(self, state: Dict[str, Any]) -> None:
+        self._instance_id = state["_instance_id"]
+        self._rpc_caller = None
+        self._registry = self._registry_class()
+        self._manage_lifecycle = False
+        self._cleaned_up = False
+
+    def cleanup(self) -> None:
+        if self._cleaned_up or IS_CHILD_PROCESS:
+            return
+        self._cleaned_up = True
+        finalizer = getattr(self, "_finalizer", None)
+        if finalizer is not None:
+            finalizer.detach()
+        self._registry.unregister_sync(self._instance_id)
+
+    def __repr__(self) -> str:
+        return f"<{self.__class__.__name__} {self._instance_id}>"
+
+
+def create_rpc_method(method_name: str) -> Callable[..., Any]:
+    def method(self: BaseProxy[Any], *args: Any, **kwargs: Any) -> Any:
+        return self._call_rpc(method_name, *args, **kwargs)
+
+    method.__name__ = method_name
+    return method

comfy/isolation/proxies/folder_paths_proxy.py

@@ -0,0 +1,206 @@
+from __future__ import annotations
+import logging
+import os
+
+from typing import Any, Dict, Optional
+
+from pyisolate import ProxiedSingleton
+
+from .base import call_singleton_rpc
+
+_fp_logger = logging.getLogger(__name__)
+
+
+def _folder_paths():
+    import folder_paths
+
+    return folder_paths
+
+
+def _is_child_process() -> bool:
+    return os.environ.get("PYISOLATE_CHILD") == "1"
+
+
+def _serialize_folder_names_and_paths(data: dict[str, tuple[list[str], set[str]]]) -> dict[str, dict[str, list[str]]]:
+    return {
+        key: {"paths": list(paths), "extensions": sorted(list(extensions))}
+        for key, (paths, extensions) in data.items()
+    }
+
+
+def _deserialize_folder_names_and_paths(data: dict[str, dict[str, list[str]]]) -> dict[str, tuple[list[str], set[str]]]:
+    return {
+        key: (list(value.get("paths", [])), set(value.get("extensions", [])))
+        for key, value in data.items()
+    }
+
+
+class FolderPathsProxy(ProxiedSingleton):
+    """
+    Dynamic proxy for folder_paths.
+    Uses __getattr__ for most lookups, with explicit handling for
+    mutable collections to ensure efficient by-value transfer.
+    """
+
+    _rpc: Optional[Any] = None
+
+    @classmethod
+    def set_rpc(cls, rpc: Any) -> None:
+        cls._rpc = rpc.create_caller(cls, cls.get_remote_id())
+
+    @classmethod
+    def clear_rpc(cls) -> None:
+        cls._rpc = None
+
+    @classmethod
+    def _get_caller(cls) -> Any:
+        if cls._rpc is None:
+            raise RuntimeError("FolderPathsProxy RPC caller is not configured")
+        return cls._rpc
+
+    def __getattr__(self, name):
+        if _is_child_process():
+            property_rpc = {
+                "models_dir": "rpc_get_models_dir",
+                "folder_names_and_paths": "rpc_get_folder_names_and_paths",
+                "extension_mimetypes_cache": "rpc_get_extension_mimetypes_cache",
+                "filename_list_cache": "rpc_get_filename_list_cache",
+            }
+            rpc_name = property_rpc.get(name)
+            if rpc_name is not None:
+                return call_singleton_rpc(self._get_caller(), rpc_name)
+            raise AttributeError(name)
+        return getattr(_folder_paths(), name)
+
+    @property
+    def folder_names_and_paths(self) -> Dict:
+        if _is_child_process():
+            payload = call_singleton_rpc(self._get_caller(), "rpc_get_folder_names_and_paths")
+            return _deserialize_folder_names_and_paths(payload)
+        return _folder_paths().folder_names_and_paths
+
+    @property
+    def extension_mimetypes_cache(self) -> Dict:
+        if _is_child_process():
+            return dict(call_singleton_rpc(self._get_caller(), "rpc_get_extension_mimetypes_cache"))
+        return dict(_folder_paths().extension_mimetypes_cache)
+
+    @property
+    def filename_list_cache(self) -> Dict:
+        if _is_child_process():
+            return dict(call_singleton_rpc(self._get_caller(), "rpc_get_filename_list_cache"))
+        return dict(_folder_paths().filename_list_cache)
+
+    @property
+    def models_dir(self) -> str:
+        if _is_child_process():
+            return str(call_singleton_rpc(self._get_caller(), "rpc_get_models_dir"))
+        return _folder_paths().models_dir
+
+    def get_temp_directory(self) -> str:
+        if _is_child_process():
+            return call_singleton_rpc(self._get_caller(), "rpc_get_temp_directory")
+        return _folder_paths().get_temp_directory()
+
+    def get_input_directory(self) -> str:
+        if _is_child_process():
+            return call_singleton_rpc(self._get_caller(), "rpc_get_input_directory")
+        return _folder_paths().get_input_directory()
+
+    def get_output_directory(self) -> str:
+        if _is_child_process():
+            return call_singleton_rpc(self._get_caller(), "rpc_get_output_directory")
+        return _folder_paths().get_output_directory()
+
+    def get_user_directory(self) -> str:
+        if _is_child_process():
+            return call_singleton_rpc(self._get_caller(), "rpc_get_user_directory")
+        return _folder_paths().get_user_directory()
+
+    def get_annotated_filepath(self, name: str, default_dir: str | None = None) -> str:
+        if _is_child_process():
+            return call_singleton_rpc(
+                self._get_caller(), "rpc_get_annotated_filepath", name, default_dir
+            )
+        return _folder_paths().get_annotated_filepath(name, default_dir)
+
+    def exists_annotated_filepath(self, name: str) -> bool:
+        if _is_child_process():
+            return bool(
+                call_singleton_rpc(self._get_caller(), "rpc_exists_annotated_filepath", name)
+            )
+        return bool(_folder_paths().exists_annotated_filepath(name))
+
+    def add_model_folder_path(
+        self, folder_name: str, full_folder_path: str, is_default: bool = False
+    ) -> None:
+        if _is_child_process():
+            call_singleton_rpc(
+                self._get_caller(),
+                "rpc_add_model_folder_path",
+                folder_name,
+                full_folder_path,
+                is_default,
+            )
+            return None
+        _folder_paths().add_model_folder_path(folder_name, full_folder_path, is_default)
+        return None
+
+    def get_folder_paths(self, folder_name: str) -> list[str]:
+        if _is_child_process():
+            return list(call_singleton_rpc(self._get_caller(), "rpc_get_folder_paths", folder_name))
+        return list(_folder_paths().get_folder_paths(folder_name))
+
+    def get_filename_list(self, folder_name: str) -> list[str]:
+        if _is_child_process():
+            return list(call_singleton_rpc(self._get_caller(), "rpc_get_filename_list", folder_name))
+        return list(_folder_paths().get_filename_list(folder_name))
+
+    def get_full_path(self, folder_name: str, filename: str) -> str | None:
+        if _is_child_process():
+            return call_singleton_rpc(self._get_caller(), "rpc_get_full_path", folder_name, filename)
+        return _folder_paths().get_full_path(folder_name, filename)
+
+    async def rpc_get_models_dir(self) -> str:
+        return _folder_paths().models_dir
+
+    async def rpc_get_folder_names_and_paths(self) -> dict[str, dict[str, list[str]]]:
+        return _serialize_folder_names_and_paths(_folder_paths().folder_names_and_paths)
+
+    async def rpc_get_extension_mimetypes_cache(self) -> dict[str, Any]:
+        return dict(_folder_paths().extension_mimetypes_cache)
+
+    async def rpc_get_filename_list_cache(self) -> dict[str, Any]:
+        return dict(_folder_paths().filename_list_cache)
+
+    async def rpc_get_temp_directory(self) -> str:
+        return _folder_paths().get_temp_directory()
+
+    async def rpc_get_input_directory(self) -> str:
+        return _folder_paths().get_input_directory()
+
+    async def rpc_get_output_directory(self) -> str:
+        return _folder_paths().get_output_directory()
+
+    async def rpc_get_user_directory(self) -> str:
+        return _folder_paths().get_user_directory()
+
+    async def rpc_get_annotated_filepath(self, name: str, default_dir: str | None = None) -> str:
+        return _folder_paths().get_annotated_filepath(name, default_dir)
+
+    async def rpc_exists_annotated_filepath(self, name: str) -> bool:
+        return _folder_paths().exists_annotated_filepath(name)
+
+    async def rpc_add_model_folder_path(
+        self, folder_name: str, full_folder_path: str, is_default: bool = False
+    ) -> None:
+        _folder_paths().add_model_folder_path(folder_name, full_folder_path, is_default)
+
+    async def rpc_get_folder_paths(self, folder_name: str) -> list[str]:
+        return _folder_paths().get_folder_paths(folder_name)
+
+    async def rpc_get_filename_list(self, folder_name: str) -> list[str]:
+        return _folder_paths().get_filename_list(folder_name)
+
+    async def rpc_get_full_path(self, folder_name: str, filename: str) -> str | None:
+        return _folder_paths().get_full_path(folder_name, filename)

comfy/isolation/proxies/helper_proxies.py

@@ -0,0 +1,158 @@
+from __future__ import annotations
+
+import os
+from typing import Any, Dict, Optional
+
+from pyisolate import ProxiedSingleton
+
+from .base import call_singleton_rpc
+
+
+class AnyTypeProxy(str):
+    """Replacement for custom AnyType objects used by some nodes."""
+
+    def __new__(cls, value: str = "*"):
+        return super().__new__(cls, value)
+
+    def __ne__(self, other):  # type: ignore[override]
+        return False
+
+
+class FlexibleOptionalInputProxy(dict):
+    """Replacement for FlexibleOptionalInputType to allow dynamic inputs."""
+
+    def __init__(self, flex_type, data: Optional[Dict[str, object]] = None):
+        super().__init__()
+        self.type = flex_type
+        if data:
+            self.update(data)
+
+    def __getitem__(self, key):  # type: ignore[override]
+        return (self.type,)
+
+    def __contains__(self, key):  # type: ignore[override]
+        return True
+
+
+class ByPassTypeTupleProxy(tuple):
+    """Replacement for ByPassTypeTuple to mirror wildcard fallback behavior."""
+
+    def __new__(cls, values):
+        return super().__new__(cls, values)
+
+    def __getitem__(self, index):  # type: ignore[override]
+        if index >= len(self):
+            return AnyTypeProxy("*")
+        return super().__getitem__(index)
+
+
+def _restore_special_value(value: Any) -> Any:
+    if isinstance(value, dict):
+        if value.get("__pyisolate_any_type__"):
+            return AnyTypeProxy(value.get("value", "*"))
+        if value.get("__pyisolate_flexible_optional__"):
+            flex_type = _restore_special_value(value.get("type"))
+            data_raw = value.get("data")
+            data = (
+                {k: _restore_special_value(v) for k, v in data_raw.items()}
+                if isinstance(data_raw, dict)
+                else {}
+            )
+            return FlexibleOptionalInputProxy(flex_type, data)
+        if value.get("__pyisolate_tuple__") is not None:
+            return tuple(
+                _restore_special_value(v) for v in value["__pyisolate_tuple__"]
+            )
+        if value.get("__pyisolate_bypass_tuple__") is not None:
+            return ByPassTypeTupleProxy(
+                tuple(
+                    _restore_special_value(v)
+                    for v in value["__pyisolate_bypass_tuple__"]
+                )
+            )
+        return {k: _restore_special_value(v) for k, v in value.items()}
+    if isinstance(value, list):
+        return [_restore_special_value(v) for v in value]
+    return value
+
+
+def _serialize_special_value(value: Any) -> Any:
+    if isinstance(value, AnyTypeProxy):
+        return {"__pyisolate_any_type__": True, "value": str(value)}
+    if isinstance(value, FlexibleOptionalInputProxy):
+        return {
+            "__pyisolate_flexible_optional__": True,
+            "type": _serialize_special_value(value.type),
+            "data": {k: _serialize_special_value(v) for k, v in value.items()},
+        }
+    if isinstance(value, ByPassTypeTupleProxy):
+        return {
+            "__pyisolate_bypass_tuple__": [_serialize_special_value(v) for v in value]
+        }
+    if isinstance(value, tuple):
+        return {"__pyisolate_tuple__": [_serialize_special_value(v) for v in value]}
+    if isinstance(value, list):
+        return [_serialize_special_value(v) for v in value]
+    if isinstance(value, dict):
+        return {k: _serialize_special_value(v) for k, v in value.items()}
+    return value
+
+
+def _restore_input_types_local(raw: Dict[str, object]) -> Dict[str, object]:
+    if not isinstance(raw, dict):
+        return raw  # type: ignore[return-value]
+
+    restored: Dict[str, object] = {}
+    for section, entries in raw.items():
+        if isinstance(entries, dict) and entries.get("__pyisolate_flexible_optional__"):
+            restored[section] = _restore_special_value(entries)
+        elif isinstance(entries, dict):
+            restored[section] = {
+                k: _restore_special_value(v) for k, v in entries.items()
+            }
+        else:
+            restored[section] = _restore_special_value(entries)
+    return restored
+
+
+class HelperProxiesService(ProxiedSingleton):
+    _rpc: Optional[Any] = None
+
+    @classmethod
+    def set_rpc(cls, rpc: Any) -> None:
+        cls._rpc = rpc.create_caller(cls, cls.get_remote_id())
+
+    @classmethod
+    def clear_rpc(cls) -> None:
+        cls._rpc = None
+
+    @classmethod
+    def _get_caller(cls) -> Any:
+        if cls._rpc is None:
+            raise RuntimeError("HelperProxiesService RPC caller is not configured")
+        return cls._rpc
+
+    async def rpc_restore_input_types(self, raw: Dict[str, object]) -> Dict[str, object]:
+        restored = _restore_input_types_local(raw)
+        return _serialize_special_value(restored)
+
+
+def restore_input_types(raw: Dict[str, object]) -> Dict[str, object]:
+    """Restore serialized INPUT_TYPES payload back into ComfyUI-compatible objects."""
+    if os.environ.get("PYISOLATE_CHILD") == "1":
+        payload = call_singleton_rpc(
+            HelperProxiesService._get_caller(),
+            "rpc_restore_input_types",
+            raw,
+        )
+        return _restore_input_types_local(payload)
+    return _restore_input_types_local(raw)
+
+
+__all__ = [
+    "AnyTypeProxy",
+    "FlexibleOptionalInputProxy",
+    "ByPassTypeTupleProxy",
+    "HelperProxiesService",
+    "restore_input_types",
+]

comfy/isolation/proxies/model_management_proxy.py

@@ -0,0 +1,142 @@
+from __future__ import annotations
+
+import os
+from typing import Any, Optional
+
+from pyisolate import ProxiedSingleton
+
+from .base import call_singleton_rpc
+
+
+def _mm():
+    import comfy.model_management
+
+    return comfy.model_management
+
+
+def _is_child_process() -> bool:
+    return os.environ.get("PYISOLATE_CHILD") == "1"
+
+
+class TorchDeviceProxy:
+    def __init__(self, device_str: str):
+        self._device_str = device_str
+        if ":" in device_str:
+            device_type, index = device_str.split(":", 1)
+            self.type = device_type
+            self.index = int(index)
+        else:
+            self.type = device_str
+            self.index = None
+
+    def __str__(self) -> str:
+        return self._device_str
+
+    def __repr__(self) -> str:
+        return f"TorchDeviceProxy({self._device_str!r})"
+
+
+def _serialize_value(value: Any) -> Any:
+    value_type = type(value)
+    if value_type.__module__ == "torch" and value_type.__name__ == "device":
+        return {"__pyisolate_torch_device__": str(value)}
+    if isinstance(value, TorchDeviceProxy):
+        return {"__pyisolate_torch_device__": str(value)}
+    if isinstance(value, tuple):
+        return {"__pyisolate_tuple__": [_serialize_value(item) for item in value]}
+    if isinstance(value, list):
+        return [_serialize_value(item) for item in value]
+    if isinstance(value, dict):
+        return {key: _serialize_value(inner) for key, inner in value.items()}
+    return value
+
+
+def _deserialize_value(value: Any) -> Any:
+    if isinstance(value, dict):
+        if "__pyisolate_torch_device__" in value:
+            return TorchDeviceProxy(value["__pyisolate_torch_device__"])
+        if "__pyisolate_tuple__" in value:
+            return tuple(_deserialize_value(item) for item in value["__pyisolate_tuple__"])
+        return {key: _deserialize_value(inner) for key, inner in value.items()}
+    if isinstance(value, list):
+        return [_deserialize_value(item) for item in value]
+    return value
+
+
+def _normalize_argument(value: Any) -> Any:
+    if isinstance(value, TorchDeviceProxy):
+        import torch
+
+        return torch.device(str(value))
+    if isinstance(value, dict):
+        if "__pyisolate_torch_device__" in value:
+            import torch
+
+            return torch.device(value["__pyisolate_torch_device__"])
+        if "__pyisolate_tuple__" in value:
+            return tuple(_normalize_argument(item) for item in value["__pyisolate_tuple__"])
+        return {key: _normalize_argument(inner) for key, inner in value.items()}
+    if isinstance(value, list):
+        return [_normalize_argument(item) for item in value]
+    return value
+
+
+class ModelManagementProxy(ProxiedSingleton):
+    """
+    Exact-relay proxy for comfy.model_management.
+    Child calls never import comfy.model_management directly; they serialize
+    arguments, relay to host, and deserialize the host result back.
+    """
+
+    _rpc: Optional[Any] = None
+
+    @classmethod
+    def set_rpc(cls, rpc: Any) -> None:
+        cls._rpc = rpc.create_caller(cls, cls.get_remote_id())
+
+    @classmethod
+    def clear_rpc(cls) -> None:
+        cls._rpc = None
+
+    @classmethod
+    def _get_caller(cls) -> Any:
+        if cls._rpc is None:
+            raise RuntimeError("ModelManagementProxy RPC caller is not configured")
+        return cls._rpc
+
+    def _relay_call(self, method_name: str, *args: Any, **kwargs: Any) -> Any:
+        payload = call_singleton_rpc(
+            self._get_caller(),
+            "rpc_call",
+            method_name,
+            _serialize_value(args),
+            _serialize_value(kwargs),
+        )
+        return _deserialize_value(payload)
+
+    @property
+    def VRAMState(self):
+        return _mm().VRAMState
+
+    @property
+    def CPUState(self):
+        return _mm().CPUState
+
+    @property
+    def OOM_EXCEPTION(self):
+        return _mm().OOM_EXCEPTION
+
+    def __getattr__(self, name: str):
+        if _is_child_process():
+            def child_method(*args: Any, **kwargs: Any) -> Any:
+                return self._relay_call(name, *args, **kwargs)
+
+            return child_method
+        return getattr(_mm(), name)
+
+    async def rpc_call(self, method_name: str, args: Any, kwargs: Any) -> Any:
+        normalized_args = _normalize_argument(_deserialize_value(args))
+        normalized_kwargs = _normalize_argument(_deserialize_value(kwargs))
+        method = getattr(_mm(), method_name)
+        result = method(*normalized_args, **normalized_kwargs)
+        return _serialize_value(result)

comfy/isolation/proxies/progress_proxy.py

@@ -0,0 +1,87 @@
+from __future__ import annotations
+
+import logging
+import os
+from typing import Any, Optional
+
+try:
+    from pyisolate import ProxiedSingleton
+except ImportError:
+
+    class ProxiedSingleton:
+        pass
+
+from .base import call_singleton_rpc
+
+
+def _get_progress_state():
+    from comfy_execution.progress import get_progress_state
+
+    return get_progress_state()
+
+
+def _is_child_process() -> bool:
+    return os.environ.get("PYISOLATE_CHILD") == "1"
+
+logger = logging.getLogger(__name__)
+
+
+class ProgressProxy(ProxiedSingleton):
+    _rpc: Optional[Any] = None
+
+    @classmethod
+    def set_rpc(cls, rpc: Any) -> None:
+        cls._rpc = rpc.create_caller(cls, cls.get_remote_id())
+
+    @classmethod
+    def clear_rpc(cls) -> None:
+        cls._rpc = None
+
+    @classmethod
+    def _get_caller(cls) -> Any:
+        if cls._rpc is None:
+            raise RuntimeError("ProgressProxy RPC caller is not configured")
+        return cls._rpc
+
+    def set_progress(
+        self,
+        value: float,
+        max_value: float,
+        node_id: Optional[str] = None,
+        image: Any = None,
+    ) -> None:
+        if _is_child_process():
+            call_singleton_rpc(
+                self._get_caller(),
+                "rpc_set_progress",
+                value,
+                max_value,
+                node_id,
+                image,
+            )
+            return None
+
+        _get_progress_state().update_progress(
+            node_id=node_id,
+            value=value,
+            max_value=max_value,
+            image=image,
+        )
+        return None
+
+    async def rpc_set_progress(
+        self,
+        value: float,
+        max_value: float,
+        node_id: Optional[str] = None,
+        image: Any = None,
+    ) -> None:
+        _get_progress_state().update_progress(
+            node_id=node_id,
+            value=value,
+            max_value=max_value,
+            image=image,
+        )
+
+
+__all__ = ["ProgressProxy"]

comfy/isolation/proxies/prompt_server_impl.py

@@ -0,0 +1,306 @@
+# pylint: disable=import-outside-toplevel,logging-fstring-interpolation,redefined-outer-name,reimported,super-init-not-called
+"""Stateless RPC Implementation for PromptServer.
+
+Replaces the legacy PromptServerProxy (Singleton) with a clean Service/Stub architecture.
+- Host: PromptServerService (RPC Handler)
+- Child: PromptServerStub (Interface Implementation)
+"""
+
+from __future__ import annotations
+
+import os
+from typing import Any, Dict, Optional, Callable
+
+import logging
+
+# IMPORTS
+from pyisolate import ProxiedSingleton
+from .base import call_singleton_rpc
+
+logger = logging.getLogger(__name__)
+LOG_PREFIX = "[Isolation:C<->H]"
+
+# ...
+
+# =============================================================================
+# CHILD SIDE: PromptServerStub
+# =============================================================================
+
+
+class PromptServerStub:
+    """Stateless Stub for PromptServer."""
+
+    # Masquerade as the real server module
+    __module__ = "server"
+
+    _instance: Optional["PromptServerStub"] = None
+    _rpc: Optional[Any] = None  # This will be the Caller object
+    _source_file: Optional[str] = None
+
+    def __init__(self):
+        self.routes = RouteStub(self)
+
+    @classmethod
+    def set_rpc(cls, rpc: Any) -> None:
+        """Inject RPC client (called by adapter.py or manually)."""
+        # Create caller for HOST Service
+        # Assuming Host Service is registered as "PromptServerService" (class name)
+        # We target the Host Service Class
+        target_id = "PromptServerService"
+        # We need to pass a class to create_caller? Usually yes.
+        # But we don't have the Service class imported here necessarily (if running on child).
+        # pyisolate check verify_service type?
+        # If we pass PromptServerStub as the 'class', it might mismatch if checking types.
+        # But we can try passing PromptServerStub if it mirrors the service name? No, stub is PromptServerStub.
+        # We need a dummy class with right name?
+        # Or just rely on string ID if create_caller supports it?
+        # Standard: rpc.create_caller(PromptServerStub, target_id)
+        # But wait, PromptServerStub is the *Local* class.
+        # We want to call *Remote* class.
+        # If we use PromptServerStub as the type, returning object will be typed as PromptServerStub?
+        # The first arg is 'service_cls'.
+        cls._rpc = rpc.create_caller(
+            PromptServerService, target_id
+        )  # We import Service below?
+
+    @classmethod
+    def clear_rpc(cls) -> None:
+        cls._rpc = None
+
+    # We need PromptServerService available for the create_caller call?
+    # Or just use the Stub class if ID matches?
+    # prompt_server_impl.py defines BOTH. So PromptServerService IS available!
+
+    @property
+    def instance(self) -> "PromptServerStub":
+        return self
+
+    # ... Compatibility ...
+    @classmethod
+    def _get_source_file(cls) -> str:
+        if cls._source_file is None:
+            import folder_paths
+
+            cls._source_file = os.path.join(folder_paths.base_path, "server.py")
+        return cls._source_file
+
+    @property
+    def __file__(self) -> str:
+        return self._get_source_file()
+
+    # --- Properties ---
+    @property
+    def client_id(self) -> Optional[str]:
+        return "isolated_client"
+
+    @property
+    def supports(self) -> set:
+        return {"custom_nodes_from_web"}
+
+    @property
+    def app(self):
+        return _AppStub(self)
+
+    @property
+    def prompt_queue(self):
+        raise RuntimeError(
+            "PromptServer.prompt_queue is not accessible in isolated nodes."
+        )
+
+    # --- UI Communication (RPC Delegates) ---
+    async def send_sync(
+        self, event: str, data: Dict[str, Any], sid: Optional[str] = None
+    ) -> None:
+        if self._rpc:
+            await self._rpc.ui_send_sync(event, data, sid)
+
+    async def send(
+        self, event: str, data: Dict[str, Any], sid: Optional[str] = None
+    ) -> None:
+        if self._rpc:
+            await self._rpc.ui_send(event, data, sid)
+
+    def send_progress_text(self, text: str, node_id: str, sid=None) -> None:
+        if self._rpc:
+            # Fire and forget likely needed. If method is async on host, caller invocation returns coroutine.
+            # We must schedule it?
+            # Or use fire_remote equivalent?
+            # Caller object usually proxies calls. If host method is async, it returns coro.
+            # If we are sync here (send_progress_text checks imply sync usage), we must background it.
+            # But UtilsProxy hook wrapper creates task.
+            # Does send_progress_text need to be sync? Yes, node code calls it sync.
+            import asyncio
+
+            try:
+                loop = asyncio.get_running_loop()
+                loop.create_task(self._rpc.ui_send_progress_text(text, node_id, sid))
+            except RuntimeError:
+                call_singleton_rpc(self._rpc, "ui_send_progress_text", text, node_id, sid)
+
+    # --- Route Registration Logic ---
+    _pending_child_routes: list = []
+
+    def register_route(self, method: str, path: str, handler: Callable):
+        """Buffer route registration. Routes are flushed via flush_child_routes()."""
+        PromptServerStub._pending_child_routes.append((method, path, handler))
+        logger.info("%s Buffered isolated route %s %s", LOG_PREFIX, method, path)
+
+    @classmethod
+    async def flush_child_routes(cls):
+        """Send all buffered route registrations to host via RPC. Call from on_module_loaded."""
+        if not cls._rpc:
+            return 0
+        flushed = 0
+        for method, path, handler in cls._pending_child_routes:
+            try:
+                await cls._rpc.register_route_rpc(method, path, handler)
+                flushed += 1
+            except Exception as e:
+                logger.error("%s Child route flush failed %s %s: %s", LOG_PREFIX, method, path, e)
+        cls._pending_child_routes = []
+        return flushed
+
+
+class RouteStub:
+    """Simulates aiohttp.web.RouteTableDef."""
+
+    def __init__(self, stub: PromptServerStub):
+        self._stub = stub
+
+    def get(self, path: str):
+        def decorator(handler):
+            self._stub.register_route("GET", path, handler)
+            return handler
+
+        return decorator
+
+    def post(self, path: str):
+        def decorator(handler):
+            self._stub.register_route("POST", path, handler)
+            return handler
+
+        return decorator
+
+    def patch(self, path: str):
+        def decorator(handler):
+            self._stub.register_route("PATCH", path, handler)
+            return handler
+
+        return decorator
+
+    def put(self, path: str):
+        def decorator(handler):
+            self._stub.register_route("PUT", path, handler)
+            return handler
+
+        return decorator
+
+    def delete(self, path: str):
+        def decorator(handler):
+            self._stub.register_route("DELETE", path, handler)
+            return handler
+
+        return decorator
+
+
+# =============================================================================
+# HOST SIDE: PromptServerService
+# =============================================================================
+
+
+class PromptServerService(ProxiedSingleton):
+    """Host-side RPC Service for PromptServer."""
+
+    def __init__(self):
+        pass
+
+    @property
+    def server(self):
+        from server import PromptServer
+
+        return PromptServer.instance
+
+    async def ui_send_sync(
+        self, event: str, data: Dict[str, Any], sid: Optional[str] = None
+    ):
+        await self.server.send_sync(event, data, sid)
+
+    async def ui_send(
+        self, event: str, data: Dict[str, Any], sid: Optional[str] = None
+    ):
+        await self.server.send(event, data, sid)
+
+    async def ui_send_progress_text(self, text: str, node_id: str, sid=None):
+        # Made async to be awaitable by RPC layer
+        self.server.send_progress_text(text, node_id, sid)
+
+    async def register_route_rpc(self, method: str, path: str, child_handler_proxy):
+        """RPC Target: Register a route that forwards to the Child."""
+        from aiohttp import web
+        logger.info("%s Registering isolated route %s %s", LOG_PREFIX, method, path)
+
+        async def route_wrapper(request: web.Request) -> web.Response:
+            # 1. Capture request data
+            req_data = {
+                "method": request.method,
+                "path": request.path,
+                "query": dict(request.query),
+            }
+            if request.can_read_body:
+                req_data["text"] = await request.text()
+
+            try:
+                # 2. Call Child Handler via RPC (child_handler_proxy is async callable)
+                result = await child_handler_proxy(req_data)
+
+                # 3. Serialize Response
+                return self._serialize_response(result)
+            except Exception as e:
+                logger.error(f"{LOG_PREFIX} Isolated Route Error: {e}")
+                return web.Response(status=500, text=str(e))
+
+        self.server.app.router.add_route(method, path, route_wrapper)
+        logger.info("%s Registered isolated route %s %s", LOG_PREFIX, method, path)
+
+    def _serialize_response(self, result: Any) -> Any:
+        """Helper to convert Child result -> web.Response"""
+        from aiohttp import web
+        if isinstance(result, web.Response):
+            return result
+        # Handle dict (json)
+        if isinstance(result, dict):
+            return web.json_response(result)
+        # Handle string
+        if isinstance(result, str):
+            return web.Response(text=result)
+        # Fallback
+        return web.Response(text=str(result))
+
+
+class _RouterStub:
+    """Captures router.add_route and router.add_static calls in isolation child."""
+
+    def __init__(self, stub):
+        self._stub = stub
+
+    def add_route(self, method, path, handler, **kwargs):
+        self._stub.register_route(method, path, handler)
+
+    def add_static(self, prefix, path, **kwargs):
+        # Static file serving not supported in isolation — silently skip
+        pass
+
+
+class _AppStub:
+    """Captures PromptServer.app access patterns in isolation child."""
+
+    def __init__(self, stub):
+        self.router = _RouterStub(stub)
+        self.frozen = False
+
+    def add_routes(self, routes):
+        # aiohttp route table — iterate and register each
+        for route in routes:
+            if hasattr(route, "method") and hasattr(route, "handler"):
+                self.router.add_route(route.method, route.path, route.handler)
+            # StaticDef and other non-method routes — silently skip

comfy/isolation/proxies/utils_proxy.py

@@ -0,0 +1,64 @@
+# pylint: disable=cyclic-import,import-outside-toplevel
+from __future__ import annotations
+
+from typing import Optional, Any
+from pyisolate import ProxiedSingleton
+
+import os
+
+
+def _comfy_utils():
+    import comfy.utils
+    return comfy.utils
+
+
+class UtilsProxy(ProxiedSingleton):
+    """
+    Proxy for comfy.utils.
+    Primarily handles the PROGRESS_BAR_HOOK to ensure progress updates
+    from isolated nodes reach the host.
+    """
+
+    # _instance and __new__ removed to rely on SingletonMetaclass
+    _rpc: Optional[Any] = None
+
+    @classmethod
+    def set_rpc(cls, rpc: Any) -> None:
+        # Create caller using class name as ID (standard for Singletons)
+        cls._rpc = rpc.create_caller(cls, "UtilsProxy")
+
+    @classmethod
+    def clear_rpc(cls) -> None:
+        cls._rpc = None
+
+    async def progress_bar_hook(
+        self,
+        value: int,
+        total: int,
+        preview: Optional[bytes] = None,
+        node_id: Optional[str] = None,
+    ) -> Any:
+        """
+        Host-side implementation: forwards the call to the real global hook.
+        Child-side: this method call is intercepted by RPC and sent to host.
+        """
+        if os.environ.get("PYISOLATE_CHILD") == "1":
+            if UtilsProxy._rpc is None:
+                raise RuntimeError("UtilsProxy RPC caller is not configured")
+            return await UtilsProxy._rpc.progress_bar_hook(
+                value, total, preview, node_id
+            )
+
+        # Host Execution
+        utils = _comfy_utils()
+        if utils.PROGRESS_BAR_HOOK is not None:
+            return utils.PROGRESS_BAR_HOOK(value, total, preview, node_id)
+        return None
+
+    def set_progress_bar_global_hook(self, hook: Any) -> None:
+        """Forward hook registration (though usually not needed from child)."""
+        if os.environ.get("PYISOLATE_CHILD") == "1":
+            raise RuntimeError(
+                "UtilsProxy.set_progress_bar_global_hook is not available in child without exact relay support"
+            )
+        _comfy_utils().set_progress_bar_global_hook(hook)

comfy/isolation/proxies/web_directory_proxy.py

@@ -0,0 +1,229 @@
+"""WebDirectoryProxy — serves isolated node web assets via RPC.
+
+Child side: enumerates and reads files from the extension's web/ directory.
+Host side: gets an RPC proxy that fetches file listings and contents on demand.
+
+Only files with allowed extensions (.js, .html, .css) are served.
+Directory traversal is rejected. File contents are base64-encoded for
+safe JSON-RPC transport.
+"""
+
+from __future__ import annotations
+
+import base64
+import binascii
+import logging
+import os
+from pathlib import Path, PurePosixPath
+from typing import Any, Dict, List
+
+from pyisolate import ProxiedSingleton
+
+logger = logging.getLogger(__name__)
+
+ALLOWED_EXTENSIONS = frozenset({".js", ".html", ".css"})
+
+MIME_TYPES = {
+    ".js": "application/javascript",
+    ".html": "text/html",
+    ".css": "text/css",
+}
+
+
+class WebDirectoryProxy(ProxiedSingleton):
+    """Proxy for serving isolated extension web directories.
+
+    On the child side, this class has direct filesystem access to the
+    extension's web/ directory.  On the host side, callers get an RPC
+    proxy whose method calls are forwarded to the child.
+    """
+
+    # {extension_name: absolute_path_to_web_dir}
+    _web_dirs: dict[str, str] = {}
+
+    @classmethod
+    def register_web_dir(cls, extension_name: str, web_dir_path: str) -> None:
+        """Register an extension's web directory (child-side only)."""
+        cls._web_dirs[extension_name] = web_dir_path
+        logger.info(
+            "][ WebDirectoryProxy: registered %s -> %s",
+            extension_name,
+            web_dir_path,
+        )
+
+    def list_web_files(self, extension_name: str) -> List[Dict[str, str]]:
+        """Return a list of servable files in the extension's web directory.
+
+        Each entry is {"relative_path": "js/foo.js", "content_type": "application/javascript"}.
+        Only files with allowed extensions are included.
+        """
+        web_dir = self._web_dirs.get(extension_name)
+        if not web_dir:
+            return []
+
+        root = Path(web_dir)
+        if not root.is_dir():
+            return []
+
+        result: List[Dict[str, str]] = []
+        for path in sorted(root.rglob("*")):
+            if not path.is_file():
+                continue
+            ext = path.suffix.lower()
+            if ext not in ALLOWED_EXTENSIONS:
+                continue
+            rel = path.relative_to(root)
+            result.append({
+                "relative_path": str(PurePosixPath(rel)),
+                "content_type": MIME_TYPES[ext],
+            })
+        return result
+
+    def get_web_file(
+        self, extension_name: str, relative_path: str
+    ) -> Dict[str, Any]:
+        """Return the contents of a single web file as base64.
+
+        Raises ValueError for traversal attempts or disallowed file types.
+        Returns {"content": <base64 str>, "content_type": <MIME str>}.
+        """
+        _validate_path(relative_path)
+
+        web_dir = self._web_dirs.get(extension_name)
+        if not web_dir:
+            raise FileNotFoundError(
+                f"No web directory registered for {extension_name}"
+            )
+
+        root = Path(web_dir).resolve()
+        target = (root / relative_path).resolve()
+
+        # Ensure resolved path is under the web directory
+        if os.path.commonpath([str(root), str(target)]) != str(root):
+            raise ValueError(f"Path escapes web directory: {relative_path}")
+
+        if not target.is_file():
+            raise FileNotFoundError(f"File not found: {relative_path}")
+
+        ext = target.suffix.lower()
+        if ext not in ALLOWED_EXTENSIONS:
+            raise ValueError(f"Disallowed file type: {ext}")
+
+        content_type = MIME_TYPES[ext]
+        raw = target.read_bytes()
+
+        return {
+            "content": base64.b64encode(raw).decode("ascii"),
+            "content_type": content_type,
+        }
+
+
+def _validate_path(relative_path: str) -> None:
+    """Reject directory traversal and absolute paths."""
+    if os.path.isabs(relative_path):
+        raise ValueError(f"Absolute paths are not allowed: {relative_path}")
+    if ".." in PurePosixPath(relative_path).parts:
+        raise ValueError(f"Directory traversal is not allowed: {relative_path}")
+
+
+# ---------------------------------------------------------------------------
+# Host-side cache and aiohttp handler
+# ---------------------------------------------------------------------------
+
+
+class WebDirectoryCache:
+    """Host-side in-memory cache for proxied web directory contents.
+
+    Populated lazily via RPC calls to the child's WebDirectoryProxy.
+    Once a file is cached, subsequent requests are served from memory.
+    """
+
+    def __init__(self) -> None:
+        # {extension_name: {relative_path: {"content": bytes, "content_type": str}}}
+        self._file_cache: dict[str, dict[str, dict[str, Any]]] = {}
+        # {extension_name: [{"relative_path": str, "content_type": str}, ...]}
+        self._listing_cache: dict[str, list[dict[str, str]]] = {}
+        # {extension_name: WebDirectoryProxy (RPC proxy instance)}
+        self._proxies: dict[str, Any] = {}
+
+    def register_proxy(self, extension_name: str, proxy: Any) -> None:
+        """Register an RPC proxy for an extension's web directory."""
+        self._proxies[extension_name] = proxy
+        logger.info(
+            "][ WebDirectoryCache: registered proxy for %s", extension_name
+        )
+
+    @property
+    def extension_names(self) -> list[str]:
+        return list(self._proxies.keys())
+
+    def list_files(self, extension_name: str) -> list[dict[str, str]]:
+        """List servable files for an extension (cached after first call)."""
+        if extension_name not in self._listing_cache:
+            proxy = self._proxies.get(extension_name)
+            if proxy is None:
+                return []
+            try:
+                self._listing_cache[extension_name] = proxy.list_web_files(
+                    extension_name
+                )
+            except Exception:
+                logger.warning(
+                    "][ WebDirectoryCache: failed to list files for %s",
+                    extension_name,
+                    exc_info=True,
+                )
+                return []
+        return self._listing_cache[extension_name]
+
+    def get_file(
+        self, extension_name: str, relative_path: str
+    ) -> dict[str, Any] | None:
+        """Get file content (cached after first fetch). Returns None on miss."""
+        ext_cache = self._file_cache.get(extension_name)
+        if ext_cache and relative_path in ext_cache:
+            return ext_cache[relative_path]
+
+        proxy = self._proxies.get(extension_name)
+        if proxy is None:
+            return None
+
+        try:
+            result = proxy.get_web_file(extension_name, relative_path)
+        except (FileNotFoundError, ValueError):
+            return None
+        except Exception:
+            logger.warning(
+                "][ WebDirectoryCache: failed to fetch %s/%s",
+                extension_name,
+                relative_path,
+                exc_info=True,
+            )
+            return None
+
+        try:
+            decoded = {
+                "content": base64.b64decode(result["content"], validate=True),
+                "content_type": result["content_type"],
+            }
+        except (binascii.Error, KeyError, TypeError):
+            logger.warning(
+                "][ WebDirectoryCache: invalid payload for %s/%s",
+                extension_name,
+                relative_path,
+                exc_info=True,
+            )
+            return None
+
+        if extension_name not in self._file_cache:
+            self._file_cache[extension_name] = {}
+        self._file_cache[extension_name][relative_path] = decoded
+        return decoded
+
+
+# Global cache instance — populated during isolation loading
+_web_directory_cache = WebDirectoryCache()
+
+
+def get_web_directory_cache() -> WebDirectoryCache:
+    return _web_directory_cache

comfy/isolation/rpc_bridge.py

@@ -0,0 +1,49 @@
+import asyncio
+import logging
+import threading
+
+logger = logging.getLogger(__name__)
+
+
+class RpcBridge:
+    """Minimal helper to run coroutines synchronously inside isolated processes.
+
+    If an event loop is already running, the coroutine is executed on a fresh
+    thread with its own loop to avoid nested run_until_complete errors.
+    """
+
+    def run_sync(self, maybe_coro):
+        if not asyncio.iscoroutine(maybe_coro):
+            return maybe_coro
+
+        try:
+            loop = asyncio.get_running_loop()
+        except RuntimeError:
+            loop = None
+
+        if loop and loop.is_running():
+            result_container = {}
+            exc_container = {}
+
+            def _runner():
+                try:
+                    new_loop = asyncio.new_event_loop()
+                    asyncio.set_event_loop(new_loop)
+                    result_container["value"] = new_loop.run_until_complete(maybe_coro)
+                except Exception as exc:  # pragma: no cover
+                    exc_container["error"] = exc
+                finally:
+                    try:
+                        new_loop.close()
+                    except Exception:
+                        pass
+
+            t = threading.Thread(target=_runner, daemon=True)
+            t.start()
+            t.join()
+
+            if "error" in exc_container:
+                raise exc_container["error"]
+            return result_container.get("value")
+
+        return asyncio.run(maybe_coro)