Merge branch 'master' into pysssss-model-db

.github/workflows/stable-release.yml

@@ -12,17 +12,17 @@ on:
         description: 'CUDA version'
         required: true
         type: string
-        default: "129"
+        default: "128"
       python_minor:
         description: 'Python minor version'
         required: true
         type: string
-        default: "13"
+        default: "12"
       python_patch:
         description: 'Python patch version'
         required: true
         type: string
-        default: "6"
+        default: "10"
 
 
 jobs:
@@ -66,13 +66,8 @@ jobs:
           curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
           ./python.exe get-pip.py
           ./python.exe -s -m pip install ../cu${{ inputs.cu }}_python_deps/*
-          sed -i '1i../ComfyUI' ./python3${{ inputs.python_minor }}._pth
-
-          rm ./Lib/site-packages/torch/lib/dnnl.lib #I don't think this is actually used and I need the space
-          rm ./Lib/site-packages/torch/lib/libprotoc.lib
-          rm ./Lib/site-packages/torch/lib/libprotobuf.lib
-
-          cd ..
+            sed -i '1i../ComfyUI' ./python3${{ inputs.python_minor }}._pth
+            cd ..
 
           git clone --depth 1 https://github.com/comfyanonymous/taesd
           cp taesd/*.safetensors ./ComfyUI_copy/models/vae_approx/

.github/workflows/windows_release_dependencies.yml

@@ -17,19 +17,19 @@ on:
         description: 'cuda version'
         required: true
         type: string
-        default: "129"
+        default: "128"
 
       python_minor:
         description: 'python minor version'
         required: true
         type: string
-        default: "13"
+        default: "12"
 
       python_patch:
         description: 'python patch version'
         required: true
         type: string
-        default: "6"
+        default: "10"
 #  push:
 #    branches:
 #      - master

.github/workflows/windows_release_package.yml

@@ -7,19 +7,19 @@ on:
         description: 'cuda version'
         required: true
         type: string
-        default: "129"
+        default: "128"
 
       python_minor:
         description: 'python minor version'
         required: true
         type: string
-        default: "13"
+        default: "12"
 
       python_patch:
         description: 'python patch version'
         required: true
         type: string
-        default: "6"
+        default: "10"
 #  push:
 #    branches:
 #      - master
@@ -64,10 +64,6 @@ jobs:
             ./python.exe get-pip.py
             ./python.exe -s -m pip install ../cu${{ inputs.cu }}_python_deps/*
             sed -i '1i../ComfyUI' ./python3${{ inputs.python_minor }}._pth
-
-            rm ./Lib/site-packages/torch/lib/dnnl.lib #I don't think this is actually used and I need the space
-            rm ./Lib/site-packages/torch/lib/libprotoc.lib
-            rm ./Lib/site-packages/torch/lib/libprotobuf.lib
             cd ..
 
             git clone --depth 1 https://github.com/comfyanonymous/taesd

alembic_db/versions/e9c714da8d57_init.py

@@ -0,0 +1,40 @@
+"""init
+
+Revision ID: e9c714da8d57
+Revises:
+Create Date: 2025-05-30 20:14:33.772039
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = 'e9c714da8d57'
+down_revision: Union[str, None] = None
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    op.create_table('model',
+    sa.Column('type', sa.Text(), nullable=False),
+    sa.Column('path', sa.Text(), nullable=False),
+    sa.Column('file_name', sa.Text(), nullable=True),
+    sa.Column('file_size', sa.Integer(), nullable=True),
+    sa.Column('hash', sa.Text(), nullable=True),
+    sa.Column('hash_algorithm', sa.Text(), nullable=True),
+    sa.Column('source_url', sa.Text(), nullable=True),
+    sa.Column('date_added', sa.DateTime(), server_default=sa.text('(CURRENT_TIMESTAMP)'), nullable=True),
+    sa.PrimaryKeyConstraint('type', 'path')
+    )
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table('model')
+    # ### end Alembic commands ###

app/database/models.py

@@ -1,4 +1,11 @@
+from sqlalchemy import (
+    Column,
+    Integer,
+    Text,
+    DateTime,
+)
 from sqlalchemy.orm import declarative_base
+from sqlalchemy.sql import func
 
 Base = declarative_base()
 
@@ -11,4 +18,42 @@ def to_dict(obj):
         if (val := getattr(obj, field))
     }
 
-# TODO: Define models here
+
+class Model(Base):
+    """
+    sqlalchemy model representing a model file in the system.
+
+    This class defines the database schema for storing information about model files,
+    including their type, path, hash, and when they were added to the system.
+
+    Attributes:
+        type (Text): The type of the model, this is the name of the folder in the models folder (primary key)
+        path (Text): The file path of the model relative to the type folder (primary key)
+        file_name (Text): The name of the model file
+        file_size (Integer): The size of the model file in bytes
+        hash (Text): A hash of the model file
+        hash_algorithm (Text): The algorithm used to generate the hash
+        source_url (Text): The URL of the model file
+        date_added (DateTime): Timestamp of when the model was added to the system
+    """
+
+    __tablename__ = "model"
+
+    type = Column(Text, primary_key=True)
+    path = Column(Text, primary_key=True)
+    file_name = Column(Text)
+    file_size = Column(Integer)
+    hash = Column(Text)
+    hash_algorithm = Column(Text)
+    source_url = Column(Text)
+    date_added = Column(DateTime, server_default=func.now())
+
+    def to_dict(self):
+        """
+        Convert the model instance to a dictionary representation.
+
+        Returns:
+            dict: A dictionary containing the attributes of the model
+        """
+        dict = to_dict(self)
+        return dict

app/frontend_management.py

@@ -196,6 +196,17 @@ def download_release_asset_zip(release: Release, destination_path: str) -> None:
 
 
 class FrontendManager:
+    """
+    A class to manage ComfyUI frontend versions and installations.
+
+    This class handles the initialization and management of different frontend versions,
+    including the default frontend from the pip package and custom frontend versions
+    from GitHub repositories.
+
+    Attributes:
+        CUSTOM_FRONTENDS_ROOT (str): The root directory where custom frontend versions are stored.
+    """
+
     CUSTOM_FRONTENDS_ROOT = str(Path(__file__).parents[1] / "web_custom_versions")
 
     @classmethod
@@ -205,6 +216,15 @@ class FrontendManager:
 
     @classmethod
     def default_frontend_path(cls) -> str:
+        """
+        Get the path to the default frontend installation from the pip package.
+
+        Returns:
+            str: The path to the default frontend static files.
+
+        Raises:
+            SystemExit: If the comfyui-frontend-package is not installed.
+        """
         try:
             import comfyui_frontend_package
 
@@ -225,6 +245,15 @@ comfyui-frontend-package is not installed.
 
     @classmethod
     def templates_path(cls) -> str:
+        """
+        Get the path to the workflow templates.
+
+        Returns:
+            str: The path to the workflow templates directory.
+
+        Raises:
+            SystemExit: If the comfyui-workflow-templates package is not installed.
+        """
         try:
             import comfyui_workflow_templates
 
@@ -260,11 +289,16 @@ comfyui-workflow-templates is not installed.
     @classmethod
     def parse_version_string(cls, value: str) -> tuple[str, str, str]:
         """
+        Parse a version string into its components.
+
+        The version string should be in the format: 'owner/repo@version'
+        where version can be either a semantic version (v1.2.3) or 'latest'.
+
         Args:
             value (str): The version string to parse.
 
         Returns:
-            tuple[str, str]: A tuple containing provider name and version.
+            tuple[str, str, str]: A tuple containing (owner, repo, version).
 
         Raises:
             argparse.ArgumentTypeError: If the version string is invalid.
@@ -281,18 +315,22 @@ comfyui-workflow-templates is not installed.
         cls, version_string: str, provider: Optional[FrontEndProvider] = None
     ) -> str:
         """
-        Initializes the frontend for the specified version.
+        Initialize a frontend version without error handling.
+
+        This method attempts to initialize a specific frontend version, either from
+        the default pip package or from a custom GitHub repository. It will download
+        and extract the frontend files if necessary.
 
         Args:
-            version_string (str): The version string.
-            provider (FrontEndProvider, optional): The provider to use. Defaults to None.
+            version_string (str): The version string specifying which frontend to use.
+            provider (FrontEndProvider, optional): The provider to use for custom frontends.
 
         Returns:
             str: The path to the initialized frontend.
 
         Raises:
-            Exception: If there is an error during the initialization process.
-            main error source might be request timeout or invalid URL.
+            Exception: If there is an error during initialization (e.g., network timeout,
+                      invalid URL, or missing assets).
         """
         if version_string == DEFAULT_VERSION_STRING:
             check_frontend_version()
@@ -344,13 +382,17 @@ comfyui-workflow-templates is not installed.
     @classmethod
     def init_frontend(cls, version_string: str) -> str:
         """
-        Initializes the frontend with the specified version string.
+        Initialize a frontend version with error handling.
+
+        This is the main method to initialize a frontend version. It wraps init_frontend_unsafe
+        with error handling, falling back to the default frontend if initialization fails.
 
         Args:
-            version_string (str): The version string to initialize the frontend with.
+            version_string (str): The version string specifying which frontend to use.
 
         Returns:
-            str: The path of the initialized frontend.
+            str: The path to the initialized frontend. If initialization fails,
+                 returns the path to the default frontend.
         """
         try:
             return cls.init_frontend_unsafe(version_string)

app/model_processor.py

@@ -0,0 +1,331 @@
+import os
+import logging
+import time
+
+import requests
+from tqdm import tqdm
+from folder_paths import get_relative_path, get_full_path
+from app.database.db import create_session, dependencies_available, can_create_session
+import blake3
+import comfy.utils
+
+
+if dependencies_available():
+    from app.database.models import Model
+
+
+class ModelProcessor:
+    def _validate_path(self, model_path):
+        try:
+            if not self._file_exists(model_path):
+                logging.error(f"Model file not found: {model_path}")
+                return None
+
+            result = get_relative_path(model_path)
+            if not result:
+                logging.error(
+                    f"Model file not in a recognized model directory: {model_path}"
+                )
+                return None
+
+            return result
+        except Exception as e:
+            logging.error(f"Error validating model path {model_path}: {str(e)}")
+            return None
+
+    def _file_exists(self, path):
+        """Check if a file exists."""
+        return os.path.exists(path)
+
+    def _get_file_size(self, path):
+        """Get file size."""
+        return os.path.getsize(path)
+
+    def _get_hasher(self):
+        return blake3.blake3()
+
+    def _hash_file(self, model_path):
+        try:
+            hasher = self._get_hasher()
+            with open(model_path, "rb", buffering=0) as f:
+                b = bytearray(128 * 1024)
+                mv = memoryview(b)
+                while n := f.readinto(mv):
+                    hasher.update(mv[:n])
+            return hasher.hexdigest()
+        except Exception as e:
+            logging.error(f"Error hashing file {model_path}: {str(e)}")
+            return None
+
+    def _get_existing_model(self, session, model_type, model_relative_path):
+        return (
+            session.query(Model)
+            .filter(Model.type == model_type)
+            .filter(Model.path == model_relative_path)
+            .first()
+        )
+
+    def _ensure_source_url(self, session, model, source_url):
+        if model.source_url is None:
+            model.source_url = source_url
+            session.commit()
+
+    def _update_database(
+        self,
+        session,
+        model_type,
+        model_path,
+        model_relative_path,
+        model_hash,
+        model,
+        source_url,
+    ):
+        try:
+            if not model:
+                model = self._get_existing_model(
+                    session, model_type, model_relative_path
+                )
+
+            if not model:
+                model = Model(
+                    path=model_relative_path,
+                    type=model_type,
+                    file_name=os.path.basename(model_path),
+                )
+                session.add(model)
+
+            model.file_size = self._get_file_size(model_path)
+            model.hash = model_hash
+            if model_hash:
+                model.hash_algorithm = "blake3"
+            model.source_url = source_url
+
+            session.commit()
+            return model
+        except Exception as e:
+            logging.error(
+                f"Error updating database for {model_relative_path}: {str(e)}"
+            )
+
+    def process_file(self, model_path, source_url=None, model_hash=None):
+        """
+        Process a model file and update the database with metadata.
+        If the file already exists and matches the database, it will not be processed again.
+        Returns the model object or if an error occurs, returns None.
+        """
+        try:
+            if not can_create_session():
+                return
+
+            result = self._validate_path(model_path)
+            if not result:
+                return
+            model_type, model_relative_path = result
+
+            with create_session() as session:
+                session.expire_on_commit = False
+
+                existing_model = self._get_existing_model(
+                    session, model_type, model_relative_path
+                )
+                if (
+                    existing_model
+                    and existing_model.hash
+                    and existing_model.file_size == self._get_file_size(model_path)
+                ):
+                    # File exists with hash and same size, no need to process
+                    self._ensure_source_url(session, existing_model, source_url)
+                    return existing_model
+
+                if model_hash:
+                    model_hash = model_hash.lower()
+                    logging.info(f"Using provided hash: {model_hash}")
+                else:
+                    start_time = time.time()
+                    logging.info(f"Hashing model {model_relative_path}")
+                    model_hash = self._hash_file(model_path)
+                    if not model_hash:
+                        return
+                    logging.info(
+                        f"Model hash: {model_hash} (duration: {time.time() - start_time} seconds)"
+                    )
+
+                return self._update_database(
+                    session,
+                    model_type,
+                    model_path,
+                    model_relative_path,
+                    model_hash,
+                    existing_model,
+                    source_url,
+                )
+        except Exception as e:
+            logging.error(f"Error processing model file {model_path}: {str(e)}")
+            return None
+
+    def retrieve_model_by_hash(self, model_hash, model_type=None, session=None):
+        """
+        Retrieve a model file from the database by hash and optionally by model type.
+        Returns the model object or None if the model doesnt exist or an error occurs.
+        """
+        try:
+            if not can_create_session():
+                return
+
+            dispose_session = False
+
+            if session is None:
+                session = create_session()
+                dispose_session = True
+
+            model = session.query(Model).filter(Model.hash == model_hash)
+            if model_type is not None:
+                model = model.filter(Model.type == model_type)
+            return model.first()
+        except Exception as e:
+            logging.error(f"Error retrieving model by hash {model_hash}: {str(e)}")
+            return None
+        finally:
+            if dispose_session:
+                session.close()
+
+    def retrieve_hash(self, model_path, model_type=None):
+        """
+        Retrieve the hash of a model file from the database.
+        Returns the hash or None if the model doesnt exist or an error occurs.
+        """
+        try:
+            if not can_create_session():
+                return
+
+            if model_type is not None:
+                result = self._validate_path(model_path)
+                if not result:
+                    return None
+            model_type, model_relative_path = result
+
+            with create_session() as session:
+                model = self._get_existing_model(
+                    session, model_type, model_relative_path
+                )
+                if model and model.hash:
+                    return model.hash
+                return None
+        except Exception as e:
+            logging.error(f"Error retrieving hash for {model_path}: {str(e)}")
+            return None
+
+    def _validate_file_extension(self, file_name):
+        """Validate that the file extension is supported."""
+        extension = os.path.splitext(file_name)[1]
+        if extension not in (".safetensors", ".sft", ".txt", ".csv", ".json", ".yaml"):
+            raise ValueError(f"Unsupported unsafe file for download: {file_name}")
+
+    def _check_existing_file(self, model_type, file_name, expected_hash):
+        """Check if file exists and has correct hash."""
+        destination_path = get_full_path(model_type, file_name, allow_missing=True)
+        if self._file_exists(destination_path):
+            model = self.process_file(destination_path)
+            if model and (expected_hash is None or model.hash == expected_hash):
+                logging.debug(
+                    f"File {destination_path} already exists in the database and has the correct hash or no hash was provided."
+                )
+                return destination_path
+            else:
+                raise ValueError(
+                    f"File {destination_path} exists with hash {model.hash if model else 'unknown'} but expected {expected_hash}. Please delete the file and try again."
+                )
+        return None
+
+    def _check_existing_file_by_hash(self, hash, type, url):
+        """Check if a file with the given hash exists in the database and on disk."""
+        hash = hash.lower()
+        with create_session() as session:
+            model = self.retrieve_model_by_hash(hash, type, session)
+            if model:
+                existing_path = get_full_path(type, model.path)
+                if existing_path:
+                    logging.debug(
+                        f"File {model.path} already exists in the database at {existing_path}"
+                    )
+                    self._ensure_source_url(session, model, url)
+                    return existing_path
+                else:
+                    logging.debug(
+                        f"File {model.path} exists in the database but not on disk"
+                    )
+        return None
+
+    def _download_file(self, url, destination_path, hasher):
+        """Download a file and update the hasher with its contents."""
+        response = requests.get(url, stream=True)
+        logging.info(f"Downloading {url} to {destination_path}")
+
+        with open(destination_path, "wb") as f:
+            total_size = int(response.headers.get("content-length", 0))
+            if total_size > 0:
+                pbar = comfy.utils.ProgressBar(total_size)
+            else:
+                pbar = None
+            with tqdm(total=total_size, unit="B", unit_scale=True) as progress_bar:
+                for chunk in response.iter_content(chunk_size=128 * 1024):
+                    if chunk:
+                        f.write(chunk)
+                        hasher.update(chunk)
+                        progress_bar.update(len(chunk))
+                        if pbar:
+                            pbar.update(len(chunk))
+
+    def _verify_downloaded_hash(self, calculated_hash, expected_hash, destination_path):
+        """Verify that the downloaded file has the expected hash."""
+        if expected_hash is not None and calculated_hash != expected_hash:
+            self._remove_file(destination_path)
+            raise ValueError(
+                f"Downloaded file hash {calculated_hash} does not match expected hash {expected_hash}"
+            )
+
+    def _remove_file(self, file_path):
+        """Remove a file from disk."""
+        os.remove(file_path)
+
+    def ensure_downloaded(self, type, url, desired_file_name, hash=None):
+        """
+        Ensure a model file is downloaded and has the correct hash.
+        Returns the path to the downloaded file.
+        """
+        logging.debug(
+            f"Ensuring {type} file is downloaded. URL='{url}' Destination='{desired_file_name}' Hash='{hash}'"
+        )
+
+        # Validate file extension
+        self._validate_file_extension(desired_file_name)
+
+        # Check if file exists with correct hash
+        if hash:
+            existing_path = self._check_existing_file_by_hash(hash, type, url)
+            if existing_path:
+                return existing_path
+
+        # Check if file exists locally
+        destination_path = get_full_path(type, desired_file_name, allow_missing=True)
+        existing_path = self._check_existing_file(type, desired_file_name, hash)
+        if existing_path:
+            return existing_path
+
+        # Download the file
+        hasher = self._get_hasher()
+        self._download_file(url, destination_path, hasher)
+
+        # Verify hash
+        calculated_hash = hasher.hexdigest()
+        self._verify_downloaded_hash(calculated_hash, hash, destination_path)
+
+        # Update database
+        self.process_file(destination_path, url, calculated_hash)
+
+        # TODO: Notify frontend to reload models
+
+        return destination_path
+
+
+model_processor = ModelProcessor()

comfy/cli_args.py

@@ -210,6 +210,7 @@ database_default_path = os.path.abspath(
     os.path.join(os.path.dirname(__file__), "..", "user", "comfyui.db")
 )
 parser.add_argument("--database-url", type=str, default=f"sqlite:///{database_default_path}", help="Specify the database URL, e.g. for an in-memory database you can use 'sqlite:///:memory:'.")
+parser.add_argument("--disable-model-processing", action="store_true", help="Disable model file processing, e.g. computing hashes and extracting metadata.")
 
 if comfy.options.args_parsing:
     args = parser.parse_args()

comfy/ldm/wan/model.py

@@ -391,7 +391,6 @@ class WanModel(torch.nn.Module):
                  cross_attn_norm=True,
                  eps=1e-6,
                  flf_pos_embed_token_number=None,
-                 in_dim_ref_conv=None,
                  image_model=None,
                  device=None,
                  dtype=None,
@@ -485,11 +484,6 @@ class WanModel(torch.nn.Module):
         else:
             self.img_emb = None
 
-        if in_dim_ref_conv is not None:
-            self.ref_conv = operations.Conv2d(in_dim_ref_conv, dim, kernel_size=patch_size[1:], stride=patch_size[1:], device=operation_settings.get("device"), dtype=operation_settings.get("dtype"))
-        else:
-            self.ref_conv = None
-
     def forward_orig(
         self,
         x,
@@ -532,13 +526,6 @@ class WanModel(torch.nn.Module):
         e = e.reshape(t.shape[0], -1, e.shape[-1])
         e0 = self.time_projection(e).unflatten(2, (6, self.dim))
 
-        full_ref = None
-        if self.ref_conv is not None:
-            full_ref = kwargs.get("reference_latent", None)
-            if full_ref is not None:
-                full_ref = self.ref_conv(full_ref).flatten(2).transpose(1, 2)
-                x = torch.concat((full_ref, x), dim=1)
-
         # context
         context = self.text_embedding(context)
 
@@ -565,9 +552,6 @@ class WanModel(torch.nn.Module):
         # head
         x = self.head(x, e)
 
-        if full_ref is not None:
-            x = x[:, full_ref.shape[1]:]
-
         # unpatchify
         x = self.unpatchify(x, grid_sizes)
         return x
@@ -586,9 +570,6 @@ class WanModel(torch.nn.Module):
             x = torch.cat([x, time_dim_concat], dim=2)
             t_len = ((x.shape[2] + (patch_size[0] // 2)) // patch_size[0])
 
-        if self.ref_conv is not None and "reference_latent" in kwargs:
-            t_len += 1
-
         img_ids = torch.zeros((t_len, h_len, w_len, 3), device=x.device, dtype=x.dtype)
         img_ids[:, :, :, 0] = img_ids[:, :, :, 0] + torch.linspace(0, t_len - 1, steps=t_len, device=x.device, dtype=x.dtype).reshape(-1, 1, 1)
         img_ids[:, :, :, 1] = img_ids[:, :, :, 1] + torch.linspace(0, h_len - 1, steps=h_len, device=x.device, dtype=x.dtype).reshape(1, -1, 1)

comfy/model_base.py

@@ -1124,11 +1124,7 @@ class WAN21(BaseModel):
                 mask = mask.repeat(1, 4, 1, 1, 1)
             mask = utils.resize_to_batch_size(mask, noise.shape[0])
 
-        concat_mask_index = kwargs.get("concat_mask_index", 0)
-        if concat_mask_index != 0:
-            return torch.cat((image[:, :concat_mask_index], mask, image[:, concat_mask_index:]), dim=1)
-        else:
-            return torch.cat((mask, image), dim=1)
+        return torch.cat((mask, image), dim=1)
 
     def extra_conds(self, **kwargs):
         out = super().extra_conds(**kwargs)
@@ -1144,10 +1140,6 @@ class WAN21(BaseModel):
         if time_dim_concat is not None:
             out['time_dim_concat'] = comfy.conds.CONDRegular(self.process_latent_in(time_dim_concat))
 
-        reference_latents = kwargs.get("reference_latents", None)
-        if reference_latents is not None:
-            out['reference_latent'] = comfy.conds.CONDRegular(self.process_latent_in(reference_latents[-1])[:, :, 0])
-
         return out
 
 

comfy/model_detection.py

@@ -373,11 +373,6 @@ def detect_unet_config(state_dict, key_prefix, metadata=None):
         flf_weight = state_dict.get('{}img_emb.emb_pos'.format(key_prefix))
         if flf_weight is not None:
             dit_config["flf_pos_embed_token_number"] = flf_weight.shape[1]
-
-        ref_conv_weight = state_dict.get('{}ref_conv.weight'.format(key_prefix))
-        if ref_conv_weight is not None:
-            dit_config["in_dim_ref_conv"] = ref_conv_weight.shape[1]
-
         return dit_config
 
     if '{}latent_in.weight'.format(key_prefix) in state_dict_keys:  # Hunyuan 3D

comfy/utils.py

@@ -50,10 +50,16 @@ if hasattr(torch.serialization, "add_safe_globals"):  # TODO: this was added in
 else:
     logging.info("Warning, you are using an old pytorch version and some ckpt/pt files might be loaded unsafely. Upgrading to 2.4 or above is recommended.")
 
+def is_html_file(file_path):
+    with open(file_path, "rb") as f:
+        content = f.read(100)
+        return b"<!DOCTYPE html>" in content or b"<html" in content
+
 def load_torch_file(ckpt, safe_load=False, device=None, return_metadata=False):
     if device is None:
         device = torch.device("cpu")
     metadata = None
+
     if ckpt.lower().endswith(".safetensors") or ckpt.lower().endswith(".sft"):
         try:
             with safetensors.safe_open(ckpt, framework="pt", device=device.type) as f:
@@ -66,6 +72,8 @@ def load_torch_file(ckpt, safe_load=False, device=None, return_metadata=False):
                 if return_metadata:
                     metadata = f.metadata()
         except Exception as e:
+            if is_html_file(ckpt):
+                raise ValueError("{}\n\nFile path: {}\n\nThe requested file is an HTML document not a safetensors file. Please re-download the file, not the web page.".format(e, ckpt))
             if len(e.args) > 0:
                 message = e.args[0]
                 if "HeaderTooLarge" in message:
@@ -93,6 +101,13 @@ def load_torch_file(ckpt, safe_load=False, device=None, return_metadata=False):
                     sd = pl_sd
             else:
                 sd = pl_sd
+
+    try:
+        from app.model_processor import model_processor
+        model_processor.process_file(ckpt)
+    except Exception as e:
+        logging.error(f"Error processing file {ckpt}: {e}")
+
     return (sd, metadata) if return_metadata else sd
 
 def save_torch_file(sd, ckpt, metadata=None):

comfy_api/latest/_ui.py

@@ -12,7 +12,7 @@ import torch
 try:
     import torchaudio
     TORCH_AUDIO_AVAILABLE = True
-except:
+except ImportError:
     TORCH_AUDIO_AVAILABLE = False
 from PIL import Image as PILImage
 from PIL.PngImagePlugin import PngInfo

comfy_api_nodes/nodes_kling.py

@@ -1690,11 +1690,7 @@ class KlingImageGenerationNode(KlingImageGenerationBase):
     ):
         self.validate_prompt(prompt, negative_prompt)
 
-        if image is None:
-            image_type = None
-        elif model_name == KlingImageGenModelName.kling_v1:
-            raise ValueError(f"The model {KlingImageGenModelName.kling_v1.value} does not support reference images.")
-        else:
+        if image is not None:
             image = tensor_to_base64_string(image)
 
         initial_operation = SynchronousOperation(

comfy_extras/nodes_wan.py

@@ -103,63 +103,6 @@ class WanFunControlToVideo:
         out_latent["samples"] = latent
         return (positive, negative, out_latent)
 
-class Wan22FunControlToVideo:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {"required": {"positive": ("CONDITIONING", ),
-                             "negative": ("CONDITIONING", ),
-                             "vae": ("VAE", ),
-                             "width": ("INT", {"default": 832, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
-                             "height": ("INT", {"default": 480, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
-                             "length": ("INT", {"default": 81, "min": 1, "max": nodes.MAX_RESOLUTION, "step": 4}),
-                             "batch_size": ("INT", {"default": 1, "min": 1, "max": 4096}),
-                },
-                "optional": {"ref_image": ("IMAGE", ),
-                             "control_video": ("IMAGE", ),
-                             # "start_image": ("IMAGE", ),
-                }}
-
-    RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "LATENT")
-    RETURN_NAMES = ("positive", "negative", "latent")
-    FUNCTION = "encode"
-
-    CATEGORY = "conditioning/video_models"
-
-    def encode(self, positive, negative, vae, width, height, length, batch_size, ref_image=None, start_image=None, control_video=None):
-        latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
-        concat_latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
-        concat_latent = comfy.latent_formats.Wan21().process_out(concat_latent)
-        concat_latent = concat_latent.repeat(1, 2, 1, 1, 1)
-        mask = torch.ones((1, 1, latent.shape[2] * 4, latent.shape[-2], latent.shape[-1]))
-
-        if start_image is not None:
-            start_image = comfy.utils.common_upscale(start_image[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
-            concat_latent_image = vae.encode(start_image[:, :, :, :3])
-            concat_latent[:,16:,:concat_latent_image.shape[2]] = concat_latent_image[:,:,:concat_latent.shape[2]]
-            mask[:, :, :start_image.shape[0] + 3] = 0.0
-
-        ref_latent = None
-        if ref_image is not None:
-            ref_image = comfy.utils.common_upscale(ref_image[:1].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
-            ref_latent = vae.encode(ref_image[:, :, :, :3])
-
-        if control_video is not None:
-            control_video = comfy.utils.common_upscale(control_video[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
-            concat_latent_image = vae.encode(control_video[:, :, :, :3])
-            concat_latent[:,:16,:concat_latent_image.shape[2]] = concat_latent_image[:,:,:concat_latent.shape[2]]
-
-        mask = mask.view(1, mask.shape[2] // 4, 4, mask.shape[3], mask.shape[4]).transpose(1, 2)
-        positive = node_helpers.conditioning_set_values(positive, {"concat_latent_image": concat_latent, "concat_mask": mask, "concat_mask_index": 16})
-        negative = node_helpers.conditioning_set_values(negative, {"concat_latent_image": concat_latent, "concat_mask": mask, "concat_mask_index": 16})
-
-        if ref_latent is not None:
-            positive = node_helpers.conditioning_set_values(positive, {"reference_latents": [ref_latent]}, append=True)
-            negative = node_helpers.conditioning_set_values(negative, {"reference_latents": [ref_latent]}, append=True)
-
-        out_latent = {}
-        out_latent["samples"] = latent
-        return (positive, negative, out_latent)
-
 class WanFirstLastFrameToVideo:
     @classmethod
     def INPUT_TYPES(s):
@@ -790,7 +733,6 @@ NODE_CLASS_MAPPINGS = {
     "WanTrackToVideo": WanTrackToVideo,
     "WanImageToVideo": WanImageToVideo,
     "WanFunControlToVideo": WanFunControlToVideo,
-    "Wan22FunControlToVideo": Wan22FunControlToVideo,
     "WanFunInpaintToVideo": WanFunInpaintToVideo,
     "WanFirstLastFrameToVideo": WanFirstLastFrameToVideo,
     "WanVaceToVideo": WanVaceToVideo,

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.3.50"
+__version__ = "0.3.49"

folder_paths.py

@@ -275,10 +275,7 @@ def filter_files_extensions(files: Collection[str], extensions: Collection[str])
 
 
 
-def get_full_path(folder_name: str, filename: str) -> str | None:
-    """
-    Get the full path of a file in a folder, has to be a file
-    """
+def get_full_path(folder_name: str, filename: str, allow_missing: bool = False) -> str | None:
     global folder_names_and_paths
     folder_name = map_legacy(folder_name)
     if folder_name not in folder_names_and_paths:
@@ -291,6 +288,8 @@ def get_full_path(folder_name: str, filename: str) -> str | None:
             return full_path
         elif os.path.islink(full_path):
             logging.warning("WARNING path {} exists but doesn't link anywhere, skipping.".format(full_path))
+        elif allow_missing:
+            return full_path
 
     return None
 
@@ -305,6 +304,27 @@ def get_full_path_or_raise(folder_name: str, filename: str) -> str:
     return full_path
 
 
+def get_relative_path(full_path: str) -> tuple[str, str] | None:
+    """Convert a full path back to a type-relative path.
+
+    Args:
+        full_path: The full path to the file
+
+    Returns:
+        tuple[str, str] | None: A tuple of (model_type, relative_path) if found, None otherwise
+    """
+    global folder_names_and_paths
+    full_path = os.path.normpath(full_path)
+
+    for model_type, (paths, _) in folder_names_and_paths.items():
+        for base_path in paths:
+            base_path = os.path.normpath(base_path)
+            if full_path.startswith(base_path):
+                relative_path = os.path.relpath(full_path, base_path)
+                return model_type, relative_path
+
+    return None
+
 def get_filename_list_(folder_name: str) -> tuple[list[str], dict[str, float], float]:
     folder_name = map_legacy(folder_name)
     global folder_names_and_paths

main.py

@@ -164,7 +164,6 @@ def cuda_malloc_warning():
         if cuda_malloc_warning:
             logging.warning("\nWARNING: this card most likely does not support cuda-malloc, if you get \"CUDA error\" please run ComfyUI with: --disable-cuda-malloc\n")
 
-
 def prompt_worker(q, server_instance):
     current_time: float = 0.0
     cache_type = execution.CacheType.CLASSIC
@@ -279,7 +278,6 @@ def cleanup_temp():
     if os.path.exists(temp_dir):
         shutil.rmtree(temp_dir, ignore_errors=True)
 
-
 def setup_database():
     try:
         from app.database.db import init_db, dependencies_available
@@ -288,7 +286,6 @@ def setup_database():
     except Exception as e:
         logging.error(f"Failed to initialize database. Please ensure you have installed the latest requirements. If the error persists, please report this as in future the database will be required: {e}")
 
-
 def start_comfyui(asyncio_loop=None):
     """
     Starts the ComfyUI server using the provided asyncio event loop or creates a new one.

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.3.50"
+version = "0.3.49"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.9"

requirements.txt

@@ -1,5 +1,5 @@
-comfyui-frontend-package==1.23.4
-comfyui-workflow-templates==0.1.59
+comfyui-frontend-package==1.24.4
+comfyui-workflow-templates==0.1.53
 comfyui-embedded-docs==0.2.6
 torch
 torchsde
@@ -20,6 +20,7 @@ tqdm
 psutil
 alembic
 SQLAlchemy
+blake3
 
 #non essential dependencies:
 kornia>=0.7.1

tests-unit/app_test/model_processor_test.py

@@ -0,0 +1,253 @@
+import pytest
+from unittest.mock import patch, MagicMock
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+from app.model_processor import ModelProcessor
+from app.database.models import Model, Base
+import os
+
+# Test data constants
+TEST_MODEL_TYPE = "checkpoints"
+TEST_URL = "http://example.com/model.safetensors"
+TEST_FILE_NAME = "model.safetensors"
+TEST_EXPECTED_HASH = "abc123"
+TEST_DESTINATION_PATH = "/path/to/model.safetensors"
+
+
+def create_test_model(session, file_name, model_type, hash_value, file_size=1000, source_url=None):
+    """Helper to create a test model in the database."""
+    model = Model(path=file_name, type=model_type, hash=hash_value, file_size=file_size, source_url=source_url)
+    session.add(model)
+    session.commit()
+    return model
+
+
+def setup_mock_hash_calculation(model_processor, hash_value):
+    """Helper to setup hash calculation mocks."""
+    mock_hash = MagicMock()
+    mock_hash.hexdigest.return_value = hash_value
+    return patch.object(model_processor, "_get_hasher", return_value=mock_hash)
+
+
+def verify_model_in_db(session, file_name, expected_hash=None, expected_type=None):
+    """Helper to verify model exists in database with correct attributes."""
+    db_model = session.query(Model).filter_by(path=file_name).first()
+    assert db_model is not None
+    if expected_hash:
+        assert db_model.hash == expected_hash
+    if expected_type:
+        assert db_model.type == expected_type
+    return db_model
+
+
+@pytest.fixture
+def db_engine():
+    # Configure in-memory database
+    engine = create_engine("sqlite:///:memory:")
+    Base.metadata.create_all(engine)
+    yield engine
+    Base.metadata.drop_all(engine)
+
+
+@pytest.fixture
+def db_session(db_engine):
+    Session = sessionmaker(bind=db_engine)
+    session = Session()
+    yield session
+    session.close()
+
+
+@pytest.fixture
+def mock_get_relative_path():
+    with patch("app.model_processor.get_relative_path") as mock:
+        mock.side_effect = lambda path: (TEST_MODEL_TYPE, os.path.basename(path))
+        yield mock
+
+
+@pytest.fixture
+def mock_get_full_path():
+    with patch("app.model_processor.get_full_path") as mock:
+        mock.return_value = TEST_DESTINATION_PATH
+        yield mock
+
+
+@pytest.fixture
+def model_processor(db_session, mock_get_relative_path, mock_get_full_path):
+    with patch("app.model_processor.create_session", return_value=db_session):
+        with patch("app.model_processor.can_create_session", return_value=True):
+            processor = ModelProcessor()
+            # Setup test state
+            processor.removed_files = []
+            processor.downloaded_files = []
+            processor.file_exists = {}
+
+            def mock_download_file(url, destination_path, hasher):
+                processor.downloaded_files.append((url, destination_path))
+                processor.file_exists[destination_path] = True
+                # Simulate writing some data to the file
+                test_data = b"test data"
+                hasher.update(test_data)
+
+            def mock_remove_file(file_path):
+                processor.removed_files.append(file_path)
+                if file_path in processor.file_exists:
+                    del processor.file_exists[file_path]
+
+            # Setup common patches
+            file_exists_patch = patch.object(
+                processor,
+                "_file_exists",
+                side_effect=lambda path: processor.file_exists.get(path, False),
+            )
+            file_size_patch = patch.object(
+                processor,
+                "_get_file_size",
+                side_effect=lambda path: (
+                    1000 if processor.file_exists.get(path, False) else 0
+                ),
+            )
+            download_file_patch = patch.object(
+                processor, "_download_file", side_effect=mock_download_file
+            )
+            remove_file_patch = patch.object(
+                processor, "_remove_file", side_effect=mock_remove_file
+            )
+
+            with (
+                file_exists_patch,
+                file_size_patch,
+                download_file_patch,
+                remove_file_patch,
+            ):
+                yield processor
+
+
+def test_ensure_downloaded_invalid_extension(model_processor):
+    # Ensure that an unsupported file extension raises an error to prevent unsafe file downloads
+    with pytest.raises(ValueError, match="Unsupported unsafe file for download"):
+        model_processor.ensure_downloaded(TEST_MODEL_TYPE, TEST_URL, "model.exe")
+
+
+def test_ensure_downloaded_existing_file_with_hash(model_processor, db_session):
+    # Ensure that a file with the same hash but from a different source is not downloaded again
+    SOURCE_URL = "https://example.com/other.sft"
+    create_test_model(db_session, TEST_FILE_NAME, TEST_MODEL_TYPE, TEST_EXPECTED_HASH, source_url=SOURCE_URL)
+    model_processor.file_exists[TEST_DESTINATION_PATH] = True
+
+    result = model_processor.ensure_downloaded(
+        TEST_MODEL_TYPE, TEST_URL, TEST_FILE_NAME, TEST_EXPECTED_HASH
+    )
+
+    assert result == TEST_DESTINATION_PATH
+    model = verify_model_in_db(db_session, TEST_FILE_NAME, TEST_EXPECTED_HASH, TEST_MODEL_TYPE)
+    assert model.source_url == SOURCE_URL # Ensure the source URL is not overwritten
+
+
+def test_ensure_downloaded_existing_file_hash_mismatch(model_processor, db_session):
+    # Ensure that a file with a different hash raises an error
+    create_test_model(db_session, TEST_FILE_NAME, TEST_MODEL_TYPE, "different_hash")
+    model_processor.file_exists[TEST_DESTINATION_PATH] = True
+
+    with pytest.raises(ValueError, match="File .* exists with hash .* but expected .*"):
+        model_processor.ensure_downloaded(
+            TEST_MODEL_TYPE, TEST_URL, TEST_FILE_NAME, TEST_EXPECTED_HASH
+        )
+
+
+def test_ensure_downloaded_new_file(model_processor, db_session):
+    # Ensure that a new file is downloaded
+    model_processor.file_exists[TEST_DESTINATION_PATH] = False
+
+    with setup_mock_hash_calculation(model_processor, TEST_EXPECTED_HASH):
+        result = model_processor.ensure_downloaded(
+            TEST_MODEL_TYPE, TEST_URL, TEST_FILE_NAME, TEST_EXPECTED_HASH
+        )
+
+    assert result == TEST_DESTINATION_PATH
+    assert len(model_processor.downloaded_files) == 1
+    assert model_processor.downloaded_files[0] == (TEST_URL, TEST_DESTINATION_PATH)
+    assert model_processor.file_exists[TEST_DESTINATION_PATH]
+    verify_model_in_db(db_session, TEST_FILE_NAME, TEST_EXPECTED_HASH, TEST_MODEL_TYPE)
+
+
+def test_ensure_downloaded_hash_mismatch(model_processor, db_session):
+    # Ensure that download that results in a different hash raises an error
+    model_processor.file_exists[TEST_DESTINATION_PATH] = False
+
+    with setup_mock_hash_calculation(model_processor, "different_hash"):
+        with pytest.raises(
+            ValueError,
+            match="Downloaded file hash .* does not match expected hash .*",
+        ):
+            model_processor.ensure_downloaded(
+                TEST_MODEL_TYPE,
+                TEST_URL,
+                TEST_FILE_NAME,
+                TEST_EXPECTED_HASH,
+            )
+
+    assert len(model_processor.removed_files) == 1
+    assert model_processor.removed_files[0] == TEST_DESTINATION_PATH
+    assert TEST_DESTINATION_PATH not in model_processor.file_exists
+    assert db_session.query(Model).filter_by(path=TEST_FILE_NAME).first() is None
+
+
+def test_process_file_without_hash(model_processor, db_session):
+    # Test processing file without provided hash
+    model_processor.file_exists[TEST_DESTINATION_PATH] = True
+
+    with patch.object(model_processor, "_hash_file", return_value=TEST_EXPECTED_HASH):
+        result = model_processor.process_file(TEST_DESTINATION_PATH)
+        assert result is not None
+        assert result.hash == TEST_EXPECTED_HASH
+
+
+def test_retrieve_model_by_hash(model_processor, db_session):
+    # Test retrieving model by hash
+    create_test_model(db_session, TEST_FILE_NAME, TEST_MODEL_TYPE, TEST_EXPECTED_HASH)
+    result = model_processor.retrieve_model_by_hash(TEST_EXPECTED_HASH)
+    assert result is not None
+    assert result.hash == TEST_EXPECTED_HASH
+
+
+def test_retrieve_model_by_hash_and_type(model_processor, db_session):
+    # Test retrieving model by hash and type
+    create_test_model(db_session, TEST_FILE_NAME, TEST_MODEL_TYPE, TEST_EXPECTED_HASH)
+    result = model_processor.retrieve_model_by_hash(TEST_EXPECTED_HASH, TEST_MODEL_TYPE)
+    assert result is not None
+    assert result.hash == TEST_EXPECTED_HASH
+    assert result.type == TEST_MODEL_TYPE
+
+
+def test_retrieve_hash(model_processor, db_session):
+    # Test retrieving hash for existing model
+    create_test_model(db_session, TEST_FILE_NAME, TEST_MODEL_TYPE, TEST_EXPECTED_HASH)
+    with patch.object(
+        model_processor,
+        "_validate_path",
+        return_value=(TEST_MODEL_TYPE, TEST_FILE_NAME),
+    ):
+        result = model_processor.retrieve_hash(TEST_DESTINATION_PATH, TEST_MODEL_TYPE)
+        assert result == TEST_EXPECTED_HASH
+
+
+def test_validate_file_extension_valid_extensions(model_processor):
+    # Test all valid file extensions
+    valid_extensions = [".safetensors", ".sft", ".txt", ".csv", ".json", ".yaml"]
+    for ext in valid_extensions:
+        model_processor._validate_file_extension(f"test{ext}")  # Should not raise
+
+
+def test_process_file_existing_without_source_url(model_processor, db_session):
+    # Test processing an existing file that needs its source URL updated
+    model_processor.file_exists[TEST_DESTINATION_PATH] = True
+
+    create_test_model(db_session, TEST_FILE_NAME, TEST_MODEL_TYPE, TEST_EXPECTED_HASH)
+    result = model_processor.process_file(TEST_DESTINATION_PATH, source_url=TEST_URL)
+
+    assert result is not None
+    assert result.hash == TEST_EXPECTED_HASH
+    assert result.source_url == TEST_URL
+
+    db_model = db_session.query(Model).filter_by(path=TEST_FILE_NAME).first()
+    assert db_model.source_url == TEST_URL